F J Zimmerman1. 1. Department of Health Policy and Management, Jonathan and Karin Fielding School of Public Health, UCLA, 650 Charles E Young Drive South, Los Angeles, CA 90095-1772, USA. Electronic address: fredzimmerman@ucla.edu.
Abstract
OBJECTIVES: Progress on health equity will require a robust metric. The aim of this article is to propose a new health equity metric that is distinct from existing measures and that allows meaningful comparisons across time and place, is calculable using health data typically available, and measures health equity across all major forms of social exclusion. STUDY DESIGN: A cross-sectional study. METHODS: The new health equity measure was calculated using data included from all 50 states and the District of Columbia in the 2017 Behavioral Risk Factor Surveillance Survey, collected by the US Centers for Disease Control and Prevention. The total sample size was 287,602. State-specific sample sizes ranged from 2269 (Alaska) to 14,685 (Kansas) with a median of 4452. A Healthy Days measure was calculated as the mean number of days that the respondents reported being physically healthy and mentally healthy out of the previous 30 days. The proposed measure defines individual health disutility as the distastefulness associated with one's health falling short of optimal achievable health, instrumentalized as the median health of the most socially privileged category, that of upper-income white men. The value of the health equity metric in a population is the mean value of this distastefulness over the entire population and has a theoretical range of -∞ to 1. RESULTS: There is substantial variation across states (mean: 0.13; standard deviation: 0.15), with the District of Columbia (0.48), Minnesota (0.37), and Connecticut (0.30) showing the greatest health equity, and West Virginia (-0.26), Arkansas (-0.18), and Kentucky (-0.13) exhibiting the least. Across states, the value of the health equity metric is not correlated with the size of black-white health disparities. CONCLUSIONS: It is feasible to use a single health equity metric for consistent and objective measurement of health equity. Doing so may facilitate more rapid progress toward health equity.
OBJECTIVES: Progress on health equity will require a robust metric. The aim of this article is to propose a new health equity metric that is distinct from existing measures and that allows meaningful comparisons across time and place, is calculable using health data typically available, and measures health equity across all major forms of social exclusion. STUDY DESIGN: A cross-sectional study. METHODS: The new health equity measure was calculated using data included from all 50 states and the District of Columbia in the 2017 Behavioral Risk Factor Surveillance Survey, collected by the US Centers for Disease Control and Prevention. The total sample size was 287,602. State-specific sample sizes ranged from 2269 (Alaska) to 14,685 (Kansas) with a median of 4452. A Healthy Days measure was calculated as the mean number of days that the respondents reported being physically healthy and mentally healthy out of the previous 30 days. The proposed measure defines individual health disutility as the distastefulness associated with one's health falling short of optimal achievable health, instrumentalized as the median health of the most socially privileged category, that of upper-income white men. The value of the health equity metric in a population is the mean value of this distastefulness over the entire population and has a theoretical range of -∞ to 1. RESULTS: There is substantial variation across states (mean: 0.13; standard deviation: 0.15), with the District of Columbia (0.48), Minnesota (0.37), and Connecticut (0.30) showing the greatest health equity, and West Virginia (-0.26), Arkansas (-0.18), and Kentucky (-0.13) exhibiting the least. Across states, the value of the health equity metric is not correlated with the size of black-white health disparities. CONCLUSIONS: It is feasible to use a single health equity metric for consistent and objective measurement of health equity. Doing so may facilitate more rapid progress toward health equity.
Authors: Michael Silva-Peñaherrera; David Gimeno Ruiz de Porras; George L Delclos; Marianela Rojas Garbanzo; Pamela Merino-Salazar; Maria Lopez-Ruiz; Fernando G Benavides Journal: Am J Public Health Date: 2021-06-10 Impact factor: 9.308