Research Findings #22: Restricted-activity Days in the United States, 1997 and 2001

Jeffrey A. Rhoades, PhD

Introduction

This report provides estimates of restricted-activity days (workdays or schooldays lost due to physical illness, injury, a mental or emotional problem, or caring for a family member with health problems) for the civilian noninstitutionalized population of the United States. Presented are data from the 1997 and 2001 Medical Expenditure Panel Survey (MEPS) Household Component representing a 5-year span, with 2001 data being the most recent data available. The percent of the population with restricted-activity days and the number of restricted-activity days per year are shown in relation to selected socioeconomic and demographic characteristics. The variables shown include age, race/ethnicity, sex, marital status, education, health insurance coverage, income, health status, and area of residence.

Restricted-activity days provide an indication of the burden of illness in the workplace and in school. With a greater understanding of the variation of this burden among groups, policymakers and health care providers would be better informed to put into practice health care that results in similar outcomes for all.The Technical Appendix describes restricted activity days in more detail and explains how estimates were derived.

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Findings

The restricted-activity days of interest are: (1) workdays lost due to physical illness, injury, or a mental or emotional problem; (2) workdays lost to care for a family member with health problems; and (3) schooldays lost due to physical illness, injury, or a mental or emotional problem.

Workdays Lost

Workdays lost for the working-age population (ages 16-64) are shown in Tables 1 and 2.

Age
In 1997 and 2001, the age group 25-54 had the highest percent of people with workdays lost due to illness, injury, or mental or emotional problems in the working-age population. In 2001, 42.0 percent of people ages 25-54 had workdays lost, compared to 37.2 percent and 34.5 percent for ages 16-24 and 55-64, respectively (Table 1).

Race/Ethnicity
Whites and others had the highest percentage of people with workdays lost due to illness, injury, or mental or emotional problems in both 1997 and 2001. (The category “whites and others” comprises whites and a small proportion of people whose race/ethnicity is not Hispanic, black, or white.) In 2001, 41.6 percent of whites and others had workdays lost, compared to 34.3 percent of Hispanics and 38.0 percent of blacks (Table 1).

In 1997 and 2001, a greater percent of whites and others than Hispanics or blacks had workdays or schooldays lost due to illness, injury, or mental or emotional problems.

Sex
A greater proportion of women than men have work absences. Pregnancy is a major reason for this difference. But pregnancy aside, women still generally have a higher absenteeism rate than men (Ballagh, Maxwell, and Perea, 1987; Bridges and Mumford, 2001).

A greater proportion of females than males had workdays lost due to illness, injury, or mental or emotional problems. In 2001, 46.5 percent of females versus 34.6 percent of males had workdays lost (Table 1). Comparing 1997 and 2001, there was a decrease in the proportion of both females (49.4 percent to 46.5 percent) and males (37.7 percent to 34.6 percent) with workdays lost (Table 1). However, from 1997 to 2001, the mean number of workdays lost during the year for people who had any workdays lost remained relatively stable at 12-13 days for females and 10-11 days for males (Table 2).

Education
As educational level increased, the proportion of people with workdays lost increased. In 2001, 32.3 percent of people with no high school education had workdays lost, compared to 42.4 percent of people with more than high school education (Table 1). At the same time, people with higher educational levels who had workdays lost had fewer such days. In 2001, people with more than high school education had 10.2 workdays lost, while those with no high school education had 13.7 workdays lost (Table 2).

Individuals with the least amount of education were the least likely to report workdays lost due to illness, injury, or mental or emotional problems in 1997 and 2001.

Perceived Health
As people’s reported health and mental health status declined, the percentage with workdays lost increased. Workers’ subjective health evaluation has been found to be strongly and significantly related to absenteeism (Leigh, 1983). In 2001, 59.7 percent of people with fair or poor health status had workdays lost, compared to only 29.3 percent of people in excellent health (Table 1). From 1997 to 2001, the proportion of people in fair or poor health or very good health who had workdays lost decreased. The proportion of people in fair or poor health who had workdays lost decreased from 66.3 percent in 1997 to 59.7 percent in 2001 (Table 1).

The number of workdays lost (among people with any lost days) also increased with deteriorating physical and mental health. Those with fair or poor health had 23.3 workdays lost in 2001, as opposed to 6.8 days for those with excellent health status (Table 2).

Workdays Lost To Care for a Family Member

Tables 3 and 4 show data on workdays lost to provide care for a family member for the working-age population (ages 16-64).

Age
In 1997 and 2001, in the working-age population, the age group 25-54 had the highest percent of people with workdays lost to care for a family member with health problems. In 2001, 23.3 percent of people ages 25-54 had workdays lost to care for a family member, compared to 9.0 percent for ages 16-24 and 15.9 percent for ages 55-64 (Table 3).

Sex
In both 1997 and 2001, a greater proportion of females than males had workdays lost to care for a family member. In 2001, 25.0 percent of females and 15.5 percent of males missed work to care for a family member (Table 3).

Marital Status
A greater proportion of married than unmarried people had workdays lost to provide care for a family member in both 1997 and 2001. In 2001, 24.8 percent of married people, compared to 13.1 percent of unmarried people, had workdays lost to provide care for a family member (Table 3). Among people who provided care to a family member, there was no difference in the mean number of days lost in 1997 and 2001 or for married compared to unmarried people (Table 4).

Metropolitan Statistical Area
People not living in a metropolitan statistical area were more likely to miss work to provide care for a family member in 1997 and 2001. In 2001, 22.1 percent of people living outside metropolitan areas, compared to 19.6 percent of people living in a metropolitan statistical area, had workdays lost to provide care for a family member (Table 3). However, among people who took off work to care for family members, there was no difference in the mean number of days lost (Table 4).

Schooldays Lost

Tables 5 and 6 show information on schooldays lost among the school age population (ages 5-22).

Race/Ethnicity
A higher proportion of whites and others than blacks or Hispanics had schooldays lost due to illness, injury, or mental or emotional problems in 1997 and 2001. In 2001, 56.6 percent of whites and others but only 42.4 percent of Hispanics and blacks had schooldays lost (Table 5). This race/ethnicity pattern also held true for both sexes in 1997 and 2001; for both females and males, whites and others had the highest percent with schooldays lost. In 2001, 56.9 percent of white and other females had schooldays lost, compared to 44.8 percent of Hispanic females and 42.5 percent of black females; 56.2 percent of white and other males had schooldays lost, compared to 40.1 percent of Hispanic males and 42.3 percent of black males (Table 5). The mean number of schooldays lost for people who had schooldays lost remained relatively stable for all race/ethnicity groups and both sexes in 1997 and 2001 (Table 6).In 1997 and 2001, a greater percent of whites and others than Hispanics or blacks had workdays or schooldays lost due to illness, injury, or mental or emotional problems.

Health Insurance Coverage
The uninsured were the least likely to have schooldays lost due to illness, injury, or mental or emotional problems in 1997 and 2001. In 2001, 33.2 percent of the uninsured had schooldays lost (Table 5). People with only public health insurance had the highest number of schooldays lost in both years. In 2001, people with only public health insurance had 6.8 schooldays lost, compared to 5.1 days for both privately insured and uninsured people (Table 6).

Perceived Health
For both perceived physical and mental health, as an individual’s reported health declined, the number of schooldays lost increased in both years. In 2001, people in fair or poor health had 22.8 schooldays lost, while those in excellent health had only 4.0 schooldays lost (Table 6). In addition, people in fair or poor health had the greatest increase in the number of schooldays lost from 1997 to 2001, an increase from 14.6 to 22.8 schooldays lost (Table 6). The pattern was similar for perceived mental health status.

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Conclusions

Findings show that restricted-activity days do vary by socioeconomic and demographic characteristics (age, race/ethnicity, sex, marital status, education, health insurance coverage, health status, and area of residence). Some examples of variation in restricted-activity days by socioeconomic and demographic characteristics follow.

People ages 25-54 were the most likely to have workdays lost due to illness, injury, or mental or emotional problems, as well as workdays lost to care for a family member, in 1997 and 2001.

In 1997 and 2001, a greater percent of whites and others than Hispanics or blacks had workdays or schooldays lost due to illness, injury, or mental or emotional problems. In 2001, 41.6 percent of whites and others ages 16-64 had workdays lost, versus 34.3 percent of Hispanics and 38.0 percent of blacks.

Females were more likely than males to have restricted-activity days. In both years, a greater percentage of females than males had workdays lost due to illness, injury, or mental or emotional problems and workdays lost to care for a family member with health problems. In 2001, 46.5 percent of females ages 16-64 had workdays lost, compared with 34.6 percent of males.

Individuals with the least amount of education, less than high school, were the least likely to have workdays lost due to illness, injury, or mental or emotional problems in 1997 and 2001. In 2001, 32.3 percent of working-age people with no high school education had workdays lost, compared to 42.4 percent of those with more than high school education.

People in fair or poor health (physical or mental) were at greater risk for experiencing workdays lost in 1997 and 2001. People in fair or poor health also had a greater number of restricted-activity days when they had such days. In 2001, 59.7 percent of working-age people in fair or poor health had workdays lost due to illness, injury, or mental or emotional problems, compared to only 29.3 percent of those in excellent health. The average number of workdays lost in 2001 was 23.3 for people in fair or poor health but only 6.8 for people in excellent health.

For additional information on restricted-activity days, analysts are encouraged to visit the MEPS Web site (www.meps.ahrq.gov). Under Data and Publications, links to the full year consolidated files HC-020 (1997), HC-028 (1998), HC-038 (1999), HC-050 (2000), and HC-060 (2001) are available. Data files provide detailed documentation pertaining to restricted activity days variables.

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Tables

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References

Ballagh J, Maxwell E, Perea K. Absenteeism in the workplace. Chicago: Commerce Clearing House, Inc.; 1987.

Bridges S, Mumford K. Absenteeism in the UK: A comparison across genders. The Manchester School. 2001 June; 69(3):276-84.

Cohen J, Monheit A, Beauregard K, et al. The Medical Expenditure Panel Survey: a national health information resource. Inquiry 1996; 33:373-89.

Cohen S. Sample design of the 1996 Medical Expenditure Panel Survey Household Component. Rockville (MD): Agency for Health Care Policy and Research; 1997. MEPS Methodology Report No. 2. AHCPR Pub. No. 97-0027.

Leigh J. Sex differences in absenteeism. Industrial Relations 1983 Fall; 22(3):349-61.

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Technical Appendix

The data in this report were obtained in interviews conducted for the Household Component (HC) of the 1997 and 2001 Medical Expenditure Panel Survey (MEPS). MEPS is cosponsored by the Agency for Healthcare Research and Quality and the National Center for Health Statistics (NCHS). The MEPS HC is a nationally representative survey of the U.S. civilian noninstitutionalized population that collects medical expenditure data at both the person and household levels. The focus of the MEPS HC is to collect detailed data on demographic characteristics, health conditions, health status, use of medical care services, charges and payments, access to care, satisfaction with care, health insurance coverage, income, and employment. In other components of MEPS, data are collected on the use, charges, and payments reported by providers.

The sample for the MEPS HC was selected from respondents to the National Health Interview Survey (NHIS), conducted by NCHS. NHIS provides a nationally representative sample of the U.S. civilian noninstitutionalized population and reflects an oversampling of Hispanics and blacks.

The MEPS HC collects data through an overlapping panel design. In this design, data are collected through a precontact interview that is followed by a series of five rounds of interviews over 21/2 years. Interviews are conducted with one member of each household, who reports on the health care expenses of the entire household. Medical expenditure and utilization data for two calendar years are collected from each household using computer-assisted personal interviewing. This series of data collection rounds is launched each subsequent year on a new sample of households to provide overlapping panels of survey data which, when combined with other ongoing panels, provide continuous and current estimates of health care expenditures.

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Restricted-Activity Days

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Age
The respondent was asked to report the age of each family member as of the date of each interview. In this report, age is usually based on the sample person’s age at the end of the reference year. If data were not collected at the end of the year because the sample person was out of scope (e.g., deceased or institutionalized), then age at the time of the previous interview(s) was used.

Race/Ethnicity
Classification by race and ethnicity is based on information reported for each family member. Respondents were asked if each family member’s race was best described as American Indian, Alaska Native, Asian or Pacific Islander, black, white, or other. They also were asked if each family member’s main national origin or ancestry was Puerto Rican; Cuban; Mexican, Mexicano, Mexican American, or Chicano; other Latin American; or other Spanish. All persons whose main national origin or ancestry was reported in one of these Hispanic groups, regardless of racial background, were classified as Hispanic. Since the Hispanic grouping can include black Hispanic, white Hispanic, and other Hispanic, the race categories of black, white, and other do not include Hispanic. Only data for people identified as Hispanic (of any race), non-Hispanic blacks, and non-Hispanic whites and others are included in this analysis.

Marital Status
Marital status was constructed from information available at three points in time during the reference year, the interview dates for the first two rounds of the reference year and at the end of the year.

Private insurance -- Private health insurance was defined as insurance that provides coverage for hospital and physician care (including Medigap coverage). Private health insurance could have been obtained through an employer, union, self-employed business, directly from an insurance company or health maintenance organization, through a group or association, or from someone outside the household.

Public coverage only -- People were considered to have only public coverage if they met both of the following criteria:

• They were not covered by private insurance during the reference year.
• They were covered by one of the following public programs: Medicare, CHAMPUS/CHAMPVA/TRICARE (Armed-Forces-related coverage), Medicaid or State Children’s Health Insurance Program (SCHIP), or other public hospital/physician coverage.

Uninsured -- The uninsured were defined as persons not covered by Medicare, CHAMPUS/CHAMPVA/TRICARE, Medicaid/SCHIP, other public hospital/physician programs, or private hospital/physician insurance (including Medigap coverage) during the reference year. People covered only by noncomprehensive State-specific programs (e.g., Maryland Kidney Disease Program) or private single-service plans (e.g., coverage for dental or vision care only, coverage for accidents or specific diseases) were not considered to be insured. People uninsured for the entire year did not have insurance coverage at any time during the survey year.

Income
Sample persons were classified according to the total yearly income of their family. Within a household, all people related by blood, marriage, or adoption were considered to be a family. Personal income from all family members was summed to create family income. Possible sources of income included annual earnings from wages, salaries, bonuses, tips, and commissions; business and farm gains and losses; unemployment and Workers’ Compensation; interest and dividends; alimony, child support, and other private cash transfers; private pensions, individual retirement account withdrawals, Social Security, and Department of Veterans Affairs payments; Supplemental Security Income and cash welfare payments from public assistance, Aid to Families with Dependent Children, and Aid to Dependent Children; gains or losses from estates, trusts, partnerships, S corporations, rent, and royalties; and a small amount of “other”income.

Income categories are defined by the ratio of family income to the Federal income thresholds, which control for family size and age of the head of family.

Categories are defined as follows:

• Poor -- Persons in families with income less than or equal to the poverty line; includes those who had negative income.
• Near-poor -- Persons in families with income over the poverty line through 125 percent of the poverty line.
• Low income -- Persons in families with income over 125 percent through 200 percent of the poverty line.
• Middle income -- Persons in families with income over 200 percent through 400 percent of the poverty line.
• High income -- Persons in families with income over 400 percent of the poverty line.

Education
Respondents were asked to report the years of date of the interviews. Categories are defined as follows:

• No high school -- Less than 9 years of schooling.
• Some high school -- 9 through 11 years of schooling.
• High school graduate -- 12 years of schooling.
• More than high school -- More than 12 years of schooling.

Perceived Health Status
In every round, the respondent is asked to rate the health of every member of the family. The exact wording of the question is: "In general, compared to other people of (PERSON)'s age, would you say that (PERSON)'s health is excellent, very good, good, fair, or poor?" A similar question is asked about mental health status. For this report, the response categories "fair" and "poor" were collapsed.
 
Place of Residence
People are identified as residing either inside or outside a metropolitan statistical area (MSA) as designated by the U.S. Office of Management and Budget, which applied 1990 standards using population counts from the 1990 U.S. census. An MSA is a large population nucleus combined with adjacent communities that have a high degree of economic and social integration with the nucleus. Each MSA has one or more central counties containing the area's main population concentration. In New England, metropolitan areas consist of cities and towns rather than whole counties. MSA data are based on MSA status as of the end of the reference year. If MSA status as of December 31 was not known, then MSA status at the time of the previous interview was used.
 
Region
Each MEPS sample person was classified as living in one of the following four regions as defined by the Bureau of the Census:

• Northeast -- Maine, New Hampshire, Vermont, Massachusetts, Rhode Island, Connecticut, New York, New Jersey, and Pennsylvania.
• Midwest -- Ohio, Indiana, Illinois, Michigan, Wisconsin, Minnesota, Iowa, Missouri, North Dakota, South Dakota, Nebraska, and Kansas.
• South -- Delaware, Maryland, District of Columbia, Virginia, West Virginia, North Carolina, South Carolina, Georgia, Florida, Kentucky, Tennessee, Alabama, Mississippi, Arkansas, Louisiana, Oklahoma, and Texas.
• West -- Montana, Idaho, Wyoming, Colorado, New Mexico, Arizona, Utah, Nevada, Washington, Oregon, California, Alaska, and Hawaii.

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Sample Design and Accuracy of Estimates

MEPS is a nationally representative subsample of the households responding to the previous year's NHIS. MEPS reflects the oversampling of Hispanic and black households resulting from the NHIS sample design. The 1997 MEPS sample consisted of 32,636 people. The response rate was 66.4 percent. The weighted MEPS population estimate for the civilian noninstitutionalized population as of December 31, 1997, was 267,704,802. For 2001, the corresponding numbers were 32,122 people, 66.3 percent, and a civilian noninstitutionalized population of 284,247,327.

The statistics presented in this report are affected by both sampling error and sources of nonsampling error, which include nonresponse bias, respondent reporting errors, interviewer effects, and data processing misspecifications. For a detailed description of the MEPS survey design, the adopted sample design, and methods used to minimize sources of nonsampling error, see Cohen (1997) and Cohen, Monheit, Beauregard, et al. (1996).

The MEPS person-level estimation weights include nonresponse adjustments and poststratification adjustments to population estimates derived from the Current Population Survey based on cross-classifications by region, MSA status, age, race/ethnicity, and sex. The overall MEPS response rate reflects response to both the MEPS and the preceding NHIS interview.

Tests of statistical significance were used to determine whether the differences between populations exist at specified levels of confidence or whether they occurred by chance. Differences were tested using z-scores having asymptotic normal properties at the 0.05 level of significance. Unless otherwise noted, only statistical differences between estimates are discussed in the text.

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Standard Error Tables

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