Evidence map›Paper›PMID 28427423›Full record

ArticleInternational journal for equity in health2017

Analysis of inequality in maternal and child health outcomes and mortality from 2000 to 2013 in China.

Yanting Li, Yimin Zhang, Shuai Fang, Shanshan Liu, Xinyu Liu, Ming Li, Hong Liang, Hua Fu

Open access · goldAbstract read
In one paragraph

Article in International journal for equity in health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
6.5field-weighted citation impact, top 4% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

22 citing papers in PubMed, 45 citations in OpenAlex.

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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

8 authors at 3 institutions in 1 country.

Yanting LiSchool of Public Health, and the Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, 200032, China.
Yimin ZhangPudong Institute for Health Development, Shanghai, 200129, China.
Shuai FangSchool of Social Development and Public Policy, Fudan University, Shanghai, 200433, China.
Shanshan LiuPudong Institute for Health Development, Shanghai, 200129, China.
Xinyu LiuSchool of Social Development and Public Policy, Fudan University, Shanghai, 200433, China.
Ming LiHealth and Family Planning Commission of Pudong new district, Shanghai, 200125, China.
Hong LiangPudong Institute for Health Development, Shanghai, 200129, China.
Hua FuSchool of Public Health, and the Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, 200032, China. hfu@fudan.edu.cn.
Shanghai Pudong Institute of Education Development · CNFudan University · CNShanghai Municipal Commission of Health and Family Planning · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInequality in maternal and child health seriously hinders the overall improvement of health, which is a concern in both the United Nations Sustainable Development Goals (SDGs) and Healthy China 2030. However, research on the equality of maternal and child health is scarce. This study longitudinally assessed the equality trends in China's maternal and child health outcomes from 2000 to 2013 based on place of residence and gender to improve the fairness of domestic maternal and child health.

methodsData on China's maternal and child health monitoring reports were collected from 2000 to 2013. Horizontal and vertical monitoring were performed on the following maternal and child health outcome indicators: incidence of birth defects (IBD), maternal mortality rate (MMR), under 5 mortality rate (U5MR) and neonatal mortality rate (NMR). The newly developed HD*Calc software by the World Health Organization (WHO) was employed as a tool for the health inequality assessment. The between group variance (BGV) and the Theil index (T) were used to measure disparity between different population groups, and the Slope index was used to analyse the BGV and T trends.

resultsThe disparity in the MMR, U5MR and NMR for the different places of residence (urban and rural) improved over time. The BGV (Slope BGV = -32.24) and T (Slope T = -7.87) of MMR declined the fastest. The gender differences in the U5MR (Slope BGV = -0.06, Slope T = -0.21) and the NMR (Slope BGV = -0.01, Slope T = 0.23) were relatively stable, but the IBD disparity still showed an upward trend in both the place of residence and gender strata. A decline in urban-rural differences in the cause of maternal death was found for obstetric bleeding (Slope BGV = -14.61, Slope T = -20.84). Improvements were seen in the urban-rural disparity in premature birth and being underweight (PBU) in children under 5 years of age. Although diarrhoea and pneumonia decreased in the U5MR, no obvious gender-based trend in the causes of death was observed.

conclusionWe found improvement in the disparity of maternal and child health outcomes in China. However, the improvements still do not meet the requirements proposed by the Healthy China 2030 strategy, particularly regarding the rise in the IBD levels and the decline in equality. This study suggests starting with maternal and child health services and focusing on the disparity in the causes of death in both the place of residence and gender strata. Placing an emphasis on health services may encourage the recovery of the premarital check and measures such as prenatal and postnatal examinations to improve equality.

Indexed as

Child HealthMaternal-Child Health ServicesMaternal HealthCause of DeathChild MortalityChild, PreschoolChinaCongenital AbnormalitiesFemaleHealth Status DisparitiesHumansIncidenceInfantInfant DeathInfant MortalityMaternal DeathDeath causes constituentHealth outcome inequalityMaternal and child health

Identifiers

PMID28427423
PMCPMC5399313
OpenAlexW2606155180

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.