Title: Using BRFSS Data in Conjunction with Other Datasets
Author: say5
Last saved by: tzw4
Company: CDC

Chronic Disease and the Environment:  Using Behavioral Risk Factor Surveillance System (BRFSS) Data in Conjunction with Supplementary Information Sources  

Using the BRFSS in Combination with Other Data Sources 
The Behavioral Risk Factor Surveillance System (BRFSS) provides state- and local-level population-based health-risk behavior and chronic disease information that can be used to target services, document geographic variation, track trends, and conduct research.  In some instances, these activities can be enhanced by combining information collected by the BRFSS with information from federal, state, or local data sources.  In the past, for example, BRFSS data have been combined with data from the U.S. National Health and Nutrition Examination Survey (NHANES) and the U.S. Census.  For this project, we demonstrate how BRFSS data can be used in conjunction with data from the Environmental Protection Agency (EPA).  

Environmental Quality Data and the BRFSS 
Pollutants in the environment have been linked to chronic diseases such as cancer, asthma, and cardiovascular health problems.  The BRFSS does not directly measure environmental quality (e.g., air pollution, water pollution, community-wide pesticide spraying); however, environmental information available from other sources such as the EPA, the U.S. Geological Survey, and state and local monitoring networks can be used in conjunction with BRFSS data to explore links between environmental risk factors and chronic disease.  For example, the combined data can be used to conduct ecological or geospatial analysis, generate hypotheses regarding pollutants and risk factors, or identify geographic areas suitable for targeted analytic investigations.
	
The Air Quality System (AQS) and the Air Quality Index (AQI)
The EPA’s Air Quality System (AQS) database contains measurements of criteria pollutants such as ozone (O_3), sulfur dioxide (SO_2), carbon monoxide (CO), and particulate matter (PM_2.5, PM_10) concentrations at sites in all 50 states, plus the District of Columbia, Puerto Rico, and the Virgin Islands (Appendix A).  Ambient measurements are collected from a network of national, state, and local air monitoring stations and used to create the Air Quality Index (AQI).  The AQI is used to report daily air quality based on levels of the criteria pollutants.  It has a scale of 0 to 500 and is categorized into the following six groups:  

AQI Index Values | Levels of Health Concern | General Health Effects
0-50 | Good | None for the general population.
51-100 | Moderate | Few or none for the general population.
101-150 | Unhealthy for Sensitive Groups | Some health effects may be experienced by sensitive people (e.g., children and adults who are active outdoors or have respiratory disease).
151-200 | Unhealthy | Mild aggravation of symptoms among susceptible people, with irritation symptoms in the healthy population.
201-300 | Very Unhealthy | Significant aggravation of symptoms and decreased exercise tolerance in persons with heart or lung disease; widespread symptoms in the healthy population.
301-500 | Hazardous | Early onset of certain diseases in addition to significant aggravation of symptoms and decreased exercise tolerance in healthy persons.  At AQI levels above 400, premature death of ill and elderly persons may occur.  Healthy people experience adverse symptoms that affect normal activity.

The intervals on the AQI scale denote the level of air pollution and are related to the potential health effects of the daily concentrations of each pollutant (Appendix C).  An AQI of 100 generally corresponds to the maximum level allowed under the Clean Air Act (Appendix B); when an AQI level of a pollutant is in excess of 100, the level of that pollutant is in the unhealthy range. The EPA determines the AQI value on a daily basis for each pollutant.  The highest individual pollutant AQI score for each major metropolitan area is reported as the daily AQI score for that area and the pollutant with the highest AQI value is identified.  For example, if the EPA reports an AQI level of 90 for O_3 for a given metropolitan area, this indicates that the O_3 level in that area is at the high end of the moderate range and that O_3 has the highest AQI reading of all pollutants on that day.  

2006 BRFSS Metropolitan Area Data
Starting from 2006, BRFSS uses the new definition of metropolitan area. However, for this project, we are still using the metropolitan areas as defined by the U. S. Office of Management and Budget and used by the U.S. Census Bureau in 1999, that is, the historical metropolitan area definition. The reason for this is that AQS data 2006 still used the historical metropolitan area definition for data collections and identifiers for the new metropolitan area code were unavailable in AQS. In order to match AQS data with BRFSS, we had to choose the historical definition. The other reason is that we had used the historical definition to match the BRFSS and AQS data for previous years (2001 to 2005). We believe that using the historical definition can help the consistence and continuity of the project. That way, we can make it easier to identify trends and also make the research findings more comparable.     

In this document, any mention of metropolitan areas refers to metropolitan statistical areas (MSAs), primary metropolitan statistical areas (PMSAs), or New England county metropolitan areas (NECMAs).  Most metropolitan areas are defined by clusters of counties; however, in the New England states, city and town areas (NECTAs) are generally more appropriate.  The Census Bureau has defined the NECMAs as an alternative to the NECTAs (Appendix G).  NECMAs were used in this project because the BRFSS only collects information on counties, not cities or towns.  MSAs, PMSAs, and NECMAs were included in this analysis based on population projections from the Census Bureau.  We calculated annual summary statistics for CO, O_3, PM_10, PM_2.5, and SO_2 in selected metropolitan areas from the 2006 BRFSS (Tables 1-6; Appendix D-F).  

Limitations and Inappropriate Uses of AQS Data with the BRFSS
Although the AQS data can be used with BRFSS data to compare measures of environmental risk factors and chronic disease, important restrictions affect how the data should be used and interpreted.  These restrictions include, but are not limited to, the following: 

•	Analysis levels and temporality.  Because the environmental data from the AQS used in this project were collected during 2006 and reported at the metropolitan area-level, they should only be used in conjunction with 2006 BRFSS data that have been re-weighted for metropolitan area-level analysis.  

•	Exposure assessment.  The AQI only approximates the level of pollution in a metropolitan area.  Because it does not measure the extent to which people are exposed to these pollutants, AQI values can not be used to identify exposures and risks for specific individuals.  Individuals within a metropolitan area may have substantially higher or lower pollution exposures due to a number of factors, including variations in individual activity patterns and physical location within a metropolitan area. The AQI values for a metropolitan area should not be linked to an individual respondent from the BRFSS. 

•	Comprehensiveness.  The AQS is not an indicator of overall air quality.  The criteria pollutants included in the AQS are only a subset of the 188 pollutants listed in the Clean Air Act.  In addition, for certain chemicals, ingestion or dermal exposure, as well as indoor sources of inhalation exposure, may contribute substantially to the total exposures of concern.  The AQS assessment does not address these other means of exposure.  

•	Quality.  Because air pollution measured in the vicinity of a particular source may not be representative of the prevailing air quality of a county or urban area, AQS data may not accurately reflect the air quality of an entire metropolitan area, particularly in geographically large metropolitan areas with few AQS monitors.  Also, the BRFSS can only provide annual measures for health risks, necessitating the use of annual summary statistics for air quality measures.    

•	Summary measures.  A metropolitan area’s daily AQI value is based on the highest pollutant-specific AQI value for that day.  It thus provides information about the predominant pollutant on a given day and some information about the levels of the other pollutants (i.e., they each had an individual AQI less than the daily AQI). However, the AQI does not fully characterize the contributions of the other criteria pollutants to air quality or take into account possible adverse effects associated with combinations of pollutants. 

Future Directions 
This project demonstrates how environmental data can be combined with BRFSS data to investigate associations between rates of chronic disease and levels of air pollutants.  It also may serve as a model for using BRFSS with other environmental information data; for example, with more detailed AQS data, researchers could conduct regional analyses.  Initiatives are also underway to expand the environmental component of the BRFSS.  For example, the 2006 BRFSS survey includes questions about indoor air quality that could help supplement the outdoor air quality information from the EPA.  In addition, a series of questions about drinking water sources and filtration in the 2006 survey could be used in combination with national water quality data to estimate potential exposure risks. 

Additional Information
Additional information on the 2006 BRFSS is available at http://www.cdc.gov/brfss.  

Additional information on MSA, PMSA, and NECMA designations used by the U. S. Census Bureau is available at http://www.census.gov/population/www/estimates/aboutmetro.html and 
http://www.census.gov/population/www/estimates/pastmetro.html.

Additional information on the AQS is available at http://www.epa.gov/air/data/aqsdb.html.  Additional information on the AQI is available at http://www.epa.gov/airnow/aqibroch/aqi.html.  

The complete AQS data set can be accessed at http://www.epa.gov/air/data/index.html.  

Cautions to Use Prevalence by MSA for Trend Analysis
Cautions should be taken when using prevalence data by MSA for trend analysis due to the relative small sample size. The small the sample size, the wider range the 95% confidence interval and the less reliable the prevalence estimations. We strongly urge you not use the BRFSS to do trend analysis by MSA.

Appendix A
The Criteria Pollutants

Ozone (O_3)
Ground-level O_3 is a harmful pollutant that is formed when oxides of nitrogen (NO_x) and volatile organic compounds (VOCs) react in the presence of sunlight.  Pollutants emitted by cars, power plants, industrial boilers, refineries, and chemical plants are major sources of NO_x and VOCs that form O_3.  Peak O_3 levels usually occur during the summer months during hot, dry weather conditions that promote O_3 formation.  O_3 can result in a variety of adverse health effects, even at low levels.

Sulfur dioxide (SO_2)
SO_2 is a colorless, reactive gas produced during the burning of sulfur-containing fuels such as coal and oil (e.g., when gasoline is extracted from oil or metals are extracted from ore).  Fuel combustion at electrical and industrial facilities is the major source of SO_2 and levels are usually highest near large industrial sources.  SO_2 dissolves in water vapor to form acid and interacts with other gases and particles in the air to form products that can contribute to respiratory illness, particularly in children and the elderly, and aggravate existing heart and lung diseases.

Carbon monoxide (CO)
CO is an odorless, colorless gas that is formed when the carbon in fuels does not completely burn.  Vehicle exhaust contributes approximately 60 percent of all CO emissions nationwide and between 85 and 95 percent of emissions in cities.  Other sources of CO emissions include fuel combustion in industrial processes and wildfires.  CO concentrations typically peak during cold weather because cold temperatures make combustion less complete, and inversions that trap pollutants low to the ground are more frequent.  CO can cause harmful health effects by reducing oxygen delivery to the body's organs and tissues.  CO is poisonous even to healthy people at high levels in the air; it can also damage the central nervous system and affect people with heart disease.  

Particulate matter (PM_2.5, PM_10)
Dust, dirt, soot, smoke, and liquid droplets found in the air are known as PM.  PM may be directly emitted or formed when pollutants react in the atmosphere.  Particles less than 2.5 micrometers in diameter (PM_2.5) are produced during combustion (e.g., in motor vehicles, power plants, wood burning) and industrial processes.  Particles with diameters between 2.5 and 10 micrometers originate from crushing or grinding operations and dust from paved or unpaved roads.  PM has been linked to a series of health problems, including aggravated asthma, chronic bronchitis, decreased lung function, and premature death. 

Additional information on the pollutants included in the AQI is available from the U.S. Environmental Protection Agency’s Air Quality Index: A Guide to Air Quality and Your Health (Washington, DC: U.S. Government Printing Office; 2000; EPA Publication No. EPA-454/R-00-005). The report may be viewed online at http://www.epa.gov. 
Appendix B

The Air Quality Index (AQI): Concentration Ranges and Associated Health Concern Levels for Ozone (O_3), Particulate Matter (PM), Carbon Monoxide (CO), Sulfur Dioxide (SO_2), and Nitrogen Dioxide (NO_2)

AQI Value | O_3 | | PM | | CO | SO_2 | Level of Health Concern
| [1-hour] (ppm)^1 | [8-hour] (ppm) | | PM_2.5 [24-hour] (µg/m^3) | PM_10 [24-hour] (µg/m^3) | | [8-hour] (ppm) | [24-hour] (ppm) |
0–50 | (1) | 0.000–0.064 | | 0.0–15.4 | 0–54 | | 0.0–4.4 | 0.000–0.034 | Good
51–100 | (1) | 0.065–0.084 | | 15.5–40.4 | 55–154 | | 4.5–9.4 | 0.035–0.144 | Moderate
101–150 | 0.125–0.164 | 0.085–0.104 | | 40.5–65.4 | 155–254 | | 9.5–12.4 | 0.145–0.224 | Unhealthy for sensitive groups
15 –200 | 0.165–0.204 | 0.105–0.124 | | 65.5–150.4 | 255–354 | | 12.5–15.4 | 0.225–0.304 | Unhealthy
20 –300 | 0.205–0.404 | 0.125–0.374 | | 150.5–250.4 | 355–424 | | 15.5–30.4 | 0.305–0.604 | Very unhealthy
301–400 | 0.405–0.504 | (2) | | 250.5–350.4 | 425–504 | | 30.5–40.4 | 0.605–0.804 | Hazardous
401–500 | 0.505–0.604 | (2) | | 350.5–500.4 | 505–604 | | 40.5–50.4 | 0.805–1.004 | Hazardous
(1)	One-hour concentrations provided for areas where the AQI is based on 1-hour values should be interpreted with caution.
(2)	No health effects information is available for these levels, so 1-hour concentrations should be used.  When 8-hour O_3 concentrations exceed 0.374 ppm, AQI values of 301 or higher must be calculated using 1-hour 0_3 concentrations.

Appendix C

Health Effects by Air Quality Index (AQI) Value and Pollutant

AQI Value | Level of Health Concern | O_3 | | PM | | CO | SO_2
| | [1-hour] (ppm)^1 | [8-hour] (ppm) | | PM_2.5 [24-hour] (µg/m^3) | PM_10 [24-hour] (µg/m^3) | | [8-hour] (ppm) | [24-hour] (ppm)
0–50 | Good | — | None | | None | None | | None | None
51–100 | Moderate | — | Unusually sensitive individuals may experience respiratory symptoms. | | None | None | | None | None
101–150 | Unhealthy for sensitive groups | Increased likelihood of respiratory symptoms and breathing discomfort in active children and adults and in people with respiratory disease, such as asthma. | Increased likelihood of respiratory symptoms and breathing discomfort in active children and adults and in people with respiratory disease, such as asthma. | | Increased likelihood of respiratory symptoms in sensitive individuals, aggravation of heart or lung disease and premature mortality in persons with cardiopulmonary disease and the elderly. | Increased likelihood of respiratory symptoms and aggravation of lung disease, such as asthma. | | Increased likelihood of reduced exercise tolerance due to increased cardiovascular symptoms, such as chest pain, in people with cardiovascular disease. | Increased likelihood of respiratory symptoms, such as chest tightness and breathing discomfort, in people with asthma.
151–200 | Unhealthy | Greater likelihood of respiratory symptoms and breathing difficulty in active children and adults and in people with respiratory disease, such as asthma; possible respiratory effects in general population. | Greater likelihood of respiratory symptoms and breathing difficulty in active children and adults and in people with respiratory disease, such as asthma; possible respiratory effects in general population. | | Increased aggravation of heart or lung disease and premature mortality in persons with cardio-pulmonary disease and the elderly; increased respiratory effects in general population. | Increased respiratory symptoms and aggravation of lung disease, such as asthma; possible respiratory effects in general population. | | Reduced exercise tolerance due to increased cardiovascular symptoms, such as chest pain, in people with cardiovascular disease. | Increased respiratory symptoms, such as chest tightness and wheezing, in people with asthma; possible aggravation of heart or lung disease.
201–300 | Very unhealthy | Increasingly severe symptoms and impaired breathing in active children and adults and in people with respiratory disease, such as asthma; increasing likelihood of respiratory effects in general population. | Increasingly severe symptoms and impaired breathing in active children and adults and in people with respiratory disease, such as asthma; increasing likelihood of respiratory effects in general population. | | Significant aggravation of heart or lung disease and premature mortality in persons with cardiopulmonary disease and the elderly; significant increase in respiratory effects in general population. | Significant increase in respiratory symptoms and aggravation of lung disease, such as asthma; increased likelihood of respiratory effects in general population. | | Significant aggravation of cardiovascular symptoms, such as chest pain, in people with cardiovascular disease. | Significant increase in respiratory symptoms, such as wheezing and shortness of breath, in people with asthma; aggravation of heart or lung disease
301–500 | Hazardous | Severe respiratory effects and impaired breathing in active children and adults and in people with respiratory disease, such as asthma; increasingly severe respiratory effects in general population. | Severe respiratory effects and impaired breathing in active children and adults and people with respiratory disease, such as asthma; increasingly severe respiratory effects in general population. | | Serious aggravation of heart or lung disease and premature mortality in persons with cardiopulmonary disease and the elderly; serious risk of respiratory effects in general population. | Serious risk of respiratory symptoms and aggravation of lung disease, such as asthma; respiratory effects likely in general population. | | Serious aggravation of cardiovascular symptoms, such as chest pain, in people with cardiovascular disease; impairment in ability to perform strenuous activities in general population. | Severe respiratory symptoms, such as wheezing and shortness of breath, in people with asthma; increased aggravation of heart or lung disease; possible respiratory effects in general population.

Appendix D
Environmental Quality Variables in the AQS Summary Dataset 

VARIABLE | DESCRIPTION
CODAYS | NUMBER OF DAYS CARBON MONOXIDE (CO) WAS MONITORED
COGT100 | DAYS WITH CO-SPECIFIC AQI >100
CO_AMED | ANNUAL DAIY CO-SPECIFIC MEDIAN AQI
CO_MAPR | MEDIAN DAILY CO-SPECIFIC AQI FOR APRIL
CO_MAUG | MEDIAN DAILY CO-SPECIFIC AQI FOR AUGUST
CO_MAX | MAXIMUM DAILY CO-SPECIFIC AQI
CO_MDEC | MEDIAN DAILY CO-SPECIFIC AQI FOR DECEMBER
CO_MED1 | MEDIAN DAILY CO-SPECIFIC AQI (1ST QUARTER)
CO_MED2 | MEDIAN DAILY CO-SPECIFIC AQI (2ND QUARTER)
CO_MED3 | MEDIAN DAILY CO-SPECIFIC AQI (3RD QUARTER)
CO_MED4 | MEDIAN DAILY CO-SPECIFIC AQI (4TH QUARTER)
CO_MFEB | MEDIAN DAILY CO-SPECIFIC AQI FOR FEBRUARY
CO_MIN | MINIMUM DAILY CO-SPECIFIC AQI
CO_MJAN | MEDIAN DAILY CO-SPECIFIC AQI FOR JANUARY
CO_MJUL | MEDIAN DAILY CO-SPECIFIC AQI FOR JULY
CO_MJUN | MEDIAN DAILY CO-SPECIFIC AQI FOR JUNE
CO_MMAR | MEDIAN DAILY CO-SPECIFIC AQI FOR MARCH
CO_MMAY | MEDIAN DAILY CO-SPECIFIC AQI FOR MAY
CO_MNOV | MEDIAN DAILY CO-SPECIFIC AQI FOR NOVEMBER
CO_MOCT | MEDIAN DAILY CO-SPECIFIC AQI FOR OCTOBER
CO_MSEP | MEDIAN DAILY CO-SPECIFIC AQI FOR SEPTEMBER
MSACODE | PMSA, MSA OR NECMA CODE CORRESPONDING TO A METRO AREA
MSANAME | METROPOLITAN AREA (PMSA, MSA, OR NECMA)
O3DAYS | NUMBER OF DAYS OZONE (O3) WAS MONITORED
O3GT100 | DAYS WITH O3-SPECIFIC AQI >100
O3_AMED | ANNUAL DAILY O3-SPECIFIC MEDIAN AQI
O3_MAPR | MEDIAN DAILY O3-SPECIFIC AQI FOR APRIL
O3_MAUG | MEDIAN DAILY O3-SPECIFIC AQI FOR AUGUST
O3_MAX | MAXIMUM DAILY O3-SPECIFIC AQI >100
O3_MDEC | MEDIAN DAILY O3-SPECIFIC AQI FOR DECEMBER
O3_MED1 | MEDIAN DAILY O3-SPECIFIC AQI (1ST QUARTER)
O3_MED2 | MEDIAN DAILY O3-SPECIFIC AQI (2ND QUARTER)
O3_MED3 | MEDIAN DAILY O3-SPECIFIC AQI (3RD QUARTER)
O3_MED4 | MEDIAN DAILY O3-SPECIFIC AQI (4TH QUARTER)
O3_MFEB | MEDIAN DAILY O3-SPECIFIC AQI FOR FEBRUARY
O3_MIN | MINIMUM DAILY O3-SPECIFIC AQI >100
O3_MJAN | MEDIAN DAILY O3-SPECIFIC AQI FOR JANUARY
O3_MJUL | MEDIAN DAILY O3-SPECIFIC AQI FOR JULY
O3_MJUN | MEDIAN DAILY O3-SPECIFIC AQI FOR JUNE
O3_MMAR | MEDIAN DAILY O3-SPECIFIC AQI FOR MARCH
O3_MMAY | MEDIAN DAILY O3-SPECIFIC AQI FOR MAY
O3_MNOV | MEDIAN DAILY O3-SPECIFIC AQI FOR NOVEMBER
O3_MOCT | MEDIAN DAILY O3-SPECIFIC AQI FOR OCTOBER
O3_MSEP | MEDIAN DAILY O3-SPECIFIC AQI FOR SEPTEMBER
P10GT100 | DAYS WTIH PM2.5-SPECIFIC AQI >100
P10_AMED | ANNUAL DAILY PM10-SPECIFIC MEDIAN AQI
P10_MAPR | MEDIAN DAILY PM10-SPECIFIC AQI FOR APRIL
P10_MAUG | MEDIAN DAILY PM10-SPECIFIC AQI FOR AUGUST
P10_MAX | MAXIMUM DAILY PM10-SPECIFIC AQI
P10_MDEC | MEDIAN DAILY PM10-SPECIFIC AQI FOR DECEMBER
P10_MED1 | MEDIAN DAILY PM10-SPECIFIC AQI (1ST QUARTER)
P10_MED2 | MEDIAN DAILY PM10-SPECIFIC AQI (1ST QUARTER)
P10_MED3 | MEDIAN DAILY PM10-SPECIFIC AQI (1ST QUARTER)
P10_MED4 | MEDIAN DAILY PM10-SPECIFIC AQI (1ST QUARTER)
P10_MFEB | MEDIAN DAILY PM10-SPECIFIC AQI FOR FEBRUARY
P10_MIN | MINIMUM DAILY PM10-SPECIFIC AQI
P10_MJAN | MEDIAN DAILY PM10-SPECIFIC AQI FOR JANUARY
P10_MJUL | MEDIAN DAILY PM10-SPECIFIC AQI FOR JULY
P10_MJUN | MEDIAN DAILY PM10-SPECIFIC AQI FOR JUNE
P10_MMAR | MEDIAN DAILY PM10-SPECIFIC AQI FOR MARCH
P10_MMAY | MEDIAN DAILY PM10-SPECIFIC AQI FOR MAY
P10_MNOV | MEDIAN DAILY PM10-SPECIFIC AQI FOR NOVEMBER
P10_MOCT | MEDIAN DAILY PM10-SPECIFIC AQI FOR OCTOBER
P10_MSEP | MEDIAN DAILY PM10-SPECIFIC AQI FOR SEPTEMBER
P25GT100 | DAYS WTIH PM2.5-SPECIFIC AQI >100
P25_AMED | ANNUAL DAILY PM2.5-SPECIFIC MEDIAN AQI
P25_MAPR | MEDIAN DAILY PM2.5-SPECIFIC AQI FOR APRIL
P25_MAUG | MEDIAN DAILY PM2.5-SPECIFIC AQI FOR AUGUST
P25_MAX | MAXIMUM DAILY PM2.5-SPECIFIC AQI
P25_MDEC | MEDIAN DAILY PM2.5-SPECIFIC AQI FOR DECEMBER
P25_MED1 | MEDIAN DAILY PM2.5-SPECIFIC AQI (1ST QUARTER)
P25_MED2 | MEDIAN DAILY PM2.5-SPECIFIC AQI (2ND QUARTER)
P25_MED3 | MEDIAN DAILY PM2.5-SPECIFIC AQI (3RD QUARTER)
P25_MED4 | MEDIAN DAILY PM2.5-SPECIFIC AQI (4TH QUARTER)
P25_MFEB | MEDIAN DAILY PM2.5-SPECIFIC AQI FOR FEBRUARY
P25_MIN | MINIMUM DAILY PM2.5-SPECIFIC AQI
P25_MJAN | MEDIAN DAILY PM2.5-SPECIFIC AQI FOR JANUARY
P25_MJUL | MEDIAN DAILY PM2.5-SPECIFIC AQI FOR JULY
P25_MJUN | MEDIAN DAILY PM2.5-SPECIFIC AQI FOR JUNE
P25_MMAR | MEDIAN DAILY PM2.5-SPECIFIC AQI FOR MARCH
P25_MMAY | MEDIAN DAILY PM2.5-SPECIFIC AQI FOR MAY
P25_MNOV | MEDIAN DAILY PM2.5-SPECIFIC AQI FOR NOVEMBER
P25_MOCT | MEDIAN DAILY PM2.5-SPECIFIC AQI FOR OCTOBER
P25_MSEP | MEDIAN DAILY PM2.5-SPECIFIC AQI FOR SEPTEMBER
PM10DAYS | NUMBER OF DAYS PARTICULATE MATTER (PM10) WAS MONITORED
PM25DAYS | NUMBER OF DAYS PARTICULATE MATTER (PM2.5) WAS MONITORED
SO2DAYS | NUMBER OF DAYS SULFUR DIOXIDE (SO2) WAS MONITORED
SO2GT100 | DAYS WTIH SO2-SPECIFIC AQI >100
SO2_AMED | ANNUAL DAILY SO2-SPECIFIC MEDIAN AQI
SO2_MAPR | MEDIAN DAILY SO2-SPECIFIC AQI FOR APRIL
SO2_MAUG | MEDIAN DAILY SO2-SPECIFIC AQI FOR AUGUST
SO2_MAX | MAXIMUM DAILY SO2-SPECIFIC AQI
SO2_MDEC | MEDIAN DAILY SO2-SPECIFIC AQI FOR DECEMBER
SO2_MED1 | MEDIAN DAILY SO2-SPECIFIC AQI (1ST QUARTER)
SO2_MED2 | MEDIAN DAILY SO2-SPECIFIC AQI (2ND QUARTER)
SO2_MED3 | MEDIAN DAILY SO2-SPECIFIC AQI (3RD QUARTER)
SO2_MED4 | MEDIAN DAILY SO2-SPECIFIC AQI (4TH QUARTER)
SO2_MFEB | MEDIAN DAILY SO2-SPECIFIC AQI FOR FEBRUARY
SO2_MIN | MINNIMUM DAILY SO2-SPECIFIC AQI
SO2_MJAN | MEDIAN DAILY SO2-SPECIFIC AQI FOR JANUARY
SO2_MJUL | MEDIAN DAILY SO2-SPECIFIC AQI FOR JULY
SO2_MJUN | MEDIAN DAILY SO2-SPECIFIC AQI FOR JUNE
SO2_MMAR | MEDIAN DAILY SO2-SPECIFIC AQI FOR MARCH
SO2_MMAY | MEDIAN DAILY SO2-SPECIFIC AQI FOR MAY
SO2_MNOV | MEDIAN DAILY SO2-SPECIFIC AQI FOR NOVEMBER
SO2_MOCT | MEDIAN DAILY SO2-SPECIFIC AQI FOR OCTOBER
SO2_MSEP | MEDIAN DAILY SO2-SPECIFIC AQI FOR SEPTEMBER
SUMGT100 | DAYS WITH A DAILY SUMMARY AQI >100
SUM_AMED | ANNUAL MEDIAN DAILY SUMMARY AQI
SUM_MAPR | MEDIAN DAILY SUMMARY AQI FOR APRIL
SUM_MAUG | MEDIAN DAILY SUMMARY AQI FOR AUGUST
SUM_MAX | MAXIMUM DAILY SUMMARY AQI
SUM_MDEC | MEDIAN DAILY SUMMARY AQI FOR DECEMBER
SUM_MED1 | MEDIAN DAILY SUMMARY AQI (1ST QUARTER)
SUM_MED2 | MEDIAN DAILY SUMMARY AQI (2ND QUARTER)
SUM_MED3 | MEDIAN DAILY SUMMARY AQI (3RD QUARTER)
SUM_MED4 | MEDIAN DAILY SUMMARY AQI (4TH QUARTER)
SUM_MFEB | MEDIAN DAILY SUMMARY AQI FOR FEBRARY
SUM_MIN | MINIMUM DAILY SUMMARY AQI
SUM_MJAN | MEDIAN DAILY SUMMARY AQI FOR JANUARY
SUM_MJUL | MEDIAN DAILY SUMMARY AQI FOR JULY
SUM_MJUN | MEDIAN DAILY SUMMARY AQI FOR JUNE
SUM_MMAR | MEDIAN DAILY SUMMARY AQI FOR MARCH
SUM_MMAY | MEDIAN DAILY SUMMARY AQI FOR MAY
SUM_MNOV | MEDIAN DAILY SUMMARY AQI FOR NOVEMBER
SUM_MOCT | MEDIAN DAILY SUMMARY AQI FOR OCTOBER
SUM_MSEP | MEDIAN DAILY SUMMARY AQI FOR SEPTEMBER
_1GT100 | DAYS WITH AN AQI >100 FOR A SINGLE POLLUTANT
_2GT100 | DAYS WITH AN AQI >100 FOR TWO POLLUTANTS

Appendix E
Environmental Quality Variables in the AQS Master Dataset (available upon request)
Variable | Description
AQI_CO | Daily AQI for carbon monoxide (CO).
AQI_O3 | Daily AQI for ozone (O_3).
AQI_PM10 | Daily AQI for particulate matter between 2.5 and 10 micrometers (PM_10).
AQI_PM25 | Daily AQI for particulate matter less than 2.5 micrometers (PM_2.5).
AQI_SO2 | Daily AQI for sulfur dioxide (SO_2).
C_CO | Daily CO concentration (ppm).
C_O3 | Daily O_3 concentration (ppm).
C_PM10 | Daily PM_10 concentration (µg/m^3).
C_PM25 | Daily PM_2.5 concentration (µg/m^3).
C_SO2 | Daily SO_2 concentration (ppm).
DATE | Day, month, and year in which the ambient pollution data were collected.
MSACODE | Four-digit numeric code corresponding to the metropolitan area (PMSA, MSA, or NECMA) in which the ambient pollution data were collected.
MSANAME | Name of the metropolitan area (PMSA, MSA, or NECMA) in which the ambient pollution data were collected.

Appendix F
SAS Code to Create SAS Dataset for Environmental Data

Reading in the AQS summary dataset
******************************************************************************
*INSTRUCTIONS:
*Save the excel dataset named  AQSUMM2006.xls in your C:\ drive;
* import the Excel dataset by using following code to convert it into SAS dataset;
******************************************************************************************************************************************;
PROC IMPORT OUT= WORK.AQSUM2006 
            DATAFILE= "c:\AQSUMM2006.xls" 
            DBMS=EXCEL REPLACE;
     SHEET="AQSSUMM_2006"; 
     GETNAMES=YES;
     MIXED=NO;
     SCANTEXT=YES;
     USEDATE=YES;
     SCANTIME=YES;
RUN;
/*****************************************************
* Now you have created a SAS temporary dataset named ‘AQSUM2006’;
*******************************************************************************************************/
Data AQSUM2006; set AQSUM2006;
/************************************************
ASSIGN LABLES TO VARIABLES;
************************************************/
label MSACODE  =   'PMSA, MSA OR NECMA CODE CORRESPONDING TO A METRO AREA'
      MSANAME  =   'METROPOLITAN AREA (PMSA, MSA, OR NECMA)'
      SUM_MAX  =   'MAXIMUM DAILY SUMMARY AQI'
	SUM_AMED =   'ANNUAL MEDIAN DAILY SUMMARY AQI'
      SUM_MIN  =   'MINIMUM DAILY SUMMARY AQI'
	SUM_MED1 =   'MEDIAN DAILY SUMMARY AQI (1ST QUARTER)'
  	SUM_MED2 =   'MEDIAN DAILY SUMMARY AQI (2ND QUARTER)'
  	SUM_MED3 =   'MEDIAN DAILY SUMMARY AQI (3RD QUARTER)'
  	SUM_MED4 ='MEDIAN DAILY SUMMARY AQI (4TH QUARTER)'
      SUMGT100 ='DAYS WITH A DAILY SUMMARY AQI >100'
      CODAYS   ='NUMBER OF DAYS CARBON MONOXIDE (CO) WAS MONITORED'
      O3DAYS   ='NUMBER OF DAYS OZONE (O3) WAS MONITORED'
      PM10DAYS ='NUMBER OF DAYS PARTICULATE MATTER (PM10) WAS MONITORED'
      PM25DAYS ='NUMBER OF DAYS PARTICULATE MATTER (PM2.5) WAS MONITORED'
      SO2DAYS  ='NUMBER OF DAYS SULFUR DIOXIDE (SO2) WAS MONITORED'
      _1GT100  ='DAYS WITH AN AQI >100 FOR A SINGLE POLLUTANT'
      _2GT100  ='DAYS WITH AN AQI >100 FOR TWO POLLUTANTS'
      SUM_MJAN ='MEDIAN DAILY SUMMARY AQI FOR JANUARY'
      SUM_MFEB ='MEDIAN DAILY SUMMARY AQI FOR FEBRARY'
      SUM_MMAR ='MEDIAN DAILY SUMMARY AQI FOR MARCH'
      SUM_MAPR ='MEDIAN DAILY SUMMARY AQI FOR APRIL'
      SUM_MMAY ='MEDIAN DAILY SUMMARY AQI FOR MAY'
      SUM_MJUN ='MEDIAN DAILY SUMMARY AQI FOR JUNE'
      SUM_MJUL ='MEDIAN DAILY SUMMARY AQI FOR JULY'
      SUM_MAUG ='MEDIAN DAILY SUMMARY AQI FOR AUGUST'
      SUM_MSEP ='MEDIAN DAILY SUMMARY AQI FOR SEPTEMBER'
      SUM_MOCT ='MEDIAN DAILY SUMMARY AQI FOR OCTOBER'
      SUM_MNOV ='MEDIAN DAILY SUMMARY AQI FOR NOVEMBER'
      SUM_MDEC ='MEDIAN DAILY SUMMARY AQI FOR DECEMBER'
      SO2_MAX  ='MAXIMUM DAILY SO2-SPECIFIC AQI'
      SO2_AMED    ='ANNUAL DAILY SO2-SPECIFIC MEDIAN AQI'
      SO2_MIN     ='MINNIMUM DAILY SO2-SPECIFIC AQI'
      SO2_MED1    ='MEDIAN DAILY SO2-SPECIFIC AQI (1ST QUARTER)'
      SO2_MED2    ='MEDIAN DAILY SO2-SPECIFIC AQI (2ND QUARTER)'
      SO2_MED3    ='MEDIAN DAILY SO2-SPECIFIC AQI (3RD QUARTER)'
      SO2_MED4    ='MEDIAN DAILY SO2-SPECIFIC AQI (4TH QUARTER)'
      SO2_MJAN    ='MEDIAN DAILY SO2-SPECIFIC AQI FOR JANUARY'
      SO2_MFEB    ='MEDIAN DAILY SO2-SPECIFIC AQI FOR FEBRUARY'
      SO2_MMAR    ='MEDIAN DAILY SO2-SPECIFIC AQI FOR MARCH'
      SO2_MAPR    ='MEDIAN DAILY SO2-SPECIFIC AQI FOR APRIL'
      SO2_MMAY    ='MEDIAN DAILY SO2-SPECIFIC AQI FOR MAY'
      SO2_MJUN    ='MEDIAN DAILY SO2-SPECIFIC AQI FOR JUNE'
      SO2_MJUL    ='MEDIAN DAILY SO2-SPECIFIC AQI FOR JULY'
      SO2_MAUG    ='MEDIAN DAILY SO2-SPECIFIC AQI FOR AUGUST'
      SO2_MSEP    ='MEDIAN DAILY SO2-SPECIFIC AQI FOR SEPTEMBER'
      SO2_MOCT    ='MEDIAN DAILY SO2-SPECIFIC AQI FOR OCTOBER'
      SO2_MNOV    ='MEDIAN DAILY SO2-SPECIFIC AQI FOR NOVEMBER'
      SO2_MDEC    ='MEDIAN DAILY SO2-SPECIFIC AQI FOR DECEMBER'
      SO2GT100    ='DAYS WTIH SO2-SPECIFIC AQI >100'
      CO_MAX      ='MAXIMUM DAILY CO-SPECIFIC AQI'
      CO_AMED     ='ANNUAL DAIY CO-SPECIFIC MEDIAN AQI'
      CO_MIN      ='MINIMUM DAILY CO-SPECIFIC AQI'
      CO_MED1     ='MEDIAN DAILY CO-SPECIFIC AQI (1ST QUARTER)'
      CO_MED2     ='MEDIAN DAILY CO-SPECIFIC AQI (2ND QUARTER)'
      CO_MED3     ='MEDIAN DAILY CO-SPECIFIC AQI (3RD QUARTER)'
      CO_MED4     ='MEDIAN DAILY CO-SPECIFIC AQI (4TH QUARTER)'
      CO_MJAN     ='MEDIAN DAILY CO-SPECIFIC AQI FOR JANUARY'
      CO_MFEB     ='MEDIAN DAILY CO-SPECIFIC AQI FOR FEBRUARY'
      CO_MMAR     ='MEDIAN DAILY CO-SPECIFIC AQI FOR MARCH'
      CO_MAPR     ='MEDIAN DAILY CO-SPECIFIC AQI FOR APRIL'
      CO_MMAY     ='MEDIAN DAILY CO-SPECIFIC AQI FOR MAY'
      CO_MJUN     ='MEDIAN DAILY CO-SPECIFIC AQI FOR JUNE'
      CO_MJUL     ='MEDIAN DAILY CO-SPECIFIC AQI FOR JULY'
      CO_MAUG     ='MEDIAN DAILY CO-SPECIFIC AQI FOR AUGUST'
      CO_MSEP     ='MEDIAN DAILY CO-SPECIFIC AQI FOR SEPTEMBER'
      CO_MOCT     ='MEDIAN DAILY CO-SPECIFIC AQI FOR OCTOBER'
      CO_MNOV     ='MEDIAN DAILY CO-SPECIFIC AQI FOR NOVEMBER'
      CO_MDEC     ='MEDIAN DAILY CO-SPECIFIC AQI FOR DECEMBER'
      COGT100     ='DAYS WITH CO-SPECIFIC AQI >100'
      O3_MAX      ='MAXIMUM DAILY O3-SPECIFIC AQI >100'
      O3_AMED     ='ANNUAL DAILY O3-SPECIFIC MEDIAN AQI'
      O3_MIN      ='MINIMUM DAILY O3-SPECIFIC AQI >100'
      O3_MED1     ='MEDIAN DAILY O3-SPECIFIC AQI (1ST QUARTER)'
      O3_MED2     ='MEDIAN DAILY O3-SPECIFIC AQI (2ND QUARTER)'
      O3_MED3     ='MEDIAN DAILY O3-SPECIFIC AQI (3RD QUARTER)'
      O3_MED4     ='MEDIAN DAILY O3-SPECIFIC AQI (4TH QUARTER)'
      O3_MJAN     ='MEDIAN DAILY O3-SPECIFIC AQI FOR JANUARY'
      O3_MFEB     ='MEDIAN DAILY O3-SPECIFIC AQI FOR FEBRUARY'
      O3_MMAR     ='MEDIAN DAILY O3-SPECIFIC AQI FOR MARCH'
      O3_MAPR     ='MEDIAN DAILY O3-SPECIFIC AQI FOR APRIL'
      O3_MMAY     ='MEDIAN DAILY O3-SPECIFIC AQI FOR MAY'
      O3_MJUN     ='MEDIAN DAILY O3-SPECIFIC AQI FOR JUNE'
      O3_MJUL     ='MEDIAN DAILY O3-SPECIFIC AQI FOR JULY'
      O3_MAUG     ='MEDIAN DAILY O3-SPECIFIC AQI FOR AUGUST'
      O3_MSEP     ='MEDIAN DAILY O3-SPECIFIC AQI FOR SEPTEMBER'
      O3_MOCT     ='MEDIAN DAILY O3-SPECIFIC AQI FOR OCTOBER'
      O3_MNOV     ='MEDIAN DAILY O3-SPECIFIC AQI FOR NOVEMBER'
      O3_MDEC     ='MEDIAN DAILY O3-SPECIFIC AQI FOR DECEMBER'
      O3GT100     ='DAYS WITH O3-SPECIFIC AQI >100'
      P10_MAX     ='MAXIMUM DAILY PM10-SPECIFIC AQI'
      P10_AMED    ='ANNUAL DAILY PM10-SPECIFIC MEDIAN AQI'
      P10_MIN     ='MINIMUM DAILY PM10-SPECIFIC AQI'
      P10_MED1    ='MEDIAN DAILY PM10-SPECIFIC AQI (1ST QUARTER)'
      P10_MED2    ='MEDIAN DAILY PM10-SPECIFIC AQI (1ST QUARTER)'
      P10_MED3    ='MEDIAN DAILY PM10-SPECIFIC AQI (1ST QUARTER)'
      P10_MED4    ='MEDIAN DAILY PM10-SPECIFIC AQI (1ST QUARTER)'
      P10_MJAN    ='MEDIAN DAILY PM10-SPECIFIC AQI FOR JANUARY'
      P10_MFEB    ='MEDIAN DAILY PM10-SPECIFIC AQI FOR FEBRUARY'
      P10_MMAR    ='MEDIAN DAILY PM10-SPECIFIC AQI FOR MARCH'
      P10_MAPR    ='MEDIAN DAILY PM10-SPECIFIC AQI FOR APRIL'
      P10_MMAY    ='MEDIAN DAILY PM10-SPECIFIC AQI FOR MAY'
      P10_MJUN    ='MEDIAN DAILY PM10-SPECIFIC AQI FOR JUNE'
      P10_MJUL    ='MEDIAN DAILY PM10-SPECIFIC AQI FOR JULY'
      P10_MAUG    ='MEDIAN DAILY PM10-SPECIFIC AQI FOR AUGUST'
      P10_MSEP    ='MEDIAN DAILY PM10-SPECIFIC AQI FOR SEPTEMBER'
      P10_MOCT    ='MEDIAN DAILY PM10-SPECIFIC AQI FOR OCTOBER'
      P10_MNOV    ='MEDIAN DAILY PM10-SPECIFIC AQI FOR NOVEMBER'
      P10_MDEC    ='MEDIAN DAILY PM10-SPECIFIC AQI FOR DECEMBER'
      P10GT100    ='DAYS WTIH PM2.5-SPECIFIC AQI >100'
      P25_MAX     ='MAXIMUM DAILY PM2.5-SPECIFIC AQI'
      P25_AMED   ='ANNUAL DAILY PM2.5-SPECIFIC MEDIAN AQI'
      P25_MIN     ='MINIMUM DAILY PM2.5-SPECIFIC AQI'
      P25_MED1    ='MEDIAN DAILY PM2.5-SPECIFIC AQI (1ST QUARTER)'
      P25_MED2    ='MEDIAN DAILY PM2.5-SPECIFIC AQI (2ND QUARTER)'
      P25_MED3    ='MEDIAN DAILY PM2.5-SPECIFIC AQI (3RD QUARTER)'
      P25_MED4    ='MEDIAN DAILY PM2.5-SPECIFIC AQI (4TH QUARTER)'
      P25_MJAN    ='MEDIAN DAILY PM2.5-SPECIFIC AQI FOR JANUARY'
      P25_MFEB    ='MEDIAN DAILY PM2.5-SPECIFIC AQI FOR FEBRUARY'
      P25_MMAR    ='MEDIAN DAILY PM2.5-SPECIFIC AQI FOR MARCH'
      P25_MAPR    ='MEDIAN DAILY PM2.5-SPECIFIC AQI FOR APRIL'
      P25_MMAY    ='MEDIAN DAILY PM2.5-SPECIFIC AQI FOR MAY'
      P25_MJUN    ='MEDIAN DAILY PM2.5-SPECIFIC AQI FOR JUNE'
      P25_MJUL    ='MEDIAN DAILY PM2.5-SPECIFIC AQI FOR JULY'
      P25_MAUG    ='MEDIAN DAILY PM2.5-SPECIFIC AQI FOR AUGUST'
      P25_MSEP    ='MEDIAN DAILY PM2.5-SPECIFIC AQI FOR SEPTEMBER'
      P25_MOCT    ='MEDIAN DAILY PM2.5-SPECIFIC AQI FOR OCTOBER'
      P25_MNOV    ='MEDIAN DAILY PM2.5-SPECIFIC AQI FOR NOVEMBER'
      P25_MDEC    ='MEDIAN DAILY PM2.5-SPECIFIC AQI FOR DECEMBER'
   P25GT100    ='DAYS WTIH PM2.5-SPECIFIC AQI >100';

RUN;

Appendix G
NECMA, PMSA, and MSA Designations Used by the EPA and BRFSS

The BRFSS denotes geographic areas using New England county metropolitan areas (NECMAs), primary metropolitan statistical areas (PMSAs), and metropolitan statistical areas (MSAs).  The AQI does not provide environmental data at the NECMA level; therefore, the PMSA or MSA that corresponds most closely to the NECMA was used to approximate the pollutant concentrations.  This approximation may not be an accurate representation of the air quality in the region.  Below is a list of the NECMAs used in the 2006 BRFSS metropolitan area data, the PMSAs and MSAs that were used to represent them in the AQS, and a brief description of the geographic differences between the two areas.  
 
BRFSS: 	1123—Boston-Worcester-Lawrence-Lowell-Brockton, MA-NH, NECMA
AQS: 	1120—Boston, MA-NH PMSA
	Hillsborough County, NH, and Strafford County, NH, are included in the NECMA, but not in the PMSA.

BRFSS:	1303—Burlington, VT, NECMA 
AQS:	1305—Burlington, VT, MSA
	The same counties are included in the NECMA and MSA, but the portions of counties included are different.

BRFSS:	3283—Hartford, CT, NECMA 
AQS: 	3280—Hartford, CT, MSA
	Litchfield County, New London County, and Windham County are included in the MSA, but not the NECMA.

BRFSS:	5483—New Haven-Bridgeport-Stamford-Waterbury-Danbury, CT, NECMA
AQS:	5480—New Haven-Meriden, CT, PMSA
	Portions of Middlesex County (Clinton town, Killingworth town) are included in the PMSA, but not the NECMA.  Fairfield County is included in the NECMA, but not the PMSA.

BRFSS:	5523—New London-Norwich, CT, NECMA 
AQS:	5520—New London-Norwich, CT-RI, MSA
	Windham County, Washington County, and portions of Middlesex County (Old Saybrook town) are included in the MSA, but not the NECMA. 

BRFSS:	6403—Portland, ME, NECMA  
AQS:	6400—Portland, ME, MSA
	York County is included in the MSA, but not the NECMA.

BRFSS:	6483—Providence-Warwick-Pawtucket, RI, NECMA  
AQS:	6480—Providence-Fall River-Warwick, RI-MA, MSA
	Bristol County, MA, and Newport County, RI, are included in the MSA, but not the NECMA.

BRFSS:	8003—Springfield, MA, NECMA  
AQS:	8000—Springfield, MA, MSA
	Franklin County is included in the MSA, but not the NECMA.