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Published in: Population Health Metrics 1/2017

Open Access 01-12-2017 | Research

Self-reported general health, physical distress, mental distress, and activity limitation by US county, 1995-2012

Authors: Laura Dwyer-Lindgren, Johan P. Mackenbach, Frank J. van Lenthe, Ali H. Mokdad

Published in: Population Health Metrics | Issue 1/2017

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Abstract

Background

Metrics based on self-reports of health status have been proposed for tracking population health and making comparisons among different populations. While these metrics have been used in the US to explore disparities by sex, race/ethnicity, and socioeconomic position, less is known about how self-reported health varies geographically. This study aimed to describe county-level trends in the prevalence of poor self-reported health and to assess the face validity of these estimates.

Methods

We applied validated small area estimation methods to Behavioral Risk Factor Surveillance System data to estimate annual county-level prevalence of four measures of poor self-reported health (low general health, frequent physical distress, frequent mental distress, and frequent activity limitation) from 1995 and 2012. We compared these measures of poor self-reported health to other population health indicators, including risk factor prevalence (smoking, physical inactivity, and obesity), chronic condition prevalence (hypertension and diabetes), and life expectancy.

Results

We found substantial geographic disparities in poor self-reported health. Counties in parts of South Dakota, eastern Kentucky and western West Virginia, along the Texas-Mexico border, along the southern half of the Mississippi river, and in southern Alabama generally experienced the highest levels of poor self-reported health. At the county level, there was a strong positive correlation among the four measures of poor self-reported health and between the prevalence of poor self-reported health and the prevalence of risk factors and chronic conditions. There was a strong negative correlation between prevalence of poor self-reported health and life expectancy. Nonetheless, counties with similar levels of poor self-reported health experienced life expectancies that varied by several years. Changes over time in life expectancy were only weakly correlated with changes in the prevalence of poor self-reported health.

Conclusions

This analysis adds to the growing body of literature documenting large geographic disparities in health outcomes in the United States. Health metrics based on self-reports of health status can and should be used to complement other measures of population health, such as life expectancy, to identify high need areas, efficiently allocate resources, and monitor geographic disparities.
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Literature
1.
go back to reference Murray CJL, Harvard Center for Population and Development Studies, Burden of Disease Unit, National Center for Chronic Disease Prevention and Health Promotion (U.S.). U.S. patterns of mortality by county and race: 1965-1994. Cambridge: Harvard Burden of Disease Unit, Harvard Center for Population and Development Studies ; National Center for Chronic Disease Prevention and Health Promotion, CDC; 1998. Murray CJL, Harvard Center for Population and Development Studies, Burden of Disease Unit, National Center for Chronic Disease Prevention and Health Promotion (U.S.). U.S. patterns of mortality by county and race: 1965-1994. Cambridge: Harvard Burden of Disease Unit, Harvard Center for Population and Development Studies ; National Center for Chronic Disease Prevention and Health Promotion, CDC; 1998.
2.
go back to reference Wang H, Dwyer-Lindgren L, Lofgren KT, Rajaratnam JK, Marcus JR, Levin-Rector A, et al. Age-specific and sex-specific mortality in 187 countries, 1970–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380:2071–94.CrossRefPubMed Wang H, Dwyer-Lindgren L, Lofgren KT, Rajaratnam JK, Marcus JR, Levin-Rector A, et al. Age-specific and sex-specific mortality in 187 countries, 1970–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380:2071–94.CrossRefPubMed
3.
go back to reference Murray CJL, Lopez AD, Harvard School of Public Health, World Health Organization, World Bank. The global burden of disease: a comprehensive assessment of mortality and disability from diseases, injuries, and risk factors in 1990 and projected to 2020 ; summary. Cambridge: Published by the Harvard School of Public Health on behalf of the World Health Organization and the World Bank : Distributed by Harvard University Press; 1996. Murray CJL, Lopez AD, Harvard School of Public Health, World Health Organization, World Bank. The global burden of disease: a comprehensive assessment of mortality and disability from diseases, injuries, and risk factors in 1990 and projected to 2020 ; summary. Cambridge: Published by the Harvard School of Public Health on behalf of the World Health Organization and the World Bank : Distributed by Harvard University Press; 1996.
5.
go back to reference Hennessy CH, Moriarty DG, Zack MM, Scherr PA, Brackbill R. Measuring health-related quality of life for public health surveillance. Public Health Rep. 1994;109:665–72.PubMedPubMedCentral Hennessy CH, Moriarty DG, Zack MM, Scherr PA, Brackbill R. Measuring health-related quality of life for public health surveillance. Public Health Rep. 1994;109:665–72.PubMedPubMedCentral
7.
go back to reference Mokdad AH. The Behavioral Risk Factors Surveillance System: past, present, and future. Annu Rev Public Health. 2009;30:43–54.CrossRefPubMed Mokdad AH. The Behavioral Risk Factors Surveillance System: past, present, and future. Annu Rev Public Health. 2009;30:43–54.CrossRefPubMed
9.
go back to reference Toet J, Raat H, van Ameijden EJ. Validation of the Dutch version of the CDC core healthy days measures in a community sample. Qual Life Res. 2006;15:179–84.CrossRefPubMed Toet J, Raat H, van Ameijden EJ. Validation of the Dutch version of the CDC core healthy days measures in a community sample. Qual Life Res. 2006;15:179–84.CrossRefPubMed
10.
go back to reference Brown DW, Balluz LS, Heath GW, Moriarty DG, Ford ES, Giles WH, et al. Associations between recommended levels of physical activity and health-related quality of life: findings from the 2001 Behavioral Risk Factor Surveillance System (BRFSS) survey. Prev Med. 2003;37:520–8.CrossRefPubMed Brown DW, Balluz LS, Heath GW, Moriarty DG, Ford ES, Giles WH, et al. Associations between recommended levels of physical activity and health-related quality of life: findings from the 2001 Behavioral Risk Factor Surveillance System (BRFSS) survey. Prev Med. 2003;37:520–8.CrossRefPubMed
11.
go back to reference Hassan MK, Joshi AV, Madhavan SS, Amonkar MM. Obesity and health-related quality of life: a cross-sectional analysis of the US population. Int J Obes (Lond). 2003;27:1227–32.CrossRef Hassan MK, Joshi AV, Madhavan SS, Amonkar MM. Obesity and health-related quality of life: a cross-sectional analysis of the US population. Int J Obes (Lond). 2003;27:1227–32.CrossRef
12.
go back to reference Strine TW, Okoro CA, Chapman DP, Balluz LS, Ford ES, Ajani UA, et al. Health-related quality of life and health risk behaviors among smokers. Am J Prev Med. 2005;28:182–7.CrossRefPubMed Strine TW, Okoro CA, Chapman DP, Balluz LS, Ford ES, Ajani UA, et al. Health-related quality of life and health risk behaviors among smokers. Am J Prev Med. 2005;28:182–7.CrossRefPubMed
13.
go back to reference Chen H-Y, Baumgardner DJ, Rice JP. Health-related quality of life among adults with multiple chronic conditions in the United States, Behavioral Risk Factor Surveillance System, 2007. Prev Chronic Dis. 2011;8:A09.PubMed Chen H-Y, Baumgardner DJ, Rice JP. Health-related quality of life among adults with multiple chronic conditions in the United States, Behavioral Risk Factor Surveillance System, 2007. Prev Chronic Dis. 2011;8:A09.PubMed
14.
go back to reference Dominick KL, Ahern FM, Gold CH, Heller DA. Relationship of health-related quality of life to health care utilization and mortality among older adults. Aging Clin Exp Res. 2002;14:499–508.CrossRefPubMed Dominick KL, Ahern FM, Gold CH, Heller DA. Relationship of health-related quality of life to health care utilization and mortality among older adults. Aging Clin Exp Res. 2002;14:499–508.CrossRefPubMed
15.
go back to reference Idler EL, Benyamini Y. Self-rated health and mortality: a review of twenty-seven community studies. J Health Soc Behav. 1997;38:21–37.CrossRefPubMed Idler EL, Benyamini Y. Self-rated health and mortality: a review of twenty-seven community studies. J Health Soc Behav. 1997;38:21–37.CrossRefPubMed
16.
go back to reference Zahran HS, Kobau R, Moriarty DG, Zack MM, Holt J, Donehoo R. Health-related quality of life surveillance--United States, 1993-2002. MMWR Surveill Summ. 2005;54:1–35.PubMed Zahran HS, Kobau R, Moriarty DG, Zack MM, Holt J, Donehoo R. Health-related quality of life surveillance--United States, 1993-2002. MMWR Surveill Summ. 2005;54:1–35.PubMed
17.
go back to reference Centers for Disease Control and Prevention. Self-reported frequent mental distress among adults--United States, 1993-2001. MMWR Morb Mortal Wkly Rep. 2004;53:963–6. Centers for Disease Control and Prevention. Self-reported frequent mental distress among adults--United States, 1993-2001. MMWR Morb Mortal Wkly Rep. 2004;53:963–6.
18.
go back to reference Chowdhury PP, Balluz L, Strine TW. Health-related quality of life among minority populations in the United States. Ethn Dis. 2008;18:483–7.PubMed Chowdhury PP, Balluz L, Strine TW. Health-related quality of life among minority populations in the United States. Ethn Dis. 2008;18:483–7.PubMed
19.
go back to reference Brown DWM, Balluz LSS, Ford ES, Giles WH, Strine TW, Moriarty DG, et al. Associations between short- and long-term unemployment and frequent mental distress among a national sample of men and women. J Occup Environ Med. 2003;45:1159–66.CrossRefPubMed Brown DWM, Balluz LSS, Ford ES, Giles WH, Strine TW, Moriarty DG, et al. Associations between short- and long-term unemployment and frequent mental distress among a national sample of men and women. J Occup Environ Med. 2003;45:1159–66.CrossRefPubMed
20.
go back to reference Jia H, Muennig P, Lubetkin EI, Gold MR. Predicting geographical variations in behavioural risk factors: an analysis of physical and mental healthy days. J Epidemiol Community Health. 2004;58:150–5.CrossRefPubMedPubMedCentral Jia H, Muennig P, Lubetkin EI, Gold MR. Predicting geographical variations in behavioural risk factors: an analysis of physical and mental healthy days. J Epidemiol Community Health. 2004;58:150–5.CrossRefPubMedPubMedCentral
21.
go back to reference Centers for Disease Control and Prevention (CDC). Community indicators of health-related quality of life--United States, 1993-1997. MMWR Morb Mortal Wkly Rep. 2000;49:281–5. Centers for Disease Control and Prevention (CDC). Community indicators of health-related quality of life--United States, 1993-1997. MMWR Morb Mortal Wkly Rep. 2000;49:281–5.
24.
go back to reference Dwyer-Lindgren L, Mackenbach JP, van Lenthe FJ, Flaxman AD, Mokdad AH. Diagnosed and undiagnosed diabetes prevalence by county in the U.S., 1999–2012. Diabetes Care. 2016;39:1556–62.CrossRefPubMed Dwyer-Lindgren L, Mackenbach JP, van Lenthe FJ, Flaxman AD, Mokdad AH. Diagnosed and undiagnosed diabetes prevalence by county in the U.S., 1999–2012. Diabetes Care. 2016;39:1556–62.CrossRefPubMed
25.
go back to reference Leroux BG, Lei X, Breslow N. Estimation of disease rates in small areas: a new mixed model for spatial dependence. In: Statistical Models in Epidemiology, the Environment, and Clinical Trials. New York: Springer; 2000. p. 179–91.CrossRef Leroux BG, Lei X, Breslow N. Estimation of disease rates in small areas: a new mixed model for spatial dependence. In: Statistical Models in Epidemiology, the Environment, and Clinical Trials. New York: Springer; 2000. p. 179–91.CrossRef
26.
go back to reference Knorr-Held L. Bayesian modelling of inseparable space-time variation in disease risk. Stat Med. 2000;19:2555–67.CrossRefPubMed Knorr-Held L. Bayesian modelling of inseparable space-time variation in disease risk. Stat Med. 2000;19:2555–67.CrossRefPubMed
27.
go back to reference Kristensen K, Nielsen A, Berg CW, Skaug H, Bell B. TMB: automatic differentiation and Laplace approximation. J Stat Softw. 2016;70:1–21.CrossRef Kristensen K, Nielsen A, Berg CW, Skaug H, Bell B. TMB: automatic differentiation and Laplace approximation. J Stat Softw. 2016;70:1–21.CrossRef
29.
go back to reference Dwyer-Lindgren L, Mokdad AH, Srebotnjak T, Flaxman AD, Hansen GM, Murray CJ. Cigarette smoking prevalence in US counties: 1996-2012. Popul Health Metrics. 2014;12:5.CrossRef Dwyer-Lindgren L, Mokdad AH, Srebotnjak T, Flaxman AD, Hansen GM, Murray CJ. Cigarette smoking prevalence in US counties: 1996-2012. Popul Health Metrics. 2014;12:5.CrossRef
30.
go back to reference Dwyer-Lindgren L, Freedman G, Engell RE, Fleming TD, Lim SS, Murray CJ, et al. Prevalence of physical activity and obesity in US counties, 2001–2011: a road map for action. Popul Health Metrics. 2013;11:7.CrossRef Dwyer-Lindgren L, Freedman G, Engell RE, Fleming TD, Lim SS, Murray CJ, et al. Prevalence of physical activity and obesity in US counties, 2001–2011: a road map for action. Popul Health Metrics. 2013;11:7.CrossRef
31.
go back to reference Olives C, Myerson R, Mokdad AH, Murray CJL, Lim SS. Prevalence, awareness, treatment, and control of hypertension in United States counties, 2001–2009. PLoS One. 2013;8:e60308.CrossRefPubMedPubMedCentral Olives C, Myerson R, Mokdad AH, Murray CJL, Lim SS. Prevalence, awareness, treatment, and control of hypertension in United States counties, 2001–2009. PLoS One. 2013;8:e60308.CrossRefPubMedPubMedCentral
32.
go back to reference Cleveland WS, Devlin SJ. Locally weighted regression: an approach to regression analysis by local fitting. J Am Stat Assoc. 1988;83:596–610.CrossRef Cleveland WS, Devlin SJ. Locally weighted regression: an approach to regression analysis by local fitting. J Am Stat Assoc. 1988;83:596–610.CrossRef
33.
go back to reference Lindeboom M, van Doorslaer E. Cut-point shift and index shift in self-reported health. J Health Econ. 2004;23:1083–99.CrossRefPubMed Lindeboom M, van Doorslaer E. Cut-point shift and index shift in self-reported health. J Health Econ. 2004;23:1083–99.CrossRefPubMed
34.
go back to reference Drum CE, Horner-Johnson W, Krahn GL. Self-rated health and healthy days: examining the “disability paradox”. Disabil Health J. 2008;1:71–8.CrossRefPubMed Drum CE, Horner-Johnson W, Krahn GL. Self-rated health and healthy days: examining the “disability paradox”. Disabil Health J. 2008;1:71–8.CrossRefPubMed
35.
go back to reference Salomon JA, Nordhagen S, Oza S, Murray CJL. Are Americans feeling less healthy? The puzzle of trends in self-rated health. Am J Epidemiol. 2009;170:343–51.CrossRefPubMedPubMedCentral Salomon JA, Nordhagen S, Oza S, Murray CJL. Are Americans feeling less healthy? The puzzle of trends in self-rated health. Am J Epidemiol. 2009;170:343–51.CrossRefPubMedPubMedCentral
Metadata
Title
Self-reported general health, physical distress, mental distress, and activity limitation by US county, 1995-2012
Authors
Laura Dwyer-Lindgren
Johan P. Mackenbach
Frank J. van Lenthe
Ali H. Mokdad
Publication date
01-12-2017
Publisher
BioMed Central
Published in
Population Health Metrics / Issue 1/2017
Electronic ISSN: 1478-7954
DOI
https://doi.org/10.1186/s12963-017-0133-5

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