| Methodology Report #15 : Demographic and Clinical Variations in Health Status 
 by
              John A Fleishman, Agency for Healthcare Research and Quality             Select for more information
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              Medical Expenditure Panel Survey (MEPS).           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 socio-demographic 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. 
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 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 socio-demographic 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 non-representative 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).   Return to Top SF-12® and EQ-5D The SF-12® contains 12 questions in which people are         asked about the following topics: 
            Limitations in performing moderate physical           activities, such as moving a table.Limitations in climbing several flights of           stairs. Extent to which pain interfered with normal work.Whether they accomplished less than they would           like at work or other regular activity as a result of their physical           health.Whether they were limited in kind of work or           other activities as a result of their physical health.How often they felt calm and peaceful.How often they felt downhearted and blue.Whether they accomplished less than they would           like at work or other regular activity as a result of emotional           problems.Whether they didn’t do work or other activities           as carefully as usual as a result of emotional problems.How often they felt that they had a lot of           energy.How often physical health or emotional problems           interfered with social activities.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. 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 SF-12® 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 EQ-5D rating scale. Standard errors are shown in Appendix Tables A and B.  Return to Top 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. 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 EQ-5D 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.  Return to Top 
               Table 1 Means for four health status measures by selected population characteristics
          
            
              
                | Population Characteristics | PCS | MCS | EQ-5D preference | EQ-5D rating |  
                | 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 |  
 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. Return to Top  
                    Table 2 Means for four health status measures by selected chronic conditions
              
              
              
              
              
                | Population Characteristics | PCS | MCS | EQ-5D preference | EQ-5D rating |  
                | 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 |    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. Return to Top  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 self         administered 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. (http://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). Return to Top 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         State specific programs (e.g., Maryland Kidney Disease Program, Colorado         Child Health Plan) 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. Return to Top 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 Z-scores 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. Return to Top  Standard Errors 
            Table A Standard errors of means for four health status measures by selected population characteristics Corresponds to Table 1 
        
              
              
                | Population Characteristics | PCS Standard Error  | MCS Standard Error | EQ-5D preference Standard Error | EQ-5D rating 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 |  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.        Return to Top
          
          
           
           Table B Standard errors of  means for four health status measures by selected chronic conditions Corresponds to Table 2 
              
              
                | Population Characteristics | PCS Standard Error | MCS Standard Error | EQ-5D preference Standard Error | EQ-5D rating 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 |  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.        
         U. S. Department of Health and Human Services         Public Health Service         Agency for Healthcare Research and Quality        
           AHRQ Pub. No. 05-0022         January 2005        
           ISBN 1-58763-200-4         ISSN 1531-5673
           Return to Top 
            
              |  Suggested Citation: Fleishman, J. A. Methodology Report #15: Demographic and Clinical Variations in Health Status. January 2005. Agency for Healthcare Research and Quality, Rockville, MD. http://www.meps.ahrq.gov/data_files/publications/mr15/mr15.shtml
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