Spatiotemporal trends in neonatal, infant, and child mortality (1990-2019) based on Bayesian spatiotemporal modeling

Shaobin Wang; Zhoupeng Ren; Xianglong Liu

doi:10.3389/fpubh.2023.996694

Spatiotemporal trends in neonatal, infant, and child mortality (1990-2019) based on Bayesian spatiotemporal modeling

Front Public Health. 2023 Feb 9:11:996694. doi: 10.3389/fpubh.2023.996694. eCollection 2023.

Authors

Shaobin Wang¹, Zhoupeng Ren^{1

2}, Xianglong Liu^{1

2}

Affiliations

¹ Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.
² State Key Laboratory of Resources and Environmental Information System, Beijing, China.

Abstract

Background: Neonatal mortality rate (NMR), infant mortality rate (IMR), and child mortality rate (CMR) show a huge difference across countries, which has been posing challenges for public health policies and medical resource allocation.

Methods: Bayesian spatiotemporal model is applied to assess the detailed spatiotemporal evolution of NMR, IMR, and CMR from a global perspective. Panel data from 185 countries from 1990 to 2019 are collected.

Results: The continuously decreasing trend of NMR, IMR, and CMR indicated a great improvement in neonatal, infant, and child mortality worldwide. Further, huge differences in the NMR, IMR, and CMR still exist across countries. In addition, the gap of NMR, IMR, and CMR across the countries presented a widening trend from the perspective of dispersion degree and kernel densities. The spatiotemporal heterogeneities demonstrated that the decline degree among these three indicators could be observed as CMR > IMR > NMR. Countries such as Brazil, Sweden, Libya, Myanmar, Thailand, Uzbekistan, Greece, and Zimbabwe showed the highest values of b_1i , indicating a weaker downward trend compared to the overall downward trend in the world.

Conclusions: This study revealed the spatiotemporal patterns and trends in the levels and improvement of NMR, IMR, and CMR across countries. Further, NMR, IMR, and CMR show a continuously decreasing trend, but the differences in improvement degree present a widening trend across countries. This study provides further implications for policy in newborns, infants, and children's health to reduce health inequality worldwide.

Keywords: Bayesian spatio-temporal modeling; child mortality; health inequality; infant mortality; neonatal mortality; spatiotemporal trends.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Bayes Theorem
Child
Child Mortality*
Health Status Disparities*
Humans
Infant
Infant Mortality
Infant, Newborn
Public Policy

Grants and funding

This study was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA20030302), National Natural Science Foundation of China (No. 42071377).