Abstract
OBJECTIVE: The present study investigated the province-level distribution and drivers of infant mortality rate (IMR) in mainland China. DESIGN: Ecological analysis based on publicly available data for all 31 provinces in mainland China. DATA SOURCES: Data on province-level IMRs in 2020 were obtained from the official websites of the healthcare commissions within each province and from the China Health Statistics Yearbook 2021. Data on potential IMR drivers were retrieved from the China Statistical Yearbook 2021. DATA ANALYSIS: GeoDa V.1.12.1 and ArcMap V.10.2 software were used to examine province-level distribution of IMR. Global and local spatial autocorrelations were performed, and Getis-ord G* hotspots and coldspots were identified. Geodetector was used to analyse the individual and joint influence of drivers on IMR. RESULTS: IMRs in 2020 varied from 1.91 to 7.60 per 1000 live births across provinces. The following statistically significant drivers with q values >0.5 were identified: health literacy of the population (0.6673), male illiteracy rate (0.6433), proportion of the population older than >65 years (0.6369), per capita government health expenditure (0.6216), forest coverage rate (0.5820), per capita disposable income (0.5785), per capita number of hospitals (0.5592), per capita gross regional product (0.5410) and sulfur dioxide concentration in the atmosphere (0.5158). The following three interactions among these drivers emerged as strongest influences on province-level IMR: proportion of population >65 years ∩ per capita gross regional product (q=0.9653), forest coverage rate ∩ per capita gross regional product (0.9610) and per capita government health expenditure ∩ sulfur dioxide (0.9295). CONCLUSION: IMR in mainland China varies substantially across the country, being generally high-west and low-east. Several factors, on their own and interacting together, contribute to IMR. Policies and programmes to reduce IMR should be formulated according to local conditions and should focus on western provinces of the country.