Evolving trends, regional differences, determinants, and disease sources of provincial-level health inequalities in china 1990-2019: a temporal convergence and novel triple decomposition analysis.

Background: Promoting health equity has been a worldwide goal, but serious challenges remain globally and within China. Multiple decomposition of the sources and determinants of health inequalities has significant implications for narrowing health inequalities and improve health equity.

Methods: Life expectancy (LE), healthy life expectancy (HALE), age-standardized mortality rate (ASMR), and age-standardized disability-adjusted life-year (DALY) rates in 31 provinces of mainland China were selected as health status indicators, obtained from the Global Burden of Disease (GBD) database. Temporal convergence analysis was used to test the evolving trends of health status. Dagum's Gini coefficient decomposition was used to decompose the overall Gini coefficient based on intraregional and interregional differences. Oaxaca-Blinder decomposition was used to calculate contributions of determinants to interregional differences. The factor-decomposed Gini coefficient was used to analyze the absolute and marginal contribution of each component to overall Gini coefficients.

Results: From 1990-2019, China witnessed notable improvements in health status measured by LE, HALE, ASMR and age-standardized DALY rates.Nevertheless, the three regions (East, Central and West) exhibited significant inter-regional differences in health status, with the differences between the East and West being the largest. The adjusted short-term conditional β-convergence model indicated that the inter-provincial differences in LE, HALE, ASMR, and age-standardized DALY rates significantly converged at annual rates of 0.31%, 0.35%, 0.19%, and 0.28% over 30 years. The overall Gini coefficients of LE, HALE, and age-standardized DALY rates decreased, while the ASMR exhibited an opposite trend. Inter-regional and intra-regional differences accounted for >70% and <30% of overall Gini coefficients, respectively. Attribution analysis showed that socioeconomic determinants explained 85.77% to 91.93% of the eastern-western differences between 2010-2019, followed by health system determinants explaining 7.79% to 11.61%. The source-analysis of Gini coefficients of ASMR and age-standardized DALY rates revealed that noncommunicable diseases (NCDs) made the largest and increasing absolute contribution, while communicable, maternal, neonatal, and nutritional diseases (CMNNDs) had a diminishing and lower impact. However, NCDs exerted a negative marginal effect on the Gini coefficient, whereas CMNNDs exhibited a positive marginal effect, indicating that controlling CMNNDs may be more effective in reducing health inequities.

Conclusions: Regional differences are a major source of health inequities in China. Prioritizing prevention and control of CMNNDs, rather than NCDs, may yield more pronounced impacts on reducing health inequalities from the perspective of marginal effect, although NCDs remain the largest absolute contributor to health inequalities.