Spatial inequalities of life expectancy in Hong Kong, 2010–2024

Hong Kong ranks among the world’s longest-lived populations, yet it remains unclear how uniform this achievement is across the territory. We conducted an ecological study of all 18 Hong Kong districts from 2010 to 2024. Age- and sex-specific mortality rates were modelled using Bayesian adaptation of the Tool for Projecting Age-Specific Rates using Linear Splines (TOPALS), from which annual period life tables were constructed to estimate life expectancy at birth (LEB). We assessed between-district inequality using the standard deviation (SD) of district-level posterior median estimates, evaluated spatial clustering using Moran’s I, and examined exploratory associations between LEB and district-level structural and social determinants. Median district-level LEB increased from 82.3 years in 2010 to 86.4 years in 2024, with a territory-wide decline during the 2022 Omicron wave. Between-district dispersion widened before the pandemic and peaked in 2020: the SD increased from 1.4 to 2.9 years among females and from 1.0 to 2.9 years among males. Dispersion declined in 2021 and remained lower after the Omicron wave. Yau Tsim Mong remained persistently disadvantaged. We found no clear spatial clustering. Five-year residential in-migration mobility was the only district characteristic showing a statistically detectable association with LEB [1.141 years, 95%CI, 0.211 to 2.071]. Hong Kong combines world-leading longevity with dynamic district-level inequalities that appeared localized rather than organized into broad contiguous high- or low-longevity regions. Between-district inequality peaked around 2020 and narrowed thereafter, while persistent disadvantage remained in individual districts. Annual district-level surveillance and place-based assessment are needed to identify persistent local vulnerability.

COVID-19 pandemic · district-level disparities · Hong Kong · Life expectancy · mortality rates · Omicron variant · Regional disparities · Social determinants of health · Global Cancer Incidence and Screening · Health disparities and outcomes · Insurance, Mortality, Demography, Risk Management