Global and regional impact of health determinants on life expectancy and health-adjusted life expectancy, 2000–2018: an econometric analysis based on the Global Burden of Disease study 2019

Abstract

Background: The health status of a population is influenced by multiple determinants, including clinical care, health behaviors, the physical environment, and socioeconomic factors. This study examines the impact of these determinants on life expectancy (LE) and health-adjusted life expectancy (HALE) at both regional and global levels using econometric analysis. Methods: This ecological study included all 194 WHO member countries from 2000 to 2018. The County Health Rankings Model was used to identify key health determinants. Thirty-six indicators were selected to measure these determinants, with data collected from the World Bank, World Health Observatory, Global Health Expenditure Database, Gapminder, United Nations Human Development Reports, and Global Burden of Disease Studies. LE and HALE were used as health status indicators, with data extracted from the Global Burden of Disease Study 2019 database. A multilevel mixed-effects linear regression model was applied for statistical analysis using Stata 16 software. Results: At the global level, the regression coefficients (β) with LE and HALE were 0.09 and 0.10 for education, −0.04 and −0.10 for injuries, 0.5 and 0.6 for urbanization, 0.10 and 0.8 for access to basic drinking water, −0.5 and −0.4 for drug use, 0.4 and 0.3 for obesity, and −0.15 and −0.16 for sexually transmitted infections, respectively. Sexually transmitted infections (β = −0.25) in the African region, access to basic drinking water (β = 0.30), alcohol consumption (β = −0.06), and drug use (β = −0.02) in the Americas, injuries (β = −0.16), air pollution (β = −0.10), and obesity (β = −0.24) in the Eastern Mediterranean, urbanization (β = 0.08) in Southeast Asia, and education (β = 0.36) and smoking (β = −0.06) in the Western Pacific had the greatest impact on HALE compared to other regions (P < 0.05). Conclusion: To reduce inequalities, improve public health outcomes, and ensure efficient resource allocation, global and interregional policies should prioritize the determinants with the highest β values for health indicators in each region. These determinants are expected to yield greater marginal health benefits, making investments in them more cost-effective.