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

• Published in: Population health metrics 2017-04, Vol.15 (1), p.16-16, Article 16
• Main Authors: Dwyer-Lindgren, Laura, Mackenbach, Johan P, van Lenthe, Frank J, Mokdad, Ali H
• Format: Article
• Language: English
• Subjects: Activities of Daily Living; Behavioral Risk Factor Surveillance System; Chronic conditions; Chronic Disease - epidemiology; Chronic illnesses; Correlation analysis; Diabetes; Diabetes mellitus; Disease control; Disease prevention; Disparities; Estimates; Ethnicity; Female; Health risks; Health Status; Health-related quality of life; Healthy Days; Hispanic Americans; Humans; Hypertension; Inequalities; Life Expectancy; Life span; Male; Mental health; Minority & ethnic groups; Models, Statistical; Morbidity; Quality of life; Risk analysis; Risk Factors; Risk taking; Rivers; Self Report; Self-reported health; Small area estimation; Smoking; Stress, Psychological - epidemiology; Surveillance; Tracking; Trends; United States - epidemiology; Variables
• ISSN: 1478-7954; 1478-7954
• DOI: 10.1186/s12963-017-0133-5

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. 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. 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. 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.