Effect of obesity on health-related quality of life among Appalachian elderly. (Original Article).

Background: There is a paucity of research on health behaviors, health status, and overall health-related quality of life among Appalachian elderly. Identifying factors among older adults that place them at risk for low health-related quality of life is important for targeting unmet health needs and guiding community efforts to help improve population health.

Methods: For this study, we examined the relationship between obesity and health-related quality of life among Appalachians aged 65 years or older using the 2000 Behavioral Risk Factor Surveillance Survey data.

Results: Our results showed that obese elderly Appalachians report poorer self-rated health and more days of poor physical health compared with their nonobese counterparts.

Conclusion: The goals put forward in Healthy People 2010 include the reduction of obesity and enhancement of quality of life. If such health disparities are to be eliminated and quality of life enhanced, a sustained effort to identify their determinants among Appalachian elderly is needed.

Key Words: aged, Appalachia, elderly, health-related quality of life, obesity

**********

Appalachia has received media attention regarding the increasing prevalence of obesity and physical inactivity in its population. In West Virginia, the only state that is entirely within Appalachia, 17% of the state's adult population was obese in 1990, and in 2000 this statistic increased to almost 23%. (1) A key objective of Healthy People 2010 is to reduce the proportion of obese adults, primarily because obesity is a risk factor for 4 of the 10 leading causes of death in the United States: coronary heart disease, diabetes mellitus, stroke, and cancer. (2,3) The societal costs of obesity are substantial, and growing. In 1995, costs attributed to obesity were estimated to be $99 billion; in 2000, $117 billion. (2,4) As a result of direct and indirect effects on health, quality of life, and economic burden, obesity is considered one of the major public health epidemics of the 21st century.

There is a paucity of research on the health behaviors, health status, and the overall health-related quality of life (HRQoL) of older adults in Appalachia. Identifying factors among older adults that place them at risk for low HRQoL is important for targeting unmet health needs and guiding broad community efforts to help improve population health. (5) Obesity is believed to have a negative impact on HRQoL. Previotis studies have shown that obese adults have lower scores on measures of HRQoL. (6-9) Obese persons are more likely to rate their health as poor. (10,11) In addition, they report more chronic conditions, lower levels of functional health, more days ill in bed, and are more likely to suffer from at least one serious illness. (10)

The relationship between obesity and ERQoL is more complex when considering studies of older adults, who generally have more health problems than young adults. (12) Among older adults, scores on self-reported quality-of-life measures indicate that as weight increases, quality of life decreases. (13) The functional and psychosocial consequences of obesity may also be amplified by the coexistence of normal age-related declines. (14) In terms of functional health, with increasing age, obese individuals have been found to be more likely to report functional limitation, specifically limitations in performing basic activities of daily living. (9,15-21) In addition, obesity may lead an older adult to withdraw from normal activities and become more dependent on others for assistance with activities of daily living. Declining functional ability, social withdrawal, and increased dependence might be considered the indirect effects of obesity. (14)

In Appalachia, the number of older adults is increasing, and higher percentages of the older population are considered obese. (22,23) It is imperative to fully understand how to best accommodate the health care-related needs of this growing segment of the population. For the present study, we examined the relationship between obesity and HRQoL among Appalachians aged 65 years or older. This research will provide valuable insight into the relationship between HRQoL and its risk factors among older Appalachians and identify subgroups with relatively poor perceived health. Information gained from this analysis could help guide interventions and allocate resources based on unmet needs and health disparities.

Methods

Setting

Appalachia has historically been considered a distinct region of the United States. According to the Appalachian Regional Commission, 410 counties have been officially designated as Appalachian, including all of West Virginia and parts of Alabama, Georgia, Kentucky, Maryland, Mississippi, New York, North Carolina, Ohio, Pennsylvania, South Carolina, Tennessee, and Virginia. The Appalachian region has a total area of approximately 200,000 square miles, with more than 22 million residents. The region is predominantly rural, with 32% of its population residing in rural counties compared with 15% of the total U.S. population. (24) Appalachia is characterized by high rates of poverty, low levels of educational attainment, relatively poor health and health-related behaviors, (24,25) and a higher percentage of older adults compared with the rest of the country. (22)

Sample

We used the 2000 Behavioral Risk Factor Surveillance System (BRFSS) for this secondary data analysis. The BRFSS was designed by the Centers for Disease Control and Prevention to collect uniform, state-specific data on health status, preventive health practices, and risk behaviors that are linked to chronic diseases, injuries, and infectious diseases in the adult population. A telephone survey is used to collect data from a random sample of adults (one per household). These data measure health conditions and behaviors over time, enabling states to monitor progress toward the reduction of risk factors by providing ongoing surveillance. For this analysis, we used data from persons at least 65 years old from the 410 counties that constitute Appalachia.

Measures

HRQoL, our dependent variable, refers to the physical, emotional, and social impact of health conditions. (26-29) HRQoL, which has been operationalized in the BRFSS since 1993, uses the following four items: 1) self-rated health on a five-point scale from excellent to poor; 2) number of days (during the past 30) that physical health was not good; 3) number of days (during the past 30) that mental health was not good; and 4) number of days (during the past 30) that poor physical or mental health interfered with usual activities. (5,30,31) The first item measures overall self-rated health; the second item is a measure of recent physical symptoms; the third is a measure of recent mental and emotional distress; and the fourth is an indicator of perceived disability as well as productivity and human capital. The latter three items are frequently referred to as "Healthy Days" measures. (5)

Our independent variable, obesity, was defined according to national guidelines for a body mass index (self-reported weight in kilograms divided by self-reported height in meters squared) of 30 kg/[m.sup.2] or more. (32) The body mass index, which expresses the relationship of weight to height, is used to screen and monitor the risk of obesity. Body mass index is considered a useful tool for clinical and research purposes and has been applied widely in population studies to estimate obesity. (14)

Data Analysis

Initial descriptive and bivariate analyses examined percentages and 95% confidence intervals of demographic and HRQoL characteristics by obesity. Statistical testing and estimation of the association between obesity and each of the four HRQoL items were conducted by linear regression and adjusted for age, sex, race, marital status, and education. Adjusted proportions and means were obtained for each HRQoL item by obesity. All analyses were conducted with SUDAAN software version 7.5.6 (Research Triangle Institute, Research Triangle Park, NC) to account for the complex survey design. (33)

Results

Analyses were conducted on 1,542 adults 65 years of age or older, of which 20.6% (n = 318) were obese. Table 1 presents descriptive statistics and information on the demographics of the sample providing the frequencies and 95% confidence intervals. The obese respondents were significantly younger than the nonobese sample, with a mean age of 72 versus 74 years, respectively ([chi square] = 42.0, P [less than or equal to] 0.001). Males represented a smaller percentage of obese respondents than the nonobese (31.5 vs. 40.6%, [chi square] = 3.9, P [less than or equal to] 0.05), and the obese had significantly lower levels of educational attainment ([chi square] = 9.7, P [less than or equal to] 0.05) than the nonobese. There was no significant difference in marital status by obesity. Although the groups differed on race ([chi square] = 8.5, P [less than or equal to] 0.01), it is important to note that the nonwhite sample was relatively small (n = 82).

Table 2 shows the bivariate relationship between HRQoL and obesity among Appalachian elderly. A [chi square] test revealed that a significantly larger percent of the obese sample reported fair ([chi square] 10.4, P [less than or equal to]0.001) or poor ([chi square] 3.6, P [less than or equal to] 0.05) self-rated health compared with their nonobese counterparts. Approximately 47% of the obese sample, compared with 28% of the nonobese sample, reported fair or poor health. Under the Healthy Days items, a t test revealed that the number of poor physical health days was significantly greater among the obese sample compared with the nonobese sample (8.1 versus 5.2 days, t = 2.7 P [less than or equal to] 0.01). There were no significant differences between the obese and nonobese respondents on number of poor mental health days and the number of days in which poor physical or mental health interfered with usual activities.

Figure 1 presents the adjusted proportions for self-rated health by obesity. Multivariate ordinary least-squares analysis adjusted for age, sex, race, marital status, and education revealed that obese respondents were significantly more likely to report poorer self-rated health compared with their nonobese counterparts (P [less than or equal to] 0.001). Among the obese respondents, 39.2% reported fair or poor health compared with 29.4% of the nonobese respondents.

Figure 2 shows the adjusted means of the three Healthy Days items by obesity. Multivariate ordinary least-squares analyses adjusted for age, sex, race, marital status, and education showed that obese respondents were more likely to report more days of poor physical health compared with nonobese (7.8 versus 5.3 days, P [less than or equal to]0.05). There were no significant differences between the obese and nonobese respondents on the number of poor mental health days or on the number of days in which poor physical or mental health interfered with usual activities.

Discussion

The results of this study indicate that among Appalachian elderly, obese individuals report poorer self-rated health and more days in which their physical health was poor compared with their nonobese counterparts. On the other two measures of HRQoL, number of poor mental health days and number of days that poor physical or mental health interfered with usual activities, no significant group differences were detected. Appropriate interpretation of the results will require that each of the four HRQoL items be considered separately, with the assumption that obesity relates to each of the items in different ways.

The first measure, self-reported health, provides subjective information and is one of the best indicators of health status and medical care use. Self-rated health has also been found to be related to mortality, morbidity, and functional status. (34-37) The finding that obese respondents are more likely to rate their health as poor is consistent with the results of previous studies. (6,10,11) It has been suggested that the condition of obesity is important in shaping negative health appraisals. This may be related to obese individuals being more pessimistic, given the widely recognized health risks as a result of excess body weight. (10)

Obesity has been found to have an effect on physical health in previous research, so it is not surprising that a relationship was detected between obesity and more reported days of poor physical health. Our results support previous studies that have used similar subjective indicators of physical health status and have detected a negative relationship with regard to obesity. (7-9,11)

A significant relationship between obesity and an increase in days of poor mental health was not found in this analysis. There is little evidence that obese older adults experience more nonphysical problems, such as adverse mental health, than their nonobese counterparts. (9) Results from other studies indicate that whereas obesity is associated with the physical dimensions of HRQoL, it has a minor (8) or undetectable effect on mental health status. (7,38,39) However, depression is a common psychological condition found in obese individuals. (14) It is possible that the measure of mental health used in this study did not capture the indirect effects of obesity on specific components of mental health.

Our study revealed no relationship between obesity and an increase in the number of days in which poor mental or physical health interfered with usual activities. Initially, this finding did not support the many studies that have documented a relationship between obesity and limited functional abilities among the elderly. (10,15-21) However, a possible explanation is that this particular item may not be an adequate measure of functional limitation in obese subjects. The question asks whether the individual's health interferes with their usual activities, not whether poor health interferes with the activities they may engage in if they were not obese. Because a sedentary lifestyle is a strong contributing factor to obesity, (14) it is possible that the usual activities of an obese individual are also sedentary in nature.

Obesity is a physical chronic health condition that has reached epidemic proportions in the United States. It is now widely acknowledged that the personal burden of chronic conditions or disease cannot be fully described by objective measures of health conditions. Psychosocial factors such as functional impairments, difficulty fulfilling personal and family responsibilities, and mental health must also be taken into consideration. HRQoL moves beyond direct manifestations of conditions to study a patient's personal morbidity, probing the various effects that conditions have on daily life and life satisfaction. (40)

Certain limitations of this study need to be acknowledged. One is that the BRFSS relies on data from telephone interviews, which excludes data from persons without telephones. According to the U.S. Census, 5% of the U.S. population did not have a telephone in 1990. Yet, the U.S. Census also found that the older the householder, the smaller the chances were of lacking a telephone. (41) Although we cannot be certain of the extent to which the lack of a telephone affected our findings, it is important to keep this in mind when generalizing the results to Appalachian elderly. In addition, previous research has found that self-reports of weight and height, components of the body mass index, do not necessarily reflect more objective measures. (42) Because of the self-report of the data used for this study, and the tendency to underreport weight and overreport height, it is likely that our estimate of obese elderly Appalachians is conservative.

As medical advances lead to cures and better treatments of diseases and delaying mortality, it is also important that those who measure health outcomes assess a population's health not only in terms of saving lives, but also in terms of improving them. Obesity can place a particularly heavy burden because it contributes to long-term illness, diminishes quality of life, and increases health-care costs. (2-4) Because obesity is the second leading cause of preventable death, it is important for health-care practitioners to subscribe to the clinical guidelines for the management of obesity put forth in 1998 by the National Institutes of Health.

Measuring HRQoL can assist in determining the burden of preventable chronic conditions such as obesity, and it can provide insights into the refationships between HRQoL and risk factors. Three decades of research have shown that global assessments of health are among the best predictors of wellbeing, health status, and medical care use. 10,43,44 HRQoL is an important public health tool for the elderly in a time when life expectancy is increasing, with the goal of improving the extra years in spite of the cumulative health effects associated with normal aging and pathologic disease processes. Although the risk of many chronic diseases and disability increases with advancing age, poor HRQoL is not an inevitable consequence of aging. Unfortunately, however, the prevalence and burden of obesity is rising among the elderly." (1, 13) Despite previous calls for action, (2,45,46) it is likely to continue to increase in the years ahead unless effective interventions are implemented.

In conclusion, the goals of increasing the span of healthy life and elimination of health disparities for Americans put forward in Healthy People 2010 include not only prevention and reduction of obesity but also enhancement of quality of life. This work has revealed that obesity has a negative impact on some aspects of HRQoL among Appalachian elderly. Additional research with other data sets needs to be conducted to replicate this study and assess whether similar relationships are found. This work will contribute to the new public health emphasis on examining and eliminating health disparities. However, increasing the amount of comprehensive and reliable research on the Appalachian elderly population has policy and programming implications. Such work will contribute to the new public health emphasis on identifying and eliminating health disparities, and could have important implications for addressing the health needs of the growing elderly population.

[FIGURE 1 OMITTED]

[FIGURE 2 OMITTED]

Table 1

Demographic characteristics by obesity among Appalachian elderly (n =
1,542)

                                   Obese                 Nonobese
                             %       95% CI (d)     %       95% CI

Age (a)
 65-74 years               83.4      78.5-88.2    60.7     56.7-64.7
 75-84 years               13.1       9.2-17.1    34.3     30.4-38.3
 85 years or older          3.6       0.6-6.5      5.0      3.4-6.5
Male(c)                    31.5      23.4-39.6    40.6     36.5-44.6
Race (b)
 White                     87.2      82.2-92.1    94.8     93.1-96.5
 Nonwhite                  12.8       7.9-17.8     5.2      3.5-6.9
Marital status
 Currently married         51.1      42.5-59.6    59.4     55.5-63.2
 Widowed                   37.0      28.9-45.0    31.5     28.0-35.0
 Other                     12.0       6.8-17.2     9.1     7.1-11.2
Education (c)
 None-some high school     38.3      30.4-47.3    25.2     22.0-28.4
 High school graduate      31.9      23.8-40.1    37.9     33.9-42.0
 Some college/technical    14.9       9.7-20.1    20.8     17.2-24.3
 school
 College graduate or more  14.4       8.3-20.5    16.2     13.2-19.1

(a)P [less than or equal to]0.001.

(b)P [less than or equal to] 0.01

(c)P [less than or equal to] 0.05.

(d)95% confidence interval.

Table 2

Health-related quality of life by obesity among Appalachian elderly

Self-rated health (%)

                                                 Obese
                                       %      Mean      95% CI (d)

 Excellent                            6.2               10.1-2.3
 Very good                           20.4               26.7-14.0
 Good                                26.8               34.5-19.1
 Fair (a)                            31.9               40.2-23.9
 Poor (c)                            14.7               20.9-8.5

How many days in the past 30...

 Physical health has been poor (b)            8.1       6.1-10.2
 Mental health has been poor                  2.8       1.5-4.1
 Physical or mental health                    3.9       2.4-5.3
 interfered with usual activities

                                                Nonobese
                                        %       Mean      95% CI

 Excellent                             11.4               14.1-8.9
 Very good                             26.9               30.6-23.2
 Good                                  33.5               37.4-29.6
 Fair (a)                              18.9               22.1-7.5
 Poor (c)                               9.4               11.2-7.5

How many days in the past 30...

 Physical health has been poor (b)              5.2       4.4-5.9
 Mental health has been poor                    1.9       1.5-2.3
 Physical or mental health                      2.5       2.0-2.9
 interfered with usual activities

(a)P [less than or equal to] 0.001.

(b)p [less than or equal to] 0.01.

(c)P [less than or equal to] 0.05.

(d)95% confidence intervals.

Accepted September 22, 2002.

References

(1.) Mokdad All. The continuing epidemics of obesity and diabetes in the United States. JAMA 2001;286:1195-1200.

(2.)U.S. Department of Health and Human Services. Healthy People 2010. Washington, DC, U.S. Government Printing Office, 2000.

(3.) Wolf AM. The economic impact of obesity: Building bridges with managed care, in Strategies for Weight Management: A Postgraduate Medicine Special Report. Minneapolis, MN, McGraw-Hill, 2001.

(4.) Center on an Aging Society. Childhood Obesity: A Lifelong Threat to Health (Data Profile No. 2). Washington, DC, Center on an Aging Society, Institute for Health Care Research and Policy, Georgetown University, 2002.

(5.) Centers for Disease Control and Prevention. Measuring Healthy Days: Population Assessment of Health-related Quality of Life. Atlanta, GA, Centers for Disease Control and Prevention, 2000.

(6.) Barofsky I, Fontaine KR, Cheskin LJ. Pain in the obese: Impact on health-related quality of life. Ann Behav Med 1997;19:408-410.

(7.) Finkelstein MM. Body mass index and quality of life in a survey of primary care patients. J Fam Pract 2000;49:734-737,

(8.) Marchesini G, Solaroli E, Baraldi L, Natale S, Migliorini S, Visani F, et al. Health-related quality of life in obesity: The role of eating behaviour. Diabetes Nutr Metab 2000;13:156-164.

(9.) Han TS, Tijhuis MA, Lean ME, Seidell JC. Quality of life in relation to overweight and body fat distribution. Am J Public Health 1998;88:1814-1820.

(10.) Ferraro KF, Yu Y. Body weight and self-ratings of health. J Health Soc Behav 1995;36:274-284.

(11.) Ramsey PW, Glenn LL. Obesity and health status in rural, urban, and suburban southern women. South Med J 2002;95:666-671.

(12.) National Center for Health Statistics. Health, United States, 2001. Special excerpt--Trend tables on 65 and older population. Hyattsville, MD, National Center for Health Statistics, Department of Health and Human Services, 2001.

(13.) Kolotkin RL, Head S, Hamilton M, Tse CK. Assessing impact of weight on quality of life. Obes Res 1995;3:49-56.

(14.) Jensen GL, Rogers J. Obesity in older persons. J Am Diet Assoc 1998;98:1308-1311.

(15.) Galanos AN, Pieper CF, Cornoni-Huntley JC, Bales CW, Fillenbaum GG. Nutrition and function: Is there a relationship between body mass index and functional capabilities of community-dwelling elderly? J Am Geriatr Soc 1994;42:368-374.

(16.) Hubert HB, Bloch DA, Fries CF. Risk factors for physical disability in an aging cohort: The NHANES I Epidemiological Follow-up Study. J Rheumatol 1993;20:480-488.

(17.) Launer LJ, Harris T, Rumpel C, Madans J. Body mass index, weight change, and risk of mobility disability in middle-aged and older women. The epidemiological follow-up study of NHANES I. JAMA 1994;271: 1093-1098.

(18.) Jordan JM, Luta G, Renner JB Linder GF, Dragomir A, Hochberg MC, et al. Self-reported functional status in osteoarthritis of the knee in a rural southern community: The role of sociodemographic factors, obesity, and knee pain. Arthritis Care Res 1996;9:273-278.

(19.) Sternfeld B, Ngo L, Satariano WA, Tager IB. Associations of body composition with physical performance and self-reported functional limitation in elderly men and women, Am J Epidemiol 2002;156:110-121.

(20.) Jensen GL, Friedmann JM. Obesity is associated with functional decline in community-dwelling rural older persons. J Am Geriatr Soc 2002;50:918-923.

(21.) Ferraro KF, Su YP, Gretebeck RI, Black DR, Badylak SF. Body mass index and disability in adulthood: A 20-year panel study. Am J Public Health 2002;92:834-840.

(22.) Barnett E, Elmes GA, Braham VE, Halverson JA, Lee JY, Loftus S. Heart Disease in Appalachia: An Atlas of County Economic Conditions, Mortality, and Medical Care Resources. Morgantown, WV, Prevention Research Center, West Virginia University, 1998.

(23.) West Virginia Department of Health and Human Resources. Prevalence of obesity: West Virginia Behavioral Risk Factor Survey 1993-1997 by County Compared to 1995 Estimated U.S. Prevalence. Charleston, WV, Bureau of Public Health, Health Statistics Center, 2000. Available at: http://www.wvdhhr.org/bph/oehp/atlas/obesity.Pdf. Accessed April 17, 2003.

(24.) West Virginia Department of Health and Human Resources. Health Risks: The Appalachian Lifestyle. Charleston, WV, Bureau for Public Health, Office of Epidemiology and Health Promotion, 1995.

(25.) Isserman AM. Appalachia then and now: An update of "The Realities of Deprivation" reported to the president in 1964. J Appalachian Studies 1997;3:3-42.

(26.) Fitzpatrick R, Fletcher A, Gore S, Jones D, Spiegelhalter D, Cox D. Quality of life measures in health care: Part I. Applications and issues in assessment. BMJ 1992;305:1074-1077.

(27.) Guyatt GH, Feeney DH, Patrick DL. Measuring health-related quality of life. Ann Intern Med 1993;118:622-629.

(28.) Hennessy CH, Moriarty DG, Zack MM, Scherr PA, Brackbill R. Measuring health-related quality of life for public health surveillance. Public Health Rep 1994;109:665-672.

(29.) Weinberger M, Nagle B, Hanlon JT, Samsa GP, Schmader K, Landsman PB, et al. Assessing health related quality of life in the elderly outpatients: Telephone versus face-to-face administration. J Am Geriatr Soc 1994;42: 1295-1299.

(30.) Newschaffer CJ. Final Report: Validation of Behavioral Risk Factor Surveillance System (BRFSS,) HRQOL Measures in a Statewide Sample. St. Louis, Prevention Research Center, St. Louis University School of Public Health, 1998.

(31.) Centers for Disease Control and Prevention. Quality of life as a new public health measure: Behavioral Risk Surveillance System, 1993. MMWR Morb Mortal Wkly Rep 1994;43:375-380.

(32.) National Heart, Lung, and Blood Institute, National Institutes of Health. Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults: Executive Summary. Bethesda, MD, National Institutes of Health, 1998.

(33. Shah BV, Barnwell BG, Bieler, GS. SUDAAN User's Manual, Release 7.5. Research Triangle Park, NC, Research Triangle Institute, 1997.

(34.) Hays JC, Schoenfeld DE, Blazer DG. Determinants of poor self-rated health in late life. Am J Geriatr Psychiatry 1996;4:188-l96.

(35.) Hays JC, Schoenfeld D, Blazer DG, Gold DT. Global self-ratings of health and mortality: Hazard in the North Carolina Piedmont. J Clin Epidemiol 1996;49:969-979.

(36.) Idler EL. Self-ratings of health: Mortality, morbidity, and meaning, in Schechter S (ed): Proceedings of the 1993 NCHS Conference on the Cognitive Aspects of Self-reported Health Status (NCHS Working Paper series, No. 10). Hyattsville, MD, National Center for Health Statistics, U.S. Centers for Disease Control and Prevention, U.S. Department of Health and Human Services, 1994, pp 36-59.

(37.) Idler EL, Russell LB, Davis D. Survival, functional limitations, and self-rated health in the NHANES I Epidemiologic Follow-up Study, 1992. First National Health and Nutrition Examination Survey. Am J Epidemiol 2000;152:874-883.

(38.) Balcombe NR, Ferry PG, Saweirs WM. Nutritional status and well being. Is there a relationship between body mass index and the well-being of older people? Curr Med Res Opin 2001;17:l-7.

(39.) Katz DA, McHomey CA, Atkinson RL. Impact of obesity on health-related quality of life in patients with chronic illness. J Gen Intern Med 2000;15:789-796.

(40.) Muldoon MF, Barger SD, Flory JD, Manuck SB. What are quality of life measurements measuring? BMJ 1998;316:542-545.

(41.) Bureau of the Census. Phoneless in America: Bureau of the Census Statistical Brief Washington, DC, Bureau of the Census, U.S. Department of Commerce, 1994.

(42.) Nawaz H, Chan W, Abdulrabman M, Larson D, Katz DL. Self-reported weight and height: Implications for obesity research. Am J Prey Med 2001;20:294-298.

(43.) Angel R, Gronfein W. The use of subjective information in statistical models. Am Sociol Rev 1988;53:464-473.

(44.) LaRue A, Bank L, Jarvik L, Hetland M. Health in old age: How do physicians' ratings and self-ratings compare? J Gerontol 1979;34:657-691.

(45.) Blair SN, Nichaman MZ. The public health problem of increasing prevalence rates of obesity and what should be done about it. Mayo Clin Proc 2002;77: 109-113.

(46.) Kumanyika S, Jeffery RW, Morabia A, Ritenbaugh C, Antipatis VJ; Public Health Approaches to the Prevention of Obesity (PHAPO) Working Group of the International Obesity Task Force (IOTF). Obesity prevention: The case for action. Int J Obes Relat Metab Disord 2002; 26:425-436.

RELATED ARTICLE: Key Points

* Obese Appalachian elderly reported poorer self-rated health compared with nonobese Appalachian elderly.

* Obese Appalachian elderly reported more days in the past 30 in which their physical health was poor compared with nonobese Appalachian elderly.

* No significant group differences were detected in the number of poor mental health days and number of days in the past 30 in which poor physical or mental health interfered with usual activities.

From the Center on Aging and Departments of Community Medicine and Psychology, West Virginia University, Morgantown, WV.

Reprint requests to R. Turner Goins, PhD, Center on Aging and Department of Community Medicine, west Virginia University, P.O. Box 9127, Margantawn, WV 26506. Email: [e-mail]

Copyright [c] 2003 by The Southern Medical Association 0038-4348/03/9606-0552