[This Transcript is Unedited]
The Palace Hotel
2 New Montgomery Street
San Francisco, California
Agenda Item: Welcome and Introduction - Vicki Mays
DR. MAYS: I'd like to officially welcome everyone, and welcome those of you who are out there on the Internet listening. This is a hearing that is being held by the National Committee on Vital and Health Statistics, by the Subcommittee on Populations.
Let me talk a little bit about the purpose of today's hearing, and then we will start with some introductions. The National Committee on Vital and Health Statistics, particularly its Subcommittee on Populations, has a charge. Part of its charge is to work in an advisory capacity to the Secretary of Health and Human Services on data.
One of the issues that we have been concerned with is, since the 1997 OMB directive, whether or not the collection of data on race and ethnicity is moving along as planned, and whether it is working sufficiently for all groups equally.
The other issues that we have been concerned with are those of disparities, in terms of whether or not we are collecting data for vulnerable populations such as racial and ethnic minority on health disparities, and what would be the data to collect beyond that of race and ethnicity. So we have often in our hearings taken testimony on what are the variables in the particular groups would be important for us to have data on.
Of course, what has emerged in many of our hearings has been things like social economic status, the capacity to be able to geo code data. For some groups, what we have heard is that there is such a paucity of data, the ability to be able to have data in sufficient numbers, so that we can actually look and determine if there are health disparities in some subpopulations, is also critical.
So this is a hearing in which we began in May in Los Angeles, hearing from the population of Asian, Native Hawaiians and other Pacific Islanders. We took the opportunity, because we are here prior to the American Public Health Association meetings, to continue the hearing because of the diversity that exists in this particular population. This gives us an opportunity to be here in San Francisco, where there are a number of experts, where many people are involved in debating and analyzing the issues that surround the measurement of race and ethnicity, as well as some innovative programming in the San Francisco area in the collection of data for some of the small populations that exist within the Asian, Native Hawaiian and other Pacific Islanders.
So this seems like a -- as much as I am from L.A., I have to admit, this is a great place to be, here in San Francisco. Given what I left, it is wonderful to be here today and not in gloomy Los Angeles.
What I am going to do is start with introductions, and then after the introductions, I will share for the purposes of those of you on the Internet what the actual hearing questions are. We designed a set of questions that by the end of the hearing we hope that we have gathered testimony to help give us some insight into some of these issues.
So why don't we start with introductions? Eugene.
DR. LENGERICH: I'm Gene Lengerich from Penn State University, member of the subcommittee.
MR. HITCHCOCK: Good morning. I'm Dale Hitchcock, Office of the Assistant Secretary for Planning and Evaluation in HHS. I am staff to the subcommittee.
DR. STEINWACHS: I'm Don Steinwachs, Johns Hopkins University, member of the committee.
MR. LOCALIO: I'm Russell Localio, University of Pennsylvania, member of the committee.
DR. HUNGATE: Bob Hungate, Physician Patient Partnerships for Health and member of the committee.
DR. BREEN: Nancy Breen. I am an economist specializing in health disparities at the National Cancer Institute, and I am staff to the committee.
MS. BURWELL: Audrey Burwell, from the Office of Minority Health and co-lead staff for the subcommittee.
DR. YU: I'm Elena Yu, professor of epidemiology at San Diego State University and a dumb student at Johns Hopkins University.
MS. PEREZ: I'm Christina Perez, regional minority health consultant in Region 9, and also here for Dr. Ronald Banks, the regional health administrator.
DR. MURRAY: I'm Carol Murray. I'm here from the University of Hawaii Social Science Research Institute.
MS. SORENSEN: Catherine Sorensen, Hawaii State Department of Health. I'm with the informatics project and also representing the Office of Health Equity.
MS. SAGATELIAN: Margo Sagatelian with the Office for Civil Rights in Region 9, Health and Human Services.
MR. SOGOLARA: Randy Sogolara, Asian and Pacific Islander Bay Area Health Council. It is a new startup. It is one year in its inception, so I am here to basically get more information.
MS. LOW: My name is Debbie Low. I'm with the U.S. Environmental Protection Agency here in San Francisco, and I am in the environmental justice program.
MS. WHITE: Gracie White, NCVHS, staff to the subcommittee.
MS. WILHIDE: Sheryl Wilhide, Magna Systems Incorporated.
DR. MAYS: For those of you on the Internet, one of the things that we have done is, we have a call-in number. So after the presentations, there is time for questions and answers, so there is a number that if you have a question for one of the presenters, you can feel free to call.
We have done this in particular to make sure, given the geographic diversity that exists in terms of covering this population, that people who are in other areas can feel free to participate. It may be a little bit early in some areas in terms of time, and it may be later in others, those of you in Hawaii are probably very decimated if you are calling in this morning, but we still wanted to make sure that there was the ability to be able to do that. So I'm going to try to remember a couple of times to repeat the numbers, so that you can feel free to repeat this option.
If you would like to call in with a question, the phone number is 877-939-8305. You will have to know the host number, which is 288088. So the host is 288088, and then you need a participant number. The participant number is 278561. So the participant number is 278561, and the call-in number is 877-939-8305.
This is a series of questions that by the end of our hearing we want to try and have some insight to. So we have shared these with some of our speakers. Each speaker will address these in different ways. No one speaker is expected to, and we know they can't answer all of these questions, so by the conclusion of this hearing we hope to have insight on these questions.
Part of our questions are for Pacific Islander populations. What techniques are used to collect data on race and ethnicity? How does language, population size or population geography impact the ability to gather data on the health status, health behaviors and health experiences of these populations? What recommendations could you make to DHHS for addressing these issues?
Next. Do you believe that there is a significant problem of misclassification of racial and ethnic categories in existing data sets? For which data sets? For which categories? What steps such as possible partnerships with advocacy groups are in place for studying the issues and for making corrections?
Is data collected on ethnicity, language spoken and national origin in ongoing surveillance data sets? On what data sets are these collected, and if you have examples, please share them. What barriers exist to data collection analysis and disease surveillance for eliminating health disparities in Asian, Native Hawaiian and other Pacific Islander populations? Describe strategies that DHHS could use to remove those barriers.
Current data collection methods emphasize the protection of the privacy and confidentiality of survey respondents, which requires a certain number of responses in order to report the data. Given these considerations as applied to small population, what number of responses would you feel are too low to report?
What are some strategies that DHHS could use to increase the capacity for Asian, Native Hawaiian and other Pacific Islanders researchers and organizations to conduct health disparities research, demonstration projects and evaluation of data? Please describe strategies that DHHS could use to support relationships between and among universities, academic researchers, community, state and local health entities. Are there any accountability mechanisms you recommend that DHHS could institute to insure the development and maturation of these partnership relationships, and how could DHHS support partnerships with the Asian, Native Hawaiian and other Pacific Islander communities to improve safety and quality in health care?
Finally, do the guidelines on race and ethnicity collection from OMH have adequate utility for the Asian, Native Hawaiian and other Pacific Islander populations, or is there a need to collect information using other expanded categories.
So that kind of gives you a sense broadly of what will be discussed by some of the speakers, as well as the areas that the committee is currently interested in receiving testimony on.
So without further ado, we are actually going to get started with Christina Perez, who is the regional minority health coordinator for Region 9. She is also here on behalf of Ron Banks, to offer welcome. Ron Banks is the regional HHS health administrator for Region 9.
Christina, welcome, and thank you for being here.
Agenda Item: Overview of Pacific Island Health Data Issues - Christina Perez
MS. PEREZ: Thank you, Vickie. Good morning, everyone. On behalf of Dr. Banks, who unfortunately could not be here today because he is in Washington, D.C., we want to welcome you to Region 9, and especially to our listening audience and the audience here in the room, we appreciate the time and sacrifice that you have made to come to be at this important meeting.
Dr. Banks had asked me to share with the subcommittee some current and recent data projects that we have undertaken in Region 9. But before I do that, I want to give you a visual snapshot of some of the characteristics of Region 9.
For those of you in the listening audience, the first slide is a slide of the regional population in Region 9. Included in this slide is the population for California, Arizona, Nevada, Hawaii, Guam, the Federated States of Micronesia, the Commonwealth of the Northern Mariana Islands, American Samoa, the Republic of the Marshall Islands and the Republic of Palau. The most populated area in this region is California, with 34,501,130 people, and the least populated is the Republic of Palau, with 19,717.
This next slide is a slide that represents the Asian, Native Hawaiian and other Pacific Islander populations in the states of Arizona, California, Hawaii and Nevada. According to the recent census, Nevada was the state in the whole country who increased in size overall. But if you look at the Asian, Native Hawaiian and other Pacific Islander populations for Arizona, you see that the population for Asians is 1.8 percent, for Native Hawaiian and other Pacific Islanders is 0.1 percent. In California the Asian population is close to 11 percent and the Native Hawaiian and other Pacific Islanders populations is .03.
In Hawaii, the Asian population is about 41.6 percent of the population, and the Native Hawaiian and other Pacific Islanders populations is 9.4. In Nevada, the Asian population is 4.5 percent and Native Hawaiian and other Pacific Islanders population is 0.4.
This particular slide just demonstrates the major regional, racial and ethnic groups in Region 9. In American Samoa, there is Samoan and Tongan. In Arizona and California, Hawaii and Nevada we have the Asian, Native Hawaiian and other Pacific Islanders, black, Hispanic and Native American. In the Commonwealth of the Northern Mariana Islands, there are Carolinians, Chamorro, Micronesians, Caucasians, Chinese, Japanese and Korean. In the Federated States of Micronesia, it is primarily Micronesian and Polynesian. In Guam it is Chamorro, Chinese, Filipino, Japanese and Korean, and in the Republic of the Marshall Islands and Republic of Palau, it is both Micronesian.
This particular slide, which is a little bit busy, is really a slide to demonstrate the number of different languages spoken, specifically in the Pacific Basin. This does not include also over 100 other languages that are spoken by Asian populations throughout this region, so I won't go through all of them. But just to mention that in Palau, for example, the languages are English and Palaun, the official language. In Sunsorolo the language are Sonosorole and English. In Tobi, the languages are Tobi and English, and Anwar, Japanese and English, depending on the state. But if you look at the Federated States of Micronesia, English is the official language, but we also have (foreign phrase).
If we look at the Department of Health and Human Services map which is typically depicted, we see that Region 9 usually just shows the states of California, Nevada, Hawaii and Arizona. But if we superimpose a map of Oceana and the Pacific Islands which has the remaining portion of Region 9, you see that the span and the breadth of the area that is Region 9 covers the area from about -- for those of you who cannot see this, Hawaiian Islands would be pictured up around Maine, and then you have American Samoa around Florida. You would have the Marshall Islands and the Federated States of Micronesia cutting through the central middle states of the United States. The Northern Mariana Islands would sit somewhere in the neighborhood of Idaho, and then Guam would be around the border of Oregon and California. Then Yap and Palau would be sitting out in the Pacific Ocean. So you can see that this is a large, large area, which in and of itself creates a number of barriers.
Just for your point of information, the air miles from San Francisco, the least amount of travel for us in Region 9, that is, the shortest distance for us to travel would be to Sacramento, California, which is only 100 miles. Then the furthest would be to Republic of Palau, which is 8,627. The numbers are large or small in between, as you can see.
In terms of communication, I am going to start from the bottom of this slide to make the point. That is, if it is 12 noon on Monday in Washington, D.C., it is two a.m. on Tuesday in Palau, and three a.m. on Tuesday in CNMI, Guam, Chuuk and Yap, and it is four a.m. on Tuesday in Ponopay, and five a.m. on Tuesday in the Marshall Islands, six a.m. on Monday in American Samoa, seven a.m. on Monday in Hawaii, and nine a.m. on Monday in California, Arizona and Nevada.
Of all of the statistical information that I was wanting to put in this presentation, I think the most remarkable and stunning and incredible is that of the infant mortality rate specifically in the Pacific Islands. The Federated States of Micronesia, according to data that I got from the Central Intelligence Agency World Fact Book for 2003 is 32.9 deaths per 1,000 live births. In the Marshall Islands, the infant mortality rate is 31.58 deaths per 1,000 live births. In Palau, the infant mortality rate is 15.76 deaths per 1,000 live births. In American Samoa, the infant mortality rate is 9.82 deaths per 1,000 live births. In Guam, it is 6.64 deaths per 1,000 live births, which is below the national average, and also, in CNMI, 5.52 deaths per 1,000 live births.
If we look at some of the morbidity and mortality data for our Asian, Native Hawaiian and other Pacific Islanders, we see that Vietnamese women have a cervical cancer incidence rate five times higher than white women. Vietnamese men have the highest rates of liver cancer for all racial and ethnic groups. Native Hawaiians have the highest breast cancer mortality rate in the nation. Native Hawaiian males, mortality rates for all cancers has increased 62 percent between 1976 and 1990. Marshallese Island females have higher breast and cervical cancer rates compared to overall U.S. rates, and Asian, Native Hawaiian and other Pacific Islander women are the least racial and ethnic group to get mammograms.
In addition, Asian Americans are disproportionately impacted by liver cancer, which is usually caused by exposure to hepatitis-B virus, and heart disease still is a leading cause of death.
In addition to the kinds of issues that we look at here in the continental U.S. that impact health disparities, what is different in the Pacific Island -- and I am focusing on the Pacific Island because of disparities, and the differences are so different compared to the continental U.S., that is, inadequate supplies of potable water, inadequate facilities of disposal of waste, threats to marine ecosystem, over fishing or illegal fishing practices, and then a high unemployment rate. In the Marshall Islands, there is a 30 percent unemployment rate. That is again from statistics from the CIA World Fact Book 2003. In Guam the unemployment rate is 15 percent, in FSM, 16. In the Commonwealth of the Northern Mariana Islands, 33 percent of the workers there are foreign workers. Of the available work force, which is just a little over 6,000 people in CNMI, 2,000 are working. That gives you an idea of the impact of the immigrant population in the CNMI, and what they are dealing with in terms of also of the health care needs of that particular population. In American Samoa, the unemployment rate is 15 percent.
That completes that portion of the overview.
The next part is to share with yu some of the data projects that we are working on in Region 9. They have recently or currently been under way, so not all of them are -- some of them are in different phases of their work.
The projects have as an overall goal the promotion of increased participation of the Asian, Native Hawaiian and other Pacific Islander populations in federal policy development, as well as increased participation in regionally funded activities within the related programmatic priorities of the regional health administrator, the Office of Women's Health, the Office of Population Affairs and the Office of Minority Health.
Lastly, the data activities promote closing the health data gap through fostering research and the collection of data for Asian, Native Hawaiian and other Pacific Islanders.
The first project I want to describe is a project that is a collaboration of the regional Office of Population Affairs and the regional health administrator. This project is a funded research study with the University of Hawaii School of Social Work, that assesses the perceived barriers to prenatal care access among Asian and Pacific Islander immigrant women in Hawaii, specifically Chinese, Vietnamese, Filipino and Samoan immigrants are the target populations for the study. The goal of the study is to identify barriers to care from the clients, the provider and the policy maker's perspectives.
A second project is the OMH state partnership initiative which is funded by the Office of Minority Health, Department of Health and Human Services, the central office. This initiative was established in federal fiscal year 1999 to assist state minority health entities to develop or expand their existing infrastructure, or to address the public health needs of racial and ethnic minorities in their states, or to undertake special projects to address emerging health related issues impacting minority communities.
One project was a California Department of Health services, Office of Multicultural Health, to assess the culture and linguistic capacity of the Department's work force to meet the diverse needs of the population.
The second phase of this project is developing and evaluating a train and trainer module for developing a cadre of public health, department staff, contractors and subcontractors on critical issues in cultural and linguistic competency in health care delivery, is in progress. The state department initiative contract was also awarded to the Hawaii State Department of Health Office of Health Equity to develop a document that would serve as an introduction to the availability of national and local data related to minority health. The name of the document is Minority Health Data Enhancement Project.
A separate and current contract with the Office of Health Equity is to assess the health promotion activities of faith based organizations. This project will conduct an evaluation of existing faith based programs in Hawaii to determine if they have contributed to changes in health behaviors of the participants, and to determine if successful projects can be adapted for broader use.
Lastly, the Arizona Department of Health Services Office of Local and Minority Health was contracted under the state partnership initiative to assess the health care needs of Asian American and Pacific Islander populations.
Another project funded by the divisional Office of Minority Health is currently contracting with the Association of Asian Pacific Community Health Organizations or APCHO, to develop a strategic plan and curriculum to implement a geographic information systems technical assistance and training module tailored to the data needs of Asian, Native Hawaiian and other Pacific Islanders. APCHO will pilot the training module with some of its affiliates on the continental U.S., and also the Pacific Basin.
In addition, the regional Office of Minority Health is contracting with the California Pan Ethnic Health Network to convene a statewide meeting for communities of color on the assessment, collection, analysis and dissemination of data. The convening will enable the participants to share information on how to collect and use available demographic data that can lead to demonstrating improved health outcomes and to identify areas of data collection that still need to be standardized.
In Portland, Oregon in March, 2002, Office of Minority Health regions eight, nine and ten held a tri-regional data workshop, collecting, using, disseminating health data on minority populations. This workshop was a collaborative effort of the U.S. Office of Public Health and Science, Office of Minority Health and regions eight, nine and ten, and the Agency for Health Care Research and Quality program.
The purpose of the workshop was intended to assist representatives of minority community-based organizations, researchers, state and local health officials understand the issues related to the collection, use and dissemination of health data on minority populations, and to develop strategies to address these issues. Asian, Native Hawaiian and other Pacific Islanders were active participants as workshop planners, panelists, researchers and community representatives from the three regions.
The last project I want to report on is that on October 2002, the Office of Women's Health, Department of Health and Human Services announced the development of a new database to provide state and local public health agencies, faith based and community-based organizations, and health advocates with reliable comparative data.
It is expected that with the database, these groups will be able to one, monitor health status changes, also develop grant proposals and perform other program and policy related tasks. The database relies on existing national data available at the state and county levels. The national database will be available on CD-ROM and the Office of Women's Health website, and a training schedule for Region 9 is currently being planned.
Lastly, I would be remiss if I did not mention the recent defeat of Proposition 54, formerly known as classification by race, ethnicity, color or national origin, and informally known as the racial privacy initiative. The initiative would have broadly affected many aspects of state and local government by restricting the collection of data or classification of individuals by race and ethnicity.
While the initiative language was brief and had several exemption categories, these were not defined in sufficient detail to determine if certain activities and data sources would be interpreted as exempt. So the outcome if implemented was unclear. Had the proposition passed, I think that we would have additional hearing questions to ponder at this meeting today.
I want to thank you very much for the opportunity to represent the region, and I'll be glad to answer any questions anyone might have.
DR. MAYS: Thank you for your presentation. It is exactly what we needed to start getting a very good sense of the diversity of the groups that exist in the region, as well as some sense of what their health issues are, and the impressive number of programs that you all currently have under way in this region. So I'm sure this will be a very beneficial presentation for us.
Let's open it up for questions. We will start with committee members, and then we will move to the audience.
DR. STEINWACHS: I found what you presented very interesting and useful. You educated me in one area, too. I hadn't realized the CIA put out a world data book, and now I'm going to try to get access to it.
MS. PEREZ: The library.
DR. STEINWACHS: Any library will do? But it did raise in my mind the question of the data sources that you have to rely on in the region in order to understand and describe the health of the populations that you have responsibility for. Could you say something about the issue of access to data for many of the smaller islands and territories?
It is very interesting that you needed to go to the CIA data book, which may be the best. I was wondering whether there were data issues particularly for the region.
MS. PEREZ: A tremendous number of data issues, as you can imagine. We go by what is available. The CIA fact book is actually really helpful, because it covers just about everything you want to know to a degree.
It does not cover health disparities information, and it does not go into too much information on subpopulations, which is for us, both on the continental U.S. and out in the Pacific Basin a big issue.
It is always a challenge for us to get information, to get accurate information. So we use actually a lot of information from our community partners. We hope that we can collectively develop some sort of way to really capture more of that data, but at the moment we really just pull together whatever is out there. It is much easier with all of the information that is available by states, the continental United States, but are much more difficult in the Pacific.
DR. STEINWACHS: Thank you.
MR. HITCHCOCK: Christina, that was great. That was just what we wanted, and yu did a very good job.
MS. PEREZ: Thank you.
MR. HITCHCOCK: An earlier version of this subcommittee did a report on the data needs of the Pacific ancillary areas. We relied in part on the CIA yearbook as well.
There was another document that we relied on a bit that I thought was quite interesting. I don't know if it is still around or not. That was the Department of the Interior's state of the Islands, annual report on the Islands. Are they still doing that?
MS. PEREZ: Yes. Actually we have the most recent document, which is 1999. It gives some of the details around the health issues, but again, the amount of detail is limited.
MR. HITCHCOCK: It has something of politics and industries and occupations and that sort of thing, as I remember.
MS. PEREZ: Well, actually, the best way to really get a realistic picture is to travel to the islands in the Pacific. That is the way to really begin to understand the degree of depravity of information that is available to them also, as well as to us.
MR. HITCHCOCK: Do you have the opportunity to travel much? Does your office actually go out to the Islands?
MS. PEREZ: It depends on funding.
MR. HITCHCOCK: For us in Washington, it is almost like international travel if we were go to go the Islands.
MS. PEREZ: Well, it is international travel actually. You cross the International Date Line.
DR. STEINWACHS: I wanted to support that there were committee members that wanted to hold these hearings in places that were out in the Pacific, but we had some funding problems.
MS. PEREZ: Well, if it were at all possible, I certainly would encourage that, because that really is the best way to get a true picture and to feel what it is like to live there or at least walk around there, talk to the people, talk to the folks working in the health departments, and to really understand what they are dealing with.
DR. MAYS: Russell.
MR. LOCALIO: Thank you for joining us. I am Russell Localio, committee member.
I have two lines of questions. I don't really know where they are going, because I don't know the answer.
MS. PEREZ: Just so long as they are not data wonk questions, because I'm not a data person.
DR. MAYS: He is a statistician.
MS. PEREZ: I just wanted to let you know ahead of time.
MR. LOCALIO: I want to give a couple of examples. You put up a slide, I believe, that talked about Vietnamese men. That was one of the examples.
MS. PEREZ: What?
MR. LOCALIO: Vietnamese men.
MS. PEREZ: Oh, yes.
MR. LOCALIO: It would be interesting to know, for example, what is the rate of liver cancer among Vietnamese men living in the continental United States for those men who were born in Vietnam, versus the rates of liver cancer of Vietnamese men who are Vietnamese born of Vietnamese parents in this country, and who has lived his entire life in this country. What types of data do you have available that could distinguish those two cases?
MS. PEREZ: Actually, I don't have at my fingertips any of that data, but I think I would probably first go to Stanford University, where they have a -- we actually worked with them, Dr. Low, I believe, is his last name, to work on their hepatitis-B prevention campaign. That might be a start for us. That is, I would go there first to see what he and his staff might have on that.
MR. LOCALIO: So in other words, you would have to rely on a private researcher's data to get information to answer a question, for example --
MS. PEREZ: Definitely.
MR. LOCALIO: -- as to whether the high rate of liver cancer is related to some genetic predisposition among Vietnamese for liver cancer, or whether it is environmental, based on some exposure that Vietnamese men had in Vietnam, for example, is that correct?
MS. PEREZ: That is correct. I also would like to add that having looked through the Healthy U.S. 2003 book to try to find that kind of data there, I haven't read it inch by inch, page by page, but it is not there, I couldn't find it. That is where I think that I might look for it.
MR. LOCALIO: I think you could expand that question to any subgroup that we are talking about here, in terms of where they are currently living, and whatever health statistic you are talking about, isn't that correct? You couldn't do that any better for Samoans who have lived in Samoa versus Samoans who live in San Francisco, isn't that correct?
MS. PEREZ: I think that is correct. I am trying to remember the California health information survey data questions to see if they would have that specific kind of information. But at the moment I think I would still have difficulty getting that information. I could be able to tell you that in California, for example, we probably have the largest community of Latinos from Sacadecas, and the largest community of Samoans in Southern California. I could tell you things like that, but I wouldn't necessarily be able to tell you about the health issues in the subpopulations.
MR. LOCALIO: I just wanted to mention that, because it is well known, for example, that there are more people of Polish descent living in the Toledo area, for example, than are living in big cities in Poland. I think we have to understand that that is a difference.
The other point you brought up that I need clarification on is, you mentioned some source of data where people could get access to information at the county level. I'm not sure, the slide went up a little fast for me and I wasn't able to -- you said something about giving people access to data at the county level?
MS. PEREZ: Yes, I think you are referring to the Office of Women's Health data project, where they use county and state data to make available to communities who want to better understand how to utilize that data. I think that might be what you are referring to, is that the one?
MR. LOCALIO: But that involves only women, is that correct?
MS. PEREZ: Yes.
MR. LOCALIO: So if you wanted to get a general picture of the health or health status of people at the county level in Region 9, what would you do?
MS. PEREZ: I would probably spend about a month trying to piece together as much information as I could.
MR. LOCALIO: A month. Okay, thank you.
MS. PEREZ: I mean, full time.
MR. LOCALIO: I'm not surprised at all. Thank you very much.
MS. PEREZ: But I think we could come up with some figures, but I think still they wouldn't be, I don't think, the most -- not necessarily the most accurate, but they would just give you a snapshot.
MR. LOCALIO: Thank you very much.
MS. PEREZ: You're welcome. I hope I answered those questions.
MR. LOCALIO: Yes, thank you.
DR. MAYS: Nancy, then Audrey.
DR. BREEN: Thank you very much for a very helpful presentation. I hope you will be able to share the slides with Vickie so she can distribute them to us. I think it is unusual for us to have all that information in one place like you presented it this morning. So thanks very much for that.
One of the things that you mentioned -- this is a followup to all of my colleagues' questions -- you mentioned that what you really need to do to see the health disparities issues revealed in these populations is to go there and to talk to people who work in health and to see the way people are living.
Our job here on this committee is to see that there are statistics and figures that can be put together in order to create that picture for people who can't go there, because 8,000 miles, we simply are not all going to be able to go there. Unless these issues are eliminated for the American public, for the Congress, they are just not going to be taken care of. So it is our job to try to figure out how to get the data that would present an accurate picture of what is going on.
You said you weren't a data person, but obviously you work with data, and you have been talking about gathering data. Could you give for us a sense of -- you have mentioned a number of data sources. I know that a number of the national data sources we have, in fact, all of them as far as I know, including the California health interview survey, have inadequate numbers of Pacific Islanders, Asian sometimes, but Pacific Islanders, to be able to analyze the data.
As we learned in the last hearing, there is quite -- they tend not to be concentrated in areas where we can focus our data collection efforts on that. So what do you think is missing? You mentioned a lot of things we do have, but what do you think is missing that we need in order to have a better picture of the health disparities and causes of health disparities in Pacific Islanders in particular?
MS. PEREZ: I think we need an investment in resources that actually enable us to work closely with these populations, so that we can really get the data. I think without those resources, it is really hard.
In the regional health administrator's office, for example, programmatic wise in his office, there is just four of us. We work with the Office of Population Affairs, Women's Health and Minority Health. We together work at sharing information. That is, sometimes I have information that one of the other staff people doesn't have.
One of the things that we always struggle with is that it is difficult for us, because there isn't a standard way of collecting the data for the populations, but also that we have to go to a number of different resources to get that information. There are few opportunities for really sharing the information and updating the information in a regular manner that at least for our population and our subpopulations in the region is usable.
So I think resources in terms of researchers and certainly being able to provide resources so that we can get the information that we need, for example, out in the Pacific Basin in these populations is I think just critical. We always say resources, but it really is very key, and a commitment to making sure that we have this information.
Understanding the populations that have migrated from the Pacific to the U.S. is a challenge and very exciting, and we are very proud to be probably the most diverse region in the whole country, but the challenges that are there exist. In order to really understand our populations that are here, we can get information from them certainly, but I think it is also important for committees such as this and other experts that you rely on for your information to make that trek to at least one of the countries to really feel the impact of what that is all about.
So I think resources will be the key, not just money, but resources in terms of experts and time and commitment.
DR. MAYS: Audrey, then Eugene.
MS. BURWELL: I just wanted to make a few supportive comments on what Christina has said about data. There are many non-governmental organizations that provide detailed data on the Pacific Islander populations. We have here in California the Northern California Cancer Center, that I think you will be interested in. Scarlet Gomez will speak tomorrow on some of those issues that you were talking about, the impact of acculturation on the health of Vietnamese, and the visuals. You also have a rich resource at the university here at UCSF, Dr. Marian Lee, who has done a lot of work in those areas.
So you're right, the national data sets just don't have enough detail. Even the whole Healthy People series, 2000 and 2010, you will see a number of the health indicators were developed using other data sources.
DR. MAYS: Eugene.
DR. LENGERICH: Thank you very much for the good orientation to the region.
As Vickie had stated early on, the role of the committee is to be -- at least, one of the roles of the committee is to be advisory to the Secretary of the Department. You work with a section of that Department, so I was wondering if you could help educate me a little bit about what you perceive as your region's role in the collection, analysis and utilization of such data. For example, is it to collect the data that would be necessary? Is it to bring individuals from the various groups or geographic locations together with the people in Washington who do the national surveys? Would it be some other specific role?
So I guess in terms of our recommendations going back, I need a little bit greater understanding what the role of the region should be in that scheme, and then what are the barriers to accomplishing that.
Then thirdly, as a specific item is, what role do you play in the GIS grant and community grant that you spoke briefly about? I have some interest in that, as well as an example of data collection. You have a data collection and utilization process that is intended to help facilitate the health improvement of various groups within your region.
MS. PEREZ: With respect to the role, I'd say all of the above that you mentioned, but also I would add that we see our role as enabling the advocates in the community to utilize data and also to develop new data so that they through the data can look at outcomes and hopefully improve the health outcomes of the populations.
Certainly it is important to build the capacity of the community to understand how to utilize data. One of our goals is to develop partnerships with our community-based organizations so they can build their technical capacity around data.
Also, some of the barriers that exist have to do with limited resources to be able to do that in a larger way, to do those things in a larger way. But certainly we have -- there are barriers. There are also a lot of enthusiastic advocates out in the community who have ideas on how to make some of these technical and capacity building interventions happen in the community.
The GIS project that I mentioned is in fact one of those projects. We were approached by APCHO, who was very excited when they saw a GIS presentation and said, this would be a wonderful tool to take out to our community and to tailor a curriculum module that would enable us to -- a curriculum module tailored to the Asian, Native Hawaiian and other Pacific Islander population, and train our participants in how to use that kind of information, not only for being able to understand the community better, but also to be competitive in terms of grants, federal grants and other grants.
So we see our role as building the capacity of the community so that in their efforts to improve the health of the population, they are supported.
DR. LENGERICH: Thank you, that is very helpful.
DR. MAYS: Suzanne.
DR. HEURTIN-ROBERTS: Hi, I'm Suzanne Heurtin-Roberts of the National Cancer Institute. I apologize, I came in late.
One of the things that really struck me was the great linguistic diversity represented among the Pacific Islands. To what extent is this a problem for local communities using data sets or having access to data? And what kind of recommendations might you make to address that, if in fact it is a problem?
MS. PEREZ: I haven't thought about it actually in that way. What I have thought about it in is the way some of the cultural linguistic -- I won't call them barriers, I think I don't think they are barriers. I think it is a richness in the population when we were able to speak in a number of different languages. But I do know that just understanding how -- making that cultural leap and intellectual leap at some level about understanding the data may be more difficult for folks who are limited English proficient.
I think access -- I guess I don't think of it so much as the language being a barrier in terms of access. I'd have to think about that a little bit more. I think of it more the language being a barrier in terms of receiving services, and that providers and contractors who provide -- or private providers of health care don't always understand the particular needs of the population, and may incorrectly use existing data on minority populations to make assumptions that are incorrect.
So I don't think of it so much as a barrier in terms of the population using the data. I look at it more as a reverse, that is, the provider population interpreting that data and using that data in such a way that they make assumptions about a population because they have read something about Asian, Native Hawaiian and other Pacific Islander populations from one document.
DR. MAYS: I'm going to piggyback on Suzanne's question, because I actually had a language question, so this may be a good time to do it.
One of the things that we struggle with particularly at the federal level is the ability to be able to have our surveys in languages other than English and Spanish. I know even as a researcher, quite often when we go out in the field and we think about the concept of translation, and you look at the number of languages for example that exist in the population.
If the federal government had the resources, would the region be able to provide both interviewers as well as individuals who could do the translation of some of the survey instruments? And would that be possible?
For example, if we wanted to ask a question on utilization of health insurance, and we wanted to talk about plans, and we had all these different terms that we wanted to use, what are some of the challenges that we would face in translating say the national health interview survey, the various MEPS -- well, not MEPS, but some of the various surveys that we do, would California be a region that could provide expertise to do that?
MS. PEREZ: I think California would be an excellent place to do a pilot or something like that. We have hundreds of languages spoken in this country. We have hundreds, actually thousands, of health professionals with advanced degrees, who are not able to practice in this country because of the licensing issues, but certainly are an incredible source of information and expertise and translation.
I can't say that all of those folks have been prepared to translate statistical information, but we have a population that could certainly try to meet that challenge. Certainly California does not have the resources to do that, money resources. We have the people resources that would probably be willing to work on something like that, and certainly we have a number of public and private entities who might be interested in doing that.
DR. MAYS: Suzanne, I don't know if you want to continue questioning?
DR. HEURTIN-ROBERTS: No, that's okay.
DR. MAYS: Edna?
DR. PAISANO: My questions relate to the previous questions. You had talked about the different time zones and the mileage difference. In those Pacific Islands, and with census and surveys, you either mail the questionnaire or you call the home. What kinds of communications are in place? Is there a mail system to each household? Are there telephones available?
Secondly, you talked about researchers' needs for going into those places. Along with that, -- of course, my work has been with the Alaska Native and Native American populations. Are outside researchers really welcomed in those communities to do that kind of work?
MS. PEREZ: The Pacific Island population I think -- I don't think that there is a barrier to approaching the state health representatives about doing research, in terms of the -- because having visited Culcheray over a year ago, they were actually very open to continuing -- I wasn't a researcher, I worked as a coordinator for minority health -- they were very interested in opportunities for doing research and working with some researchers or experts.
Not everyone has a phone. In fact, there are a very few people with cell phones on island only, but in order to use a phone, you would need to walk a block or two to use the phone. There are Internet stations where you can go and use the Internet for -- I think it is around ten hours during the day. It opens at a certain time and closes at a certain time. Sometimes some of them are open a little bit longer. But there are limitations there in terms of communication that you wouldn't find on the continental U.S., certainly.
But I think research is a very welcomed activity there, in partnership.
DR. BREEN: Is there mail delivery to eery house? That was another question.
MS. PEREZ: That I don't know. I wasn't there long enough, and no one wrote me while I was there, so I couldn't tell. But calling just San Francisco to touch base with my family, I would say up until 1 o'clock to be able to speak with them at 6 o'clock in the morning their time. So there are certain differences or different opportunities that you will need to work with.
DR. MAYS: Let's see if we have any questions from any of our audience participants? Would you please identify yourself?
MS. SORENSEN: Kathy Sorensen with the Hawaii Department
of Health. I wanted to say, I can appreciate what you say about going to visit the places. I had an opportunity about 15 years ago to work in several jurisdictions. It is not that they don't collect the data; that had collected lots of data.
That is part of my two-part question. Has there been any data training, how to collect data, ongoing by the staff? Also, is there any work towards developing of core data sets, and that would include standardizing, and helping in that sort of sense?
MS. PEREZ: I can answer the second question really quick. I don't know on that one. In terms of the data training, we are actually working very closely with the Pacific Islander Health Officers Association, which is a representative of the jurisdictions. Hopefully through that partnership we will be able to -- and data is definitely one of the priority areas for that association, that we will probably be doing some work with them on data.
MS. BURWELL: If I can just add, in terms of vital statistics, I think Guam and one or two others are getting technical assistance from the National Center for Health Statistics.
MR. LOCALIO: I have a followup question based on one of your responses. You mentioned the need to build a capacity in the community to use data, and enable -- given the technical capacity to use data that might be available, and you also talked about the need for resources in order to have this data generated.
The problem is, suppose we had resources made available to NCHS to do a targeted survey of any of these subpopulations, and suppose to enhance the usefulness of any of those data we had GIS information. Suppose we took off everybody's name and their address. Under current statutes and regulations, the only place you could use those data would be in the main office of NCHS in Maryland.
Now, that means that somebody would have to go there physically to be able to use that. Would that be responsive to those needs?
MS. PEREZ: Well, let me phrase it this way. It would be great if you could have satellite NCHS offices around the country, five.
MR. LOCALIO: Thank you very much.
DR. MAYS: We have no -- I just want to make sure; Sheryl, we have no Internet questions? Great, thank you.
We greatly appreciate this introduction. I think it was perfect, in the sense that it gave us a broader review of the issues, the challenges, and I think you did quite well at giving us a sense of what we might be able to recommend to think about how to deal with some of those challenges. So thank you very much, we are very appreciative of your time.
MS. PEREZ: Thank you very much. Welcome to San Francisco.
DR. MAYS: Thank you. We are going to move to our next presenters, because I can see that our colleagues are here. Can we take about a five-minute break, to give you some time to load up? Then I will introduce you when we return.
(Brief recess.)
DR. MAYS: I think we are back on. For those of you out there on the Internet, the phone number is 877-939-8305. The host is 288088. They don't need the host? Sorry, you only need -- once you dial 877-939-8305, is then the participant, which is 278561.
Let's turn to our next presentation. We are very grateful and quite excited to have our colleagues from the Asian Pacific Islander American Health Forum. We know them quite well from much of the work that they have been doing in this area, which not only does it benefit California, but it benefits us nationally.
For those of you who know who the chair of the committee is, that is John Lumpkin. He used to be in the Illinois Department of Public Health. Ho Tran, who is now the president of the Asian Pacific Islander Health Forum, was also there. So by way of Chicago, she also has come to California. So we are very happy to have here.
With her is Gem Daus. Many of us also know him. He is also going to be talking a little bit about some of the access issues in terms of Asian, Native Hawaiian and other Pacific Islander population.
So, Ho Tran, thank you very much for being here. The California bridge is here or something else, in terms of how long it takes to travel, so we greatly appreciate the time investment that you put in, even though you live here, just the time to get here to be with us today. So thank you very much.
Agenda Item: The Need for Detailed ANHOPI for Health Policy - Ho Tran
DR. TRAN: Thank you so much for the invitation today to present, especially to Vickie.
The session that I am going to present, it is on health data needs for the elimination of health disparities for Asian, Native Hawaiian and other Pacific Islander populations. This is a testimony to the Subcommittee on Populations, National Committee on Vital and Health Statistics, submitted by the Asian Pacific Islander American Health Forum.
The overview. We talk about who we are first, and introduce ourselves, and especially who we represent and the findings and our recommendations based on information that is very much based on the recommendations that the testimony will be talking about.
What is APIAHF? It stands for Asian Pacific Islander American Health Forum. It is a very long name, so whenever I introduce myself, usually I have to take two breaths. So it make it short, we call it the Health Forum. We are a national advocate for Asian Americans and Pacific Islanders.
The history. The organization was founded in 1986 by a group of Chinese physicians and especially activists in the community in San Francisco, in response to a report on minority health put out by the Reagan Administration. This report was only about black health in relation to white health, so we were even not in the picture. So now the organization exists to make sure that our needs are being heard, and to be at the table when decisions are being made.
Our mission is very much proactive. We started initially to be promoting to improve the health of Asian Americans, but just recently we changed to a more proactive way, which is to enable Asian Pacific Islanders to attain the highest possible level of health and well-being.
So what do we do? We are a national policy advocacy organization. Our main core value is on research. Based on the research we draft policy advocacy pieces. At the same time we do have programs within the organization. We do have a cancer survivor network, which is at a national level, understanding that cancer is not very much studied among API, and especially the support on survivorship.
We do have capacity building for its prevention, and we are providing for technical assistance as well as capacity building organizational management for CBOs in the community. We work very closely with five organizations in the community. One is the Maui Foundation in Maui.
We do have a census information center. Our policy director, Gem, will be talking to you afterward. The health information network is being funded by the Office of Minority Health at least for the last five years. It is information sharing on the Internet, very much informative, at the same time culturally but not yet linguistically appropriate.
We do have a national institute on domestic violence. We are not a direct service provider, but more on capacity building, technical assistance and research.
Finally, not least is the tobacco education network and the funding comes from the state of California, and we work as a coalition of networks statewide, as a consortium.
When we talk about our main core value, it is very much on the policy department. For the health forum policy platforms, it is to increase access to health care. It is a value of the organization as a vision when it was started by the group in 1986. With this increase in health care we want to have quality in health care as well.
In order to increase the access as well as the quality, we also want to assure a diverse and competent health care work force, and especially increase research and data collection. Last but not least, it is to increase community-based health promotion and disease prevention program.
Who do we represent? Before I go into who do we represent, I just want to stress again about the way we function at the organization. We are very much into coalition building, and everything we do, we do with partners. So the reason we are here is that we are working very much with all of you to make sure that API is being touched upon.
These will be our members, researchers, community-based organizations and health care providers in the API communities. But we also work with other racial and ethnic groups. As an example we work very closely with an organization called Alpha 21. It is in your packet. We will be holding the first conference for this organization. Alpha 21 came out of -- it is a multicultural, multiracial ethnic organization for the parity in health for all populations. So the conference is this coming Saturday from nine to four p.m.
This is very important, because numbers count, but more importantly we can and should work together to accomplish common goals. We do have the same problems. It might be diverse either from the culture, from the linguistic, but basically we do have the same problems.
Who are we representing at the organization? The name speaks for itself. It is the Asian Pacific Islander population. I am not going to touch much about the very specific demographics data, but to show you how the Asian population has grown over the last decade. Based on this transparency, we are 13.2 percent -- I'm sorry, we are missing one word here, the growth rate. The U.S. population growth rate, it is 13.2 percent. Asian alone population is based on the census data, the Census 2000. The Asian population alone will see a growth of 48 percent, but if you count Asian alone or in combination, it is now almost a 72 percent increase. That is from 1990 to the year 2000. The minimum-maximum range for the increase in the past -- when we talk about Hawaiian and other Pacific Islander population, that the 1990 census counted 365,000 Pacific Islanders. Using the Pacific Islander alone population in the year 2000, this population increased by 34,000, or 9.5 percent between 1990 and the year 2000.
In the Pacific Islander alone or in combination, population is used, an increase of 509,000, or 140 percent results, this from ten-year range. The minimum-maximum range for the increase in the Pacific Islander population was 9 percent to 140 percent increase. You can see the wide range of the percent, of the rate, and it is also gives an impact on how from the researcher standpoint we used the data either alone or in combination altogether for all denominators.
In terms of the percent distribution of selected detailed Native American and other Pacific Islander groups by alone or in combination population in year 2000, the graph shows that for Native American alone, you have only 35.1 percent. But once you combine together in combination with one or more other race and/or Pacific Islander detailed group, you can see almost double the number. For Samoan, it is the reverse, so we have 68.3 percent alone, and in combination it is 31.7. Tongan is 75.2, and combination is 24.8. Guamian, 62.9 percent and Fujian, 72 percent.
Of all respondents who report Native American, either alone or in combination, 65 percent reported one or more other races of Pacific Islander groups.
What are the findings, what we have found to be the state of API data as of now. The Census is perhaps the best example of how data collection can work for APIs. We can detail the description by forming Asian and ANHOPI subgroups. But all the data gathering efforts are not so informative.
The findings, it is two examples. The first is the implementation of the 1997 OMB standard, and the second one is the Healthy People 2010. From the implementation of the OMB standards, as you know the 1997 standards mandated the use of the minimum five race categories when collecting race data. These included Asian as well as a separate category for ANHOPI. So everything the report found as of this year. The Health and Human Services implemented the revised standards for 85 percent, which is 149 of the 175 forms. 128 over 175 forms were used, used multiple race reporting. So we do commend HHS for the broad implementation of these standards.
I believe that we all know about Healthy People 2010, and you do have a copy in your package as well. The second key finding is in Healthy People 2010. Healthy People 2010 is a comprehensive nationwide health promotion and disease prevention agenda for improving the health of all people in the nation by the year 2010. It serves as the plan of action and resource allocation for the HHS.
Our stated goal for Healthy People 2010 is to eliminate health disparities. However, there is very little data on Asian Americans and Pacific Islanders. This paucity of data in this and other federal government data sets will make it difficult to measure programs toward eliminating health disparities.
We knew that this could be the case, so in order to assess the situation, we recommended at the time that the document use the following notations: Asian or Pacific Islander data. They took this suggestion, and the suggestion was that when there is no Asian or Pacific Islander data, to specify whether Asian or Pacific Islander data has not been collected at all as a DNC, Asian or Pacific Islander data has been collected but has not yet been analyzed as DNA, and Asian or Pacific Islander has been analyzed but is not reported due to small sample size, DSU.
We commend the HHS for taking our recommendation. You can see that it is being shown, the data is being shown from Healthy People 2010. This clarification is very useful for prioritizing future efforts in data collection and analysis for API.
Of the 22 objectives in the Healthy People 2010, only three currently comply with OMB. Six only have aggregate data of API data. Five have both aggregated for Asians but not for ANHOPI, and eight do not even have statistically reliable aggregated data for API.
What are the consequence? The consequence that the under representation of API and inadequate sample sizes in many national, state and local surveys render many databases useless for examining demographic and policy related trends affecting API. I have to say that when I belonged to the national cancer PRT just held in Chicago, and I looked into the data for API, most of the data is either DNC, DNA or DSU, very little information about API on cancer information.
Another consequence is that the under representation of API, example are previous attempts to create a health clinic failed when API population numbers were linked together as one group. The Asian population numbers rendered the API statistics insignificant. Therefore, indicating PIS not having health problems and not needing a health clinic, so that is what is happening in San Diego, California, found by the Pacific American Foundation.
The recommendations from the organization which we also feel we are representing the API population, to collect more disaggregated data. As an example, it is more into some other data for API. When I invited to talk, representing to speak on behalf of API on health issues, it is sometimes very difficult for me to make a case, because most of the time we felt much better as numbers in comparison with other populations. Example like, we have better infant mortality rate, we have lesser rate of cancer, but when you disaggregate the data, that shows a loss of diversity within the API population.
For smoking cessation example, even that we have a lower rate of smoking in comparison to the white population, 18 percent for API in general, but once you disaggregate the data, 87 percent of Vietnamese smoke -- no, 67 percent of Vietnamese smoke, 87 percent of Cambodian and Laotian people smoke. So just to give you the diversity, not to say that for ANHOPI we don't have enough data to show that picture.
What we recommend to this committee is to follow the Census example in order to collect enough data, not only for the minimum five, but for subgroups as well. I can share with you taking from the policy brief from the UCLA. I will talk a little bit more about that.
This is now the form on the Census form. As you can see, we have the person's race, white, black, African American or Negro, American Indian or Alaska Native, and from that we have to print name of principal tribe. For the ANHOPI we have at least three diverse racial ethnic groups: Asia Indians, Chinese, Filipino, Other Asians, and then to print their race, Japanese, Korean, Vietnamese, Native Hawaiian, Guamanian, Samoan and other Pacific Islander.
Another recommendation is for API population. It is to convene experts to determine solutions to the methodological problems posed by small populations. What are the valid and reliable methods for characterizing the health of small populations. Just to give you an example from the policy brief from UCLA that was extrapolated from the data, and we do have some information about the study of health of Asian and ANHOPI. I can say that they are much less than other population.
Example for cancer screening test by race and ethnicity in California year 2001. For Asian, for Pap test it is 71.5 percent, but for ANHOPI it is 69.1 percent. So all the numbers for ANHOPI is very, very negative. Mammogram, 63.4 percent, RC screening, 39.1 and PSA test isn't even statistically reliable.
We always blame the low socioeconomic impacts on the negative findings at the same time, but from the findings from NCHS even that are below the 200 percent of federal poverty level are above for ANHOPI, that are very much less. For the Pap test, they are 57.3 percent below poverty level, and for above 78.2 percent, in comparison to other population it is much, much less than the other population. To say that for the percent of recent cancer screening test by race and for covered by Medi-Cal, it is the same, so I don't want to take much of your time.
Another recommendation, it is to conduct more small targeted surveys, assess populations of which we don't know what we have in any sizeable numbers in the large national surveys. I can say that Vickie was talking about, when I was back in Chicago working for the Department of Public Health, that it is very difficult even to make a case at the state level for small populations, because it is always that you are not even existing. But we would like very much to see, if we don't have the percentage, to see the trend of other population, so it is a challenge for researchers, not to go only by race, but also by trends, to analyze existing data as indicated in Healthy People 2010.
Another recommendation is talking about language issue, that language does impact data on researchers. It impacts because if people do not understand the questions, the answer will be very much different, or even because of the language there will not even be an effort to reach out to the population. An example is the BRFSS. In my state at the time -- now my state is California, but Illinois, the two languages were only English and Spanish, so how can we say that BRFSS represents the population, because there is no language in the Asian population, so how we can be represented. So to collect primary language data more opportunely, to conduct surveys in languages besides Spanish on a regular basis, and if it is difficult to understanding that the cost of resources -- I heard about the resources, but maybe at least as a start to translate the information in the questionnaire in other languages. But it is just a suggestion, but it is just a glimpse of the issue, because also the questionnaires might need also to be culturally competent at the same time, at least as a start. So do the validated translations of survey questions and instruments.
Another recommendation is to increase the capacity for ANHOPI researchers and organizations to conduct health disparities research, to insure that ANHOPI are included in programs that target under represented minorities, particularly at NIH. The last is the third one, AAPI survey institutions, H.R. 333, and I think you have the information here.
To require the Social Security Administration to collect race and ethnicity data, because it is very important for Medicare population, and to fund the American Community Survey. Evaluate programs on previous recommendations. You have it in your packet, that is the health data needs of the Pacific insular areas, Puerto Rico and the U.S. Virgin Islands, so we need to do some evaluation of this report.
Thank you for your attention.
DR. MAYS: Thank you very much. Gem, would you like to follow?
Agenda Item: Assessing ANHOPI Data: Gem Daus
MR. DAUS: Good morning. My name is Gem. I work in the Washington, D.C. office of the Health Forum. What I am going to present is some information on the census information centers, of which we are one.
I'll give you some basic information on the CIC program, some actual data that is in the green packet that we passed around. Then also, I wanted to highlight a few issues that were presented by the Census 2000 and ways that you can support the community.
The Census Information Centers or CICs is run out of the Bureau of the Census Customer Liaison Office. The reason for this program is really to disseminate census information particularly to under served communities. There are 50-plus designated CICs, and we are a diverse set of organizations, ranging from direct service community-based organizations, some universities, some national advocacy organizations, as well as some tribal nations like the Navaho Nation is one.
What the Census provides us is free data, training, special products and also special access to some databases and other in-kind support. I also wanted to mention that part of the special access is actually access to an advanced query system, so that we don't have to go to Suitland to run those queries. They know when it is our computer logging in, and we can run those kinds of queries.
This is from a survey that we did last year to see what the Census Information Centers were doing. You can see that mostly, they are doing a lot of racial and ethnic data research. The diversity of the CIC is that all of the quote-unquote minimum five are represented. The other activities, writing grants and proposals, research and data analysts, advocacy, program planning, also business and economic research, grant making and measuring policy impact.
This is information and dissemination that we do, both for ourselves in our program as well as for customers. There are several that serve particularly Asian, Native Hawaiian and other Pacific Islander populations. The ones that I put in yellow are the ones that have done work relating to health. For example, the Asian American Federation of New York did some studies on Chinatown in New York and how they were affected by 9/11, particularly how they fared in terms of mental health. So that is a real great example of an organization using the census data to do some work for their local community.
The National Asian and Pacific Center for Aging in Seattle is doing a lot of work trying to characterize the elderly Asian population. The Social Security Administration has very limited data on the race and ethnicity of its enrollees, and therefore Medicare has bad data, because Medicare gets its data from SSA. So they are trying to wrestle with that to figure out what the needs are for these populations.
(Foreign phrase) is the Native Hawaiian health system, and you have some testimony in your packet from them. Then the Urban Coalition in Minneapolis works very much with the Hmong population there, in particular using census data to advocate for public programs like TANF, welfare.
We have a website that isn't quite live yet, cicinfo.org, but it should be live in a few weeks. Then of course, you can always go to the census.gov site, which is very big.
For us at the Health Forum, we respond to data requests. We get calls. Most of the time they are pretty easy to handle on the phone. We have done needs assessments. We did one for Alameda County to help them justify an after-school program. We have work in census data in our fact sheets, and of course we are doing advocacy.
We have also done training and technical assistance. If you have ever used the American Fact Finder, which is the query system on Census, for most people it is not natural. It is counterintuitive. So what we have found is that we have to train people how to use it and how to think like Census. So we have done these trainings in five cities. They include a day to go over just the census information, as well as another half day to go over health databases. We take them basically on a tour of both national health databases as well as ones that are available from their state or from their state data centers and other sources.
Then finally, one of the other things that we try and do is coordinate with the other API CICs, particularly in how to present data consistently. Because of the multi-race issue and because of the number of categories and different ways that you can cut things, it is easy for people to get mixed up and wonder what it is they are presenting and what it is they are reading. So we do try and be consistent in our presentation of the data.
In your packet there is an Excel spreadsheet that looks like this. I just wanted to give you an example of some of the data that is available.
The first two pages is the top ten states for each of the Asian ethnicities. So for example under Asian Indian, the top ten states listed in order, the population, and then the percent. Then there is also a running cumulative percentage. So you see that 75 percent of the Asian Indian population is in ten states. For the most part, number one is California, except for Bangladeshi and Pakistani in New York is number one.
The last two pages is a similar analysis, but for the Asian, Native Hawaiian and other Pacific Islander; 80 percent of this population is in ten states, and California, Hawaii, Utah, Washington, Texas, New York, Florida and Nevada, Oregon and Arizona.
This is the low numbers, both of them represented the low numbers, not the multiracial numbers. Then the last page is -- I wanted to give you a sense of some of the Pacific Islanders. When you see U.S. totals, that does not include American Samoa, CNMI or Guam. When you see a population total for U.S., it does not include those Pacific Islanders. It includes Washington, D.C., it includes Hawaii, it includes Puerto Rico sometimes, but it does not include the Pacific Islanders. That is why I broke out in this case the numbers of Pacific Islanders in these places.
We are hoping to do these kinds of data for other characteristics such as poverty, disability and other things that are available from the long form data.
Now, because we have this great mass of data, there are some issues, particularly in health because of the number of categories now. The question becomes, can we characterize the health of these different categories, in particular the multi-racial categories.
Then the other issue is, can we measure change in health status. The Census is one degree away from most data sets, so if the Census changes, it ripples throughout anything that any other survey does. Then the last issue is looking forward to Census 2010.
On the first two issues, the answer is yes-but. I think you know probably in some cases better than I that all of these categories and all of these changes bring up a lot of issues because of comparability, what is the actual changes in population from 1990 to 2000. In the examples that Dr. Tran showed, you saw that it was a range; which of those numbers would you use as your denominator.
There are methods for bridging, so that you can get a standard denominator and create a rate, create an incidence. But still, you have to think about all of the machinations you have to go through to get good data. The base really does ripple through the whole system.
So comparing 1990 to 2000, you have to be very careful how you make those comparisons. The other thing is, because Census was one of the first surveys to use the new OMB standards, a lot of the data that we are seeing now, because they were collected before 2003, are not yet presenting data in the same way. So it is sometimes difficult to match those one set to another.
The American Community Survey I wanted to mention, even though it is not a part of DHHS. This is the survey that will replace the long form in Census 2010. The plan is that in Census 2010 there will only be a short form, and that the data that we normally get from the long form will be gotten from the American Community Survey, which hopefully will be done more often, I think yearly or maybe every other year.
The problem is that it is currently being tested, and Census funding typically dips between the big censuses. One of the things that we advocate for is to keep their funding up so that they can do the testing that will allow them to do a good American Community Survey.
One of the things that we are concerned about is that outreach and translation will not be as extensive as it was for Census 2000. So once again, people who don't speak English will not be represented, people from small populations may not be represented, and the sampling frame for Census 2000 was one in six. We don't know what it is going to be for the American Community Survey, but we hope that it can be -- it would be great if it could be as good as or better than Census 2000. But of course, they need some funding to do that.
These are the -- this is information on the long form. Then these are the kinds of information that we were able to get. So a lot of beyond populations. These are the indicators that we really look at to see how a population is doing.
We have started an analysis for California of language isolation and languages spoken at home by county, and we are hoping to do that for ten other states.
The last thing I wanted to say is that the Census does not have grantmaking authority. So all of us at Census Information Centers, we get free data, we get training and all of that, but we don't get any money from the Census. So what we have to do is recover our costs, so sometimes we may charge for what we do, especially if it is a pretty intensive search. We do also get grants and form partnerships. We are currently working as a group among the 50 to see if we can actually get some funds that will help all of us.
Just so you know, Census Information Centers are like a lot of other organizations, in that we have our staffing issues and our funding issues, but we have really powerful tools that can help our communities.
So that's it.
DR. MAYS: Thank you. Let's open it up for questions. We will start here with the members first. Virginia, and then Russell.
DR. CAIN: Thank you very much. Both presentations were very helpful and we appreciate them.
I wanted to -- this could go to either one of you, but reflecting back to some of the comments that Dr. Tran mentioned, I want to go back to some of the language issues that you talked about, particularly with regard to data collection.
By collecting data mainly in English or Spanish, do you have any estimates of what percentage of the population we are missing, and is that particularly concentrated in some subgroups rather than others?
MR. DAUS: I'll start. That is one of the reasons we started analyzing the language data, both language isolation and who doesn't speak English very well, so that we can see where those pockets are.
The Asian population and the Pacific Islander population are pocketed. You can see from the list of ten states, we are concentrated pretty much in metropolitan areas. So hopefully what we will be able to see is what the language isolation is for Hmong versus Vietnamese versus Japanese. Japanese for the most part speak English, Japanese Americans. Hmong, you probably have a higher language isolation rate there. Then where the Hmong are, Minneapolis, Fresno, Sacramento. So you will see those kinds of concentrations.
DR. TRAN: I don't have the exact percentage, but I can say that it would be a large percentage, because they don't possess the skills as to respond to a questionnaire, but they feel more comfortable to speak in their own language. So even for the Vietnamese population, they came in different waves. The first wave came in 1975, but if you ask a question in English or in Vietnamese, they would prefer to do it in the Vietnamese language.
DR. BREEN: I believe that 60 percent of Asians in California, according to the CHIS, were immigrants.
DR. MAYS: Russell.
MR. LOCALIO: Thank you very much, you have been most helpful. I have a question. I want to give you an example as to the extent and detail of data that you have access to through a CIC.
For example, if someone asked how many males ages 40 to 45 living north of Lake and south of 15th and Minneapolis are there, is that the type of detail that you have?
MR. DAUS: You can get that data down to the census tract level. There are confidentiality filters, though. I forget what the three criteria are, but there is a level at which you may not get any data.
MR. LOCALIO: I see, because if you have age and you have location and you have disability, therefore they will prevent that.
MR. DAUS: And remember, the long form data is a sample, so you are not starting from the census, which is 100 percent.
MR. LOCALIO: This is a Title 13 census restriction that they put on you?
MR. DAUS: Yes.
MR. LOCALIO: These are census data?
MR. DAUS: Yes, these are census data, right.
MR. LOCALIO: Thank you.
DR. LENGERICH: Just to follow up a little bit, do you see any differences between health data, confidentiality, identifiability of health data versus census data, in the way the restrictions that are placed upon the various data sets?
MR. DAUS: Do I see any confidentiality issues?
DR. LENGERICH: Any differences in confidentiality issues between health data and census data that is not specific to health.
Russell's question was very specific about individuals living in that area. Health people may ask the same question, but interested in incidence or prevalence of a particular disease. So my question is, do you see differences in the way confidentiality, identifiability is handled within those two different types of data?
MR. DAUS: I don't know. I know that in addition to Census Information Centers, there are state data centers, and they have the same level of access. They can run their own data queries, and in a sense supply the numbers to whoever needs them. So if they can't get it, no one else will be able to get it, either, because we are using a different system to get those numbers.
I'm not sure if I am answering your question, but they can supply the data, and no one else has to know the search mechanisms or the filters or anything like that.
MS. TRAN: I can say that there is a difference in confidentiality between the two sets. The health data is more issues that is confidential, that is more personal. It affects the health issues and things like that. So for the census data it is not very into the health related issues per se, so that is the difference in confidentiality.
DR. STEINWACHS: Gem, you were making the point that Census doesn't have money resources to help users. It would help me to hear you expand a little bit about what you think is the best way for Census, and it could also apply to DHHS, to try and make it such that groups that want to be able to use the data for purposes of planning, targeting services, identifying problems, can do that.
I guess what Census does do is, it helps with the access, with training. I know that you said you were able to seek out some grants to support what you are doing. Are there some specific gaps that if it were possible to fill in existing groups, including your own, that we ought to try and endeavor to do so?
MR. DAUS: One of the things that we are trying to do, we are funded from the OMH, and as part of our health information network, trying to work in our census analysis as part of that.
One of the things that that I think HHS can do is really help people understand how the two are connected. You have got census data on the one hand, but then you've got all of these health surveys. The census can't really provide that kind of information. But the Data Council or some sort of outreach program can help people understand how the two are connected, how a change in the census causes a change into health data. Then particularly working with communities, in the sense that we try to help our different constituents understand both, I think we only did five; there are so many more we could do.
DR. BREEN: Thank you both for very illuminating presentations. You were talking about the American Community Survey and saying that that is going to replace the long form in 2010. It is going to be a smaller sample size. I did some calculations, and I think it is about 15 percent instead of 20 percent of the U.S. population that will be surveyed more intensively as part of the census effort.
Right now, the role the Census plays in collection of health data is really to adjust the sample sizes from pretty small relative to the Census, pretty small samples of the population to estimate the population. I'm wondering, have you thought about whether ACS could play a role in collecting health data? It is related to this issue of the confidentiality. I think ACS right now, they have a moratorium, but they are a little more open in principle to collecting additional data on ACS than they have been on the long form, but I think they would be very concerned if it were to affect their very, very high response rates.
As you know, the response rates are legislated; you need to respond to the Census if you are asked. So we would be essentially legislating people to answer questions about their health. Have you given this thought, or could you talk about that a little bit, please?
MR. DAUS: It would be nice if they could add a few questions. But I can tell you that --
DR. BREEN: Excuse me, just let me say one more thing. I think it is really the only way an existing survey is going to get the sample we need to gather data on these small populations.
MR. DAUS: Right. I can tell you that with the long form, they went through this process where a lot of people particularly in Congress, who were concerned that the long form was too long. So they did an analysis of every question to see what was supposed by statute, reg and so on and so forth. So anything that was not supported by statute and maybe reg level was taken out.
So to add a question to American Community Survey, I don't know if they are going to do the same kind of thing. I kind of expect that they would, but they have got questions on disability already. So if they are able to add other kinds of questions, I think that definitely would be useful for what you said, the sample size issue.
DR. MAYS: Bob.
DR. HUNGATE: I had two questions that may stand more for my own ignorance than anything else, but I am going to steer into them anyway.
In the Census data, the granularity of data collected for Asian is much greater than that for black. For instance, I don't see Ghanan, and I don't know what has caused that distinction, and is there a change under way there to get more granularity in the black data. That is question one.
MR. DAUS: There is another set of data called ancestry data. That is on the long form, not on the short form. That is where you get African ancestry, European ancestry. You don't get Asian ancestry because that is on the short form.
DR. HUNGATE: So it is somewhere. I noticed that a lot of immigrants in New England from Ghana and different places, and they are recent. It is not so much ancestry; it is current culture.
The second question relates to the suggestion that Dr. Tran made on translation of questionnaires. I find that very interesting and an intriguing way to approach the problem of under sampling of populations.
On the plane on the way out, I was reading the newspaper, and I see where Lightening Flic Wilson, who is the last fluent speaker of Wampanog language, died. He was a direct descendent of the Massasoid. That is a really small population, and there is no way that sampling is going to get at it. Their language is very unique.
Two questions. Is there a definitive listing of languages that are recognized?
MR. DAUS: Yes, the Census does collect language data as well. So it does have a list of I don't know how many, hundreds. And interestingly enough, Native Hawaiian is not one of them.
DR. HUNGATE: But there is a language; it is not there.
MR. DAUS: Right.
DR. HUNGATE: So the list is not complete.
MR. DAUS: That's right.
DR. HUNGATE: So there is not a complete list. That troubles me a little bit, because then you are working from -- you know you are making more approximations someplace along the line.
The other part of this is that you collect data so someone can act on the data. The most likely people to act are those that are in the center of the population that you are involved with, in the geography itself. So the idea of making an effective translation available supporting that to augment the data collection within the community in ways that would be comparable seems to me to be a very attractive system design approach to get at it.
One of the questions that might be answered in connection with that is, we have argued for over sampling, but we haven't I think looked at how many populations would you have to over sample, and what would be the total increase in the number of questionnaires that would have to be -- what would be the cost of doing over sampling.
I guess I am just raising a subject for discussion and am interested in your thoughts, because I'm sure you have thought about it.
MR. DAUS: Yes. I would ask those questions to the people who did CHIS. You may have had that presentation already, but they did translate into six languages, and they had surveyors who spoke language -- that were trained to do surveys in their language. In this first iteration, they got a pretty good sample size for everything except Cambodian, I think.
So I think that would be really illustrative, what were the lessons they learned in terms of whether the translations were even useful, did they like being called on the phone versus visited, things like that.
I know that there are some other localities trying to do similar kinds of outreach. So the reason we made the suggestion about disseminating valid translations is that it is hard enough to do a survey in English; to actually have to translate that and interpret that for another language takes a lot of work. To the extent that it can be used for another purpose, I think that would be useful.
DR. HUNGATE: It seemed to me in thinking about that that if you had an exhaustive list of languages, then you could pursue to see if there is a partnership interest in the translation of a particular language, so that you knew you had the right -- and then a way to make it work. The way in which you go about it is deciding whether it is going to be effective.
DR. MAYS: Edna.
DR. PAISANO: I had two questions, but Nancy Breen asked my first one about health questions on the American Community Survey.
The other question I have in relation to the American Community Survey, is it being conducted in the Pacific Islands as well? I know it will be in Hawaii, but is it being conducted in American Samoa and Guam?
MR. DAUS: I don't know. That's a good question. I'll find out.
MR. HITCHCOCK: You mentioned the HHS Data Council at one point. We had tried to schedule a presentation on the American Community Survey for yesterday's Data Council meeting back in D.C., and we couldn't get representatives to come. But we are scheduling it for December, Edna. You sit on the Council, so you will be able to hear a lot of the answers to these questions.
DR. MAYS: Do we have any questions from members in the audience?
I want to ask a couple that have to do specifically with the recommendations. Let's start with the one that says, convene experts to determine the solutions to the methodological problems posed by small populations. I have two questions. Do you have specific methodological issues that you would like to see covered? And two, what is your suggestion of how we find those experts?
MR. DAUS: I'm not a researcher. I did take a methods class, and I understand sampling and how large numbers make your day. But I also know that there are people who have worked on -- I forget what they are called, but basically statistical methods for rare populations.
So what we want to do is put together the brain power to figure out what that might be.
DR. MAYS: I guess I'm asking if there is a possibility for that. If you have specifics, it would be useful. If you don't have them today, if you have specifics it would be useful if you actually got them to us, because there is a possibility that this might go forth. So while we have you thinking about it, it would be great to find out if as users you see very specific methodological problems that you think should be pursued, and two, who individuals are that have the expertise to talk about this.
MR. DAUS: Elena is right here, you have one there. But I think we have access to -- we work with some researchers, and we are actually convening some HIV/AIDS researchers on Sunday. So I think that we can pose the question to people that we know, to see number one, what kinds of issues they would be interested in, in specific, to answer your question, and also if they know others who might be interested in that kind of committee.
DR. MAYS: We would be interested in receiving that. Do you want to say something?
MS. TRAN: Yes. I just want to reiterate the information from Gem, to invite you to come to -- it is held this coming Sunday, Sunday from nine to 11. It is a group of researchers on HIV, but to think about research in small minority populations, small populations. The address is 450 Sutter, and on the sixth floor.
DR. MAYS: Let me pursue another one of your recommendations, that is, conduct more small targeted surveys that would assess populations which we don't normally have in any sizable numbers. Can you tell us specifically which populations you are suggesting?
MR. DAUS: In most cases it will be the newer populations, the Southeast Asians and the Pacific Islanders. They are not new, but those are usually where we don't have anything. So I would recommend that.
The other connection that has to be made there is, Healthy People 2010 only uses national data sets. So what we would like to see is, is there some sort of addendum or other way that we can say that for this particular objective we don't have national data, but there is some local data or some other data that obviously is only -- it has its limitations, but it might shed some light on the progress for this objective, for this population.
DR. MAYS: Your recommendation on evaluating the previous recommendations on a report that this committee did, again, do you have any specific things that you want us to look at, or anything that is particularly bothersome? Is it determining whether or not those recommendations have been implemented?
MR. DAUS: Yes, in particular -- and I think Christina mentioned this -- to what extent have they gotten the technical assistance, the personnel, the training, to do that kind of data gathering.
I know for example that Guam recently had a visit from CDC to help them set up their surveillance systems for HIV. I think also as well for one of the Marshalls had a similar visit recently. So we would be interested to see how have they grown, so that it is not always a negative picture. I do think there has been some progress made, but we'd like to be able to see that.
DR. MAYS: Anything else? I want to thank you for spending time with us today. It has been very useful. I can say that in particular, your recommendations are well welcomed. You hit very good points, some of which the committee itself has made recommendations.
I will ask Gracie White to share with you for example the letter that we did send to the Secretary about the targeted surveys, so it is something that we are thinking about, and even trying to follow up on. So that was why I was asking you some of those questions.
So this has been very useful, and we greatly appreciate your time, so thank you both for being here.
MR. DAUS: Thank you.
DR. MAYS: We should take five minutes, just so the next speaker can gets set up also. So we'll take a five-minute break to let her switch and get set up, and then we'll get started again, and we will break for lunch at 12:30.
(Brief recess.)
DR. MAYS: We are fortunate to have Elena Yu with us. Some of you may know that she has a background of being with NCHS at one point in time, so I think she is now on both sides of this. So I think that she can be very helpful, in the sense of, as we ask for everything we can ask for, she can also understand the other side, what really happens. So it is very nice to have her with us.
Elena has been -- I saw her do a presentation on the issue of looking at some of the measurement and classification issues, and is exactly the right person to be here with us for this. I really do appreciate your taking the time and pulling this presentation together, so thank you very much. So why don't we start?
Should I say for the sake of Dawn that while she is a professor at San Diego State University, she is also a student at Johns Hopkins.
DR. STEINWACHS: And I should say for Johns Hopkins that we are lucky to have her.
Agenda Item: ANHOPI Measurement and Classification Issues: Elena Yu
DR. YU: Thank you. I hope you all had a very large breakfast, because this session is scheduled for an hour, and we are not supposed to break until 12:30.
I had three versions of my presentation, long, longer and longest. Originally I was prepared to give a 30-minute talk, but this morning I got a message that I should make it longer. So you are going to hear my medium-length presentation on this subject.
I received the hearing questions last Friday, and I did not know how strictly I was to follow those until a confirmation set of hearing questions came to me on Monday from Vickie Mays. I know that this is serious stuff, stuff that I should stick to the theme of these hearings, so I have.
First let me give you an overview of my entire presentation, and we can swing through some of the information that has already been provided by Gem Daus and by Christina Perez and Ho Tran. I would like to just very quickly show the demographic growth rate, population characteristics, and identify the classification and identification issues and what is the relevance in terms of health for wanting to classify and measure ANHOPIs.
Then I would like to quickly move to the meat of my presentation, which is data and data needs, and finally probably drop a few bombshells in terms of recommendations, because my recommendations will call for major paradigm shifts. Unless we really undertake these paradigm shifts, we will never get out of the hole that we have been in since 1960s when NCHS was created.
Asian Americans, Native Hawaiian and other Pacific Islanders are the second fastest growing minority in the United States. The population increased by my calculation by 76 percent from 1990 to the year 2000. They surpassed the growth rate of Latinos, which is 58 percent, and their number is estimated at close to 30 million, if you include multiracial ANHOPIs.
Fourteen percent of the Asian Americans and 54 percent of ANHOPIs are multiracial, by their own self reports. Immigration contributed about 86 percent of that growth. This has significant implications in terms of surveys you want to conduct, in terms of risk factors and risk markers for health, and in terms of access to care.
The Census data showed that the count of ANHOPIs are 23 percent Chinese, 17 percent Filipinos, 16 percent Indians, 11 percent Vietnamese, 10 percent Koreans, seven percent Japanese and about four percent Hawaiians, and the remaining are others.
Census terminology has changed over time. First we were referred to as Asians, which implied that we were aliens, that we were foreigners, and that we were outsiders. It negates the fact that many of us are U.S. born and some of us are U.S. citizens. Native Hawaiians and other Pacific Islanders, ANHOPI, carries a different connotation and this identification was important for Native Hawaiians and other Pacific Islanders, because the concept of territorial preemption is implied in the identification of the population. They were here before the explorers came, they were, they are, the original inhabitants, and they come from a mixture of Polynesian, Micronesian and Melanesian cultures.
Throughout my presentation, we need to distinguish between ANHOPI and ANHOPI, that is, whether we are showing data including Asians or excluding Asians.
Population characteristics; I'm just going to go over some important points with regards to health that I think are also important to take account of and to consider and to remember when we play health surveys.
One, this population has very large household size, compared to the general U.S. population. 36 percent of them live in households with four or more persons, 19 percent of them live in households with three or more persons. Two-thirds of them speak a non-English language. ANHOPIs 25 years and older are two times more likely than non-Hispanic whites to have at least a college education, but at the other extreme of the spectrum, two times more likely to have had ninth grade education or less. So you are dealing with a population that is extremely diverse at both ends o the educational continuum.
There are a bimodal income and a bimodal employment distribution as well. Many of them are professionals. Many of them are also service workers or laborers, or just simply unskilled workers. They are two times more likely than non-Hispanic whites to be renters, and in the metro areas they pay 20 percent higher rent than non-Hispanic whites. In the suburbs they pay 30 percent more. This is a sign of whatever you call it, but it means that the same income level of $50,000 a year buys you different goods and different houses, and you don't have the same purchasing power. So therefore, any statistical analysis that controls for income does not really control for the population differences and other correlates of that income.
Classification methods. There are many papers written on classification methods. One of them by Vickie Mays compared four different methods of classifying ANHOPIs, whether it is the group that they most identify with, whether you pick the rarest group and give priority in the identification, or whether you use the California Department of Finance, which gives precedence to Latino ethnicity and inflates the Latino numbers, because many Filipinos could be classified as Latinos, or you use a combination of the second and the third method.
Now, having gone through the paper however, I would like to stress the following, that the classification methods really did not significantly impact the health estimates for Asian Americans in CHIS 2001. It did not impact the percent non-elderly adults reporting no insurance, it did not impact the percent of adults with no usual source of health care, the percent of adults reporting asthma diagnosis, percent of women reporting a Pap test in the past year, percent of men older than 50 years old who reported a PSA test. In other words, whatever method you use to classify them, Asian Americans are low by all health indicators.
So what is the big difference for Asian Americans? That is a strange question for me to ask, given that I am an epidemiologist, and that I pay attention to methods. However, they do make a significant difference for the Native Hawaiian and other Pacific Islanders.
The variability in estimates range from two percent to ten percent of the estimates. That is how big a difference they make. If I were to pick the rarest group and give that the priority, I would beef up my estimates by ten percent. If I don't, I would deflate it by two percent. So that is the range of variability.
If confidence intervals were included and calculated or could be calculated, then these confidence intervals in my opinion would probably be overlapping, so what is the big deal? Differences for ANHOPIs. The method of classifying ANHOPIs does affect health estimates, and only certain health estimates. In small populations like ANHOPIs, a tiny numerical change will result in a big percentage change, and that is the bottom line message I would like the group to have. But for Asian Americans, they are going to be pretty much the same.
So regardless of the classification method, for example, the percentage of ANHOPIs 18 years and older reporting a Pap test in the past year is lowest in the CHIS 2001 for Asians, followed by Native Hawaiian, compared with Latino, whites and other. I think that we should not lose the substance of the message in our strive to measure API or ANHOPIs accurately.
The critical question is, have we lost sight of what is important by focusing too much time and effort on the classification and measurement of ANHOPIs, such that we neglect the substance of these issues. The Chinese have an expression, (foreign phrase), meaning, it is the tip of the horn of a buffalo. What scholars have been doing has been to crawl into that little space and argue about how big that space is, instead of looking how big the buffalo is. That is a little bit of culture here.
Imprecision exists with every method of classification and measurement, and we have to accept that. ANHOPI classification can be improved however by applying a consistent set of questions. Ask about place of birth to determine nativity, U.S. born or foreign born. That liver cancer data, for example, somebody asked a very good question, and I have an answer for that later on which I shall talk about.
You should also ask about language spoken as a child, because that really determines your mind set, and essentially is correlated with many other factors that are related to health. English language proficiency is very important, because it in some ways influences your access and ability to absorb health information that are out there for the public to consume. Levels of education carries place of birth, because that helps to determine what generation are you in the United States, and urban-rural origin.
So race and ethnicity are social constructions that go beyond biology and genetics. They change with time and place. That is something we need to accept. It is not just unique to only ANHOPIs; it occurs with all groups.
We need transparency in the classification and measurement That is, every publication that studies AAPIs or ANHOPIs should specify how they classify and how they identify these populations. That should be explicitly stated.
The best method of classification depends on the research question. There is no one best method, anymore than there is any one best strategy to study a population. It depends on your research question. Data obtained using different classification methods should not be compared, or should be compared with caution. You should always stress where the differences could lie.
So a critical issue for me is health disparities; do ANHOPIs experience any health disparities compared with other racial and ethnic groups? What barriers exist that deprive them of equal access to the U.S. health care system? Do they receive different or inferior treatment, given the same diagnosis, and why? Do they have different and less desirable outcomes, given the same treatment and why?
Some would argue that lack of agreed-upon method of classification may harm comparability of findings across settings, and therefore we should spend more resources on identifying them and measuring them. Yes, that is important, but my question is, what can we compare if we do not even have population focused surveys to produce the most fundamental baseline or descriptive data for Native Hawaiians and other Pacific Islanders?
The next question people raise is, what about multiple race? Isn't that a confusion? You couldn't tell anymore just how many of them are out there? Well, is it not informative if I tell you that my review of the literature shows me that ANHOPI adolescents who identify themselves as belonging to a multiple race compared to those who identify themselves as belonging to a single race are consistently reported to have a higher rate of depression, greater rate of substance abuse, more school dropouts and out of wedlock pregnancies and pregnancy complications. Are the information not useful and not enough for you to plan for certain kinds of services? I say it is enough, and you can go further. Yes, we can go further if we have resources, but given the limited resources and the $87 billion deficit that we are in, I think that is good enough as a start, and we should get going.
If differences exist, is there inequity in the differences observed between ANHOPI and white American population? Do differences within the ANHOPI population reflect disparities? To what do we attribute these disparities, and what are the social significance of these disparities? I think these are the substantive issues that we should be focusing on.
We should remember always that race and ethnicity is merely a marker. We always hear in epidemiology that all diseases and health have a genetic basis. I sit in the audience and I wonder, don't all diseases have a behavioral basis as well? Would we be better off to devote as much resources to behavioral health research as we do to genetic research, because at least -- we cannot change our genes, but we can change our behavior and lifestyles.
What are the important identifiers of health risk in ANHOPIs? Your nativity? Are you born inside the Pacific Islands or outside the Pacific Islands? We need to know where the parents are born, so we can determine their immigrant status. For example, my view of the literature shows that the Filipinos living in Guam are not much different than the Samoans living in California in terms of access to care. That means there is something about being new in a territory that makes you less knowledgeable about where to go for health care, and that that is an important factor to take account.
Generation; first generation, second generation, third, fourth, fifth for the Japanese, sixth generation. That is important, because it tells you how much of that language they know, how much of the traditions they have kept, and whether they are more Americanized in their diet, in their physical activity level than they are compared to the first generation.
And language. Command of the English language is important, because that almost tells you whether they are going to be included in the health surveys or excluded. Rural/urban area, where did they live the longest before they were age 21? That is almost a very good indicator of adaptability. It is a proxy measure when studies do not have an acculturation measure, and also how well integrated they are into the U.S. society.
There are other relevant identifiers of health risk. Frequent or infrequent use of traditional healers and medicine before age 21, and health literacy, continued use of traditional healers or medicine after age 21, dietary preferences and physical activity, socioeconomic status.
So to sum up, there are many non-genetic confounders that we must collect when we study ANHOPIs. We should ask about nativity, generation in the United States, culture, English proficiency, health literacy, socioeconomic status, dietary preferences, region of origin, whether it is urban or rural, and use of traditional medicine.
The importance of culture. Many researchers on minority health have pointed out repeatedly that if we could just control for SES, health disparities would disappear. Such an attitude in my opinion negates the relevance and ubiquity of language and cultural influences on health. The problem is how to control for SES when the playing field is not level. Minorities have different purchasing power than non-minorities, so controlling for income does not make the two groups comparable, really. There is residual confounding.
Let me illustrate that with this data on health insurance from the CPS-2001, that showed poor people without health insurance for the entire year 2000 by ethnicity. Everybody here now in this chart is equally poor. So that is controlled for SES, controlled for income. So when you control for income, blacks and non-Hispanic whites have the same level of uninsured, but Asian Pacific Islanders and Latinos have higher rates of uninsured. That shows you that controlling for income will not eliminate the disparities that you are seeing. This is primary access to care. Who has access to care? A large percentage of Asians and Pacific Islanders and Latinos do not have the first access to care.
The whole issue of cultural competence is ignored when you just say that all you have to do when you analyze ethnic data is to control for SES, because cultural competence on the part of the health care system is an important contributor to health disparities that we must measure, that we must document, and we must quantify. Where is the data for ANHOPIs?
National surveys of the U.S. population would never in my opinion include sufficient number of ANHOPIs to allow for proper analysis. Routine government surveys sample mostly English-speaking Asian Americans and Pacific Islanders. Among the Filipinos who speak Spanish, I can tell you what their age would be; they would be older than I am. I went to schools in the Philippines, I finished college in the Philippines. I was the last cohort of graduates required to take four years of Spanish in college, one year of Spanish in high school, in order to graduate, the last cohort. That means anybody younger than me cannot speak Spanish, but my generation and older, yes, they could speak a smattering of Spanish. So they would not be included in most NCHS surveys so far.
Geographic coverage of many government surveys is the entire United States. But ANHOPIs are not distributed throughout the entire United States, so it is not loaded -- the cards are not stacked up to the favor of Asian Americans and Pacific Islanders. The kind of sample used by NCHS, which is, sample the population in proportion to the representation in the population, will always result in too few ANHOPIs, and it will always show unreliable estimates for ANHOPIs. It will always show very wide confidence intervals for this group, no matter how you massage that data.
What are some of the barriers to care for ANHOPIs? Who enters the health care system? Available CPS surveys show that non-U.S. citizens are two times more likely to be uninsured than citizens. One-third of the ANHOPIs who live within 100 percent below the federal poverty level were uninsured. The association between education and insurance in this population is actually U-shaped.
What do I mean by that? The largest percentage of uninsured is found among those with lower level of education, and those with the highest level of education. Why? People with a high level of education end up being entrepreneurs, when they cannot find jobs that they qualify for in the U.S. job markets. They send up their own companies. They are high education, they are immigrants, they are healthy. Why should they pay thousands of dollars for health insurance? What would they get out of it?
At one time when I was funded for six years on soft money, every year I never know where my salary for next year was going to come from, I did not pay for health insurance. Why should I? I'm healthy. I want to go see a doctor when it is due, schedule you for an appointment two months from now, when I am sick right now, and I speak English well. So I cannot cope with that bureaucracy; I'd rather fly home. An airline ticket costs me $600. That is cheaper than a health insurance premium I have to pay every month. I fly home, I get my traditional health care. I was raised in traditional Chinese medicine until age 21 when I came to this country. I do not need American doctors, who do not have a prevention orientation to health.
I am trying to share with you the AAPI perspective. I am considered an educated AAPI. What more of the others who are less educated and less exposed to Western cultures?
Children's insurance. One out of every four AAPI children are uninsured, compared to one out of every six for non-Hispanic whites in the United States. This is the latest data. CHIP health insurance extends to only 7.2 percent of AAPI children, compared to one-third of black Americans and one-fourth of Latino children. So that is the extent of uninsurance you are seeing among children of ANHOPI descent.
Barriers to secondary access. There is a study published in 2000 showing that among patients who received managed care in the past year, from 48 physician groups in California and five other states, five measures of secondary access was the worst for AAPIs. These are preventive services, time related access for routine care or general need, telephone access, specialty services, and general access.
The Asian race is significantly associated with less counselling, and medical encounter that requires verbal communication and longer physician-patient contacts, as well as a good grasp of the patient's culture and values. This is a study conducted in 2000.
Let's take smoking cessation, which is a big thing in this country, and which has been very successful in the general U.S. population. Among smokers, smoking cessation is fundamental to maintaining good health. The percentage of smokers in a health maintenance plan is therefore, in my opinion, a very good proxy of the success of mainstream health professionals in lowering smoking prevalence and improving the health of participants.
Let's look at data for Asian Americans. In a Northern California health plan, I shall not name which one, everybody knows it, smoking prevalence of AAPI subgroups is 20.1 percent for Japanese, 18.7 percent for Filipinos, 13.9 percent for South Asians, and 23.1 percent for Asians, in a health plan; these are people who were all insured. Compare that to the Healthy People objective of 12 percent. AAPI females are becoming smokers, 18.6 percent in Japanese-Americans, 34 among Native Hawaiians.
So let's take a very quick look at the initiative to eliminate racial and ethnic health disparities. Let me cover just the six areas, and very quickly fly through some of the data, just to give you a flavor of what do we know and what don't we know, and what do we need to know.
The leading causes of death for Asian Americans and Pacific Islanders is cancer, 27 percent, heart disease, 26 percent, stroke, nine percent, accidents, five percent, chronic lower respiratory disease, three percent, pneumonia and influenza, three percent, diabetes, three percent. So while in the general U.S. population, the leading cause of death is heart disease, in this population it is cancer competing with heart disease.
Myth. Asian Americans have a low infant mortality rate. They are therefore a healthy population, and do not experience health disparities. This is the most common data presented by everyone, including NCHS researchers, about how healthy Asians are.
What did I find? Mortality data suffered from misclassification problems that do affect estimates of racial infant mortality. Under reporting errors are reproducible when collection measures are not taken over the years. Asian Pacific Islanders differ in infant mortality rates, and that variability is not reflected when you lump them all together as one group, because the groups that have the worst infant mortalities are smaller in numbers. So when you take an average, that average is inflated, or looks good. So high infant mortality rates and adverse maternal risk factors are found in a group that today is classified by NCHS as other AAPI, so we will never know who they are; we just know that they are the residuals of what they do not classify.
One out of every five AAPI infants born in the normal weight range died in the post neonatal period. Every physician in practice will tell you a post neonatal death is less likely to be due to genetic factors and more likely to be due to environmental factors.
The infant mortality rate due to birth defects is the second highest for AAPIs after Native Americans. In the 35 to 39 year age group, AAPI mothers have two times pregnancy related mortality per 1,000 live births, compared to non-Hispanic whites. More Asian Americans and Pacific Islanders give birth in the age range of 35 to 39; there are more older mothers giving birth among Asian Pacific Islanders. That may explain the higher birth defect rates, and that may explain greater complications as well. But we really do not have systematic studies. We just know from the body of medical literature that these factors are associated, and we know these disparate facts from statistics, but no one has put them together. It is difficult to go beyond these numbers to do any studies with the vital statistics data.
Single gene disorder. Thalassemia is a single gene disorder that disproportionately affects all Asian Americans and Pacific Islanders. The reported prevalence overseas for Asians ranges from three percent and 40 percent of the populations studied, depending on how they are sampled.
Sickle cell disease, let me show you as a contrast. We all hear about sickle cell disease among African Americans. It occurs in one out of 390 births to African Americans in California, but thalassemia occurs in one out of 160 Laotian births. How much do we know about it? I have thalassemia. It was misdiagnosed for 27 years of my life as anemia, and I was given iron pills, iron injections, all kinds of treatment. Everybody missed the diagnosis. When I finally was diagnosed with thalassemia by a Canadian physician in Canada, and they have a very good health care system, my brother, who is a physician practicing in the United States in Ohio, said it is impossible, because his medical training told him that thalassemia is a Mediterranean disease. So he said, where is our Mediterranean ancestry? I said, maybe we have some Arab blood, because after all, I was born in a village where in the 13th century, an Arab was mayor, during the silk trade, by the sea route.
So anyway, it was an education for him, an eye-opener for him. He is a U.S. trained physician, he is not foreign trained.
Asian Americans and Pacific Islanders have low death rates for cancer, CVD and stroke. That is another myth that we get all the time from many presentations at meetings. Let me show you what my studies found. These are from NCHS reports on deaths, knowing that they are under reporting, and there are some problems there, but nevertheless they are very informative.
I'd like you to concentrate on the group 45 to 54. These are the baby boomer generation. Look at that yellow bar. It is 53 percent of women, AAPI females, died of cancer. That is their leading cause of death, is cancer, of those who died of cancer. You go upwards, 45 percent, 36 percent, 23 percent, so cancer is a major killer, is the major killer for women in this population, and the question is why.
The top two leading causes of death for AAPIs are CVD and cancer, and the distributions change by age. So if you lump them all together just for the age group from 25 and above, it is heart disease, but then if you break it down, you see heart disease really starts to take over cancer as a leading cause of death, is at 65 and above. But Asians don't live long enough to die of heart disease; they die first of cancer.
What about stroke? We heard so much about how good the Japanese diet is, and how low their cardiovascular disease rate is. But few people know that the stroke rate is very high in Japan, as well as among Japanese in California and Japanese in Hawaii.
If you look at the death rate due to stroke, proportion of the population within the Asian community compared to the white community who die of stroke, for every age group from 25 onwards, you see that the Asians have very high proportions dying of stroke. This is for females, and the next chart I didn't show is for males.
Now, what does the clinical preventive services task force recommend? This is the most authoritative source about how to maintain your health. The only preventions proven to reduce coronary events in asymptomatic persons are modifications of risk factors such as smoking, high cholesterol, elevated blood pressure, poor diet and nutrition, overweight and obesity and physical inactivity. Smoking cessation, cholesterol and blood pressure reduction for all with risk factors are highly recommended by the clinical preventive services task force.
Well, there is another myth, that Asian Americans do not have body weight problems, and therefore diabetes is not a major health problem for them. If you look at the death due to diabetes, you see that proportion is not small for Asian Americans. It exceeded the rate for the proportion of whites dying of diabetes. So diabetes is a serious problem for Asian Americans, despite the fact that many of them are thin.
On the other extreme, Pacific Islanders are heavy. So the Asian population may be small and thin, many of them have diabetes, and you have the other extreme, where obesity is associated with diabetes.
How do we prevent diabetes? Adoption of a healthy lifestyle, which includes early detection of glucose intolerance, identification of insulin resistance syndrome, proper diet, regular exercise program, weight reduction, periodic monitoring of blood glucose levels, and adherence to all medications. These are standard recommendations, and the government has been pushing for this. The HHS has been pushing for this.
We know from studies that for persons at risk for diabetes, the effect of lifestyle change, at least seven percent reduction in weight and 150 minutes of physical activity per week, is as good as, if not slightly better than, medication, Metformin, in controlling blood glucose. This came from a big study published in the New England Journal of Medicine. I should have cited it, I forgot.
For persons diagnosed with diabetes, the effect of exercise was better than Metformin when they compared, when they ran clinical trials comparing exercise with Metformin, the leading diabetes medication.
My meta analysis showed -- and I looked at only clinical trials of diagnosed diabetes and physical exercise for the whole world. I found only seven studies. This was a class project I did at Hopkins, with three other students. We read the same papers, but we each do our own analysis and paper writing, and so this is my analysis, which may not be the same as that of my friends, classmates.
We found altogether only seven studies of clinical trials on diagnosed diabetes and exercise. Many of them were poorly done. They were not done long enough, because HBA-1C, which is the outcome measure that measures your blood glucose levels in the past two or three months, many of these studies on exercise were conducted for so short a period, two weeks, three weeks, four weeks, not long enough to show an effect. Yet, it showed an effect when you do a pulled analysis and you take account of variance and the small sample size in there. In fact, it showed a reduction of .7 percent. If you know diabetes and if you know your HBA-1C, you know that the number looks small, but it is a very significant change.
So there is in fact, based on the studies in England and studies that are now coming out from other countries, there is no threshold for glucose control. A one percent reduction in HBA-1C is associated with a 37 percent reduction in the risk for microvascular complications, and a 21 percent decrease in the risk for any end point or death related to diabetes. So the association between HBA-1C and mortality are stronger than any documented association for cholesterol, for BMI, for blood pressure and mortality. If you really want to live long, control your glucose level.
What about HIV/AIDS in the Asian population? It is the sixth leading cause of death for men 25 to 34 years old. It is the eighth leading cause of death for men 35 to 44 years old. Fifty-three percent of the AIDS cases occur in just five SMAs, Los Angeles, Long Beach, San Francisco, Honolulu, New York City and San Diego.
Facts about AAPI HIV/AIDS. The actual numbers are numerically small, but four times as many AAPIs diagnosed with AIDS also have TB, compared to white Americans. Men having sex with men followed by intravenous drug users is the predominant form of exposure category for Asians. Asian Pacific Islanders are two times as likely as whites to report having acquired the disease through heterosexual contacts, because many of the Asian at risk populations are bisexual.
We have extremely limited data on AAPI HIV and AIDS. Access to care issues in this population have not been the focus of research activities in the past two decades. Citizenship and legal immigration status may have restricted eligibility to publicly funded programs which supply the data for routine tabulations that we see.
The other question that is related to issues of health disparities among this population is the question of whose disparities are we talking about. After all, President Clinton only mentioned six major areas of disparities, and there are more areas of disparities for Asian Americans.
Asian Americans and Pacific Islanders have disproportionately higher rates of avoidable mortality and preventable diseases due to cervical cancer, liver cancer, because of their exposure to the hepatitis-B virus, tuberculosis, hepatitis-B virus infection, pneumonia and influenza and substance abuse.
To illustrate for tuberculosis, the AAPI TB case rates are about 18 times higher than those of non-Hispanic whites. Foreign born AAPIs are six times more likely to have TB compared to U.S. born AAPIs. More than a third of the AAPI TB cases come from just five countries: Philippines, Vietnam, India, China and Korea.
This graphically illustrates the TB case rates for Asian Americans. The blue bars are Asians, and look how low it is for whites. That is a health disparity issue that was never in Clinton's initiative to eliminate racial and ethnic disparities for Asian Americans.
This is another one for females. It shows a similar pattern. For influenza, I am looking at 65 and over, because we should all be getting the flu vaccines to help prevent complications from influenza. This would indicate to me that this is a population that is not getting flu vaccines in the same frequency as the general U.S. population. It pinpoints an area of health education, and maybe public health practice that we should be doing, because more AAPIs are proportionately dying off from pneumonia and influenza than white Americans after the age of 55.
Recommendations. What are my recommendations to NCHS? It is about time we start thinking about doing special large scale population focused surveys on ANHOPIs, instead of just continually including them in large U.S. populations. We have done so since the 1960s. NCHS was established in 1959. We have done so since the 1960s.
I worked at NCHS from 1981 to '83. I looked at this issue. The questions I raised then are still here today, and that surprises me, that no one has thought of special legislation to do large scale population focused surveys. We have to stop thinking about being included in the major community surveys being conducted in the United States, because we are never going to grow in such large numbers as to be statistically significant in their analysis. So therefore, our health problems will never show up with the same stunning message that it is showing up for black Americans, for Latinos and other groups.
We need special legislation. We need to be working with Asian American lawyers and white American lawyers and black American lawyers to get laws passed, to authorize Congressional funding to NCHS, to the Census, to CDC, to conduct special surveys on ANHOPIs.
Self identification of ANHOPIs is important, instead of observer identification. No one would know looking at me that I have a Filipino cultural background. No one would know that I was raised in a Filipino family. Yet, I am. So these are issues we need to be aware of.
Use of multiple access of classification and health risk identifiers should be included in all health surveys in order to improve racial and ethnic classification and also for service delivery and followup later on of their health problems. Those health identifiers I mentioned earlier, nativity and all those non-generic confounders.
Where do we find the Asians to do our surveys? It is actually both difficult and easy. If you stop thinking about the whole United States and you concentrate on where are they densely populated, then you know where they are. If you look at the ten places with the highest percentage of Asians, nine out of ten is in California. The tenth one is in Hawaii. If you look at the top ten places with the highest percentage of Native Hawaiians and other Pacific Islanders, you will see Hawaii, you see Utah, you see California, Utah again, and California. So you know where to go. It is very easy. You don't need 50 states. The top ten places with the largest number of Asians: New York, Los Angeles, San Jose, San Francisco, Honolulu, San Diego, Chicago, Houston, Seattle, Fremont, California. Top ten places with the largest Pacific Islanders: Honolulu, New York, Los Angeles, San Diego, Long Beach, San Jose, Sacramento, San Francisco, Seattle, Heyward, California.
Of the ten largest places, San Diego has the largest proportion of Pacific Islanders. So if you only have money to do one study, you should know where to go. Los Angeles, Phoenix, that is the order in which you find the ANHOPIs.
So whether they are classified alone or in combination, there is such a fuss about, how many multiracial, how confusing it is to have multiracial compared to single. However you look at it, you are looking at 73 percent or 76 percent living in the West. It is three-quarters of the population.
Over half of the Pacific Islanders live in just two states. Eighty percent of the ANHOPIs live in just ten states. So if you have the money to go for ten states, go for ten states, but if you don't, go for two states.
What are the other methodological issues that I would like to raise? One is, framing the research questions is very important. Who frames the question, and why is that question being framed the way it is? Because that affects what kinds of answers we get.
Sample size and sampling, research design, rationale for inclusion, eligibility for participation and analysis of data. Framing the question. I will use one study as an example. Scientific naivete, blind compliance with NIH rules about the inclusion of minorities in clinical trials. Difficulty in finding study subjects or a desire to extend equity and access to care, that led to the encouragement of ANHOPI participation in HRT trials in the women's health initiative.
My question, where are the necessary descriptive and symptom prevalence data to justify ANHOPI participation? Do we have any data to show that a large proportion of the baby boomers are suffering from the same kind of menopausal symptoms that white and black women are suffering from, like flushing and I don't know what else, because I did not experience them.
Are clinical trials without supporting data from prevalence and case control studies scientifically defensible and ethically justifiable? Is drugs the only treatment approach for menopausal symptoms, and to many conditions that contribute to ANHOPI health disparities? Is this what we call public health? Is this what public health is all about? Drugs and clinical trials, and drugs and giving drugs to people to control their health conditions.
I'm not putting down drugs. I think under certain conditions, drugs are important. But I think there are preventive measures that we could take that we have largely ignored because many behavioral scientists who enter public health do not have sufficient credentials to question existing practices, or do not have the guts, as I do, and are not afraid of the consequences of losing their jobs when they raise those questions.
Why do ANHOPIs who exercise and maintain a slim body weight in my observation not experience the kinds of menopausal symptoms that are often reported by white and black Americans? Could there be an association?
I'll tell you how this question came through. My doctor told me when I was in my 40s that I had to report to him the moment I felt flushing, and I said, what is flushing? He described to me, you feel someone opened up the oven in front of you and closed it right away. I waited ten years, 11 years, nothing happened. So I went and talked to many older Asian women. I said, have you experienced this? They were living overseas and they said, is this what you learn in American universities? Is that what epidemiology is about? I really want to know, how did you experience menopause? They said, one day I woke up, I found out that I missed it for two months, and that was it. That sentence is repeated over and over again.
Then I talked to American women, and they talked to me about sweating, about flushing, about not being able to sleep, about I don't know what else. I forgot now, I can't remember anymore. I said, are Americans making this up, or what is going on?
So the big discovery came about when I went on a cruise. This was a Yangtze River cruise in China, where half of the passengers happened to be Americans, and half were Chinese from different parts of the world. They were Chinese from Mainland China, Chinese from Hong Kong, Chinese from Taiwan, Chinese from Canada and Chinese from the United States.
On one of those boring days, one of the admirals came up to me and said, we would like you to give a talk, because we found out you are an epidemiologist, and we never know what that is, so can you give us a talk on any topic you want. So I said, what is the topic that American women want to hear about? They said, hormone replacement therapy.
This was May of last year. So I went up and I gave a talk. In the middle of my talk, a Chinese lady asked, what is hormone replacement therapy? She came from Taiwan. The Americans looked so surprised, that this woman never heard of it. So I explained. The next question came from the Chinese, why do American women take it? So I threw that question on the American audience, and they explained they have symptoms. I said, could you please explain the symptoms, and they said, flushing. I translated this, and everybody looked -- then the Americans say, don't they have it? The Chinese said no.
I said, wait, how many Chinese women have it? I asked them to raise their hand. Only one woman raised her hand. That woman was obese. All the other women were slim. So then one Chinese woman said, how many of the American women exercised before they went into menopause? None. Then she said to me in Chinese, don't translate this into English, but don't you think it has to do with their fatness? I said, I wish the researchers were as smart as the lay people in asking these kinds of questions.
I then asked that question when the women's health initiative investigators came to Hopkins to give a talk. The only measure they had was BMI. BMI does not measure percent body fat. I think the critical factor is percent body fat. Estrogen works well when you have body fat, according to the literature that I read. Maybe I am not good enough as an epidemiologist, haven't read enough, but that is what the literature suggests; there is an association between body fat and the beneficial effects of estrogen. So could it be that this is the missing link? Yet, the women's health initiative, according to that talk that I heard, did not collect data on percent body fat. How many million dollars was that study? I don't remember, but it was humongous.
So how a research question is framed determines the direction of research and whether or not we will find answers to the questions.
We need large sample sizes to study Asian American health disparities, sample sizes that will take account of their cultural and linguistic diversities. The CHIS has always been mentioned as something that has fulfilled that dream, because they have a very large sample size.
My issue with the CHIS, and it is not personal, it is scientific, is that because that sample size was achieved by over sampling, you end up getting more of the same people. So the data are correlated, so you are not getting the full range of variability you should be getting from the full range of variability you should be getting from the population.
We need core health surveys in ANHOPI languages, through special Congressional appropriations, in the same way that the NHANES in Hispanic was funded, in the same way that the NHIS is funded, CPS is funded, women's health initiative is funded. We need those studies. We cannot work around that issue. We have to really take the bull by the horn and face it and work towards that goal.
We should also consider alternative study designs in the meantime. Surveys in selected health plans like Kaiser Permanente in the West Coast, Oxford Health Plans in the East Coast. There are some new health plans emerging because of the mergers of several health plans now. We should really focus on those settings to collect data, because there, primary access to care has been controlled. Everybody has insurance, or they wouldn't be there. So now, given that everybody has their health insurance, how well are they being treated, given they have the same coverage now?
We need to ask that question. There are not enough studies on that.
We need case control study designs. Since we can find all the cases, what we need now is to find our controls. We need case cohort study designs. We have large scale surveys that supply you with a cohort of small numbers of Asian Americans, but nevertheless a cohort. Now how about considering case cohort study designs?
We need coordinated multi-site population focused surveys. Because Asian Americans are concentrated in only selected areas, how about picking investigators from those areas and make them all meet together regularly, consider standardizing survey questionnaires, consider training them to do research and collect data. And to follow-back mortality surveys. We have done that at NCHS. We have so many follow-back surveys on white and black infants; how about on Asian Pacific Islanders in selected areas? We need to encourage collaborations between researchers beyond one's own institution, because that is the only way we are going to get large enough numbers of Asian American subjects.
Another important methodologic issue is the question of inclusion. Do the inclusion criteria that currently limit participation to English-speaking persons, for example, in the national health interview survey and the national health and nutrition surveys conducted by NCHS, do these surveys restrict the participation of Asian Americans, by the simple fact that they only have English language instruments available.
Does the Fourteenth Amendment not require that routine health surveys be conducted in a language that would allow equal participation of ANHOPIs? I talked to some lawyers. I took a course on public health and law at Hopkins, and it was an eye-opener when the law professor says, yes, under the Fourteenth Amendment you can push for health surveys for Asian Americans. That is one of the best courses I took at Hopkins. I told that professor, I wish you would offer one more: how to develop health policies, because I would be there. They said, you have to be a lawyer. I said, there more years and $90,000; I don't have it.
What are my recommendations for research? Minimum recommendation, two super funded multi-site surveys in AAPI languages through Congressional appropriations, one focused on chronic diseases, cancer, heart disease, stroke, diabetes, substance abuse and depression. Why? Because they have common risk factors.
Two, infectious diseases, vaccine preventable diseases. There is no excuse for Asian Americans not to get the vaccines they need when these vaccines are available. It is simply that we did not reach out to them, that the mainstream society's medical care system did not get to them, and the question is, why the dickens they did not get to them.
Current state of data collection. Government surveys are the only source of large scale national data on ANHOPIs. NCHS is a major player here. California is a major potential source. The problem is that trained ANHOPI epidemiologists are not involved from conception to writeup. They are invited sometimes as consultants. They are spoken to before the proposal was submitted. Their name might even appear. But when the grant comes in, they were not told, they were not invited in the planning, they were not included.
Then when data analysis comes, they might be invited to the later planning meeting, but really, how the authorship will be divided was never discussed. So would you get involved, if you don't know how much time you should be putting in, and you are being held accountable by your employer about your travel time?
Hawaii is another major source, but again, it is too far away, and the question is, how do we gain access to those data?
Some data exists from routine government sponsored surveys and investigator funded studies, but the numbers are small and the confidence intervals are very wide. Most epidemiologists, and I would say all schools of public health are not trained to analyze data that are not normally distributed. All your statistics classes talk about normal distribution. You have to be a biostat major to take non-parametric statistics. We are not trained to analyze highly correlated data and data that are difficult to bridge with other data sets. We all know we need SUDAN, but when you go to RTI, SUDAN gives you lessons for two days. After that, you're on your own, and you have many questions and you can't answer them, and you don't know where to go.
Now, here is the bombshell. I am a full professor, tenured, and I say that universities are archaic. For minority health, for ANHOPI minority health, universities are archaic, and I'll explain why.
Many of the intellectual resources at universities are unfamiliar with minority health research issues. You would be lucky if you can find three persons outside of California, and I don't know about California, I even question California, let's just say outside California to be on the safe side from attacks, that outside of California, you would be lucky if you can find three professors who know anything about ANHOPI minority health issues to form a dissertation committee. If you cannot have that committee, how can students write their dissertations on that topic? Very few of those professors would even know how to approach the issue of minority health, especially for ANHOPIs. They know about blacks, they don't know about Latinos, they don't know about ANHOPIs.
Very few of those universities, no matter how much money they have, will be able to employ a critical mass of minority researchers as faculty members without suffering repercussions.
I sat on recruitment committees where the first sentence uttered by the chairman is, here is the ground rules. If we have two candidates of equal qualifications, one is white and one is Asian, we will vote for the white. This is the recruitment committee. I am on that committee. It is five to one. Should I vote against or for it? Do I squeal? Do you think I will get anywhere if I squeal?
This is the reality of universities. They do not truly educate or train minority health researchers to become leaders and decision makers. They train them to become very good computer data analysts. They are pigeonholed into those positions. They are considered not good enough if they don't know their SAS. If you spend your whole life doing SAS, you miss the big picture. You miss the policy issues.
On the other hand, people say, aren't there ANHOPI professors in the academic setting? Yes, there are. They are burdened with non-minority committee work. They are burdened with teaching courses that are not minority health courses, because there are not enough students interested in minority health. They are mentoring students that have language problems.
Any student that has a language problem is inevitably assigned to me, as if I speak so many languages. I do, but not that many. They have a heavy teaching load. Their courses are changed more frequently than for other groups of professors, and they have a hard time getting release time.
They have low wages. What is the average salary for a professor at many universities. This was about five years ago when I looked at the data. $60,000 a year. I think a truck driver makes more money than that.
Community involvement and public health practices are seldom regarded as productive work. These are the problems with minorities working in the setting of universities, and that is why I say, if you are serious about minority health research, especially for ANHOPIs, universities would be the last place to give you the infrastructure you need to do that kind of work.
My suggestion is the creation of an ANHOPI policy research institute, which would transcend university walls, transcend community organizations that now exist, and transcend the ANHOPI clinics that now exist, but working with all of them. It would provide a permanent setting for internships to students that are scattered at the top universities, that want to do ANHOPI research, but cannot find mentors. Fellowships to health professionals, and promote collaboration among researchers and students, and address cutting edge research and policy issues, where Ph.D levels and doctorate levels of researchers are needed, not just master's level. Develop and maintain the ANHOPI data banks jointly with government agencies like NCHS, Census and CDC.
What are the components of the institute? It needs an advocacy arm, which means that this institute should maintain some kind of relationship with the forum. It needs clinics, which means that it should have a working relationship with APCHO. It needs research, which means that it should link with many of the ANHOPI faculties, and oftentimes there is only one of them in every department, not every department, but one of them in some of the departments of epidemiology throughout the 30-some schools of public health in the United States.
We should do demonstration, by linking researchers in the community through public health lectures, continuing education and practices. Therefore, it should get the media involved. There are more than a thousand alternative media in the United States; they should be involved here.
Legislative arm should develop policies. It should work with lawyers. There is an Asian American network of lawyers, and it should have ties to the U.S. Congress, the Senate, the Justice Department and the White House.
What are the requisites for such a policy research institute? It should be fiscally independent from universities. It should have its own grants and contracts management office, its own IRB, its own permanent grounds or campus, it should have research facilities, and it should hold weekly seminars on ANHOPI policy issues. It should have permanent and visiting researchers.
I was quite surprised some years ago when my leave for absence was approved without pay. I approached the forum and I said, may I spend a year doing research with your data sets, and the answer I got was, no, we don't have such a mechanism to absorb you. Yet, the forum said they have the data and they have no researchers.
So basically, the issue is a bread and butter issue for many of the community organizations. They are concerned that if they absorb these Ph.D researchers, they will be the ones to get all the grants, and that the forum would end up with no grants. What they don't realize is that these researchers run only after certain grants. For our promotion and tenure, only certain grants would help us in our career. Some other grants would not help us in our career. It is like two persons with left shoes to sell cannot have a business, but if one person has a left shoe and one person has a right shoe, then the Chinese say, yu can have a business. One or the other can buy the other out, and then you can walk with two pairs of shoes.
That is really what the forum is and what researchers are. One has the left shoe, the other has the right shoe, but somehow they haven't been put together, they haven't even communicated. Yet, I was one of the persons that contributed to the creation of the forum at a San Francisco meeting many years ago. We voted for it, we were very much in favor for it. Many researchers were very much in favor for it. But after it was established, many researchers were alienated by not being included, and the question is, why? We are not fighting for the same pot of money. Why not? Work together.
ANHOPI policy research will require prior agreement with independent investigators about data ownership and procedures for data analysis and co-authorships. That system has to be developed. It will fill a gap in the training of minority scientists at all major U.S. educational institutions. I get calls from students at leading universities saying, they want to do a thesis on Asian Americans. They cannot find a single professor who even understood what they were talking about.
It will insure a cohort of researchers whose interest in ANHOPI health research will not be trivialized by the institution that employed them. I get questions like, so you did a report for CMS on Asian American health disparities. What good is it to us? What good is it to our colleagues or all white Americans? I don't know how to answer that question. That was the question posed to me. You've got a 600-page report; what benefit do we the university get out it? You tell me how I should answer that, because I don't know, and that is being posed to me.
Efficient use of resources. We have all the data, and we can collect better and more data, but where do we put them? To try to hope that one single investigator can be your big P.I. and collect all that data, I can tell you, Hopkins is full of professors who have storages with data, boxes and boxes of data. I hear this from all the Hopkins master's students. They have a fear of entering those storage because they say, we can't find them, and you are supposed to sort them out to get your dissertation or thesis done. I have storage of data. I am paying $150 a month for data that are sitting in storage. It is too much of a burden to put on a single individual to hold all those data, because you will get moved. Your office gets moved, your residence gets moved, your employer changes over time. You move those data with you, but you don't really know what to do with them. We need to really seriously address that issue.
We need to be able to make timely response to policy health research. We now have a cohort of ANHOPI scientists who are retiring or who have just recently retired. Many of them are very talented and mentally alert and technically very competent. It is a non-diminishing intellectual resource, because there will be many more coming up. How about recruiting them as potential mentors and researchers for this health policy research institute that I am dreaming about?
Many of them have talked to me, and we have talked about this idea. We just did not know how to get it funded, how to get it off the ground.
A question of accountability of the institute. You have a board of directors, you have management teams. You have a process of selection. You develop your transfer of power. Systems of management have to be developed, and the system will manage the people. Your board of directors will comprise of scientists, of community people and of management personnel. You have joint publications with funding agencies. That would hold accountability, that would make sure that the data are published, and the funding agency would have a copy of the data set, so you don't have a fought issue here.
Many of the data that are now being released by NCHS, and I have seen some publications coming out of famous ANHOPI professors, and I shall not mention their name, where they show the data, the paper is published. The numbers showed that the confidence intervals overlap. The sentence said significant difference, and I wrote to the author and I said, how could you say there is a significant difference when in fact there is not? Clearly that is community pressure to establish a significant difference when the data does not bear it out.
So accountability has to come from two sources. You have to be accountable to the community, but you also have to be accountable to the scientific community, or else you lose your credibility.
What has happened in the past is that those in the academic setting who are working with a community have great credibility in the community, but lack credibility in the scientific community, because their publications constantly show data that contradict the words that they say in the paper.
Then you have those who are overly cautious, who say only what the data allow you to say, and then the community attack them because they did not say enough to favor the community in their grantsmanship. But really, we have two audience here, and we have two accountability to make here one, one to the scientific community, one to the lay community. They have to be consistent, because data are data and they don't lie.
Health advocacy. We need to fund public-private collaboration with ANHOPI specific networks of social service agencies, including voluntary organizations, alternative media, legal or journalistic associations to promote health, to publicize ANHOPI health risks, to encourage participation in intervention programs and use of screening tests.
Education. This is another bombshell that I am dropping. We need a paradigm shift in how we educate public health students. The Policy Research Institute should work with public health students to prepare ANHOPI specific health communication materials in a language that they can understand as part of the culminating experience for graduation for MPH programs. This ought to be part of the culminating health experience.
What we have done as American educational institutions is, we take all these minority students that come in, but we really did not use the language and cultural resources that they have to benefit the community. Instead, we educate them, we taught them about how to study white populations. They come out, they know nothing about how to study minority populations.
The Policy Research Institute should offer courses on indigenous diet and nutrition, because that could never be offered in a university setting. It is so difficult to get courses approved or changed in a university setting. And promote culturally enriching physical health as part of the core public health education and practice in addition to applied behavioral science, medical epidemiology and biostatistics expertise.
So what is needed? A major donor to donate large tracts of land, like NIH started out with a donor who donated tracks of land over a period of years. We need federal funding initially for seed money to create the institute for five to seven years, and then in preparation for self sufficiency at the end of that period, and we need commitment from both the scientific and the lay communities.
That is all.
DR. MAYS: Great, thank you. Here is what we are going to do, because we are running behind in terms of lunch. We are supposed to do health, so I don't want the committee falling out.
DR. YU: Sorry to go on so long.
DR. MAYS: That's okay. Here is what we are going to do, because I know Elena can also be with us this afternoon. Why don't we take a few questions now, and then we are going to adjourn. Then we can continue the questions both from the members as well as the audience after lunch.
So let's start with Eugene.
DR. LENGERICH: This may be a straightforward question, but I was just wondering if you could talk a little bit more about your ideas around the urban-rural origins and growing up and how you measure that; is that a self report, what sort of ways to you assess that information.
DR. YU: There have been questions. In one of the health surveys that I did for some service agencies in Chicago, we did develop a good set of questions on that.
What we did was ask them, before you were age 21, in what kind of community did you spend most of your life, whether it is a small village, a town. Then we had some predefined number of the population, and is it the capital of your country, because the capital of many developing countries is the prime city.
If you go to Beijing, China, yu go to Taipei, it is like living in New York. But if you are outside of that prime city, all the other areas is a very far cry from that city in terms of lifestyle, in terms of exposure to Western values, exposure to Western science and medicine.
So I do believe they affect your ability to deal with bureaucracy and public health. The medical care system in this country is a bureaucracy, and it affects whether or not you are able to be aggressive and assertive, whether you seek a very personalized relationship.
Latinos have a concept called personalismo, meaning to say, you relate to people on a personal basis and you take things very personally. If you come from rural areas, you are more likely to be that type of person, which then says something about difficulties that you might have when you get treated by a nurse today that is not there when you go next time, and then you have to repeat your story to this nurse again. You don't quite know how to talk on the phone about your health problems to people.
So that to me is a very relevant issue. There are ways to develop those questions. Fortunately for that health survey that we did, for the community, the questions were excellent. The community forced me to limit the sample size to 150, because they thought 100 was good enough, and so 150 is already very good. What they did not realize is that I could do very little with 150. I argued with them about increasing it to 300, so that you have a five percent error. It is very difficult.
So this is the problem with working with the communities when it comes down to sample size and resources. You don't have the resources. You may have excellent questions; you can't do anything with that data afterwards.
DR. MAYS: Nancy.
DR. BREEN: I wanted to first off thank you very much for a very marvelous, provocative presentation to this committee. I think it was very, very helpful in terms of helping us think through this issue. We have been grappling with this. This is our second hearing on this topic, so we are really looking for new ways to think about it. So thank you very much for giving us some new ways to start to think about it.
One thing I wanted to follow up on now is, you mentioned the California health interview survey. California is very rich in Asians; we have seen that all morning. Currently what is being done is, the sample is based on the different counties, and then there is a list sample in order to get over sampling among certain Asian groups that aren't going to naturally occur in order to get an adequate sample size.
Did you have some alternative ways of going about getting adequate sample sizes without perhaps using the list, or have yu thought about how you would approach that?
DR. YU: Yes.
DR. BREEN: Could you share with us a bit how you might approach that?
DR. YU: Yes. Some years ago I did work with Paul Levy at Illinois. I was there at the same time Ho Tran was there at the University of Illinois. As you know, Paul Levy is a very famous sampling statistician. He wrote the book, Survey Sampling, that most public health students are exposed to.
We actually developed a sampling design that we were going to write up, but never did, because I was too busy and he was too busy, then I went to Hopkins, and that further delayed me. I'm blaming someone now for my own negligence in writing it up.
DR. BREEN: It may not be too late.
DR. YU: The concept is this, very quickly. Pick your census tracts with say 20 percent or more Asian Americans. Go down, pick your blocks with 20 percent or more Asian Americans and Pacific Islanders, and then do the hard legwork of canvassing door to door.
Once you get canvassing door to door, you would be able to establish which household has how many Asian Americans and Pacific Islanders, which household does not. You can supplement this approach with a reverse directory that gives you all the addresses at that location, so you know you are not missing the households. With the reverse directory, you have the address and the name of the householder. Some Asians who married white would not have an Asian last name. You can do a sensitivity/specificity analysis, based on surnames; how many would you have missed and how many would you have really identified as truly Asian.
So once you define the geographic boundary against which to do these studies, it is doable. Actually, Paul and I were going to write it up, but we never did. The reason in part was because most of the grants mechanism do not allow you sufficient space to write such a detailed sampling plan. It is extremely difficult to get such a paper published just solely on sampling, on how to sample it.
So we ended up talking about it but never writing it. But I felt that is probably the closest and best method we have of using the census data to do sampling of Asian Americans.
DR. BREEN: Can I ask a followup to that? One of the reasons I have heard that the list sampling is used is, it is relatively cheap and considered adequate. Do you have a sense of the cost of this? It sounds like it is a fairly expensive procedure.
DR. YU: Yes, it is. In fact, when I presented this concept at a meeting, it was a Gerontological Society of America meeting. At that time I was thinking of just studying elderly Asian Americans, but this sampling method could be applied to any group or any topic you want.
Westat was there. When Westat asked me the question, how much do you think it will cost -- and Paul and I worked out the numbers, and we figured at that time for a sample size of 2,000 that we could do it -- this was in the mid '90s -- that we could do it for a million, and Westat said, I wouldn't do it for two millions.
Yes, cost is a problem, but did cost bother us when we did the women's health initiative? Why is it that cost is always a stumbling block when we are doing studies of Asian Americans? We always say it costs too much. What costs too much is relative to what we think that data is worth.
I think that good data on ANHOPIs is worth billions right now, because they can open up keys to many questions, research questions, critical substantive research questions about majority Americans that we have never entertained. The example is menopausal symptoms. Had we studied Asian Americans in a much earlier era and gathered enough descriptive data, we would probably have been guided into a different direction of research to supplement the kind of research that emphasizes only drugs. We would probably have gone into physical exercise and looked at physical exercise and menopausal symptoms instead of looking only at drugs.
How do you explain otherwise, that of the seven studies in this whole world on diagnosed diabetes and exercise, only two were conducted in the United States? Given all the resources of NIH, given all the talented people coming to the United States to study, and all the high powered clinical trials that you have? No one thought of doing a good clinical trial on diagnosed diabetes and exercise.
These two U.S. studies were very poorly done. One was in San Diego, the other one was in Pittsburgh. They were not long enough, and they were conducted 12 to 15 years ago. How do you explain that? How do you explain that, with all the money we got? That is a mind boggler to me. I just can't understand it.
DR. BREEN: One more followup and then I'll stop. It sounds like you might have figured out how to answer your colleagues' question about what good was that CMS study that you did on Asians.
DR. YU: I don't know how to answer. I'm supposed to write on it.
DR. BREEN: I think you just did. But also, you mentioned a number of steps that you developed in your data sampling strategy. We might want to start with a little scaled down version. It strikes me that there were some steps that would still provide better data than a list sample, while not being maybe quite the Cadillac that you just described, we could do a Honda Accord or something, that that might be possible.
DR. YU: Yes. In fact, actually I had a graduate student work with me on that. We looked at San Diego County's census tracts, and then we identified the blocks with 20 percent or more Filipinos. At that time we were developing a Filipino cancer screening study. Then we got down to every level, just picked 20 percent of every level, and finally we got down to the boundaries, the streets that defined the census blocks, and then we used the reverse directory to identify the streets and the households within those blocks. Then we went down into houses and did a canvassing of houses.
They did this 30 years ago with studies of whites and blacks in this country. Why is it they are refusing to do it for Asian Americans in this country at this time? Given all the computer technologies that we have? This is something I cannot understand.
DR. BREEN: I think that is a very feasible way to go about it though, don't you?
DR. YU: Yes, definitely
DR. MAYS: I think there are some other sampling questions, there are a couple I want to ask, but I think we are going to hold those and continue some questions before we proceed into some other deliberations.
I want to thank you for the time and effort that you put into your presentation to bring us some of the most up to date information. Even though I just heard you present in September, again you have done even more work, so I want to say on behalf of the committee I really appreciate, particularly given the short time line you had, the information that you pulled together and the thoughtfulness that you presented in order to give us an overview, and also as well a set of recommendations to consider. So thank you very much.
What I would suggest is that we adjourn for lunch before I have to scoop people out of these chairs here. Let's come back at about 2:15.
(The meeting recessed for lunch at 1:05 p.m., to reconvene at 2:20 p.m.)
A F T E R N O O N S E S S I O N (2:20 p.m.)
DR. MAYS: We are returning back from our lunch break, and we are going to be continuing with questions and answers to our previous presenter, Dr. Elena Yu.
Again, I'll repeat, if you want to call in, the phone number is 877-939-8305. Then you need to know the participant code, which is 278561.
Let me take questions first from the members, and then we will open it up more broadly. These are questions for Dr. Yu. Nancy is claiming her time.
DR. BREEN: I had another one. Dr. Yu, you mentioned that -- I hope you remember the context, because I'm not sure I can reproduce it. But you talked about multiple axes of classification. Does that ring a bell?
DR. YU: Yes.
DR. BREEN: Could you talk about what you were thinking of, talk a little more about that?
DR. YU: We are so accustomed to think of classifying ANHOPIs the way the OMB has told us to do so, that is, the population is white Americans, black Americans and then ANHOPIs, and to also divide it along quote-unquote ethnicity, which means Latino or non-Latino.
As a result, many of the standard health surveys that the government routinely collects would get this information. What I am saying is that this information may not be sufficient to do many of the health analyses that we need to do, and to also target special groups for services. We need to supplement these questions with additional questions about where they were born, nativity, generation in the U.S., where the parents were born, because once you ask where the parents were born, if they tell you that the parents were born in the United States, you know that this person that you are talking to is a second generation.
We need to ask questions about level of education, and we also should ask questions about rural/urban origin. I do believe that that really affects your ability to adapt to modern bureaucracies, as I mentioned earlier.
So this list of non-genetic confounders that I showed on my slides are the additional questions that should go into every survey. If we could do that, then the imprecision in the measurement of race and ethnicity is in some ways actually already improved. It would help us target certain groups better for services. It would help us to identify the high-risk groups. That may be a solution to this problem of how do we measure and classify the different minority groups to meet the objectives of Healthy People 2010.
DR. BREEN: Thank you.
DR. MAYS: Suzanne.
DR. HEURTIN-ROBERTS: Dr. Yu, you and the speakers before you mentioned a little bit about translating surveys into various languages. Could you also comment on -- or just give me your thoughts on the issue of cultural equivalency of survey items, because I think it is more than a language issue.
DR. YU: I am glad you asked that question. My presentation does not -- the time allotted to me does not give me enough time to really address the issue of language. I myself speak about seven languages, just by accident of being born in a certain setting, in a certain educational situation. I could understand the complexity of the issues.
Let me describe to you how I dealt with it in a study I did, which was a pilot project funded by NCI on cancer control among Asian Americans. At that time, we were working on only two groups, the Chinese and the Koreans in Chicago. What we did was, for the Chinese part -- because when you say Chinese, the main language groups in the U.S. are Mandarin speakers, Cantonese speakers and Taiwanese speakers, and then you have a fourth group, Shonghanese speakers.
When you say Koreans however, it is more or less, compared to the Chinese, a uniform group. There might be slight changes in accent, intonation, but it is really one language, so it is a lot easier to work with.
So what we did was, I had a Korean co-P.I. We entered into an agreement that all the Korean studies, she would be the lead author and I would contribute in terms of substance, but I would not know the language or the culture as well as she did, because she was raised as a Korean. For all the Chinese part, I am in charge. She would contribute what she knows about the Koreans and ask questions whether it would apply to the Chinese part.
For the Chinese translation part, what we did was, we had translators in the U.S. who are from these different groups work on a translation from the NCHS version of a cancer control questionnaire. But I also contacted professional translators in Hong Kong to get me the Cantonese version. There is going to be a slight difference in the way the language is used in Hong Kong versus the Cantonese speakers in this country. We compared those differences, we discussed them.
So it is doable. In other words, we worry so much in this country, since it is so monolingual, about all the different language versions and all that, but people outside of the United States live with multiple languages, grew up with multiple languages. It is no problem. It is a question of, are you willing to invest the resources, and are you willing to go through the rigorous process of translation, back translation, and hours of meetings to iron out all the nuances of the different words and different meanings.
Clearly, people who speak multiple languages know that a literal translation is a very poor way of establishing equivalence. What you really need to get out is the meaning behind the words. They know how to do it. We had four different versions of a translation of an instrument, and then we would compare all four f them and say, why are we seeing these differences and what is the meaning.
Then we would pilot test it. We did the pilot test on it. We interview people with it and say, why did you give me the answer that you gave me? This is probing. You do what is known as a think-aloud method; how did you get at this answer, what was your understanding of the word we just used. That way, you know exactly where the problem is. But it is labor intensive.
But we have done this. NCHS did this kind of study, applying cognitive psychology strategies to serve the questions. They have done this on white populations, why are we so unwilling to do it on ANHOPIs? When you say it costs so much, it really reflects a value judgment that you don't think it is worth doing, it is worth the cost. But I think we need to change that prejudice in our mind set about the worthiness of studying these populations, because they might contribute something substantive to science.
DR. HUERTIN-ROBERTS: Thank you.
DR. MAYS: Other questions? Russell.
MR. LOCALIO: I have one question you may be able to help us with. One of your slides had the estimated population of certain groups by city, and some of the cities that had the largest number of people in various groups.
Now, in your opinion, if one were to try to find these various subgroups, is the issue of differences among the subgroups more important than differences among the cities within one subgroup? Depending on your answer, how do you deal with that problem?
DR. YU: That is a very, very good question. I think it all depends on what you want to study, what is the research question. If you are talking about factors behind uninsurance, I think the group differences are not so critical, as to the reasons why they are not insured. There are reasons why a lot of AAPIs are not insured. They are associated with factors associated with non-insurance. That is to say, they are employed in small firms with less than 500 employees. They cannot afford to provide the insurance to these people.
There are certain factors, and it depends on what yu are looking at. If I am looking at the percentage of ANHOPIs who have not used cancer screening tests, I think that AAPI as a group are low users of cancer screening tests. AAPI as a group are highly vulnerable and have a very high prevalence of hepatitis-B virus. So group differences are not so great if you compare the AAPI groups versus white.
But there are certain other kinds of health issues where inter-group differences might be very important. In that case, within the AAPI groups, some groups -- if you look at obesity, I would say that that problem is much more dominant among the Native Hawaiians, among the Samoans. If you are talking about oversized babies, babies born that are weighing too heavy, that problem does occur more prevalently among Native Hawaiians and Samoans than say among Japanese or Chinese.
So it depends on what you are looking at. We need to target our sample and sampling strategy to the problem, instead of trying to come up with one sampling strategy for all types of research questions. We don't do that in our studies of white Americans, why do we want to do that in our studies of AAPIs?
DR. MAYS: We asked a question about methodological issues. I want to come back to that. I think part of what happens is that it is very easy for us to recommend those surveys. Then what happens is, it isn't until somebody is in the middle of it and they say, oh my gosh, we have to do this, we have to -- so part of what I think would be useful as we struggle with what some of the issues are is to try beforehand and highlight what is different and why it is necessary to do that.
Can you talk about -- you can do it either as specific or general, as the knowledge base is there to do it. What is different that causes us to have to use a different set of methods?
For example, if there are within ANHOPI populations households that have three generations of family in that, what does that mean relative to for example our ability to be able to do enumerations? What are some of the issues that are different, that if we sit down and try and come up with strategies that we should be paying attention to for ANHOPI populations to be specific, methodological differences, and there are differences that occur as a result of something about the population?
DR. YU: That is a very good question, and it is extremely broad. I could group my answers into different segments.
First of all, the implication for a large household size for AAPIs compared to non-whites, in terms of applications. Then I'll come back and talk about the methodology issues.
It means that if we miss that one household of three generations, we are missing a sizeable segment of the population, because you are missing a lot of people in that one household. It is not like the white American population, that the average size is 1.2 persons, for example. If you miss that, no big deal, there is another 1.2 person household. But with the AAPI, if you miss that household, you are missing four to nine people right there. That means that if you have a vaccination program, you are missing all these people that you should have been vaccinating.
It also has some opportunities here, because that means that if you are successful in reaching out to them, to the AAPI households, you are hitting all nine of them, from the youngest to the oldest all at once. So there is an advantage to knowing that AAPIs have a very large household size, because they have implications for public health education, they have implications for prevention measures.
Now, in terms of sampling, it means that we need to go back and think. I don't know how many of you know James Jackson. I was a graduate student and I admired him terribly at the time, because he was in my mind the first black American scientist trained as a behavior scientist, who was funded to do the black American family study. This was in the 1980s.
We were just in awe. I said, God, it would be great if one day we could have such a study of the Asian Americans. So we tried to -- I read many of James Jackson's work, I attended many of his seminars, and I was just very much wanting to have such a study done on Americans.
What did he do? He canvassed door to door in Detroit. Why is it that we can accept that when it comes to a study of black Americans, but we cannot accept the idea of canvassing door to door when we are doing studies of ANHOPIs? This is something I cannot understand.
We do need to do that, because we need to have that primary enumeration process in order to know how many people are there, in order to be able to apply the sampling methods of using a table of random numbers that we are taught in our biostatistics classes to do.
So I think it is very important methodologically to have to go through that process, to pay for the cost of doing it, as we have done 40 years ago, 50 years ago, for studies of white Americans, 20 years ago for studies of black Americans. We should be able to do that for ANHOPIs. The technology is there, the knowledge is there. The question is, are we willing to put our money where our mouth is.
I hope I answered the question.
DR. MAYS: Yes, and I have one followup. It is funny, because it actually comes from my experience. I was a postdoc at the program for research on black Americans at ISR at Michigan with James, and you're right, they were among the first to actually do such a survey.
One of the things that they did is, they called it the three-gen study; they had a three-generational study. The problem is that despite having this wonderful three-gen data, it is like the statistical techniques to do these three-generational data haven't progressed quite as quickly. I think now we are a little bit better off, because I think the developmental life span people have worked on it.
But that becomes another issue, whether or not there are differences in terms of -- a different need in terms of statistical techniques, in terms of working in a population, when you have some of the complexity of issues that you have.
For example, going into the household, and you have three generations in the household. You collect data on those three generations in the household, and yu don't analyze it -- you shouldn't be analyzing it the same way.
So I am wondering if you have given some thought about what even some of the other statistical needs might be, given the complexity of some of the issues in this population.
DR. YU: I am not a statistician, I need to qualify my answers to that, but I do as an epidemiologist look at substantive issues. I think that there are ways to slice the data.
For example, in a three-generation family, if I were to analyze the data, I would like to see the cultural shifts, or the extent to which different degrees of cultural integration in the United States affect health care and access to health.
With the Asian American families compared to other families, I would suspect that having younger generations in the family who speak English would help and would be of benefit to older generations, because they are the ones that would broker the contact of the seniors with the health care system. They are the ones that actually act as translators. This is what some ANHOPIs call an ethnic tax. That is to say, hospitals and physicians do not provide translators, and put the burden of translation on the youngest family member of the AAPI families, who then have to take the elderly to the doctor and take the translation, and they are not always the best translators.
You have two issues here. You have the confidentiality issue involved, and then you have the problem of proficiency. Just because the guy looked Asian and is born in an Asian family doesn't mean that he speaks the Asian language fluently as a translator would have. So this is what in the minority community they call an ethnic tax, that no other ethnic groups are ever burdened with that responsibility, to act as translator, but the ANHOPI families are burdened with that problem.
So I think there are ways to look at the data. You can use the household as your unit of analysis and look at the data differently. You can cut the data and look at just the oldest generation, the third generation, the second generation and the first generation, and you can compare between groups, and I'm sure that if you have the funding for it, that there will be biostatisticians who would come up with new methods of analyzing the data. The question is, are you willing to put the money up for it.
DR. MAYS: Thank you. Any other questions among the committee? Edna and then Virginia.
DR. PAISANO: To follow up with that question, I don't know whether you or one of the previous speakers talked about intermarriage, either among other Asian groups or the Pacific Islanders with whites.
I guess part of my question is, if you are looking at a sample and you are trying to classify a household as one of the Asians or one of the Pacific Islanders. Either the husband or the wife or the spouse or the householder, one is non-Asian, do you still consider that an Asian household or a Pacific Islander household?
DR. YU: That is a very good question. I think that the answer to that question should depend on the research topic and the purpose of research. You could define them as being included or as being excluded.
The multiracial households, the households that became multiracial because of marriage, can be classified either way. What we should do, we should always include a methodological piece of research into every survey we are doing with ANHOPIs in order to measure the sensitivity and specificity of your classification method in actually locating the AAPIs.
Unfortunately, we do not have a blackboard here, or I could illustrate it with you. If you think of a two by two table, you could define for example your ANHOPI household as any household that contains at least one person who is an ANHOPI, or you could define it as any household that contains at least two persons that are ANHOPI.
Now, you could vary that number. Whatever your classification method is, that is your classification method. On the other side of the dimension, you could say, when you knocked on a household, what did you find, and limit your sampling to cell A or cell A and B or cell A, B and C or A, B, C, D, whatever, and then calculate your sensitivity and specificity from there. That would tell you how good you are at classifying your populations.
I know that if you were studying the Japanese, interracial marriage rates are very high. If you are studying the Native Hawaiians, interracial marriage is very high. If you are studying the Cambodians, if you are studying Koreans, inter-marriage rate is relatively low, compared to other ANHOPI groups. So it really depends on which subgroup you are studying, what is the critical issue here, and what is your research question.
Even if you look at my family alone, I have relatives who are African Americans, who marry African Americans. I have a distant nephew who is half black and half Chinese. I have relatives who are half Jewish and half Chinese and half Portuguese. So if you look far enough at any of the Asian American families, you will find that many of them are multiracial. The question is, what are you looking at, what questions are you asking.
It depends. It depends on your research problem, and we should stop thinking of a one size fits all approach to the study of ANHOPIs. We should be explicit about how we are classifying them, but that allows us to take the findings into account, take the methodology of collecting the data into account as we interpret the findings.
I hope I have answered your question?
DR. PAISANO: Yes.
DR. MAYS: Virginia?
DR. CAIN: In your presentation, you had suggested that there are a lot of data sets out there of the ANHOPI population, but that they are not accessible to people, they are stored in basements or something.
DR. STEINWACHS: They are in the Hopkins basement.
DR. CAIN: They are all in the Hopkins basement. Is there any reason that they aren't archived at places like ICPSR or someplace else, and are there things that could be done to make them accessible to other researchers?
DR. YU: Let me clarify myself. There are some AAPI data, not a lot compared to other groups. The data that we have were collected before the computer technology overpowered our whole society. So many of those data were collected on -- they were saved on CD's, but we have a compactability issue. They were saved during the days when the Wang was still existing.
DR. CAIN: Oh, wow.
DR. YU: Remember the Wang has the word processor?
DR. STEINWACHS: I'm not that old.
DR. YU: Remember Wordstar? Did anybody ever hear of Wordstar?
DR. MAYS: Yes, I remember that.
DR. YU: And the code book was written in Wordstar. The problem with those data is that we have no way to convert them, or it would take so much effort to convert them into Word Perfect or Word, it would take so much effort to find the code book. There are those datas. They are in the hands of individual investigators in the days before we even knew about data banks.
ISR is a very good institution, and has really developed a standard method of cleaning up data, making them publicly accessible. Unfortunately, many of these data that are in the hands of individual investigators are in self storage. Right now, if you were to ask these investigators to bring them out, documenting them would be very difficult, unless you are willing to pay for their time. There is no way to salvage those data anymore. If they were not published, they are gone forever.
However, there are a minimum amount of data coming out of NCHS surveys. The vital statistics record for example is an excellent source. That is where I got most of my data on mortality. Those data have not been thoroughly written up. I think I am probably one of the few in the country that started to write this up because of CMS asking me to write a report on Medicaid and Medicare for ANHOPIs, so I had to review the data. I wrote it up. I haven't published them even, and I should be, but how could I when I have my dissertation to worry about? This is the demand on my time.
DR. STEINWACHS: One must have priorities.
DR. YU: I don't have two heads, I can't ride two horses. So when I say there is plenty of data, plenty in a very relative sense. There is not absolutely no data, there is some data. The question is, how do we get them written up, how do we get them analyzed.
NCHS has NHIS data, but the problem with those data sets is that the Asians are classified as one big group. Even if you pull data for different years, you don't get a large enough sample to do analysis by different stratified groups. So there is that problem.
I am saying that we cannot continue the same practice year after year. We have to start thinking outside of the box, and the solution is really population focused surveys.
Did I answer your question?
DR. CAIN: Yes, to a certain extent. One of the things that I am wondering though is, is it worthwhile to try and retrieve some of those data sets that you are talking about, even if it requires an investment of money in standardizing them or bringing them up to current standards?
DR. YU: It depends on the investigator. Again, if you were to fund them, would they be able to bring them up, would they be able to supply the documentation for it. That we don't know, unless we have a master list of all the investigators who are funded to do AAPI studies we wouldn't know.
But for example, Kaiser Permanente has collected data on Asian Americans. You can identify Chinese, Filipinos and Native Hawaiians from their data set. The question is, as an individual investigator, if you ask me today, you say Elena, I'm going to fund you to analyze Kaiser Permanente data, I don't know who in Kaiser Permanente I would contact to get that data set. Not that I haven't tried.
We talk about Northern California Cancer Center. I have called them. Do you know what the answer I got was when I called them and said I wanted to analyze their cancer data? They said, somebody is already doing it. Two years later I met that somebody. I shall not mention the name. The person said, I didn't do it because I didn't get funded.
This is the kind of treatment we get. So it makes it very ineffective for us to analyze the data. We don't know -- I come from a small city, rural background, it makes a difference. I don't know how to access the bureaucracy to analyze the data. That is why my suggestion is, we need a policy research institute that administratively will go after these data, pull them together and make them available to public health students for their thesis, for their dissertations, make them available to Congress. I think we need that. I don't see a solution out of this, any other solution out of this. For us to rely on individual investigators from big-time universities to do this, I don't think so.
DR. MAYS: I want to follow up. I don't want to let this question go yet, because I think there is something there.
I know that for example NIA put money into finding and archiving data sets. I know NIMH has done it. They have put them at the Murray Center. Of course, we know that IPCSR does this as part of what they do.
Let me come at this question a different way, which is, with the help of people like you and others, would someone be able to find the PIs that have collected data on ANHOPIs, and then allow whoever, in a contract or whatever, for them to look at the data and assess whether or not it might be feasible and that it might be of a nature that it would be important enough to put resources in it and to put it into some archival place where it would be accessible to a larger group of people.
I'm saying this because it is not just some of the data that we are thinking about, but if we broaden this, there may be data over in some of the islands, some of the other places. We might say the CIA needs to -- they have got some data, maybe we need to go to the CIA and find what they have.
But I think I want to push this. I do think that there are short term and long term strategies. I think this is a short term strategy that I have seen, places like the Murray Center in Cambridge, and they have tons of students who go in and use a lot of that data. They have contacted lots of us. They are asking for data sets of mine that are really old. At first I thought it was crazy, and I started looking at the extent to which that has facilitated work, and probably made the careers of some people, and made them believe -- the very things that you are asking for made them believe that they could do this and have an academic job.
So I'm going to do it differently. Could we find those investigators? Would there be a body of people, either at the forum or other places, who could help us find these individuals and then let there be an assessment about the feasibility of taking that data?
DR. YU: Let me answer that question. Definitely, yes, we can find those individuals who have been funded to collect data. I have approached them with this idea.
Let me give you the answer, and then we can jointly think about how we should solve this problem. The answer that they gave me, I approached one investigator about this. It was a data set that he hadn't analyzed for about five years, by the time I talked to him. His answer was, yes, I'll give you the data, I'll let you analyze it, but I must be the first author. I said, then fine. I was never even thinking of excluding you as an author, but first author, I don't know about that. Where would I be in this lineup if there are already two investigators? That means I would be the third author, for going after the data and analyzing it.
If you are a faculty member trying to get tenure, if you don't have first co-authorship paper, you know you are not going to go far with it. So if you have two projects, one in which you could be a first author of a paper and one in which you could be a third author of a paper, where would I put my effort in as a faculty member who wanted to move up in the academic career? I went after the paper where I would be first author. I put low priority on a paper where I would be third author. So I ended up never analyzing that data set.
I think my situation is very typical of what most authors go through. Most investigators wouldn't mind sharing the data, but when it comes to writeup, they would prefer that somehow they have a role in the writeup, or that somehow you give them a copy of what you are writing up, because yu could possibly misinterpret and contradict what they have already published, and they have no chance to respond.
If you could solve that problem, one of authorship, two of how they could give feedback to that answer, I think that we could solve the problem of lack of data in the short term. The question is, I never knew how ICPSR worked that out. I think my understanding of the way ICPSR worked out those data sets is that once you give those up, you give them up forever. You give up your right to authorship, you give up the right to mentor the people who are analyzing that data completely. I don't know Asians who would be willing to do that, the ones that I know who has the data.
MR. HITCHCOCK: Elena, these are publicly funded data sets that you can't get access to?
DR. YU: They were funded, yes. They were publicly funded now, but this was before.
DR. MAYS: I was going to say, anything that is an R0-1, if it is investigator initiated, you maintain control. But now there are some data sharing policies.
I think it is worth the committee thinking about this to some extent.
DR. YU: Yes, definitely.
DR. MAYS: I do think some -- I understand exactly what you are saying, having had people approach me quite often, I understand. Also from having been at Michigan, I know a little bit about the ICPSR setup.
One of the things that I was taught is, before our data sets are finished, we have what is known as a data use policy, because we know people will want to use it. So we actually have those things. So I think it is something.
Did you have another question? Let's move on. Don.
DR. STEINWACHS: Just a quick one. You said something, and I just wanted to make sure I understood it correctly. It was enticing to me. I think it was something in reference to individuals who have multiple racial and ethnic identities being at increased risk for adverse health.
It seems to me that is something that hasn't gotten a lot of focus. It does talk to what I think is a social and behavioral -- it has rubbed off from Virginia -- issue. You don't fit into society quite the same way once you see yourself or others see you as having multiple identities, and that culture and so on.
It seems to me it might be worth also in some ways to talk about what our priorities are in public health, trying to address that group, as different from what we do now, which is to try and label you generally into a specific category. You talked about the different definitions and others have, but it might be some value in a focus for research and public health investigation on that group.
DR. YU: Definitely. In fact, I was quite shocked when I started reviewing the data for CMS, to look at multiracial adolescents, because that is really the group where -- if you are going to have life problems, that is when it emerges. If you don't resolve those identity crises at adolescence, they carry on through life, and one thing leads to another. Smoking leads to drugs leads to sexual experimentation, leads to others. The association is there epidemiologically. If you want to target prevention efforts, this is the group worth spending resources on, definitely.
DR. MAYS: Are there any questions or comments from individuals in the audience?
MR. HITCHCOCK: I'm not in the audience. When you were talking about your family, and you were saying that there are some people who are Portuguese, black, whatever, you mentioned Jewish in there as well. I guess we still have trouble collecting data on religion, but I would think it would be an important variable, given that we could collect it. Maybe some investigators can if they are grantees. The federal government has a hard time doing it. We could ask about religiosity, but we can't ask about specific religious beliefs or practices, which could be very important, I would think.
DR. YU: Yes. I think that religion is a very important variable for certain AAPI groups. It is not as critical for Chinese Americans, for example, even though there are many who are Catholics, there are many who are Protestants, and there are many who are Buddhist. But for other groups, like for Koreans, for example, religion is an important factor, and for some other groups it is.
It definitely is a variable we should collect. Its importance within the ANHOPI groups vary by subgroups.
DR. MAYS: I want to thank you, both for your presentation and also for coming back and answering questions. As you can tell, your presentation sparked a lot of thought in us, so I appreciate again your time in pulling it together. Thank you very much.
DR. YU: Thank you.
DR. MAYS: We are going to take a five-minute break, and then we are going to reconvene. This is a time for the committee to deliberate. Part of what I would like to do is review what is going on in the hearing today. I'm trying to make our report writing a little bit easier.
I want to review what we think some of the recommendations are that have come up, and have some sense -- before we lose that, have some sense of where we want to go with recommendations. I have been trying to keep a list of some things, and I'm sure other people have other things. And of course this is open, it is not a closed session, so other people can also comment on that. Then we will turn our attention to a couple of other pieces of subcommittee business, and then we will adjourn.
So let's take a break.
(Brief recess.)
Agenda Item: Subcommittee Deliberation of Issues
DR. MAYS: What I would like to do is take some time to talk about and discuss as a committee what we heard, what the recommendations as you have heard them that you think this committee should seriously focus on.
I guess if you can discuss those things that seem to be particularly compelling to you, let's make sure we give them some priority, things that may have been -- I don't want to say shocking, but things that you just didn't realize, and that it may be very important for us to highlight those.
Who wants to start?
DR. CAIN: I'll go. One of the things that I heard from all speakers, maybe I am reading into the subtext, was that --
DR. MAYS: I'm just going to make sure that either Dale or Audrey are taking notes on this.
DR. CAIN: -- was a willingness, the need for a willingness to tackle and address and deal with the incredible diversity we have, rather than glossing it over. We do have the ability to do things scientifically, we have the research tools, and I think it might be a matter of just public will to address this.
So I think that everyone in different ways gave that message, that there really needs to be a willingness to really work with the diversity and not try to keep categorizing things and lumping. It is okay to split.
DR. STEINWACHS: Just to add a piece of that, it struck me that some of the conversation, why there might be biases, why we don't invest as much money in looking at Asian populations, invest more in African American. I think part of that message may be perceptions, it was argued, misperceptions, about who is healthy and who is worse off.
There is a tendency I think in society to say, those that are worse off are the ones who may merit more of that investment, but you wouldn't do the same thing if you were better off. One of the arguments Dr. Yu was making, which I thought resonated, was that we need to lay out an agenda that recognizes that we can learn something for the rest of us, possibly from those who are actually doing better in some circumstances, and vice versa, so a balanced agenda.
It does raise what is a gut-level assessment, and maybe this is the scientific way of doing it, saying what is a big enough group for which one would view that there is public health significance. So if you are down to five people, is that a public health problem or just a medical care problem? If you are at 25 people -- so I think there has to be some way for us to talk to that. You can be a small population, but how small? I think the danger currently is that you have to be pretty big in order to have a sense of public health significance. So maybe we need to think about some ways to talk about what that size issue is, even though there is not a precision in doing that.
MR. HITCHCOCK: I think you are right on that. It needs to be a big group, but it helps to be a noisy group. Elena mentioned needs for funding and maybe even legislative language requiring some improvements to be made in these data. That is something that I heard. We really haven't discussed it, having advocates that could somehow get something like this written into law. It doesn't always take all that much to get an amendment onto something. That would be very helpful.
MS. BURWELL: I'd like to follow up on Dale. It is one thing to get something authorized, but to actually say appropriated, where you said many times it translates perhaps into some action.
DR. STEINWACHS: There is a lot of latitude if there is the will, so certainly within NIH as within other parts of HHS, there are offices of minority health, and minority has a political definition of who those minorities are. But that is what we are talking about here, so it is a question of to what extent do you prevail upon and encourage.
Certainly NIH has done some things to encourage R0-1 investigators to pay attention to the composition and not exclude. That doesn't mean they have a sense of why they ought to over sample.
The other is again the kind of flexibility that you have of putting out RFAs, putting out initiatives to try and build more information. So there are some things that if you can do it through Congress, it may be better, because you get more money, more recognition.
The other is, there are ways that both this committee as well as people who sit on this committee are in positions to help discuss what needs to be done when you think about future priorities for investing and developing information, either at the research level or in public health statistics.
MR. LOCALIO: I had a thought. I'm not sure it is the right kind of thought, but it seems like --
DR. STEINWACHS: Do you want us to vote on it?
MR. LOCALIO: No. The existing paradigm has been to design and conduct a survey that focuses on obtaining information about the health of the country. In the process, it hopes that there are subgroups, however defined, that are sufficiently numerous that as a byproduct, one might be able to obtain information about various subgroups.
An analog in a clinical trial is, you have a clinical trial that is large enough so that you expect to obtain information about the differences between the people on drug and the people on placebo, but you hope to be able to obtain information on the effect of drug versus placebo among women, among children, et cetera.
The other way one could approach it would be to say, maybe the paradigm should be that there are surveys that are very focused and targeted on well defined subgroups, and then as a byproduct of that, you are able to combine the results of those surveys and then get results on the population as a whole. The analog in clinical trials would be, you do a lot of clinical trials on various different subgroups, and then you do a meta analysis to try to combine those results into some overall estimate.
Now, this is being very simplistic, because there are a lot of cost issues involved and efficiencies in designing surveys one way or the other. I am sure that the powers that be are never going to drop the idea of having the large heavily stratified and clustered surveys that get at the health or various status of the entire population.
But one way to improve the acceptability of the targeted surveys would be to make sure that all the targeted surveys are not simply targeted surveys that generate data only on the targeted populations, but their results can be combined and then used to create information about larger groups.
I suppose it is possible to take every ethnic, racial and religious group if you wanted to in this country, and divide them into a lot of little cells, and do separate targeted surveys on each one of these cells, and then combine them, and you could reconstitute the entire country.
That is my paradigm. However, I have to say there are a lot of problems there.
DR. STEINWACHS: That is the medical disease paradigm, right?
MR. LOCALIO: Sure. It is also the NIH paradigm. That wasn't for the record.
DR. STEINWACHS: I wouldn't say that for the record.
MR. LOCALIO: I just wanted to throw that out, because one of the things I see is that it is very much easier to convince people of the need and the benefit or the favorable benefit-cost ratio of a particular endeavor if you can say that there is one cost and more than one benefit. It is as simple as that.
DR. MAYS: I do think that kind of paradigm shift that you raised -- I was wondering whether or not that can be discussed with -- who is the report that Diane -- Health U.S., to see if there is any way that in Health U.S., in terms of enhancing it, the idea of offering data in that way might actually be not only instructive, but useful to people, to pull it out.
It is interesting, because the lesson you would learn with the ANHOPI population is that when I did this separately, this is what I have, but then when I put them all together, I lost a lot of this. So that is a very subtle lesson, but it might be useful.
I think the bigger problem may be, depending upon what they use -- no, it is internal. NCHS has the ability to sit in the little Maryland suite and analyze the data.
DR. STEINWACHS: Let me build in one way on Russell's point, which I think is excellent. Health U.S. has as I understand it more of a monitoring perspective, and monitoring doesn't necessarily help lead you to intervention. Certainly monitoring raises issues and say things are looking better or things are looking worse, but it doesn't necessarily help you define what the action is.
I should have read the statistics thing that this committee has done on statistics for the 21st century, then I would have the answer to this, so I may be saying something you have already said. But if you were to transform this to say, what is the information we need to help define an intervention and action agenda, then it seems to me this idea of identifying clusters around which you need information, and those clusters can deal both with what we are talking about here, race and ethnicity, and they may deal with geography, they could deal with groups defined because of higher risk of certain kinds of health disorders that are part of the agenda for objectives for 2010.
I think it would be a different way of thinking about it, and it would reduce maybe some utility in monitoring in some ways, possibly, but you would be beefing up your capacity say, where do we need to intervene, and how do we intervene, I guess, let me put it that way, how do we intervene.
DR. MAYS: Anyone else?
MS. BURWELL: I just wanted to follow Don. Health U.S. is the annual report that NCHS has to submit to Congress, and it is focused heavily on monitoring. A lot of people at NCHS have talked about trying to quote-unquote jazz it up to reflect the flavor of what is going on with racial and ethnic populations. At best, you get maybe a limited chart book, because of that particular report's mission.
It goes back to the fundamental question where we are talking about, what the missions are, and what they are mandated to do. I think the 21st century report was one attempt to try to think beyond what they -- they being NCHS -- ordinarily does.
Since 1990, and before that, but it was really documented in 1990 with the disadvantaged minority health improvement act, that there is substantial need to have special studies for racial and ethnic populations, new methodological approaches, mentoring, training, making sure that people of the populations could do the research. But there again, resources got in the way.
So I'm thinking that the 21st century report is one way that NCHS and others are hoping to build some momentum to be able to address some of the paradigm shifts that we have heard from our speakers, and also what the committee has heard previously.
DR. STEINWACHS: I would think it would be fun to explore, if you did a fundamental redesign from a nationally representative cluster sampling approach, which we do now, to a sampling approach built around some key strata, and then the idea that you could still come up with national estimates, but you would be targeting in a way that we have not been targeting around what you saw as the issues for this decade or this five years or whatever.
MR. LOCALIO: Let me just clarify that. I've got to go back and review the current sampling designs, but it seems to me the stratification is done by geography these days.
I think what you are saying is, you would change that, and have the stratification done by some population group. Then within that, you would do the sampling. Then you would combine the strata and get the whole, and you would then be certain that each of those strata would contain a population subgroup of interest that would be adequate. I think that is what you're saying. I'm trying to translate that into sampling-ese.
DR. STEINWACHS: Well, you're good. They didn't teach me enough sampling-ese, so I like that.
The other, which is not very radical either, is you could be asking a different set of questions to people in different strata. So you could have the common core, but when you got to the ANHOPI, you might have a set of questions that were different than when you got to another stratum. So this idea that all strata have all questions wouldn't have to be there.
So a different way to think about supplements to the surveys, they would be stratum specific possibly, as you thought about those things that were key factors in understanding health and health behaviors.
DR. MAYS: It is a little bit in terms of what happens now in terms of NHANES. NHANES has a core set of questions that NCHS pays for, no matter what. If nobody is ever interested in them, that is still their core set of questions.
Then beyond that, they have interested parties within NIH that then add on questions. Part of what we need to think about is that there is now another center, the National Center for Minority Health and Health Disparities. Probably it might be useful to think about that particular center also rising to the occasion of the consideration for these population-specific groups, that there is funding to answer some of these questions.
The route of just the R0-1s or even the route of the centers, which is what I think they are funding these days, will not get what could happen in terms of that additional funding to be given to NCHS or whoever is conducting some of these large surveys. So we probably shouldn't let it slip from our radar, that that might be a useful request for the Secretary to consider in that office, since part of that office's mandate is to actually be responsible to all these populations.
DR. BREEN: Another thing came out of my personal experience. NCI funds a cancer control module as I said before for NHIS. In 2001, we also funded a cancer control module on the California health interview survey. I had thought maybe we could somehow pool those data.
In fact, as we have learned today, Asians -- or have been learning over the course of our hearings -- Asians are concentrated on the West Coast, and a very large proportion live in California. So why not?
Well, the why-not is because when you have a sample size of 55,000 in California but you have a national health interview survey with a sample size of 40,000, then the effective sample size of your California population becomes dinky. So all of these Asians are not counting for much when you try to incorporate them back into the national data set.
It strikes me that it might be useful for us to have some methodological -- or recommend some methodological work be done in order to be able to incorporate small populations that are concentrated in small portions of the United States to be able to be better represented in some way, rather than just folded into the national data set, which is pretty small, and therefore is not going to give them much more power than they had to start with in that national data set.
I don't have a solution to that problem. I don't know if this is -- you said you are not a survey statistician, so I will presume this is not your area of expertise, either. It is not mine. But it seems like an area that might be worth pursuing, because it would -- it seems like a terrible waste of data.
DR. MAYS: Let me just follow up, and then Eugene has his hand up. One of the issues might be that if we continue to focus on trying to get the national estimates -- I think we should fund some methodological work to do this, but it may be that if we continue to try and do national estimates, that it is kind of like chasing your tail to some extent, as opposed to even taking CHIS and something else in Illinois and something else somewhere else and actually doing a meta analysis.
A meta analysis takes a lot of time and energy, and you can debate it. Some people swear by it, other people swear at it.
DR. BREEN: We do have those techniques, and it would be a way to not waste the data, which really is the issue.
DR. MAYS: That may be something to think about relative to what are some of the kinds of RFAs, RFPs, PAs or whatever you want to think about, that would actually lead both to the development of some methodological papers, but also to somebody analyzing data in ways in which it then gives us some useful information.
So it isn't just the California study, but somebody can then do California, New York and Illinois.
Eugene and then Don.
DR. LENGERICH: I raised my hand a couple of comments ago, so it will be interesting to see how this comment actually plays out. I think Nancy and Vickie, your comments --
DR. STEINWACHS: Don't you want to modify your comment and bring it up to date?
DR. LENGERICH: This may be a summary, how's that? I'll do a meta analysis here. But I like the way the last couple of comments are going, steering towards methodologic issues or studies. What I had raised my hand earlier about was reflecting upon the sampling. I guess I was just going to point out that I think when we talk about sampling frames, we need to be very specific about the particular surveys and particularly those coming out of NCHS.
There is NHANES, which truly is meant to represent the country, I believe, and it makes no attempt to present regional geographic estimates, to my knowledge. It is very broad. Then there is HIS, which does take into geographical consideration and attempts to make regional estimates, and that is clearly part of what it is intended to do. Then there are things like SLATES, which is a state and local survey, which has that as its primary target.
So I get a little concerned -- and this is back a couple of comments ago, when we think about the sampling frame, we need to be very specific about which of those national surveys we are referring to. That leads me to be a lot more in favor of the final, where Vickie and Nancy were going with the methodologic targeted surveys, with our existing surveys, and support that kind of recommendation.
DR. MAYS: It was up to date.
DR. LENGERICH: Thank you. You just filled it in before I knew it needed to be filled in. You did a great job.
DR. MAYS: Russell, you're on.
MR. LOCALIO: Two followup comments on methodology. One we touched on, and that is how might one combine various surveys into something that is larger, and what would be the methodology around that.
Now, I know there is some ongoing work on the question of how do you take a survey that may be too small and come up with somewhat better estimates by using outside data, whether it is additional surveys or national surveys.
I have to say that what I hear from the street is that one of the difficulties in some of this methodological work is one of the issues that I have brought up repeatedly, and that is the restrictions on access to the data whereby you could do this research. In other words, if you have to go to Hyattsville to do this research, it is very hard to do it.
So I think one of the things that we have to always come up with, and this came up again this morning, are there restrictions that are currently placed on access to the data worth the cost, whether it is methodology, or in terms of individual subpopulations getting access to the resulting data? So I think a lot of this is tied in.
DR. STEINWACHS: I reflect on the fact, every time I think of the academic institutions as archaic, that the universities are about a thousand years old now, and we still wear those black robes, which I think we can thank the monks for, who were the keepers of the knowledge for a thousand years before that or so. So we have survived, and a lot of things have disappeared over that period of time, so maybe we shouldn't become too modern. Maybe being archaic has something to do with survival, even though it has nothing to do with immediate relevance.
DR. MAYS: I'm going to follow up on Russell's comment. I'm going to leave the black robes along, because I have to wear those every year. I have to do graduations, so I'll leave that one alone.
But anyway, when we met with -- when Sondig met with the committee at the full committee meeting, this issue was raised with him about sharing with the Census Bureau as a possibility of increasing. You can see the value of what the Census Bureau has done.
Maybe it would be worthwhile for us to actually put that in writing, to make that a specific request. The subcommittee has translated that request to Jennifer, and now we translated it at the full committee meeting to Sondig. But it might be useful to us. We keep coming back to it, we just keep coming back to it.
So I think it would be useful, rather than looking like, when you get a chance could you let us know, to, this is critical as we are moving along, trying to make recommendations to have a sense of whether this is doable or not doable.
So I guess I am going to suggest that that is something we may do, is just draft a letter to Sondig, following up on having raised this, and ask for a response in a specific amount of time.
MR. LOCALIO: Just to follow up on that, I did speak to him very briefly after his presentation. I said I thought this was an issue that needed clarification. If as I anticipated a problem came up, in having subpopulations getting access to subpopulation data, it would be a problem if they had to go to Hyattsville,
He was very open to it. He said, maybe we should have a meeting devoted to that only issue. We talked about the beginning of the year. I said yes, I would hope so. So maybe -- I'm not talking about a big meeting, I'm just talking about a meeting devoted solely to that issue and to what the options are.
Maybe what we ought to think about in preparation for that is, what have we heard today and on other days as to the needs that various people have that would have to be addressed in whatever an NCHS policy might be.
I don't think we can do much about Census. I think Census probably has a longer history and I think it has a more restrictive statute. But I do have to say that the e-gov statute, Dale, that you gave me has a very different outlook, in terms of sharing and especially sharing for what is called statistical purposes.
Almost everything that we have heard today in terms of peoples' needs fall within the ambit of statistical purposes as it is defined in that very recent legislation. It talks about analysis and complex analysis. So given that we have that new piece of legislation that says share, and given that we have expressed today a series of desires that people would like, for example, more of these data centers or something like that, given that we talked about the difficulty in getting access to data sets that have already been collected and are in file drawers, boxes --
by the way, I do know what Wordstar is, having used it -- in various forms that make access difficult, we ought to say, if we revisit this problem, what are all of the needs and then what are the possible solutions.
It should be very global. It should be not just one need and one solution, but all the needs and a variety of solutions.
DR. MAYS: I'm going to suggest then that the Subcommittee on Populations try and pull such a meeting together, and that we also ask for representatives to be from NHII in the privacy and confidentiality group, to join us for that. This really does overlap into some of their issues as well as ours.
MR. LOCALIO: What about having somebody from OMB as well, given that OMB -- Dale, correct me, is OMB e-gov? I think that was entirely an OMB initiative, and I believe OMB drafted it. So if possible, have somebody in from OMB and say what are the implications if the e-gov legislation -- how are they thinking about it, and should other agencies conform to that, even if the statute does not mandate that.
I don't know about Census, because as I said, Census is a much older and more difficult problem.
DR. MAYS: I think we should invite them.
MR. LOCALIO: Although if Census goes to the American Community Survey, that becomes less like -- an American Community Survey is not a census.
DR. STEINWACHS: It is like an NHIS.
MR. LOCALIO: Census is, you count every body. An American Community Survey is a sample.
DR. BREEN: The long form of the Census was a sample, too.
MR. LOCALIO: I know.
DR. MAYS: We are going to put that as one of our action items.
DR. BREEN: What is the e-gov legislation?
MR. HITCHCOCK: There are about 24 e-government initiatives. One of them is statistical sharing data for statistical purposes. Another one is doing a one-stop for access to government geospatial data.
DR. BREEN: Maybe we should distribute the e-mail or the website or whatever?
MR. HITCHCOCK: Yes, we can do that.
MR. LOCALIO: The thing you sent me was about 60 pages long. There are only three pages in that that are relevant.
DR. MAYS: We can ask you if you will send it, and then we will send that around to the committee.
MR. LOCALIO: Let me see if I can send that back to you, the three pages that I think are relevant, and if you could then take a look at that, verify that that is what you mean, or that it covers everything, and then you can send it around.
MR. HITCHCOCK: I can do that, and I can also send around just a page that lists all 24 of them, and links to each individual topic.
DR. BREEN: I think we should also have Census. The other problem besides the access to data that is confidential, not personal identifiers, but things that might reveal individual identities, is this commingling business, where you can't have the Census and any other data set that the government collects on the same computer. That is a giant barrier, too, which I think we need to try to think of some solutions to address. So I would encourage Census coming to this meeting.
DR. HUNGATE: I'm going to move a little bit from where we are, but I think it is building on the same base. I was impressed by the national children's study and its length of plan. I was saying to myself, that is going to yield a lot of data. Is it going to be responsive to the kinds of inputs that we heard here today?
So I've asked myself, what have I got to do now to try to get that to do that, to be sure that that happens? I ended up on this kind of an approach, and I'd appreciate feedback as to whether I'm crazy or not.
The lineup the national children's study has is 100,000 surveys, 100,000 participants. I know going in that is going to be inadequate for populations at some size, because it is not going to sample enough people to have anything representative at some size of the population.
Now, that is a mathematically determinate number, I think. It is going to have to be an awful lot bigger to get to some of the small populations that you really want to look at. So you have to accept that if you are going to do a good job, you are going to have to argument what you are doing. You ought to do it in a rational way.
So I say, I want to go look at the Census data and see what the population sizes are for the populations of interest. If those are the population sizes, and they are not going to be all the same size, they are going to be variable, there are probably groups that are very small, some that are bigger. So there is going to have to be a stratification decision of those group sizes, based on group size, for what you have to do to get at it.
I think that it is going to be that you also think about not only what is going to be the outcome of the survey, but who is going to use it when we are done with it. I think if I were doing it, the smaller the population is, the more I want to have a partnership within the population that does the work, so that I can specify within the national study what the study is.
DR. MAYS: That is an excellent idea. Actually we are going to put this on the agenda for tomorrow. I'm very glad you brought tit up now because I don't want to lose this.
One of the things that they talked about is that they are planning to do a similar -- they are in love with the women's health initiative, and they were talking about doing this similar to the women's health initiative, where what you would have would be different groups, academic institutions or someone out there who would actually then be the people helping to collect this data.
If that is the case, then if we work with them earlier on to specify this, then you would have to meet this requirement. You are responding because you can get certain groups. In SWAN, for example, part of why UCLA did that is because we are in a site where we can bring in the Asian population.
DR. HUNGATE: This makes sense.
DR. MAYS: So then what you have is, in the RFP, it clearly says what they are looking for in terms of expertise. That would help enormously, because at least you would be putting it with investigators who have to reach some of those populations. That is a requirement.
DR. HUNGATE: I guess what I am thinking is that our recommendation along this line would be broadly speaking to make this survey do that, the stratification. But it seems to me that we ought to also think about how do you define the population sizes and maybe put some recommendations in differences of approach that relate to the population size. I think it is not a one size fits all.
MR. HITCHCOCK: I think that is an excellent idea. One of the things that we have been hearing all along is how difficult it is sometimes for smaller community surveys to go in through the back door, something like NHANES or NHIS. If we are planning a new survey, why don't we plan it in such a way that there is a front door that groups can use to get into the survey, link up with the survey and possibly run smaller parallel studies that may be smaller or not so comprehensive in scale, but yet comparable on some items, at least.
Why not plan it with something in the design that would allow for outside groups to build onto the survey, participate in it?
DR. HUNGATE: I got a chance to speak with our presenter on the subject. We ended up on the Metro together, so we had five stops in which to talk about it.
DR. MAYS: You did good in those five stops.
DR. HUNGATE: I did all right. I asked what is their plan for argumentation, and he said, we have one, and they are actively going on direction.
So I think that this is not at all inconsistent with what they are doing, and that it just might be a way to tie in what we are doing in that augmented way.
DR. MAYS: I think it was good that we were able to get him at this meeting. I think to some it looks like there is not a lot going on, but in the background as I understand it, there is a lot going on, and that once it all gets pulled together, it will look like all of a sudden everything came together, when there has actually been work going on to help justify the direction that the study is going to go in.
So when I asked about sending in a letter, whether or not March would be a good time, he was like, no, sooner rather than later. So what we are going to try and do, which is why I asked Leslie to be on the phone with us tomorrow when we have some deliberation time, is that given that we may have a full committee meeting in January, the end of January, we should try and have a letter ready to go for that meeting.
Again, we don't want to have to, after the study is out, to then chase after it and say, can you do this, can you do that. I think now is really the time to try and move ahead.
DR. HUNGATE: I think there is a chance to get it right here, that there really is the leverage of doing one of them in a way that is truly responsive to the need. I think it would be huge in terms of other kinds of impacts. The pilot that works people understand after that.
DR. MAYS: Definitely, that is after lunch on our agenda, so let's revisit it, because I want to do some planning about getting a letter written about what we want to say.
As I pointed out to him, I said we might be recommending some additional workshops that you need to do. It might be we are recommending some different conceptualizations. So he really did say we should do it sooner rather than later, so let's discuss this some more. But I think that is an excellent suggestion. It clearly builds upon what we have heard in the hearings, so I think that will be very helpful.
I'm just going to go down some of the recommendations that I have heard, because I don't want to lose these recommendations, and see where we can go with them. Some of our presenters have given us recommendations, like the one from Ho Tran actually has specific recommendations. Now we have also heard those. So these are some of the things that I have jotted down, and maybe my interpretation, and then I'd like to get other things out and say let's get rid of that or keep that or something like that.
First of all, there is one about translation in terms of the language, in terms of the survey questions. I'm not going to flesh all this out, but definitely this issue about translating the surveys, particularly if we can translate the NCHS surveys, whether NCHS is collecting the data or not, the question of, can some of the NCHS surveys be translated up and available, so that if other people wanted to repeat that, they would be able to repeat that.
I think I have heard a lot of stuff about language. I think we were asking questions about language. Suzanne?
DR. HEURTIN-ROBERTS: In terms of language and actual cultural equivalency, I think there is a tension that we have to acknowledge. On one side we are calling for cultural appropriateness specific to a group of a survey instrument. On the other hand, we have Don with his population quilt of the U.S., and talking about meta analyses. There is a tension between comparability across surveys, and the idea of making something truly appropriate and useful for a culture, a specific population, let's say.
Now, I think you can't get around having something appropriate for a specific population, because otherwise you end up with data that is not very meaningful. On the other hand, if you want to compare, we have to devise some method to get around that, especially if we are talking about doing something on a national scale.
DR. MAYS: What would be really great if is in some way, either NCHS or NIH had this website, that the questionnaires are up there, and if I in California translated something and then had a equivalency, then I just put it up, and then it is there for other researchers to use it. If anything, then you end up with your variables in a whole lot of other data sets, which most of us are fine with that, even if we don't get access to it. But to have the questions up and available to some extent would -- if there was some way to be able to do that in terms of the use of technology, it would make all the difference in the world.
It costs quite a bit to translate an instrument. If it is done and you are very specific about how you did it so that you know which subgroup, and then it was up and available, it would really make a difference, I think.
DR. BREEN: There is a precedent for that. One of my colleagues at NCI is putting together a similar kind of thing for smoking questions. She is developing the tobacco control supplement to the CPS. So it is translated into Spanish routinely. She is translating it routinely or having it translated into some Asian languages.
The whole idea is to get it up on the web so that researchers who want to use questions or that whole instrument could do so. So it sounds to me that this is on a very small scale, and it is not informal, but I don't know that she is going to be developing the technology that would be needed to have an accessible data set with a large number of questions, which I think is kind of what we are thinking of. But this is a beginning, anyway.
So it is not unprecedented, what you are suggesting. I think it is very doable.
DR. CAIN: I think that the National Library of Medicine is doing this on a larger scale as well, not necessarily translated questionnaires, I don't know if they have branched out into that, but we could get some more information about what NLM is doing.
DR. MAYS: Can we ask NLM to maybe come to even the next subcommittee and find out if it is just a matter of, we need to ask and it happens? It doesn't sound like we need to write the Secretary over this unless it is a money thing, but I think that they may have resources actually to do that. So I think I would like to follow up on that.
Eugene?
DR. LENGERICH: This is a question that is mostly out of ignorance, but is there some sort of quality or a process that these translations should have processed through before they get put on that accessible website? So should that be part of the recommendation as well, that they meet a certain standard or process before they are available?
DR. BREEN: Definitely, yes. Just to say what translation method you used, and to provide full information would be better than having standards that somebody set.
DR. YU: I'd like to make two comments. One is that we should definitely encourage those investigators who have already translated certain instruments and who have already published papers from the studies to share those instruments at a website that is accessible to everybody.
For example, we had the Asian American cancer control questionnaires in Mandarin, Cantonese and Korean. I wanted to share them with a lot of people. I don't have the resources to put them up on the website. I tried spending $3,000 to put my niece into learning how to write websites. Unfortunately, she got stuck on graphics. She doesn't know how to put up the graphics. She knows how to write a program to put it up, but then the question is, how do I maintain it. I don't have the personal resources to do that.
There are already Asian investigators with data sets, with translated versions of instruments, especially on cancer screening tests and use of cancer screening tests. There must be at least about 20 studies already in 20 AAPI languages. We should somehow go to those investigators and ask them to put it up on the website, so people who are going to do research will hire native speakers who can read those languages, and make a judgment as to how two or three different versions differ and what is applicable to their situation.
The second comment I have concerning a question raised by somebody earlier about the issue of equivalence versus the standardized translations. I think that can be resolved by having core versus supplement questions.
Let me give you as an example the smoking questions that we added to our cancer control studies. When we did the interviews in Chinese, we added a question that I know as a member of that ethnic group that the Koreans do not have. Among Chinese from Taiwan, a very common addictive substance used is betelnut, chewing betelnut. That is associated with lesions in your mouth. That is also highly suspected to be a carcinogenic agent for oral cancer.
In the Chinese questionnaire, we copied and translated and tested the equivalency between the cancer control questions, smoking questions that NHIS used with our Chinese version, but in the Chines version we added a question, have you used betelnut. Then we asked how often did you use it.
In the Korean version that question is missing, because Koreans don't use that. So this would be how you would address the equivalency versus translation question. It is one approach. Just like the NHIS, they have a core question and then they have supplement questions. We should think that way in terms of studying the different ethnic groups. Then we would be able to capture something that is culture specific and yet be able to come up with estimates that are comparable at a population level across different populations.
So those would be my two comments.
DR. MAYS: I think that fits into what Don was recommending in terms of when you think about how you set it up. Once you knew the person's race and ethnicity, there are certain skip patterns that are engaged for those people. So it could be that it is still core, but it is core for a particular group. Again, I think that is something to think about.
So we are getting all these recommendations down, and I think what we should do -- I'll actually ask the staff to do it because I'm not as good at it -- is the distinction between what has to go up at the level of Thompson. Some of these can go directly to NLM, some can go to NCHS. NCHS now has a Board of Scientific Counselors, and it might be very useful in the January meeting for them to receive this as a set of issues that have evolved, because they give us some insight into possible ways that they think NCHS might be able to do this. So that may be part of the liaison role.
I think as we come up with these recommendations, you ought to be thinking about where they need to go. That would probably help us.
Training. There was a lot of discussion about training at all these different levels that I think we should think about. There is training of how to use the Census data, in terms of specifically at the community level. There was NIH training fellowships for data analysis, for example, in ANHOPI populations. There was training to insure that there is technical assistance. There was training in terms of the development of investigators from these populations.
We often don't talk about that as much, but that seems to me today has really emerged as the necessity for either technical assistance or going back to -- I know at some point i time when there were the training grants, some of the training grants that come from NIH, certain categories of people qualify and others don't, so it may be the time to examine that.
I think that -- Audrey, what was the program called that you ran at NCHS?
MS. BURWELL: Minority health statistics grants program.
DR. MAYS: Minority health statistics grants program has disappeared. That was another source of nurturing and developing individuals. I think that Dr. Sondig did raise that it would be nice if such programs could come back, but that may be a resource issue. But it may be important for us to identify these things. This does sound like this is probably at the level of Secretary in terms of commenting about the need for training.
DR. BREEN: Maybe, but the National Center for Minority Health and Health Disparities does an enormous amount of training.
DR. MAYS: You're right.
DR. BREEN: So I would consider them as substitutes. They actually have more money than the program that was --
DR. MAYS: And they can put out very specific programs to do that. There are a variety of ways to do that. In their center grant they require that. So there is a lot of different ways to try to contribute to that. So I think this may be something to bring to their attention in terms of this particular population.
MS. BURWELL: I would only like to caution that even though the National Center for Minority Health and Health Disparities has a larger pot, I think we should encourage development wherever it is appropriate, because you have a much better rate of success if you have more activities going on.
DR. MAYS: Suzanne.
DR. HEURTIN-ROBERTS: One of the things that we can't forget is the Pacific Islanders, the incredible diversity. We need to go beyond just training -- which is not unimportant, training regular scientific investigators, but we also need to train the local populations to be able to use data, access data, ask the questions of the data that they would like answered.
She said the word development; I'm thinking of foreign development that occurs economically and so on. I think there needs to be some sort of development in these areas, in terms of local access and -- what is the word? It is not research literacy, but some equivalent of that.
DR. MAYS: I think it is like a census model, almost as if it could get taken other places. You think about census data, this is incredible, to have the community groups accessing the Census data and having a query system.
It is basically what CHIS does. You take this mass of data and you pull it down to a query system. It is the same thing that we have seen Suzanne Haynes doing with the women's health data. They are able to get this so that you can do all kinds of cross tabs and find out various things. But again, there just hasn't been the focus on Pacific Islanders.
DR. HUNGATE: That is part of what I was thinking about, that group particularly and the approach to the national children's. It seems to me that one of the best ways to develop that strength is to have a contract within the island for the development of the information, and do it on a specific -- not on an abstract. I don't know whether it would work or not, whether anybody would apply for the contract.
DR. HEURTIN-ROBERTS: The issue is who could apply and would they be equipped to even apply. I don't know.
DR. HUNGATE: And I don't know.
DR. MAYS: Something you said reminded me of a suggestion you made. That was about generating a complete list of languages. I think you all over there were talking about that. That may be important. So as you are putting up these questionnaires or whatever, you have a sense of, oops, we don't have these ten, and if nobody is doing it, that is where we need to put some funds to do it. There are no researchers that have those.
So I think being able to -- and I have no idea how to do that. Suzanne, you are an anthropologist, so maybe you can help here. Aren't there languages that aren't recorded languages, that are just oral? So I'm not sure how we would tackle it.
DR. HEURTIN-ROBERTS: We are talking about those languages right now. There are languages like that.
DR. MAYS: Yes, so I think we need as a recommendation to find a way -- again, I don't know whose back yard that falls in, but to generate a complete list of languages. Then your comment was also, pursue a partnership for translation and use. Again, I think if it is available, what you will see is that the agencies, institutes and centers will think more about using that mechanism.
DR. YU: I'd like to supplement the discussion about training, and bring in one more perspective. The national research service award, NRSA, is Congressionally funded. I often heard from people administering those grants that they haven't got enough minority applicants. That is one perspective.
The other perspective that I wanted to share with you is that in the mid-90s, I was approached by somebody in Samoa, asking me whether as a professor of epidemiology at San Diego State University I would be willing to write an NRSA grant for them to bring young public health workers from Guam, Samoa and the Marshall Islands to San Diego State University to train them in epidemiology and biostatistics, using as examples data from their territories.
I thought that was a great idea, but I told them that I could not pursue it, and the reason was that I am a lone ranger in my school. In other words, I am the only AAPI. If I were to pursue it, it is a sure failure, because I do not have colleagues who know much about the issue or the data.
Yes, they will be very happy to be co-PI's, but they would be of little help to me in terms of, once we get funded, how do we get the work done.
I guess my question now is, or the point I am trying to make how, is that we should think about ways to utilize the NRSA, but also think about local settings, where we could get a critical mass of ANHOPI researchers who could work together and train people from this population of students or public health students from these populations to utilize the data.
This is what led to my idea of proposing an ANHOPI policy research institute, because I do not see this possible within a university setting. There isn't ever going to be a critical mass, even at UCLA.
DR. MAYS: I guess what I would say is that there are actually a couple of places that one could piggyback on that to international health. In the summer ICPSR -- I don't know if they have done it in the last summer or two, but in the past they have actually had workshops in their summer session on Asian data analysis.
So I think what we might want to do -- I think the idea is a good one, trying to figure out how to stimulate research within all these training things to do this. In the summer institute in Johns Hopkins, they have one, the New England Research Institute. You get a group of people and bring them together in the summer, and you are in some wonderful setting for a week. U-Mass does it, so it is the epidemiologists who actually do that. It may be useful to try and stimulate someone to do that on an ongoing basis.
Yes.
DR. BREEN: And building on Elena's idea but shifting it a little bit, it wouldn't necessarily be a bad idea to have the public health people coming from Guam and Samoa into these programs that are not particularly focused on AAPI populations, but bringing their data with them, because they would have the advantage that they would be working with good researchers in the field, and good professors in the field, and those professors and the students they would be working with would also be introduced to a lot of the health problems and become more knowledgeable about the health problems in areas that otherwise they probably would not be exposed to.
So it wouldn't necessarily be a bad -- it might be a very good thing, to mainstream them into these other programs, but as a group, not as individuals. I agree with you, the idea of being the lone ranger or being isolated is very difficult. It is not -- I think a more nurturing environment would be better.
DR. MAYS: You can apply to do that at NIH, to have T-32s. There is a short training.
DR. HEURTIN-ROBERTS: I think Nancy's point is that you can apply for those things, but what you really need is to arrange for a group to get together en masse and work together so there could be support.
I was recently in a meeting with Alaska Natives, and we were telling them about training opportunities. Even if they could get here, their young people don't fare very well, because it is such a completely different environment. So at least if there is a group together, there is some support to get you through this.
DR. MAYS: Good point. Virginia.
DR. CAIN: I was going to also mention that that there is some room though for the individual people coming and working with a professor over here, which we do certainly have in the individual fellowship opportunities, so that people can pull together an application with a professor over here and come over for training. So I don't think those should be discounted.
DR. MAYS: I think what we are going to have to do is figure out who that goes to. I'm not sure who we are talking to. It is a great idea, but somebody out there has to do that, or we have to figure out how do we publicize who the experts are.
It may be that after we have these convene an expert workshops or something, which is what I think the forum suggested, then we have a list of people or something like that, who on somebody's website could be listed.
Audrey.
MS. BURWELL: In terms of bringing together students, we have the Washington -- the WINS program, the Washington Interns for Native Students. We have the HACU program. So there are models for Hispanics. So now we have to find the critical mass for the ANHOPI. Ho Tran had it in here, to create AAPI serving institutions. That is one way.
There are ways that several of the institutes or others can fund these students to come to the existing public health institutes that are here. So there are a number of short term things that can be done in addition to some longer term thinking.
And in terms of the website for languages, the Office of Minority Health has a center for linguistic and cultural competency. That is something that we probably would love to be able to put up on the OMHRC website.
DR. MAYS: Great. We don't have to write a letter then.
MS. BURWELL: No letter.
DR. MAYS: That one is taken care of. Just report back when it is finished.
We talked about this ability to determine foreign born versus U.S. born data. It is funny you raised it, because I have to do a presentation on it, and I thought it was so simple to get it. I spent hours to find out it is not simple at all. So that is one of the recommendations we have, the ability to generate regional data, particularly when people are geographically clustered.
But the question comes, whether or not at the federal level they are willing to do regional data, or whether that becomes a regional -- like Region 9, in terms of presentations. It is very clear that Region 9 alone, if you did major surveys in Region 9, that they would be able to contribute to greater knowledge about ANHOPI populations. But again, I don't know enough about Bethesda to know how this works.
MR. HITCHCOCK: I think that in the federal statistical systems, they basically use the standard Census regions, which are the four broad regions. I have not seen population estimates based on the Department's regions.
DR. MAYS: Any thought about, is this one we leave alone, or is there any thought about, is there any value to approaching Census about this?
MR. HITCHCOCK: That is a good question, too. You saw what Region 9 looks like. It contains California, Arizona and Nevada or something like that. It is a real hodgepodge, a little outside the administrative concept.
DR. STEINWACHS: Let me try another twist on you. The sampling approach for NHIS is cluster sampling. There are certain areas that stay in the sample frame for at least a decade, other things that rotate. So you can think of a way of restratifying the cluster sampling so you can still do your regional estimates, but essentially have data being collected over time in certain geographic areas.
You might then still have to over sample in those areas, too, so I'm not saying there isn't a cost with it. But you could develop a structure that would do this, that would fit without having to -- it has the complexity, but it doesn't make it that much more difficult.
DR. CAIN: I have another recommendation. Are we ready to change?
DR. MAYS: Yes.
DR. CAIN: I really like the idea of paradigm change. One of the things that Elena said that was very useful was the idea that we have focused so much on biology and biological factors, and we probably should focus equally perhaps, if not more, on social and behavioral factors and social and behavioral contexts, in which all this occurs.
I would argue that if we are trying to address, reduce, eliminate health disparities, we will get much farther by collecting social and behavioral data than we will be collecting simply genetic differences.
DR. MAYS: So what is your recommendation?
DR. CAIN: My recommendation is that we emphasize -- give greater emphasis to the social and behavioral factors involved in health disparities.
DR. MAYS: I think that recommendation is very good, but I think what happens is the way it gets lost after we say it. There are a million and one ways to do it. We don't have enough consensus about what the priorities would be. Those priorities differ by some of the racial and ethnic populations.
I think if we are going to do that one, we may want to think seriously about whether we might want to have some hearings to try and come up with recommendations of what some of these cores should be, some of these core measures should be. Then we have to adapt them a little bit to which surveys they fit in. You can do one thing in NHIS, and you need to do something different in NHANES. Then if you have an investigator, it is an R0-1, you can't even tell them what to do.
But I think if there was at least a body of variables and some rationale, and then the encouragement in the RFAs as to why those are important, then I think you would generate their use.
So I honestly think that we have reached the point that a large group of people would say that they are okay with doing it, but it is like, we start right away with SES, and people don't want to tell you their income. Some people are arguing now that we need to know more about wealth than we need to know about poverty.
So it would help us -- if we really want to do this, I think the best way we can help is to be more specific. It falls right into your office.
DR. CAIN: I think it is useful to do something like that. Certainly in talking with many of the biomedical researchers, they are interested. I think there is a recognition that they need to go beyond what they have been doing. But they are not going to turn their study into a behavioral study, or they are not going to become SES researchers. But if we could give them some reasonable approach to tackling it in their study that doesn't turn it into an entirely different study, I think they would be amenable to collecting some data.
DR. HEURTIN-ROBERTS: But I think we need to do more than just add items for biomedical researchers. I think we need to shift emphasis on the investigations that we are doing. I think we need to invest the resources in this, agreed, in a very coherent and systematic fashion and studied fashion, but I think we really need to get moving on this, because we are not going to get much farther than we are unless we start moving in that direction.
One of the things that we could do is, if we were going to have these small targeted things, I think that we could perhaps work to agree on what social and behavioral factors might be included in the cores of Don's quilt.
DR. STEINWACHS: I'm going to go home and start working on my quilt. I can tell already, I think I need some training.
Could I just throw in one thing? Vickie, you had it in your list before of recommendations. At one point I thought we might have some session looking at alternative methodologies that dealt with the quilt.
One of the things that always worries me as we try and strengthen the social and behavioral, and I would argue, some of the other environmental factors, is that our surveys are designed not to collect anything about the social environmental community context. Yet we know much of health care is shaped at the community level, and a lot of health factors are, too.
It also will get Russell to begin to think about how do we deal with the privacy side of this. But there are some designs that are working now that do have qualitative data being collected at community levels.
DR. HEURTIN-ROBERTS: You are my new best friend.
DR. STEINWACHS: I knew we could bond over this relationship.
DR. MAYS: This is a really friendly group.
DR. STEINWACHS: I just want to plant the seed, and then I'll let it go. RWJ funds the center for setting health system change, and they have a design that makes national estimates, but has high sampling rates in 12 communities around which they do periodic case studies. Those case studies get a lot of interest. They go out and talk to key actors in the community systematically and synthesize it. You can put the health utilization data together with that, and in a framework like NHIS, that actually sits in some communities for ten years, you could have things that would help build a mini-longitudinal series that would help you understand why you see something different for ANHOPIs in one context than in another.
DR. BREEN: Suzanne was at these meetings, too, a series of meetings built up to a larger one. NCI, when we first started working in earnest on health disparities, had a meeting of experts to think about how we could best move forward.
What we did was to call it an agenda for understanding the social determinants of cancer. A lot of good ideas came out of that meeting. I think this discussion is getting really rich. We are thinking, we have finished up one set of hearings, and where are we going to go next. I think to think about methods to better use the data that we have and use it more efficiently, and also to think about what are some of the key pieces we need to study and how to go about it.
As people at the meeting pointed out, half jokingly, but only half, was if money had gone into social determinants like it went into the Genome Project, we would know all about social determinants, because it is very complicated. Part of the reason it is complicated is because it is complicated, and another reason is because people from many different disciplines are weighing in on it, and they have different things to say about it.
But it is not out of the question to have people collaborating across the work that they do in order to do a much better job. But it would require not only a research agenda or a plan, but also significant resources put towards it. I think that is the kind of recommendation that this committee could also make, if it were a thoughtful recommendation to really beef up the activity of OBSSR and that sort of thing, so that there is much more of a social emphasis on this work than it has gotten in the past.
Social science has really gotten second shrift or third or fourth or 18th in the medical sciences. It is not used as effectively as it should be. There is a lot more out there that we don't employ or deploy. I think we can think about how we can move these things together. Some of the ways we have been thinking about joining data would be an important first step towards doing that, that could be built on a foundation for building.
DR. MAYS: One of the things that we should do at the executive subcommittee retreat in November is, if there is some major project that we want to do that is either going to require commissioned work or more activities, that is the point at which to bring it up, so in the planning phase they know it.
I know we had talked about the mental health statistics, and the whole issue of what is a core set of questions that you should be asking around health, and how can you ask those questions and not have any mental health data. I think maybe the presentation at the meeting is a broader one to say that to some extent as we think about the portfolio of health data, that it does need to be broadened in this day and age, and it needs to be broadened to include social determinants, it needs to be broadened to include mental health, and that is probably something we should undertake to consider in a serious way the recommendations that we could make, both about doing those types of studies and that type of funding could be available within the research side at NIH, but at NCHS what you have is a rethinking about what core is, and some commitment in a collaborative way of some of the continual funding of some of these things so that you just don't have, well, if I'm not interested in mental health, it drops out. Blood pressure never drops out. They indicated that there are better measures of blood pressure, but instead, they stick with the old one just so they can consistently have the data. But it never drops out, even though there are better measurements of it.
But we have not seen that, and we haven't gotten there yet relative to some of the population health issues. Maybe that is a way to think about presenting this to the executive committee as part of what we want to do.
Then we are doing racial and ethnic groups, but we are also doing population health. I think that is a good way to think about an agenda, because it is an agenda that includes everyone, but is very specific, like a targeted survey. We make sure we have our groups, and then we go back to the broader population health. How can you really comment on population health if you don't have some of these people there? It is almost like Elena's presentation about HRT; oops, you may have jumped the gun, and had you had these other populations in, you would have learned about more than one answer for this particular problem.
Russell.
MR. LOCALIO: I need some clarification. What types of information are we talking about when we say behavioral or social characteristics? What are we talking about? Can you give some examples?
DR. HEURTIN-ROBERTS: I don't know what would go in the core, but it could be social support, social cohesion, social capital.
DR. CAIN: Community characteristics.
DR. HEURTIN-ROBERTS: Community characteristics, geographic information, environmental -- well, that's not social.
DR. BREEN: But environmental information is social because it gets located by human beings in human systems.
DR. HEURTIN-ROBERTS: Right.
DR. BREEN: Does that give enough?
MR. LOCALIO: Yes. Are we talking about whether you ride a motorcycle, things like that? Are we talking about, do you carry a weapon? Are we talking about diet?
DR. HEURTIN-ROBERTS: It could be diet. I think diet would be important.
DR. MAYS: If it is a health study and the health study is interested in predicting certain diseases, then maybe there are diet questions. But in addition to diet questions, you want physical activity questions, but what would be different is, you might ask about safety, in terms of your ability to engage in physical activity. Not everybody has a park. When you put the context on it, we will all know that we will ask about the diet questions and we will ask about physical activity. But if we think about certain populations, we think about, if you live in a rural area, maybe we don't ask you about only whether or not you have a membership in a gym; we might ask how far you walk to get to the bus.
DR. CAIN: Or the physical activity in your work versus -- we think about physical activity when somebody goes out jogging, but there are a lot of occupations that are much more physically active than others.
DR. STEINWACHS: That doesn't apply to the occupation we are in.
DR. CAIN: No, it doesn't.
DR. MAYS: I don't know that questions that are there would disappear as much as, some of the questions that are there are asked in a way in which it is indicative of a specific lifestyle of a specific group.
I think Virginia's example that she gave is perfect. I was at a presentation, and somebody was saying how -- and it was Chicago, so I really knew a lot about the neighborhood they were talking about. They kept saying, do you know how far you have to walk to get to the bus? They live in a place where the elevators are broken in the projects, and they walk up ten flights of stairs. But instead they were asked about jogging and leisure things, and it came out terrible, just terrible. You go, but they live to be 90.
MR. LOCALIO: You have answered my question. I was just going to say, you can't ask a question about lifestyle unless you ask it in the context of the population, because it varies.
DR. MAYS: The problem is, there are many researchers that ask about physical activity, and they really believe that they are doing well. But if we had things on a website where they say, I never thought about that, I think you would find that they would actually ask it.
MR. LOCALIO: I also want to make the comment that, I know some people have talked about the Genome Project and genetics, and I know there have been a lot of resources spent there. But there is a whole area on gene-environment interaction, which I don't have to tell people about, but you don't have to just use just genetics and just the environment; you have to look at both together.
I think we are talking about a very large survey, if we are going to get all this information. How do you get all of this information in a survey or any type of a home visit without spending a day and a half with people? I think we have some very practical issues here that people have to think about.
DR. HUNGATE: To that point, I think we are accustomed to thinking of surveys as something we understand and use all the time. Surveys don't make very good use of the efficiency of the Internet and information management. I think we are going to have to start thinking about how do you find groups that have interests that are different from the normal interests, who might like to put their own data into an Internet point, so it is self reported information as opposed to surveyed information, so it doesn't have the statistical validity that you would like to have because it is not sampled correctly, but it is information that comes from a point that needs to get added into the other survey information in order to get the benefit.
Now, I think that is a methodology issue that I don't know the answer to, but it seems to me is important as we move forward in a new information system that might really enable us to get a lot more information than we can get with surveys, if we knew how to put it together.
DR. MAYS: I just want to comment on Russell's comment. When we had our hearing in which we brought in a lot of the population-based survey people, one of the things that we were all surprised about is that they don't talk to each other a lot.
I don't know that any one survey has to ask it all. Weren't we told that there is a data coordination or survey across HHS?
DR. BREEN: Data integration.
DR. MAYS: Data integration, that is what it is. So I think that is a possibility. Even if someone mapped out, NHANES asked this and it does that, so and so asked this and it does that, then figure out, can you link any of this. It gets us back to some of the linkages and what Nancy was saying before, in the sense of some of the other things, meta analysis or proving something that might help us to be able to get at some of this.
DR. LENGERICH: I want to go back to Russ' question for clarification, and draw a distinction between the two sets of answers that I heard. I thought one was very much a set of social environmental data and another was a set of individual based information about their social patterns or maybe their social history.
I think those are two substantially different sorts of approaches to gathering information about the contribution of a social context to health. I think when we started these, we were very focused on the collection of individual based data. So I think as we broaden that health approach, I think we need to make sure that we keep those two issues separate, because there are different methodologies and different issues involved with them.
So I would like to see us keep individual social and behavioral determinant issues separate from the environment and social determinant issues. I think they are both important, but they are a different set of methodologies, different set of players, I think.
DR. MAYS: Nancy.
DR. BREEN: I think that is a really important point and a good point. I think I'd like to make another point related to it. I think it is also important to -- this is where it becomes critical to somehow ground the individual data we are collecting in geography. Of course we need to keep in mind these confidentiality concerns, but we also need to -- since they are likely to be collected in different ways, and they are different data collection efforts with different methodological concerns, they need to be linked at the end of the day, so that we can university the social context within which people are behaving as they behave. I think we are going to get a much better explanation for why they are behaving those ways.
Some of it is cultural, and they may be bringing that from other countries, but they may also be functioning in a neighborhood that is their culture or is not their culture, and therefore they are reacting in ways that may seem irrational to social science theory or economic theory or something like that. But in fact, it can be explained if you can link that individual behavior into the broader social context.
I think that is where we are doing in the social sciences and in analyses, but we are not there yet. But I think there is a general consensus, a general feeling or ethos that that is where we would like to go. If this committee through its recommendations could help to push the thinking in that direction more explicitly, I think it would be very useful.
DR. LENGERICH: I agree. I see there are three areas. One is individual level information about social and behavioral issues, and the second is the environment. The third is as you were saying, what are the methods to put those two types of data together to produce even more relevant predictors of health status, health outcomes.
DR. YU: Multi-level analysis would do that.
DR. LENGERICH: Well, yes, that is right, but I don't think that is used enough. So I think the recommendation is getting us to use that, as researchers to use that more frequently.
DR. STEINWACHS: One side comment. A lot of these do actually cluster in the family, but we don't develop information on the family. So it is really not an independent sample. We have done that already, but we ignore it largely.
DR. CAIN: I think it is helpful to think about them culturally, but also recognize that the data can be collected in a number of different ways, and it is not quite so neatly divided out. You can collect data from individuals about their social environment, and you can go to the social environment directly and get the information from them. There are a number of different techniques there. So it is not quite as clean a division as we are discussing.
DR. STEINWACHS: And with kids, we sometimes use people in their environment to actually report on them, and get into the elderly there sometimes also.
DR. HEURTIN-ROBERTS: I'd like to get back to the question of how long a survey would it need to be. Obviously we don't want people there for a week.
Certainly the social sciences, sociology, political science and so on, they are very comfortable with surveys. There are ways to get data with minimal -- while minimizing the time and the effort needed. That is part of the task to be accomplished.
The other thing we can do is, I would argue that the social sciences, social information, behavioral information, some of that in some limited amount to be determined by some group does need to be part of a core. Yes, you could ask everything else, but you probably don't want to, but there needs to be at least some limited information across which you can make comparisons for a population or several populations.
I think that if we -- it is fine to have -- we were talking about possible self reported data. That is okay, but that data is not nearly as useful as data would be if it were done with good sampling and a systematic fashion in a real survey. So I think there needs to be a social component of whatever survey core we are talking about.
DR. MAYS: I think that is something important that this committee can give some serious thought to. I think based on what we were saying that we should consider that as part of the direction that we are going. I think we were starting in pieces with the mental health data, and doing it in crisis fashion; we've got to take care of NHANES and we've got to take care -- maybe it is time for us to take care of this as an issue. We still have to take care of NHANES, we still have a little crisis, but I think that this is something that we need to discuss.
There is one other recommendation that we need to talk about and then I think we should end, and that is the American Community Survey, what we want to do about that.
DR. BREEN: There is one other one on that same page that we need to address.
DR. MAYS: Okay, but I just want to make sure we don't lose this. If these recommendations could get sent to us by Tuesday, because Friday is when we have the executive committee retreat, then we can pass them around. You can make sure if there is anything left out, or anything you want to tweak, and then when we are at the meeting, it would be useful that we could actually have that to share and discuss, because that is when we are doing our planning.
I had on here about ACS, whether we should make recommendations about ACS. Also, the need for translation of ACS. What else did I have about ACS? A recommendation that ACS collect some health data. So I have that for ACS. Do you have another one?
DR. BREEN: Above that is, require the Social Security Administration to collect racial and ethnic data. I had occasion to try to use social security data a year or so ago, and what a mess it is. Let me tell you why I say that.
The Social Security Administration --
DR. MAYS: Remember we are on the Internet.
DR. BREEN: The Social Security Administration -- when people come into the social security system, they need to fill out a form. They have to give their date of birth and they have to give a lot of information. And of course, everybody in the social security system is filling out this information.
The problem is that the data doesn't all get computerized, so they don't all exist in the database. What has happened over time, as ebbs and flows for funding in social security have occurred, they either put more or less data into their database. They either summarize or they don't summarize their database. I don't think they put a big priority on getting accurate racial and ethnic data collected from people, which you would think they would be getting good data.
I guess what has happened is, over time the forms have probably changed consistent with OMB regulations. It was very troubling to me that this wasn't a good source of data. I had thought, oh my goodness, the Social Security Administration, this is going to be gold standard type data, and it isn't.
One of the reasons it is not, and I was told this by someone who is now retired, so I can share this, but she said that before the data was under the Nixon Administration, these data were used to expose something. Prior to that, the data had been routinely used by researchers. It is when data is used by researchers that it is good data, because researchers clean the data, they evaluate the data, they make sure that the data is good data. They point out to the people who are collecting these claims data the problems in the data, which they then rectify.
Unless you have this relationship between the data collection agency and researchers so that you have got an iterative process which is continually improving and cleaning the data, you don't end up with very good data.
So that is what has happened with social security. That is the reason it is not very good data. I think that it would be very useful to focus on getting better data from the Social Security Administration.
Now, for our purposes, we have Medicare data, but it is still -- well, social security is no longer linked to Medicare, and so I don't know how they get their information, if that is gotten independently.
MR. HITCHCOCK: I think Medicare gets their information from the Social Security Administration.
DR. BREEN: So it remains a problem for the Medicare data as well. I know NCI for example has a SEER Medicare data set, and that is used by researchers a lot, so that tends to be relatively clean. But there are problems with social security numbers, they don't use social security numbers exactly, but there are identifying numbers based on social security somehow.
So I think we need to focus on this, maybe recommend that the data set be more available to researchers. I'm not sure exactly what we want to recommend, but I think we should attend to the social security data.
DR. MAYS: I think it would be good to bring them in and let's hear from them. I know that the IOM panel, the one that we just got the report from, what is that one called?
MR. HITCHCOCK: Adequacy of the racial and ethnic data collected by HHS for administering its programs.
DR. MAYS: They had some hearings. I think they actually met and talked with the Social Security Administration. So it may be that we can find out -- I don't know exactly what all is available. I know that the workshop data is available. But I think they are getting close to the report, and it might even be possible to find out what they found out. I think they are making recommendations. So we may want to tap into that, because the work for us may be done about the investigation of what the issues are.
So if we could put it on radar. Can you talk to Ed Perrin and ask as to whether or not that is information that might be shared with us, and if there is a recommendation that may already be done.
DR. BREEN: While we are talking about large administrative data sets that we do have in this country that would be very useful to researchers, in addition to Medicare and social security is the IRS data, which is also limited in the information that it can give. But it is a pretty good source on income and wealth.
Social security data, the reason I had wanted it was for the earnings information. The combination of the IRS data and the social security data ideally should provide a pretty good profile of income and wealth in this country, as well as employment.
DR. MAYS: Can I just ask, is that IRS data set readily available to researchers?
DR. BREEN: It used to be also.
DR. YU: Do they have race and ethnicity data though? I don't think so.
DR. BREEN: I don't think they do have race and ethnicity data, but they do have social security information that could be linked to the -- they do have a social security number which could be linked to the social security information, which could be improved to have adequate racial and ethnic data.
DR. MAYS: Russell has to say something.
MR. LOCALIO: IRS does have a database that is available to people. I talked to somebody I think two years ago about this. But of course, you know the most confidential information we have in this country are individual tax returns. So it would be impossible for anybody to get individual identifiers. That is the most confidential information in this country.
DR. BREEN: I didn't mean that they would be available to researchers, but it would be similar to -- they would be linked by the government, by one of the agencies that has the ability to do that.
MR. LOCALIO: We would have to check on that, but I think that is one thing that never happens. I think the IRS data is the one data set that nobody ever gets. That is my understanding.
DR. HEURTIN-ROBERTS: One more quick recommendation. I very much like the idea that we need to study persons of mixed ethnicities as a group in their own right. I think we are trying to stick to a model of ethnic diversity in the U.S. that doesn't really exist. I think that more and more, we are going to have persons of mixed whatever, as we have greater communication, greater mobility. So we need to address those people for what they are, and not try to categorize them as something they are not.
DR. MAYS: I think that is very true, in terms of the future. That is exactly what we are going to deal with, is the kids at this point. If you look at the data, there will be a high rate of mixed ethnicities as we move on.
We have five minutes, so I am going to seriously stop us at five.
DR. BREEN: What is striking too is, Elena is finding that -- and this has been found in the Latino community too, that adolescents who are in transition have a really hard time transitioning in this society and finding their identity.
It seems like that should be a focus, because I think it is important to focus on difficult populations, the canary in the mine again. This is a group where it may be a microcosm of problems adolescents face in this society, and would help us understand a lot more broadly than just this group, because the problems are so intense in that group.
DR. MAYS: Do we have anything we want to say about the American Community Survey?
MR. HITCHCOCK: Can we get them to come and talk to us? I always like to hear from people first.
MR. LOCALIO: We have a contact.
DR. MAYS: Okay, so that is also on our radar. So it is very clear that at the March meeting, we need to be on the side of one of those three-hour breakout sessions if possible, Audrey, because it seems like there are a couple of people that it would be useful for us to hear from.
Are you talking about the full committee? Or is this just something for us as the subcommittee?
MR. HITCHCOCK: I would think this is something they would like to hear about.
DR. MAYS: All right, then it may be the full committee. All right, folks. Tomorrow, because I know some of you may also be wanting to catch planes, here is the way that we go. Audrey, do you have any updates?
MS. BURWELL: Mr. Early can't make it, but he has submitted written comments.
DR. MAYS: Okay. We will start at nine tomorrow. We have a presentation that actually starts at 9:15, just so that you know, from Elena with the California Pan Ethnic Health Network. CPANS is what we call them here. Then we will have a presentation tomorrow from somebody from the Northern California Cancer Center. Then we will have someone from Palau by phone, I don't know what time it is there, and then we have Dr. Murray and Dr. Sorensen, who are with us. Lunch, and then after that we are going to talk to Leslie by telephone about the NCS.
There was one other item that we were going to try and do at the meeting. Oh, I want to talk about geocoding. We have done a little bit of that today, but I want to get specific about that. We want to talk a little bit about geocoding.
So we should be out of here tomorrow before 3:30, so we should be finished by 3:30, and if we can get out of here earlier than 3:30, we will do that. It is up to you. I am giving you the schedule.
DR. HUNGATE: I thought it was up to the Chair.
DR. MAYS: No, the published schedule is 3:30.
DR. HUNGATE: We have to talk to our leadership.
DR. MAYS: Well, your leader will get you out by 3:30, because I think people need to know when they can leave to go catch their planes. Then I turn it back to the members; if they all sit mute, then we are out of here earlier. But otherwise we will be out of here by 3:30.
(Whereupon, the meeting was adjourned at 5:00 p.m., to reconvene Friday, November 14, 2003.)