Spatiotemporal disparities in maternal mortality and the role of multiscale administrative levels: a 20-year study across Chinese counties

Lingfeng Liao ¹ Fengling Yuan ¹ Yaqian He ² Xu Shixi ³ Xingyi Tang ¹ Mingyu Xie ⁴ Xianteng Tang ⁵ Zhangying Tang ⁵ Guo Zeng ¹ Yumeng Zhang ^1* Chao Song ^1*

• ¹ HEOA-West China Health & Medical Geography Group, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
• ² Department of Geosciences, University of Arkansas, Fayetteville, North Carolina, United States
• ³ School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Dongcheng, Beijing Municipality, China
• ⁴ School of Public Health, Xi'an Jiaotong University, Xi'an, China
• ⁵ State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, School of Geoscience and Technology, Southwest Petroleum University, Chengdu, Sichuan Province, China

China has made progress in reducing maternal mortality ratio (MMR), yet county-level spatiotemporal heterogeneity persists. This study aims to identify spatiotemporal disparities in MMR and quantify the impacts of various administrative levels on these disparities.We analyzed county-level MMR panel data from 1996 to 2015, employing the spatial Gini coefficient, Anselin Local Moran's I, and Getis-Ord Gi* to assess spatiotemporal disparities related to spatial inequity and geographic clustering. Additionally, we applied a Bayesian multiscale spatiotemporally varying intercepts (BMSTVI) model to unveil the national temporal trend and multiple sub-national spatial patterns in maternal mortality risk. We further quantified the relative contributions of five subnational administrative levels using the spatiotemporal variance partitioning index (STVPI).Results suggested that from 1996 to 2015, the proportion of MMR in counties achieving Sustainable Development Goals (SDGs) increased from 27.05% to 93.40%, yet spatiotemporal disparities remained. The spatial Gini coefficient and geographic clustering analyses indicated temporally varying but spatially stable inequities patterns, highlighting the spatial inequity lock-in (SILI) effect. Hotspot analysis identified sensitive and exemplary counties, underscoring the need for targeted regional interventions. The BMSTVI model indicated a declining trend in MMR risk over 20 years, with the most substantial reduction from 2003 to 2012. While the geographic distribution of high-risk areas remained relatively stable, analyses at finer administrative levels enabled more precise identification of affected locations and improved intervention effectiveness. Finally, the STVPI revealed that spatial effects contributed 83.91% (95% CIs: 78.66%-89.47%) to MMR variations, far exceeding the 11.60% (95% CIs: 7.27%-16.55%) from temporal effects. The contribution from the administrative countylevel was the highest (29.15%, 95% CIs: 19.69%-35.06%), followed by contributions from the seven geographical regions (14.10%, 95% CIs: 6.61%-34.06%), rural-urban differences (13.77%, 95% CIs: 4.93%-39.2%), provincial level (12.41%, 95% CIs: 8.06%-16.85%), and city level (11.21%, 95% CIs: 7.53%-13.84%).These findings underscore the crucial need for region-specific, time-sensitive policies to achieve maternal health equity across Chinese counties. This study provides a robust empirical foundation for a multi-tiered adaptive policy framework grounded in systematic spatiotemporal assessment across macro, meso, and micro scales to guide targeted maternal health interventions globally.