The role of unhealthy behaviors on an individual’s self-reported perceived health status. (English) Zbl 1393.62133

Summary: Many health plans and employers gather information about their enrollees in the form of self-reported surveys. This information is useful in assessing the risk pool of the population, targeting disease or case management programs to affected personnel, and developing/assessing wellness/incentive programs to lower medical costs and improve quality of life. The purpose of our study is to explore the role of individual-level unhealthy behaviors in influencing self-reported perceived health status. We extend prior research to estimate the effects of unhealthy behaviors on subsequent perceived health status using longitudinal data for the noninstitutional civilian adult population in the United States. We link data from two sources, the National Health Interview Survey (NHIS) and the longitudinal form of the Medical Expenditure Panel Survey (MEPS). Both the NHIS and MEPS data were collected using a complex survey design, enabling our results to be representative of the U.S. noninstitutionalized civilian population. We find that an increase in the number of unhealthy behaviors reduces the likelihood of individuals perceiving their health status as Excellent. In contrast, the likelihood of individuals perceiving their health status as Poor increases as the number of unhealthy behaviors increases, with a more pronounced effect for individuals with medically diagnosed conditions or perceived functional limitations.


62P25 Applications of statistics to social sciences


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[1] Aday, L. A.; Andersen, R., A framework for the study of access to medical care, Health Services Research, 9, 3, 208-220, (1974)
[2] Agresti, A., Tutorial on modeling ordered categorical response data, Psychological Bulletin, 105, 2, 290-301, (1989)
[3] Agresti, A., Analysis of Ordinal Categorical Data, (2010), John Wiley & Sons, Hoboken, NJ · Zbl 1263.62007
[4] Anand, P; Kunnumakara, A. B.; Sundaram, C.; Harikumar, K. B.; Tharakan, S. T.; Lai, O. S.; Sung, B.; Aggarwal, B. B., Cancer Is a preventable disease that requires major lifestyle changes, Pharmaceutical Research, 25, 9, 2097-2116, (2008)
[5] Ananth, C. V.; Kleinbaum, D. G., Regression models for ordinal responses: A review of methods and applications, International Journal of Epidemiology, 26, 6, 1323-1333, (1997)
[6] Andersen, R. M., A behavioral model of families’ use of health services, Research Series, 25, (1968), Center for Health Administration Studies, University of Chicago Press, Chicago
[7] Andersen, R. M., Revisiting the behavioral model and access to medical care: does it matter?, Journal of Health and Social Behavior, 36, 1, 1-10, (1995)
[8] Andersen, R. M.; Davidson, P. L., Changing the US Health Care System: Key Issues in Health Services Policy and Management, Improving access to care in America, 3-31, (2007), Jossey-Bass, San Francisco
[9] Anderson, J. A., Regression and ord ered categorical variables, Journal of the Royal Statistical Society Series B (Methodological), 46, 1, 1-30, (1984)
[10] Arcury, T. A.; Gesler, W. M.; Preisser, J. S.; Sherman, J.; Spencer, J.; Perin, J., The effects of geography and spatial behavior on health care utilization among the residents of a rural region, Health Services Research, 40, 1, 135-156, (2005)
[11] Armstrong, B. G.; Sloan, M., Ordinal regression models for epidemiologic data, American Journal of Epidemiology, 129, 1, 191-204, (1989)
[12] Babitsch, B.; Gohl, D.; von Lengerke, T., Re-revisiting Andersen’s behavioral model of health services use: A systematic review of studies from 1998–2011, GMS Psycho Social Medicine, 1-15, (2012)
[13] Bailis, D. S.; Segall, A.; Chipperfield, J. G., Two views of self-rated general health status, Social Science & Medicine, 56, 2, 203-217, (2003)
[14] Battaglia, M. P.; Hoaglin, D. C.; Frankel, M. R., Practical considerations in raking survey data, Survey Practice, 2, 5, 1-10, (2009)
[15] Bender, R.; Grouven, U., Ordinal logistic regression in medical research, Journal of the Royal College of Physicians of London, 31, 5, 546-551, (1997)
[16] Brant, R., Assessing proportionality in the proportional odds model for ordinal logistic regression, Biometrics, 46, 4, 1171-1178, (1990)
[17] Burge, F. I.; Lawson, B. J.; Johnston, G. M.; Grunfeld, E., A population-based study of age inequalities in access to palliative care among cancer patients, Medical Care, 46, 12, 1203-1211, (2008)
[18] Chou, S.-Y.; Grossman, M.; Saffer, H., An economic analysis of adult obesity: results from the behavioral risk factor surveillance system, Journal of Health Economics, 23, 3, 565-587, (2004)
[19] Cockerham, W. C.; Sharp, K.; Wilcox, J. A., Aging and perceived health status, Journal of Gerontology, 38, 3, 349-355, (1983)
[20] Cohen, S. B., Agency for Healthcare Research and Quality Working Paper No. 11002, An estimation methodology to permit longitudinal cohort analyses based on the national health interview survey and medical expenditure panel survey, (2010), Rockville, MD
[21] Conner, M.; Norman, P., Predicting Health Behaviour: Research and Practice with Social Cognition Models, (2005), Open University Press, Buckingham, England
[22] Contoyannis, P.; Jones, A. M., Socio-economic status, health and lifestyle, Journal of Health Economics, 23, 5, 965-995, (2004)
[23] Cutler, D.; Glaeser, E., What explains differences in smoking, drinking and other health-related behaviors, American Economic Review, 95, 2, 238-242, (2005)
[24] DeMaris, A., Regression with Social Data: Modeling Continuous and Limited Response Variables, (2004), John Wiley & Sons, Hoboken, NJ · Zbl 1136.62411
[25] Deri, C., Social networks and health service utilization, Journal of Health Economics, 24, 6, 1076-1107, (2005)
[26] DeSalvo, K. B.; Bloser, N.; Reynolds, K.; He, J.; Muntner, P., Mortality prediction with a single general self-rated health question, Journal of General Internal Medicine, 21, 3, 267-275, (2006)
[27] DeSalvo, K. B.; Jones, T. M.; Peabody, J.; McDonald, J.; Fihn, S.; Fan, V.; He, J.; Muntner, P., Health care expenditure prediction with a single item, self-rated health measure, Medical Care, 47, 4, 440-447, (2009)
[28] DeSalvo, K. B.; Fan, V. S.; McDonell, M. B.; Fihn, S. D., Predicting mortality and healthcare utilization with a single question, Health Services Research, 40, 4, 1234-1246, (2005)
[29] DeSalvo, K. B.; Fisher, W. P.; Tran, K.; Bloser, N.; Merrill, W.; Peabody, J., Assessing measurement properties of two single-item general health measures, Quality of Life Research, 15, 2, 191-201, (2006)
[30] Fasoli, D. R.; Glickman, M. E.; Eisen, S. V., Predisposing characteristics, enabling resources and need as predictors of utilization and clinical outcomes for veterans receiving mental health services, Medical Care, 48, 4, 288-295, (2010)
[31] Fleishman, J. A.; Cohen, J. W., Using information on clinical conditions to predict high-cost patients, Health Services Research, 45, 2, 532-552, (2010)
[32] Fleishman, J.A.; Cohen, J. W.; Manning, W. G.; Kosinski, M., Using the SF-12 health status measure to improve predictions of medical expenditures, Medical Care, 44, 5, I54-I63, (2006)
[33] Gruber, J.; Frakes, M., Does falling smoking lead to rising obesity?, Journal of Health Economics, 25, 2, 183-197, (2006)
[34] Guimarães, J. M. N.; Chor, D.; Werneck, G. L.; Carvalho, M. S.; Coeli, C. M.; Lopes, C. S.; Faerstein, E., Association between self-rated health and mortality: 10 years follow-up to the pró-saúde cohort study, BMC Public Health, 12, 676, (2012)
[35] Harris, K. M.; Edlund, M. J.; Larson, S., Racial and ethnic differences in the mental health problems and use of mental health care, Medical Care, 43, 8, 775-784, (2005)
[36] Idler, E. L., Age differences in self–assessments of health: age changes, cohort differences, or survivorship?, Journal of Gerontology, 48, 6, S289-S300, (1993)
[37] Idler, E. L.; Benyamini, Y., Self-rated health and mortality: A review of twenty-seven community studies, Journal of Health and Social Behavior, 38, 1, 21-37, (1997)
[38] Jylhä, M., What Is self-rated health and why does it predict mortality? towards a unified conceptual model, Social Science & Medicine, 69, 3, 307-316, (2009)
[39] Kenkel, D. S., Should you eat breakfast? estimates from health production functions, Health Economics, 4, 1, 15-29, (1995)
[40] Kolenikov, S., Calibrating survey data using iterative proportional Fitting (raking), Stata Journal, 14, 1, 22-59, (2014)
[41] Lebrun-Harris, L. A.; Baggett, T. P.; Jenkins, D. M.; Sripipatana, A.; Sharma, R.; Seiji Hayashi, A.; Daly, C. A.; Ngo-Metzger, Q., Health status and health care experiences among homeless patients in federally supported health centers: findings from the 2009 patient survey, Health Services Research, 48, 3, 992-1017, (2013)
[42] Li, C.; Ford, E. S.; Mokdad, A. H.; Balluz, L. S.; Brown, D. W.; Giles, W. H., Clustering of cardiovascular disease risk factors and health-related quality of life among US adults, Value in Health, 11, 4, 689-699, (2008)
[43] Machlin, S. R.; Chowdhury, S. R.; Ezzati-Rice, T.; DiGaetano, R.; Goksel, H.; Wun, L.-M.; Yu, W.; Kashihara, D., Methodology report # 24: estimation procedures for the medical expenditure panel survey household component. agency of healthcare research and quality, (2010), Rockville, MD
[44] Manderbacka, K.; Lundberg, O.; Martikainen, P., Do risk factors and health behaviours contribute to self-ratings of health?, Social Science & Medicine, 48, 12, 1713-1720, (1999)
[45] Maurer, J., Assessing horizontal equity in medication treatment among elderly mexicans: which socioeconomic determinants matter most?, Health Economics, 17, 10, 1153-1169, (2008)
[46] McCullagh, P., Regression models for ordinal data, Journal of the Royal Statistical Society Series B (Methodological), 42, 2, 109-142, (1980) · Zbl 0483.62056
[47] McHugh, J. E.; Lawlor, B. A., Perceived health status Is associated with hours of exercise per week in older adults independent of physical health, Journal of Physical Activity & Health, 10, 8, 1102-1108, (2013)
[48] Mokdad, A. H.; Marks, J. S.; Stroup, D. F.; Gerberding, J. L., Actual causes of death in the united states, 2000, JAMA, 291, 10, 1238-1245, (2004)
[49] Peterson, B.; Harrell Jr, F. E., Partial proportional odds models for ordinal response variables, Applied Statistics, 39, 2, 205-217, (1990) · Zbl 0707.62154
[50] Pisinger, C.; Toft, U.; Aadahl, M.; Glümer, C.; Jørgensen, T., The relationship between lifestyle and self-reported health in a general population, Preventive Medicine, 49, 5, 418-423, (2009)
[51] Schoenborn, C. A.; Benson, V., Relationships between Smoking and Other Unhealthy Habits: United States, 1985, (1988), National Center for Health Statistics, Hyattsville, MD
[52] Singh-Manoux, A.; Guéguen, A.; Martikainen, P.; Ferrie, J.; Marmot, M.; Shipley, M., Self-rated health and mortality: short- and long-term associations in the whitehall II study, Psychosomatic Medicine, 69, 2, 138-143, (2007)
[53] Snell, E. J., A scaling procedure for ordered categorical data, Biometrics, 20, 3, 592-607, (1964) · Zbl 0126.16501
[54] Tsai, J.; Ford, E. S.; Li, C.; Zhao, G.; Pearson, W. S.; Balluz, L. S., Multiple healthy behaviors and optimal self-rated health: findings from the 2007 behavioral risk factor surveillance system survey, Preventive Medicine, 51, 3-4, 268-274, (2010)
[55] Walker, S. H.; Duncan, D. B., Estimation of the probability of an event as a function of several independent variables, Biometrika, 54, 1-2, 167-179, (1967) · Zbl 0159.47604
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.