Spatial-Temporal Distribution and Key Drivers of Inequalities in the Gap Between Health-Adjusted Life Expectancy and Life Expectancy: Evidence from a Megacity in China, 2010-2019.

Abstract Purpose The improvement of the quality of life (QoL) is reflected in the narrowing of the GAP between health-adjusted life expectancy (HALE) and life expectancy (LE). Less is known about the effect that the expansion of megacities may have on narrowing the gap. The purpose of this study was to disclose this potential relationship.Methods Annual life tables were constructed from identified death records and population counts from multiple administrative sources in Guangzhou, China, 2010-2019. Joinpoint regression was used for evaluating the time trends and global Moran’s Ⅰ and local Moran’s Ⅰ was used for evaluating spatial autocorrelation at the county-level during the entire study period. Generalized principal component analysis and multilevel models were used to examine the county-level association between the GAP and socioeconomic, health services, population structure, and population dynamics.Results From 2010 to 2019, LE increased by 2.8 years (2.8 years for males and 2.9 years for females) and total HALE increased by 2.4 years (2.5 years for males and 2.2 years for females). The counties with higher or lower LE, HALE, and their GAP were presented spatial agglomeration distribution characteristics. The central city and the neighboring counties had higher LE and HALE, and lower GAP. The ratio of male to female and the natural population growth rate were positively correlated with the GAP, while the gross domestic product per area, the density of resident population, the number of practicing (assistant) physicians per thousand, the number of hospital beds per thousand, the per capita disposable income, the ratio of child to old people, the net migration rate and the total migration rate were negatively correlated with the GAP.Conclusion In megacities, LE and HALE were higher and their GAP was lower in the central city than in the urban fringe. Socio-economic and health services were key to narrow the GAP. The widening GAP can be explained by a high proportion of females and old people, who were longevity but unhealthy. Population density within the urban carrying capacity produced a positive effect on narrow the GAP, and these were attributed to the healthy immigrant effect.