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Spatial-temporal distribution of preterm birth in China, 1990-2020: A systematic review and modelling analysis.
Hu, Wei-Hua; Gao, Xin-Yuan; Li, Xiu-Xiu; Lin, Qing-Mei; He, Li-Ping; Lai, Ying-Si; Hao, Yuan-Tao.
Afiliação
  • Hu WH; Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China.
  • Gao XY; Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
  • Li XX; Peking University Center for Public Health and Epidemic Preparedness & Response, Peking University, Beijing, China.
  • Lin QM; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, China.
  • He LP; Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China.
  • Lai YS; Department of Science and Education, Maternal and Child Health Center in Nanshan District, Shenzhen, China.
  • Hao YT; Department of Health Care, Foshan Women and Children Hospital Affiliated to Southern Medical University, Foshan, China.
Paediatr Perinat Epidemiol ; 38(2): 130-141, 2024 Feb.
Article em En | MEDLINE | ID: mdl-38168744
ABSTRACT

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.
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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Nascimento Prematuro Tipo de estudo: Prognostic_studies / Qualitative_research / Systematic_reviews Limite: Female / Humans / Newborn País/Região como assunto: Asia Idioma: En Revista: Paediatr Perinat Epidemiol Assunto da revista: EPIDEMIOLOGIA / PEDIATRIA / PERINATOLOGIA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Nascimento Prematuro Tipo de estudo: Prognostic_studies / Qualitative_research / Systematic_reviews Limite: Female / Humans / Newborn País/Região como assunto: Asia Idioma: En Revista: Paediatr Perinat Epidemiol Assunto da revista: EPIDEMIOLOGIA / PEDIATRIA / PERINATOLOGIA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China