Assessing Health Determinants Worldwide: Econometric Analysis of the Global Burden of Diseases Study 2000-18 - Highlighting Impactful Factors on Daly, Yll, and Yld Indicators Publisher Pubmed

Summary: Health gaps explained? Study links STIs, injuries, urbanization to DALYs—region-specific. Suggests targeted policies. #GlobalHealth #Determinants

Irandoust K^{1, 2} ; Daroudi R¹ ; Tajvar M¹ ; Yaseri M³
Source: Journal of Global Health Published:2024

Abstract

Background As the health status of a population is influenced by a variety of health determinants, we sought to assess their impact on health outcomes, both at the global and regional levels. Methods This ecological study encompassed all 194 member countries of the World Health Organization (WHO) from 2000 to 2018. We first identified all health determinants and then retrieved the related data from various global databases. We additionally considered three indicators - disability-adjusted life years (DALYs), years of life lost (YLL), and years lived with disability (YLD) -in evaluating health outcomes; we extracted their data from the Global Burden of Disease (GBD) 2019 study. We then applied econometric analyses using a multilevel mixed-effects linear regression model. Results The analysis using the DALY indicator showed that the variables of sexually transmitted infections, injuries prevalence, and urbanisation had the highest effect size or regression coefficients (β) for health outcomes. The variables of sexually transmitted infection (β= 0.75, P < 0.001) in the African region; drinking water (β = -0.60, P < 0.001), alcohol use (β= 0.20, P < 0.001), and drug use (β = 0.05, P = 0.036) in the Americas region; urbanisation (β = -0.34, P < 0.001) in the Eastern Mediterranean region; current health expenditure (β = -0.21, P < 0.001) in the Europe region; injuries (β = 0.65, P < 0.001), air pollution (β = 0.29, P < 0.001), and obesity (β = 0.92, P < 0.001) in the SouthEast Asia region; and gross domestic product (β = -0.25, P < 0.001), education (β = -0.90, P < 0.001), and smoking (β = 0.28, P < 0.001) in the Western Pacific region had the most significant role in explaining global health outcomes. Except for the drug use variable in regional findings, the role of other variables in explaining the YLL indicator was greater than that of the YLD indicator. Conclusions To address global health disparities and optimise resource allocation, global and interregional policymakers should focus on determinants that had the highest β with health outcomes in each region compared to other regions. These determinants likely have a higher marginal health product, and investing in them is likely to be more cost-effective. © 2024 The Author(s). All Rights Reserved.