Objectives. We examined factors that influence health-related quality of life (HRQOL) among individuals aged 50 years and older with and without functional limitations.
Methods. We analyzed data from the 2009 Behavioral Risk Factor Surveillance System to assess associations among demographic characteristics, health care access and utilization indicators, modifiable health behaviors, and HRQOL characterized by recent physically and mentally unhealthy days in those with and those without functional limitations. We defined functional limitations as activity limitations owing to physical, mental, or emotional health or as the need for special equipment because of health.
Results. Age, medical care costs, leisure-time physical activity, and smoking were strongly associated with both physically and mentally unhealthy days among those with functional limitations. Among those without functional limitations, the direction of the effects was similar, but the size of the effects was substantially smaller.
Conclusions. The availability of lower cost medical care, increasing leisure- time physical activity, and reducing rates of cigarette smoking will improve population HRQOL among older adults with and without functional limitations. These factors provide valuable information for determining future public health priorities. (Am J Public Health. 2012;102:496-502.)
Disability affects a substantial portion of the population, and the prevalence of disabilities increases with age. Adults with disabilities represent 31% of those aged 55-64 years and 52% of those aged 65 years and older.[
Disability definitions have evolved over the past 2 centuries because of the medical profession's changing attitudes regarding health care treatment of individuals with disabilities and changing societal perspectives, including the destigmatization of attitudes and beliefs regarding disability and increased support for designing environments that encourage independent living.[
The shift in focus in public health to health promotion and quality of life is advancing quickly because of increases in life expectancy and the increasing number of individuals living with chronic diseases. Furthermore, as the population of the United States continues to age, the public health community has become more focused on understanding how to improve health-related quality of life (HRQOL) among individuals with multiple chronic conditions and disabilities.[
When depicting the nature of the relationships among disability, functional limitations, and HRQOL, it is important to consider the perspective of the individual evaluating the health outcome. Previous studies have shown significant differences between self-report and proxy reports for individuals with disabilities.[
In a seminal article on understanding the structure of perceived health (more recently referred to as HRQOL) among older Americans, Johnson and Wolinsky[
Measuring HRQOL can assist in determining the burden of disabilities and chronic diseases and can provide valuable new insights into the relationships between HRQOL and risk factors. We investigated which risk factors and public health policies should be considered for improving HRQOL among those with and those without functional limitations. On the basis of the conceptual definitions the ICF presented, the theoretical model presented by Johnson and Wolinsky,[
The BRFSS, a state-based cross-sectional survey, is the largest ongoing telephone health survey in the United States. Its objective is to collect uniform, state-specific data from adults regarding preventive health practices and risk behaviors associated with chronic diseases, injuries, and infectious diseases. Data are collected in all 50 states, the District of Columbia, Puerto Rico, the US Virgin Islands, and Guam. The BRFSS methods, design, and data sets can be found at
Functional limitations. We defined functional limitations according to responses to 2 questions: "Are you limited in any way in any activities because of physical, mental, or emotional problems?" and "Do you now have any health problem that requires you to use special equipment, such as a cane, a wheelchair, a special bed, or a special telephone?" We classified respondents who replied yes to either question as having a functional limitation.[
Demographic factors. We included 6 demographic factors in the multivariate models: age group (those aged 50-64 years and those aged ≥65 years); gender; race/ethnicity (Hispanic, White non-Hispanic, Black non- Hispanic, other non-Hispanic); education ( Health care access. We assessed the effects of 3 health care access variables: health insurance coverage, regular health care provider, and medical care cost issues. The question for health insurance coverage was "Do you have any kind of health care coverage, including health insurance, prepaid plans such as HMOs [health maintenance organizations], or government plans such as Medicare?" The question for regular health care provider was "Do you have one person you think of as your personal doctor or health care provider?" Finally, the question for medical care cost issues was "Was there a time in the past 12 months when you needed to see a doctor but could not because of cost?" Health care utilization. We assessed the effects of 2 health care utilization variables: reporting a routine medical checkup in the past year, and reporting having received an influenza vaccine in the past year. We derived whether an individual had had a routine medical checkup in the past year from the following question: "About how long has it been since you last visited a doctor for a routine checkup?" For individuals who responded that they had a routine checkup in the past 12 months, we coded the variable as yes. We derived whether an individual had had an influenza vaccine in the past 12 months from 2 questions: "During what month and year did you receive your most recent flu shot?" and "During what month and year did you receive your most recent flu vaccine that was sprayed in your nose?" We coded an answer indicating yes to within the past 12 months as yes but otherwise as no. Modifiable health behaviors. We assessed the effects of 3 potentially modifiable health behaviors on HRQOL: current cigarette smoking, consumption of fruits and vegetables, and leisure-time physical activity. We derived current cigarette smoking from an affirmative response to "Have you smoked at least 100 cigarettes in your entire life?" and an affirmative response of either "every day" or "some days" to the question "Do you now smoke cigarettes every day, some days, or not at all?" The indicator variable for having eaten fruits and vegetables 5 times per day was a BRFSS computed variable we derived from questions regarding consumption of fruits and vegetables. We derived participating in leisure-time physical activity from the question "During the past month, other than your regular job, did you participate in any physical activities or exercises such as running, calisthenics, golf, gardening, or walking for exercise?" The CDC previously developed 4 core HRQOL measures that have demonstrated content validity, construct validity, criterion validity with the Rand Medical Outcomes Study Short Form-36 health survey, predictive validity, test-retest reliability, and internal consistency.[ To account for the BRFSS complex sample survey design and sampling weights, we used SAS-callable SUDAAN version 10.0 (RTI International, Research Triangle Park, NC). We considered prevalence estimates and means statistically significant if the 95% confidence intervals (CIs) did not overlap. We used multiple regression models to simultaneously estimate the independent effects of demographic factors, health care access, health care utilization, and modifiable health behaviors. We stratified models by functional limitation status. We have reported unstandardized parameter estimates (b) and P values. Given the large sample size for both those with and those without functional limitations, we considered these parameter estimates statistically significant at P<.01. Compared with individuals without functional limitations, those with functional limitations were more likely to be older, female, Black non-Hispanic, less educated, in a household with a lower annual income, and separated, widowed, divorced, or unmarried (Table 1). Those with functional limitations were more likely to have a regular health care provider (93.4%; 95% CI 93.0. 93.8 vs 90.5%; 95% CI = 90.1, 90.8, respectively) and report medical care cost issues (15.9%; 95% CI= 15.3, 15.8 vs 7.3%; 95% CI=7.0. 7.6, respectively). Those with functional limitations were also more likely to have had a routine medical checkup and influenza immunization in the past year. Finally, those with functional limitations were more likely to be cigarette smokers (18.4%; 95% CI=17.8, 19.0 vs 12.9%; 95% CI= 12.5, 13.3) and less likely to eat 5 or more fruits and vegetables each day (24.4%; 95% CI 23.7. 25.0 vs 26.1%; 95% CI=25.7, 26.6) or to have participated in leisure-time physical activity in the last month (57.7%; 95% CI = 57.0, 58.4 vs 79.0%; 95% CI = 78.5, 79.4). Those aged 50 years and older with functional limitations reported an average of 9 more physically unhealthy days (11.4; 95% CI=11.2, 11.6 vs 2.1; 95% CI = 2.0, 2.2) and 4 more mentally unhealthy days (5.8; 95% CI = 5.6, 6.0 vs 1.9; 95% 0=1.8, 2.0) than did those same aged adults without functional limitations. Most of those with and those without functional limitations reported no mentally unhealthy days, and more than 30% of those with functional limitations and 74% of those without functional limitations reported no physically unhealthy days. Individuals differed significantly on responses to several of the independent variables among those with and those without functional limitations by age group (Table 2). Among those aged 50 to 64 years, the percentage who could not afford medical care was substantial (23.3% vs 9.6% for those with and those without limitations, respectively), but this gap decreased for those aged 65 years and older (6.5% vs 2.9%), likely because of the broader availability of Medicare coverage. Among those aged 50 to 64 years, 25.4% of those with functional limitations were current smokers, whereas 15.3% of those without functional limitations were current smokers; the difference in percentages of current smokers by functional status was smaller for those aged 65 years and older (9.2% vs 7.8%). As expected, those with functional limitations in both age groups were much less likely to report engaging in leisure- time physical activity than were those without functional limitations. For the HRQOL outcomes, individuals with a functional limitation reported substantially more physically unhealthy days for both age groups than did those without functional limitations (12.1 days vs 1.8 days for those aged 50-64 years, and 10.6 days vs 2.5 days for those aged ≥65 years). Interestingly, for individuals with functional limitations, those aged 65 years and older reported 1.5 fewer physically unhealthy days than did those aged 50 to 64 years. For those without functional limitations, the difference was in the opposite direction. The mean number of mentally unhealthy days for both functional status groups was substantially less for those aged 65 years and older (3.6 days for those with functional limitations and 1.3 days for those without functional limitations) relative to those aged 50 to 64 years (7.7 days and 2.2 days, respectively). In general, the independent associations with physically unhealthy days for those with functional limitations were substantially larger than they were for those without functional limitations (Table 3). Physically unhealthy days decreased with increasing age among those with functional limitations but increased with increasing age among those without functional limitations. Physically unhealthy days decreased with increasing annual household income among those with and those without functional limitations. For the health care access and health care utilization variables, differences in physically unhealthy days were the largest for medical care cost issues: 2.67 and 1.94 more days for those with and those without functional limitations, respectively. Having health care coverage, having a regular provider, receiving an influenza immunization in the last year, and having a routine medical checkup in the last year were also associated with more physically unhealthy days in both groups, but the relative effects were smaller than those for medical care cost issues. It is possible that those reporting more physically unhealthy days were sicker and, hence, more likely to seek health care coverage, have a regular health care provider, receive an influenza immunization, and receive regular checkups; however, because of the cross-sectional nature of this analysis, the directionality of these relationships cannot be determined. For the modifiable health behaviors among those with functional limitations, physically unhealthy days was higher among current smokers (1.46 more days than nonsmokers) and lower among those who engaged in leisure- time physical activity (5.28 fewer days than sedentary individuals). For those without limitations, leisure-time physical activity was associated with fewer physically unhealthy days.
Variables Functional Limitation: No. Functional Limitation: Weighted % (95% CI) No Functional Limitation: No. No Functional Limitation: Weighted % (95% CI) Aged ≥65 y 34 725 44.3 (43.6, 45.0) 61 880 34.8 (34.4, 35.3) Male gender 25 625 45.6 (44.9, 46.4) 58 887 49.6 (49.1, 50.1) Race/ethnicity White non-Hispanic 57 751 79.0 (78.2, 79.7) 124 965 79.3 (78.8, 79.8) Black non-Hispanic 5390 10.2 (9.7, 10.8) 9378 8.3 (7.9, 8.6) Hispanic 2395 7.1 (6.5, 7.6) 5546 8.2 (7.7, 8.6) Other non-Hispanic 2321 3.7 (3.4, 4.1) 4916 4.2 (4.0. 4.6) Educational level < high school graduate 8331 12.6 (12.1, 13.2) 9847 7.7 (7.4, 8.1) High school graduate or GED 21610 30.6 (30.0, 31.3) 43933 28.0 (27.6, 28.5) ≥ some college 37 916 56.8 (56.0, 57.5) 91025 64.2 (63.7, 64.7) Annual household income, $ <25 000 31 063 40.5 (39.8, 41.3) 33 991 20.0 (19.6, 20.5) 25 000-74 999 27 498 41.4 (40.7, 42.1) 69 821 45.2 (44.7, 45.7) ≥75 000 9296 18.1 (17.5, 18.7) 40 993 34.8 (34.3, 35.3) Marital status Currently married 30 873 57.1 (56.4, 57.8) 87 514 71.3 (70.8, 71.7) Separated, divorced, or widowed 31401 34.9 (34.2, 35.6) 46 887 22.4 (22.0, 22.8) Never married or unmarried couple 5583 8.0 (7.6, 8.5) 10 404 6.3 (6.0, 6.6) Health care access Has any health care coverage 63 197 92.2 (91.8, 92.7) 134 883 92.2 (91.8, 92.5) Has a regular health care provider 63 660 93.4 (93.0, 93.8) 131 838 90.5 (90.1, 90.8) Medical care cost issues 9584 15.9 (15.3, 16.5) 9182 7.3 (7.0, 7.6) Health care utilization Routine checkup in past y 54 842 81.9 (81.3, 82.4) 111 723 77.8 (77.3, 78.2) Had flu shot or spray in past y 42 502 60.2 (59.5, 60.9) 78 746 50.9 (50.4, 51.4) Modifiable health behaviors Current cigarette smoker 12 084 18.4 (17.8, 19.0) 18 260 12.9 (12.5, 13.3) Ate ≥5 fruits and vegetables per d 16 399 24.4 (23.7, 25.0) 37 828 26.1 (25.7, 26.6) Engaged in leisure-time physical activity in last mo 38 497 57.7 (57.0, 58.4) 113 354 79.0 (78.5, 79.4) Note. BRFSS=Behavioral Risk Factor Surveillance System; CI = confidence interval; GED-general equivalency diploma. For mentally unhealthy days, the size of the effects was also substantially larger for those with functional limitations. The largest demographic effects were for age, income, and gender. For those with functional limitations, those aged 65 years and older reported 3.64 fewer mentally unhealthy days than did those aged 50 to 64 years. For those without limitations, this difference was 0.86 days. For the health care utilization and health care access variables, only medical care cost issues was statistically significant for either functional status group. Those with limitations who also reported medical care cost issues had 3.49 more mentally unhealthy days than did those who did not; those without limitations who reported medical care cost issues had 2.68 more days than did those who did not. For modifiable health behaviors, mentally unhealthy days were associated with current smoking (2.35 more days than nonsmokers) and reporting leisure-time physical activity (1.98 fewer days than the sedentary) for those with functional limitations. For those without functional limitations, smoking was associated with more mentally unhealthy days whereas eating fruits and vegetables and leisure-time physical activity were associated with fewer mentally unhealthy days. The Health and Human Services' Healthy People 2020 initiative has identified 4 overarching goals that relate to HRQOL, disability, and aging. Measuring HRQOL can help determine the burden of preventable diseases, injuries, and disabilities and can provide valuable new insights into the relationships between HRQOL and risk factors. We found that those with functional limitations reported more physically and mentally unhealthy days than did those without functional limitations.[
Functional Limitation: Aged 50-64 Years, Weighted % (95% CI) Functional Limitation: Aged ≥65 Years, Weighted % (95% CI) No Functional Limitation: Aged 50-64 Years, Weighted % (95% CI) No Functional Limitation: Aged ≥65 Years, Weighted % (95% CI) Covariates Medical care cost issues 23.3 (22.4, 24.2) 6.5 (6.0, 7.1) 9.6 (9.2, 10.0) 2.9 (2.7, 3.3) Current smoker 25.4 (24.6, 26.3) 9.2 (8.6, 9.7) 15.3 (14.8, 15.7) 7.8 (7.5, 8.2) Leisure-time physical activity 59.3 (58.3, 60.3) 54.4 (53.5, 55.3) 80.0 (79.5, 80.6) 75.9 (75.3, 76.5) HRQOL outcomes Physically unhealthy days 12.1 (11.8, 12.3) 10.6 (10.3, 10.8) 1.8 (1.7, 2.0) 2.5 (2.3, 2.6) Mentally unhealthy days 7.7 (7.5, 8.0) 3.6 (3.5, 3.8) 2.2 (2.1, 2.3) 1.3 (1.2, 1.4) No physically unhealthy days 30.5 (29.6, 31.4) 38.9 (38.1, 39.8) 74.4 (73.8, 75.0) 75.2 (74.6, 75.8) No mentally unhealthy days 49.5 (48.5, 50.4) 71.7 (70.9, 72.5) 75.1 (74.5, 75.7) 85.5 (85.0, 86.0) Note. BRFSS= Behavioral Risk Factor Surveillance System; CI = confidence interval; HRQOL= health-related quality of life. In the multivariate models, we found that medical care cost issues, smoking, and leisure- time physical activity resulted in large significant effects on both physically and mentally unhealthy days among those with functional limitations and that the absolute magnitude of these effects exceeded those of individuals without functional limitations. These results highlight important factors to consider intervening on and the potential benefits of targeting individuals with disabilities for these programs. In terms of medical care cost issues, 23% of individuals with functional limitations aged 50 to 64 years reported being unable to see a physician because of cost. This is a significant health disparity in which those individuals who are in the greatest need of health care services are also the most likely to report cost issues. Furthermore, the large significant effects of medical care cost issues on both physically and mentally unhealthy days suggests that low- cost medical services (sometimes provided by Medicare and Medicaid) are often unavailable for individuals aged 50 to 64 years and that the resulting lack of affordable health care has significant effects on HRQOL. To increase leisure-time physical activity among older adults, public health agencies need to continue implementing effective policies and practices that promote physical activity, including decision prompts, community campaigns, social support in community settings, and community deliverable exercise programs.[ Finally, there were large significant effects of smoking on HRQOL for individuals with functional limitations. In addition, we showed that substantially more individuals aged 50 to 64 years with functional limitations report current smoking relative to comparably aged persons without functional limitations. Therefore, targeted smoking cessation programs and tobacco prevention policies should be explored to determine whether these efforts can efficiently reduce these large health disparities.[ This study has several limitations. First, because BRFSS is a survey derived predominantly from residential telephone owners and includes only noninstitutionalized adults, it may underrepresent those with more severe functional limitations who may have worse HRQOL. BRFSS may also underrepresent low-income individuals and those with cell phones but not landlines. Moreover, given the cross-sectional nature of the BRFSS data, it is difficult to determine causality. We have modeled the relationship between leisure- time physical activity and HRQOL in a unidirectional manner using linear regression models. Several longitudinal studies have supported this interpretation related to the impact of changes in physical activity on HRQOL outcomes,[
Variables Physically Unhealthy Days Model: Functional Limitation, b (P) Physically Unhealthy Days Model: No Functional Limitation, b (P) Mentally Unhealthy Days Model: Functional Limitation, b (P) Mentally Unhealthy Days Model: No Functional Limitation, b (P) Intercept 10.66 (< .001) 1.51 (< .001) 6.94 (<.001) 2.62 (<.001) Male gender -0.05* -0.26 (<.001) -0.86 (<.001) -0.70 (<.001) Race/ethnicity White non-Hispanic (Ref) 1.00 1.00 1.00 1.00 Black non-Hispanic -0.08* 0.27* -0.19* -0.13* Hispanic 0.61* 0.92 (<.001) 0.48* 0.17* Other 0.70* 0.54 (.018) 0.47* 0.21* Educational level < high school graduate 0.75 (.013) 1.28 (< .001) 0.66 (.014) 0.51 (.002) High school graduate or GED (Ref) 1.00 1.00 1.00 1.00 ≥some college -0.99 (< .001) -0.27 (<.001) -0.06* 0.01* Annual household income, $ <25 000 2.95 (< .001) 0.94 (<.001) 1.69 (<.001) 0.42 (<.001) 25 000-74 999 (Ref) 1.00 1.00 1.00 1.00 ≥75 000 -1.78 (<.001) -0.25 (<.001) -1.44 (<.001) -0.25 (<.001) Marital status Currently married (Ref) 1.00 1.00 1.00 1.00 Separated, divorced, or widowed -0.34* -0.01* 0.33 (.038) 0.37 (<.001) Never married or unmarried couple -0.22* 0.23* 0.22* 0.34 (.006) Aged ≥65 y -1.87 (<.001) 0.28 (<.001) -3.64 (<.001) -0.86 (<.001) Health care access Has any health care coverage 1.04 (.006) 0.31 (.034) 0.00* -0.23* Has a regular health care provider 1.20 (.002) 0.46 (<.001) 0.35* 0.11* Medical care cost issues 2.67 (<.001) 1.94 (<.001) 3.49 (<.001) 2.68 (<.001) Health care utilization Routine checkup in past y 1.00 (< .001) 0.41 (<.001) 0.01* 0.01* Had flu shot or spray in past y 0.63 (< .001) 0.23 (<.001) 0.20* 0.04* Modifiable health behaviors Current cigarette smoker 1.46 (<.001) 0.08* 2.35 (<.001) 0.81 (<.001) Ate ≥5 fruits and vegetables per d 0.43 (.026) -0.06* -0.18* -0.25 (<.001) Leisure-time physical activity in last mo -5.28 (<.001) -1.11 (<.001) -1.98 (<.001) -0.49 (<.001) Note. BRFSS=Behavioral Risk Factor Surveillance System; GED=general equivalency diploma. *Not significant. Individuals with disabilities represent a considerable proportion of the community, and the results of this study highlight that these individuals may differentially benefit from targeted public health policies, programs, and interventions. According to the results of this study as well as previous studies, there are several options for priority public health action. These include ( People with disabilities represent a vast proportion of individuals in the population who public health is intended to benefit. They experience a number of health-related problems that are potentially amenable to public health interventions. Further, people with disabilities are a highly disadvantaged group that are often subject to negative social environments and may have limited access to social support; as such, they should be a priority population for public health efforts. Furthermore, because of the potential for growing financial costs associated with the projected increase in burdens, identifying means to improve the health of aging populations may prove to be a cost-effective solution as well as a meaningful step in improving the quality of life for older adults. Reprints can be ordered at This article was accepted September 15, 2011. This article was prepared for the CDC series on aging and the roles of public health. The work presented in this article was funded solely by the US Centers for Disease Control and Prevention (CDC).
Note. The findings and conclusions in this study are those of the authors and do not necessarily represent the views of the CDC. This study was a secondary analysis of anonymous, publically available data, and institutional review board approval was not required. By William W. Thompson, PhD; Matthew M. Zack, MD, MPH; Gloria L. Krahn, PhD; Elena M. Andresen, PhD and John P. Barile, PhD At the time of the study, William W. Thompson, PhD was with the Division of Adult and Community Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention (CDC), 4770 Buford Highway NE, MSK-51, Atlanta, GA 30341 (e-mail: wct2@cdc.gov). Matthew At. Zack was with the Division of Adult and Community Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention (CDC), Atlanta. GA. Gloria L. Krahn was with the Division of Human Development and Disability, National Center for Birth Defects and Developmental Disabilities, CDC. Elena M. Andresen was with the Department of Epidemiology and Biostatistics, University of Florida, Gainesville. John P. Barile was with the Division of Adult and Community Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention (CDC), Atlanta. GA.