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Report 15

Demographic and Clinical Variations in 

Health Status

Methodolo Methodology 

Advancing Excellence in Health Care • www.ahrq.gov

Agency for Healthcare Research and Quality






































































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Abstract

Researchers have developed a number of measures

of health status that can be used to assess general levels

of population health, to compare different

sociodemographic groups, and to monitor the outcomes

of clinical interventions. Using nationally representative

data from the Medical Expenditure Panel Survey

(MEPS), this report from the Agency for Healthcare

Research and Quality summarizes population differences

using two generic measures: the SF-12® and the

EuroQol. In general, groups defined by age and

education showed the greatest variation in health status;

differences by sex, race/ethnicity, and geographic

location were relatively small. Persons diagnosed with

diabetes, asthma, or hypertension had worse physical

health status than those who did not have these

conditions.

Suggested citation

Fleishman JA. Demographic and clinical variations in health status.

Rockville (MD):Agency for Healthcare Research and Quality; 2005.

MEPS Methodology Report No. 14.AHRQ Pub. No. 05-0022.

Health Care Information and Electronic Ordering

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Web site—http://www.ahrq.gov/—makes practical,

science-based health care information available in

one convenient place.

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information, consumer health, and data.

The Web site features an Electronic Catalog to the

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resources. Many information products have an

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charge from the AHRQ Clearinghouse within 5

working days.

http://www.ahrq.gov/ http://www.ahrq.gov/


































































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Report 15

Demographic and Clinical Variations in 

Health Status

Methodology Methodology 

Advancing Excellence in Health Care • www.ahrq.gov

Agency for Healthcare Research and Quality

AHRQ Pub. No. 05-0022

January 2005
The Medical Expenditure Panel

Survey (MEPS)

Background

The Medical Expenditure Panel Survey (MEPS) is

conducted to provide nationally representative estimates

of health care use, expenditures, sources of payment,

and insurance coverage for the U.S. civilian

noninstitutionalized population. MEPS is cosponsored

by the Agency for Healthcare Research and Quality

(AHRQ), formerly the Agency for Health Care Policy

and Research, and the National Center for Health

Statistics (NCHS).

MEPS comprises three component surveys: the

Household Component (HC), the Medical Provider

Component (MPC), and the Insurance Component (IC).

The HC is the core survey, and it forms the basis for the

MPC sample and part of the IC sample. Together these

surveys yield comprehensive data that provide national

estimates of the level and distribution of health care use

and expenditures, support health services research, and

can be used to assess health care policy implications.

MEPS is the third in a series of national probability

surveys conducted by AHRQ on the financing and use

of medical care in the United States. The National

Medical Care Expenditure Survey (NMCES) was

conducted in 1977, the National Medical Expenditure

Survey (NMES) in 1987. Beginning in 1996, MEPS

continues this series with design enhancements and

efficiencies that provide a more current data resource to

capture the changing dynamics of the health care

delivery and insurance system.

The design efficiencies incorporated into MEPS are

in accordance with the Department of Health and

Human Services (DHHS) Survey Integration Plan of

June 1995, which focused on consolidating DHHS

surveys, achieving cost efficiencies, reducing respondent

burden, and enhancing analytical capacities. To

accommodate these goals, new MEPS design features

include linkage with the National Health Interview

Survey (NHIS), from which the sample for the MEPS

HC is drawn, and enhanced longitudinal data collection

for core survey components. The MEPS HC augments

NHIS by selecting a sample of NHIS respondents,

collecting additional data on their health care

expenditures, and linking these data with additional

information collected from the respondents’ medical

providers, employers, and insurance providers.

Household Component

The MEPS HC, a nationally representative survey

of the U.S. civilian noninstitutionalized population,

collects medical expenditure data at both the person and

household levels. The HC collects 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.

The HC uses an overlapping panel design in which

data are collected through a preliminary contact

followed by a series of five rounds of interviews over a

21/2-year period. Using computer-assisted personal

interviewing (CAPI) technology, data on medical

expenditures and use for 2 calendar years are collected

from each household. This series of data collection

rounds is launched each subsequent year on a new

sample of households to provide overlapping panels of

survey data and, when combined with other ongoing

panels, will provide continuous and current estimates of

health care expenditures.

The sampling frame for the MEPS HC is drawn

from respondents to NHIS, conducted by NCHS. NHIS

provides a nationally representative sample of the U.S.

civilian noninstitutionalized population, with

oversampling of Hispanics and blacks.

Medical Provider Component

The MEPS MPC supplements and validates

information on medical care events reported in the

MEPS HC by contacting medical providers and

pharmacies identified by household respondents. The

MPC sample includes all hospitals, hospital physicians,

home health agencies, and pharmacies reported in the

HC. Also included in the MPC are all office-based

physicians: 

• Providing care for HC respondents receiving

Medicaid.

• Associated with a 75-percent sample of households

receiving care through an HMO (health maintenance

organization) or managed care plan.

• Associated with a 25-percent sample of the

remaining households.

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iii

Data are collected on medical and financial

characteristics of medical and pharmacy events reported

by HC respondents, including:

• Diagnoses coded according to ICD-9 (9th Revision,

International Classification of Diseases) and DSMIV (Fourth Edition, Diagnostic and Statistical Manual

of Mental Disorders).

• Physician procedure codes classified by CPT-4

(Current Procedural Terminology, Version 4).

• Inpatient stay codes classified by DRG (diagnosisrelated group).

• Prescriptions coded by– national drug code (NDC),

medication names, strength, and quantity dispensed.

• Charges, payments, and the reasons for any

difference between charges and payments.

The MPC is conducted through telephone interviews

and mailed survey materials.

Insurance Component

The MEPS IC collects data on health insurance

plans obtained through private and public-sector

employers. Data obtained in the IC include the number

and types of private insurance plans offered, benefits

associated with these plans, premiums, contributions by

employers and employees, and employer characteristics.

Establishments participating in the MEPS IC are

selected through three sampling frames:

• A list of employers or other insurance providers

identified by MEPS HC respondents who report

having private health insurance at the Round 1

interview.

• A Bureau of the Census list frame of private-sector

business establishments.

• The Census of Governments from the Bureau of the

Census.

To provide an integrated picture of health insurance,

data collected from the first sampling frame (employers

and other insurance providers) are linked back to data

provided by the MEPS HC respondents. Data from the

other three sampling frames are collected to provide

annual national and State estimates of the supply of

private health insurance available to American workers

and to evaluate policy issues pertaining to health

insurance. Since 2000, the Bureau of Economic Analysis

has used national estimates of employer contributions to

group health insurance from the MEPS IC in the

computation of Gross Domestic Product (GDP).

The MEPS IC is an annual panel survey. Data are

collected from the selected organizations through a

prescreening telephone interview, a mailed

questionnaire, and a telephone followup for

nonrespondents.

Survey Management

MEPS data are collected under the authority of the

Public Health Service Act. They are edited and

published in accordance with the confidentiality

provisions of this act and the Privacy Act. NCHS

provides consultation and technical assistance.

As soon as data collection and editing are

completed, the MEPS survey data are released to the

public in staged releases of summary reports and

microdata files. Summary reports are released as printed

documents and electronic files. Microdata files are

released on CD-ROM and/or as electronic files.

Printed documents and CD-ROMs are available

through the AHRQ Publications Clearinghouse. Write or

call:

AHRQ Publications Clearinghouse

Attn: (publication number)

P.O. Box 8547

Silver Spring, MD 20907

800-358-9295

703-437-2078 (callers outside the United States

only) 

888-586-6340 (toll-free TDD service; hearing 

impaired only)

To order online, send an e-mail to: 

ahrqpubs@ahrq.gov.

Be sure to specify the AHRQ number of the

document or CD-ROM you are requesting. Selected

electronic files are available through the Internet on the

MEPS Web site: 

http://www.meps.ahrq.gov/

For more information, visit the MEPS Web site or 

e-mail mepspd@ahrq.gov.
v

Table of Contents

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

SF-12® and EQ-5D . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Tables showing means for four health status measures:

1. By selected population characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

2. By selected chronic conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Technical Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Population characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Sample design and accuracy of estimates. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Rounding. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Standard error tables. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1

Introduction

The ultimate goal of medical care is to foster

optimal levels of health and well-being. Researchers

have developed a number of measures of health status

that can be used to assess general levels of population

health, to compare different sociodemographic groups,

and to monitor the outcomes of clinical interventions.

These measures go beyond traditional indexes of

mortality or morbidity by focusing on the extent to

which people are impaired in physical, social, and

mental functioning.

The Short-Form 12, or SF-12® (Ware, Kosinski, and

Keller, 1996), and the EuroQol 5-D, or EQ-5D (Brooks,

1996; Dolan, 1997) are two of the more widely used

measures of health status. Although a large number of

studies report sex, racial/ethnic, and age comparisons

using these two measures, many are based on

nonrepresentative samples of patients seeking care for

specific conditions; relatively few studies report

comparisons based on data from a nationally

representative U.S. sample. This report presents

descriptive data on group differences in the SF-12® and

the EQ-5D, based on data collected in 2000 from the

nationally representative sample of the Medical

Expenditure Panel Survey (MEPS).

SF-12® and EQ-5D

The SF-12® contains 12 questions in which people

are asked about the following topics:

1. Limitations in performing moderate physical

activities, such as moving a table.

2. Limitations in climbing several flights of stairs.

3. Extent to which pain interfered with normal work.

4. Whether they accomplished less than they would

like at work or other regular activity as a result of

their physical health.

5. Whether they were limited in kind of work or other

activities as a result of their physical health.

6. How often they felt calm and peaceful.

7. How often they felt downhearted and blue.

8. Whether they accomplished less than they would

like at work or other regular activity as a result of

emotional problems.

9. Whether they didn’t do work or other activities as

carefully as usual as a result of emotional problems.

10. How often they felt that they had a lot of energy.

11. How often physical health or emotional problems

interfered with social activities.

12. Overall rating of health (from excellent to poor).

Responses to these questions are combined to form

two summary scores. The underlying concept is that

overall health is composed of a physical and a mental

component. The Physical Component Summary (PCS)

weights responses to the first five items more heavily.

The Mental Component Summary (MCS) weights

responses to items 6-9 more heavily. The PCS and the

MCS each have a mean of 50 and a standard deviation

of 10.

The EQ-5D contains five questions about the extent

of problems in mobility, self-care, daily activities, pain,

and anxiety/depression. Each question has three

possible responses: no problem, mild problem, or severe

problem. Each possible combination of responses to the

five questions constitutes a “health state.” In prior

research, Dolan (1997) developed a method for

assigning a number to each health state that represents

an average preference for one state versus another. The

most highly valued state (perfect health) has a score of

1.0; death has a score of 0.0; and other health states have

a score in between, with higher numbers indicating that a

state is valued more highly. (Some health states actually

receive a negative number, indicating that death is

preferable to being in that state.) In addition, the EQ-5D

includes a sixth question, which asks respondents to rate

their current overall health on a scale that ranges from 0

through 100, where 0 means “worst possible health” and

100 means “best possible health.” Thus, the EQ-5D

produces two scores: the preference-based index and the

rating scale. 

Demographic and Clinical Variations in Health Status 

by John A. Fleishman, Ph.D.,Agency for Healthcare Research and Quality
The SF-12® and the EQ-5D were administered to

adult (age 18 and over) respondents in MEPS in the

second half of 2000. A self-administered questionnaire

was distributed to all adult respondents (in Spanish

when requested). This questionnaire contained the SF12® and the EQ-5D. Overall, a total of 15,438 adult

respondents completed the questionnaire. Because

some respondents did not provide answers to all

questions in the SF-12® and the EQ-5D, analyses were

based on 11,295 respondents with no missing data.

These cases comprised 73 percent of those who were

eligible and provided questionnaire data. Readers are

cautioned that when analytic weights are applied to the

subgroup used in the analysis, the estimated population

total is less than the corresponding total for the eligible

population. The estimated population total for the

subgroup used in the analysis is 152,676,200. By

contrast, the estimated population total for the 15,438

respondents with any questionnaire data is 202,737,847. 

Tables 1 and 2 present scores for the PCS, the

MCS, the EQ-5D preference-based index, and the EQ5D rating scale. Standard errors are shown in Appendix

Tables A and B.

Findings

For 11,295 adult respondents, the mean PCS score

was 50.04 (standard error = 0.1180) and the mean MCS

score was 51.50 (standard error = 0.1163). Both scores

are close to the norm of 50. The mean EQ-5D

preference score was 0.83 (standard error = 0.0029) on

a scale with a maximum value of 1.0, and the mean

EQ-5D rating scale score was 79.84 (standard error =

0.2196) on a scale from 0 to 100. 

Sex

For each of the four outcome measures (PCS, MCS,

EQ-5D preference, ED-5D rating), men averaged

slightly higher scores than women (Table 1). Although

small in magnitude, the differences were statistically

significant for each measure. Prior research using these

measures has also found that men typically report being

in better health than women.

Age 

One would expect that health status would decline

as one grows older, and the findings generally support

this expectation (Table 1). The PCS, EQ-5D preference,

and EQ-5D rating scores all dropped consistently from

each age group to the next older group. The magnitude

of the difference from one group to the next was smaller

at younger ages and larger at older ages. For example,

the difference between the two youngest groups on the

PCS was 0.90 points (53.76 – 52.86), while the

difference between the two oldest groups was 6.70

points (43.97 – 37.27). Thus, physical health status

declines as one ages, and the decline accelerates at older

ages. 

The MCS is an exception to this pattern. Agerelated differences in mental health status showed no

clear trend across age. People aged 55-74 had

significantly higher mental health scores than those

aged 18-24. It is not the case that older people

generally are in poorer mental health compared to

younger individuals.

Race/Ethnicity 

Racial/ethnic differences in health status were

generally small, and the pattern was inconsistent across

the different measures (Table 1). For each measure,

differences between racial/ethnic groups did not reach

statistical significance.

Education

In contrast to the relatively small racial/ethnic

differences, educational attainment was strongly and

consistently related to health status (Table 1). For each

measure, people with a high-school degree reported

better health status than those who did not complete

high school. People with at least some college

experience reported the highest average levels of health

status for each measure. 

When interpreting these differences, keep in mind

that people who did not complete high school may also

be older than those with more advanced education. This

possible age difference may underlie some of the

educational differences.

2
3

Geographic Characteristics

People who lived in metropolitan statistical areas

(MSAs) reported significantly higher mean levels of

health status than residents of nonmetropolitan areas on

the PCS, EQ-5D preference score, and EQ-5D rating

scale (Table 1). However, the magnitudes of the

differences were small. Differences in mental health

were not statistically significant. Because

nonmetropolitan residents tend, on average, to be older

than metropolitan area residents, these differences may

arise from underlying differences in age.

Regional differences were statistically significant for

the PCS and EQ-5D rating scale (Table 1). Residents of

the South had the lowest PCS scores, and residents of the

West region had the lowest scores on the EQ-5D rating

scale. The magnitude of these differences was small.

Regional differences were not significant for the MCS or

the EQ-5D preference score. 

Insurance Coverage 

MEPS obtained detailed and exhaustive information

concerning the health insurance coverage of each person

in the sampled households. The group with “any

insurance” coverage includes those with either public or

private health insurance during July 2000. Those with no

insurance during this period reported significantly lower

MCS scores than those with some insurance (Table 1).

(Because young adults are among the most likely to have

no health coverage and because most of the elderly have

health insurance under Medicare, age-related factors may

also underlie the MCS difference.) The two insurance

groups did not differ significantly on either of the EQ5D measures or on the PCS. 

Clinical Status 

The four measures of health status examined in this

report provide overall summaries of a person’s health.

The presence or absence of a specific chronic condition

is one factor that should exert a strong influence on

overall health status. During the MEPS interview,

respondents reported whether a doctor or other health

professional had ever diagnosed them with hypertension

(high blood pressure), diabetes (high blood sugar), or

asthma. 

Table 2 shows means for the four health status

measures, depending on whether or not the person had

each of these chronic conditions. On all four measures,

people with high blood pressure had significantly lower

scores than those who had not received this diagnosis.

Similarly, people with diabetes had lower scores on all

four measures than people without diabetes, and people

with asthma had significantly lower scores than those

without asthma.

When interpreting these results, one should

remember that those without the condition in question

(e.g., diabetes) may have other conditions, so those with

diabetes are being compared to those without, who may

have other serious medical conditions. In addition,

MEPS did not ascertain the severity of these conditions,

nor the presence of any complications. Finally, because

this information was self-reported, it is possible that

some respondents may have inadvertently neglected to

mention that they had the condition.

Nevertheless, two important patterns are apparent in

the results in Table 2. First, the impact of clinical status

was much greater than characteristics such as sex,

race/ethnicity, region, MSA status, and insurance

coverage. Second, the impact of clinical status was

smaller for the MCS than for the other three measures.

References

Brooks R. EuroQol: the current state of play. Health

Policy 1996; 37(1):53-72.

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.

Dolan P. Modeling variations for EuroQol health states.

Med Care 1997; 35:1095-1108.

Ware JE, Kosinski M, Keller SD. A 12-item short-form

health survey: construction of scales and preliminary

tests of reliability and validity. Med Care 1996; 34:220. 
4

Note: Table entries are means for each health status measure, estimated within each demographic category. PCS is the Physical Component

Summary score from the SF-12®; MCS is the Mental Component Summary score from the SF-12®. EQ-5D refers to the EuroQol

instrument.

Source: Center for Financing, Access, and Cost Trends, Agency for Healthcare Research and Quality: Medical Expenditure Panel Survey,

Household Component, 2000 Full-Year File.

Total sample 50.04 51.50 0.83 79.84 

Sex

Women 49.30 50.71 0.82 79.05

Men 50.81 52.34 0.85 80.68

Age in years

18-24 53.76 51.41 0.90 85.05

25-34 52.86 51.30 0.88 82.19

35-44 51.71 50.92 0.85 81.04

45-54 49.42 51.22 0.81 78.59

55-64 47.74 52.35 0.79 77.79

65-74 43.97 53.15 0.76 74.45

75 and over 37.27 51.67 0.66 67.25

Race/ethnicity

White 49.92 51.52 0.83 79.90

Black 50.17 51.73 0.83 80.16

Hispanic 50.44 51.07 0.84 79.12

Other 51.09 51.57 0.86 79.43

Education

Less than high school 46.81 50.10 0.76 74.35

High school degree 49.30 51.50 0.82 79.03

At least some college 51.59 51.96 0.87 82.19

Metropolitan Statistical Area (MSA)

MSA 50.36 51.52 0.84 80.08

Non-MSA 48.67 51.42 0.81 78.80

Census region

Northeast 50.49 51.37 0.84 80.65

Midwest 50.66 52.01 0.84 80.78

South 49.31 51.44 0.82 79.57

West 50.13 51.14 0.84 78.55

Any insurance (July 2000)

Yes 49.94 51.73 0.84 79.95

No 50.54 50.34 0.82 79.31

Health status measure

Population EQ-5D EQ-5D

characteristic PCS MCS preference rating

Table 1. Means for four health status measures by selected population

characteristics
5

Note: Table entries are means for each health status measure, estimated within each category of chronic condition. A “yes” for each condition

indicates that the person was told by a physician or other health professional, at some prior time, that he or she had the specific condition.

PCS is the Physical Component Summary score from the SF-12®; MCS is the Mental Component Summary score from the SF-12®. EQ-5D

refers to the EuroQol instrument.

Source: Center for Financing, Access, and Cost Trends, Agency for Healthcare Research and Quality: Medical Expenditure Panel Survey,

Household Component, 2000 Full-Year File.

Hypertension (ever)

No 51.58 51.74 0.86 81.88

Yes 44.20 50.59 0.73 72.09

Diabetes (ever)

No 50.51 51.60 0.84 80.61

Yes 41.65 49.66 0.69 66.25

Asthma (ever)

No 50.33 51.67 0.84 80.32

Yes 47.04 49.79 0.77 75.04

Health status measure

Population EQ-5D EQ-5D

characteristic PCS MCS preference rating

Table 2. Means for four health status measures by selected chronic conditions
6

Technical Appendix

This data in this report were obtained during

interviews for the Household Component (HC) of the

2000 Medical Expenditure Panel Survey (MEPS). MEPS

is cosponsored by the Agency for Healthcare Research

and Quality (AHRQ) 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 and on the

supply side of the health insurance market.

The sample for the 2000 MEPS HC was selected

from respondents to the 1999 National Health Interview

Survey (NHIS), which was 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. Two calendar years of medical

expenditure and utilization data are collected from each

household and captured using computer-assisted personal

interviewing (CAPI). This series of data collection

rounds is launched again each subsequent year on a new

sample of households to provide overlapping panels of

survey data which, when combined with data from other

ongoing panels, provide continuous and current estimates

of health care expenditures. 

Data in this report from the Short-Form 12 (SF-12®)

and the EuroQol 5-D (EQ-5D) were obtained in the

second half of 2000, in Round 2 for Panel 5 and Round 4

for Panel 4. Questionnaires containing these

instruments, as well as other unrelated questions on

health care experiences, were distributed to adult MEPS

respondents (those aged 18 and older as of July 2000).

Respondents completed the questionnaires at their

convenience and returned them by mail. Of those

eligible to receive the questionnaire, 93.5 percent

responded. For analyzing data from the selfadministered questionnaire, special weights were

developed incorporating adjustments for questionnaire

nonresponse. Statistical analyses incorporated these

weights and also accounted for the complex MEPS

survey sampling design.

A total of 1,899 cases (14 percent) were missing one

or more SF-12® items. Scores for the Physical

Component Summary (PCS) and the Mental Component

Summary (MCS) of the SF-12® were imputed for 1,305

(69 percent) of these cases using the proprietary SF-12

algorithm for estimating missing data developed by

QualityMetric, Inc. (www.sf-36.org).

Data on clinical conditions were obtained in Round

3 for Panel 5 and Round 5 for Panel 4, which took place

approximately 6 months after the data collection for the

SF-12® and EQ-5D. Respondents were asked whether

each household member had ever been diagnosed by a

doctor or other health professional as having selected

chronic clinical conditions: diabetes (excluding

gestational diabetes), asthma, and high blood pressure.

These diagnoses were not validated by comparison with

medical records.

Analyses were based on the 2000 full-year file 

(H-39). They were based on 11,295 cases with no

missing data on any variable used in the analyses.

(Imputed scores for the PCS-12 and MCS-12 were not

considered to be missing.) These cases comprised 73

percent of those who were eligible and completed the

self-administered questionnaire. Readers are cautioned

that when analytic weights are applied to the subgroup

used in the analysis, the estimated population total is less

than the corresponding total for the eligible population.

The estimated population total for the subgroup used in

the analysis is 152,676,200. In contrast, the estimated

population total for the 15,438 respondents with any

questionnaire data is 202,737,847. 

Although the sample of 11,295 cases with no

missing data is not strictly nationally representative,

estimates based on this sample do not diverge greatly

from estimates based on the maximum number of

available cases. For example, the overall means based on

all available data were 49.22 for PCS-12 (unweighted n =

14,728), 51.16 for MCS-12 (unweighted n = 14,728),

0.82 for EQ-5D preference (unweighted n = 14,888), and

78.82 for EQ-5D rating (unweighted n = 13,100).
7

Population Characteristics 

Race/Ethnicity 

Classification by race and ethnicity was based on

information provided by the household respondent for

each household member. The respondent was asked if

each person’s race was best described as black, white,

Asian or Pacific Islander, American Indian, or Alaska

Native. The respondent was also asked if each person’s

main national origin or ancestry was Puerto Rican;

Cuban; Mexican, Mexicano, Mexican American, or

Chicano; other Latin American; or other Spanish.

Persons claiming a main national origin or ancestry in

one of these Hispanic groups, regardless of racial

background, were classified as Hispanic. Since the

Hispanic grouping can include persons of any race, the

race categories of black, white, and other do not include

Hispanic. 

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 based on the sample person’s age as of July

1, 2000.

Metropolitan Statistical Area

Individuals were identified as residing either inside

or outside a metropolitan statistical area (MSA) as

designated by the U.S. Office of Management and

Budget (OMB), 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 within 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. 

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. 

Insurance Coverage

Insurance coverage was based on an extensive set of

questions ascertaining public and private sources of

coverage for each respondent. The uninsured were

defined as people not covered by Medicare, TRICARE,

Medicaid, other public hospital/physician programs, or

private hospital/physician insurance during July 2000.

The relevant variable in the MEPS data is INSJU00X.

Individuals covered only by noncomprehensive Statespecific programs (e.g., Maryland Kidney Disease

Program, Colorado Child Health Plan) or private singleservice plans (e.g., coverage for dental or vision care

only, coverage for accidents or specific diseases) were

not considered to be insured. 

Sample Design and Accuracy of

Estimates 

MEPS is designed to produce estimates at the

national and regional level over time for the civilian

noninstitutionalized population of the United States and

some subpopulations. 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.

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 Zscores having asymptotic normal properties at the 0.05

level of significance. Unless otherwise noted, only

statistically significant differences between estimates are

discussed in the text. 

Rounding

Estimates presented in the tables were rounded to

the nearest hundredth. Standard errors, presented in

Tables A and B, were rounded to the nearest 0.0001. 

8
9

Note: Table entries are standard errors of the mean for each health status measure, estimated within each demographic category. PCS is the

Physical Component Summary score from the SF-12®; MCS is the Mental Component Summary score from the SF-12®. EQ-5D refers to

the EuroQol instrument.

Source: Center for Financing, Access, and Cost Trends, Agency for Healthcare Research and Quality: Medical Expenditure Panel Survey,

Household Component, 2000 Full-Year File.

Standard error

Total .1180 .1163 .0029 .2196 

Sex

Women .1465 .1505 .0039 .2556

Men .1440 .1300 .0032 .2852

Age in years

18-24 .1771 .2977 .0057 .3938

25-34 .1981 .2291 .0050 .4151

35-44 .1834 .2375 .0042 .3511

45-54 .2290 .2298 .0056 .5097

55-64 .3529 .3419 .0086 .6078

65-74 .3673 .3327 .0082 .6288

75 and over .5157 .5608 .0130 .9905

Race/ethnicity

White .1394 .1303 .0032 .2444

Black .3160 .3510 .0083 .7623

Hispanic .2664 .2748 .0070 .4963

Other .5694 .6712 .0132 1.393

Education

Less than high school .3168 .2943 .0081 .5874

High school degree .2006 .1823 .0041 .3186

At least some college .1425 .1378 .0030 .3222

Metropolitan Statistical Area (MSA)

MSA .1339 .1306 .0035 .2609

Non-MSA .2289 .2491 .0047 .4030

Census Region

Northeast .3067 .2539 .0066 .5607

Midwest .1638 .2418 .0058 .3942

South .1998 .1835 .0050 .3670

West .2508 .2378 .0064 .3858

Any insurance (July 2000)

Yes .1343 .1265 .0032 .2603

No .2776 .2954 .0065 .4514

Health status measure

Population EQ-5D EQ-5D

characteristic PCS MCS preference rating

Table A. Standard errors of means for four health status measures by selected

population characteristics

Corresponds to Table 1
10

Note: Table entries are standard errors of the mean for each health status measure, estimated within each chronic condition category. PCS is

the Physical Component Summary score from the SF-12®; MCS is the Mental Component Summary score from the SF-12®. EQ-5D refers

to the EuroQol instrument.

Source: Center for Financing, Access, and Cost Trends, Agency for Healthcare Research and Quality: Medical Expenditure Panel Survey,

Household Component, 2000 Full-Year File.

Standard error

Hypertension (ever)

No .1127 .1240 .0028 .2421

Yes .2758 .2436 .0062 .4424

Diabetes (ever)

No .1140 .1151 .0029 .2153

Yes .5470 .4852 .0129 .9706

Asthma (ever)

No .1182 .1137 .0029 .2229

Yes .4757 .3982 .0115 .7010

Health status measure

Population EQ-5D EQ-5D

characteristic PCS MCS preference rating

Table B. Standard errors of means for four health status measures by selected

chronic conditions 

Corresponds to Table 2
AHRQ Pub. No. 05-0022

January 2005

ISBN 1-58763-200-4

ISSN 1531-5673

U.S. Department of Health 

and Human Services

Public Health Service

Agency for Healthcare Research

and Quality

540 Gaither Road

Rockville, MD 20850