Spatial–temporal distribution of preterm birth in China, 1990–2020: A systematic review and modelling analysis

• Published in: Paediatric and perinatal epidemiology 2024-02, Vol.38 (2), p.130-141
• Main Authors: Hu, Wei‐Hua, Gao, Xin‐Yuan, Li, Xiu‐Xiu, Lin, Qing‐Mei, He, Li‐Ping, Lai, Ying‐Si, Hao, Yuan‐Tao
• Format: Article
• Language: English
• Subjects: Bayesian analysis; Birth; Birth rate; China; Data search; Epidemiology; Geographical variations; Health risks; Intervention; Mathematical models; multilevel logistic regression model; Neonatal care; Premature birth; preterm birth; Provinces; Quality assessment; Regression analysis; Risk; Socioeconomic factors; Spatial analysis; Spatial distribution; Surveys; systematic review; Temporal distribution
• ISSN: 0269-5022; 1365-3016
• DOI: 10.1111/ppe.13028

Background Little is known about the long‐term trends of preterm birth rates in China and their geographic variation by province. Objectives To estimate the annual spatial–temporal distribution of preterm birth rates in China by province from 1990 to 2020. Data Sources We searched PubMed, EMBASE, Web of Science, CNKI, WANFANG and VIP from January 1990 to September 2023. Study Selection and Data Extraction Studies that provided data on preterm births in China after 1990 were included. Data were extracted following the Guidelines for Accurate and Transparent Health Estimates Reporting. Synthesis We assessed the quality of each survey using a 9‐point checklist. We estimated the annual preterm birth risk by province using Bayesian multilevel logistic regression models considering potential socioeconomic, environmental, and sanitary predictors. Results Based on 634 survey data from 343 included studies, we found a gradual increase in the preterm birth risk in most provinces in China since 1990, with an average annual increase of 0.7% nationally. However, the preterm birth rates in Inner Mongolia, Hubei, and Fujian Province showed a decline, while those in Sichuan were quite stable since 1990. In 2020, the estimates of preterm birth rates ranged from 2.9% (95% Bayesian credible interval [BCI] 2.1, 3.8) in Inner Mongolia to 8.5% (95% BCI 6.6, 10.9) in Jiangxi, with the national estimate of 5.9% (95% BCI 4.3, 8.1). Specifically, some provinces were identified as high‐risk provinces for either consistently high preterm birth rates (e.g. Jiangxi) or relatively large increases (e.g. Shanxi) since 1990. Conclusions This study provides annual information on the preterm birth risk in China since 1990 and identifies high‐risk provinces to assist in targeted control and intervention for this health issue.