Evidence map›Paper›PMID 35549888›Full record

ArticleBMC pediatrics2022

Geographical disparities in infant mortality in the rural areas of China: a descriptive study, 2010-2018.

Xue Yu, Yanping Wang, Leni Kang, Lei Miao, Xiaowei Song, Xuemei Ran, Jun Zhu, Juan Liang, Qi Li, Li Dai and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC pediatrics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Xue YuNational Office for Maternal and Child Health Surveillance of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
Yanping WangNational Office for Maternal and Child Health Surveillance of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
Leni KangNational Office for Maternal and Child Health Surveillance of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
Lei MiaoNational Office for Maternal and Child Health Surveillance of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
Xiaowei SongDepartment of gynaecology and obstetrics, Maternal and Child healthcare hospital of Dujiangyan, Chengdu, Sichuan, China.
Xuemei RanDepartment of pediatrics, Hanyuan people's Hospital, Hanyuan, Sichuan, Yaan, China.
Jun ZhuNational Office for Maternal and Child Health Surveillance of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
Juan LiangNational Office for Maternal and Child Health Surveillance of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
Qi LiNational Office for Maternal and Child Health Surveillance of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
Li DaiNational Office for Maternal and Child Health Surveillance of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
Xiaohong LiNational Office for Maternal and Child Health Surveillance of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
Chunhua He *National Office for Maternal and Child Health Surveillance of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China. hch7646@163.com.
Mingrong Li *National Office for Maternal and Child Health Surveillance of China, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe infant mortality rate (IMR) is considered a basic measure of public health for countries around the world. The specific aim of our study was to provide an updated description of infant mortality rate among different regions in rural China, and assess the trends and causes of the IMR geographical disparities.

methodsData were collected from China's Under-5 Child Mortality Surveillance System(U5CMSS). The annual number of deaths and causes of death were adjusted using a 3-year moving average underreporting rate based on annual national data quality control results. The average annual decline rate (AADR) and the relative risk (RR) of the IMR and cause-specific infant mortality were calculated by Poisson regression and the Cochran-Mantel-Haenszel method. Data analysis was completed by SAS software.

resultsThere was an apparent decrease in infant mortality in rural China from 2010 to 2018, at the AADR of 11.0% (95%CI 9.6-12.4), 11.2% (95%CI 10.3-12.1) and 6.6% (95%CI 6.0-7.3) in the eastern, central and western rural areas, respectively. The IMR was highest in the western rural area, followed by the central and eastern rural areas. Compared with the eastern rural area, the RR of infant mortality in the central rural area remained at 1.4-1.6 and increased from 2.4 (95%CI 2.3-2.6) in 2010-2012 to 3.1 (95% CI 2.9-3.4) in 2016-2018 in the western rural area. Pneumonia, preterm birth /LBW and birth asphyxia were the leading causes of infant deaths in the western rural area. Mortality rates of these three causes fell significantly in 2010-2018 but contributed to a higher proportion of deaths in the western rural area than in the central and western rural ares.

conclusionsOur study indicated that the infant mortality rate dropped significantly from 2010 to 2018, however, geographical disparities of IMR in rural China are still persist. Therefore, there is an urgent need for public health programmes and policy interventions for infants in western rural China.

Indexed as

Premature BirthCause of DeathChildChild MortalityChinaFemaleHumansInfantInfant MortalityInfant, NewbornPregnancyRural PopulationGeographical disparitiesInfant mortality rateLeading causesRural China

Identifiers

PMID35549888
PMCPMC9097431

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.