Evidence map›Paper›PMID 37821133›Full record

ArticleBMJ open2023

Tracking progress towards equitable maternal and child health in Yunnan: a systematic assessment for the Health Programme for Poverty Alleviation in China during 2015-2020.

Yuan Huang, Xia Xiao, Ying Wan, Qingyun Ye, Zhongting Yang, Lingling Xu, Shuqi Chen, Huifang Li, Fangfang Wang, Yurong Chen and 5 more

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.2field-weighted citation impact, top 18% 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

4 citing papers in PubMed, 2 citations in OpenAlex.

  1. Review
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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

15 authors at 2 institutions in 1 country.

Yuan HuangSchool of Public Health, Kunming Medical University, Kunming, Yunnan, China.ORCID 0000-0002-7588-1549
Xia XiaoSchool of Public Health, Kunming Medical University, Kunming, Yunnan, China.
Ying WanInformation Centre, Yunnan Maternal and Child Health Care Hospital, Kunming, Yunnan, China.
Qingyun YeSchool of Public Health, Kunming Medical University, Kunming, Yunnan, China.
Zhongting YangSchool of Public Health, Kunming Medical University, Kunming, Yunnan, China.
Lingling XuSchool of Public Health, Kunming Medical University, Kunming, Yunnan, China.
Shuqi ChenSchool of Public Health, Kunming Medical University, Kunming, Yunnan, China.
Huifang LiSchool of Public Health, Kunming Medical University, Kunming, Yunnan, China.
Fangfang WangSchool of Public Health, Kunming Medical University, Kunming, Yunnan, China.
Yurong ChenSchool of Public Health, Kunming Medical University, Kunming, Yunnan, China.
Dandan ZhaoSchool of Public Health, Kunming Medical University, Kunming, Yunnan, China.
Qian ZhangInformation Centre, Yunnan Maternal and Child Health Care Hospital, Kunming, Yunnan, China.
Jiarui ZhengHealth Care Centre, Yunnan Maternal and Child Health Care Hospital, Kunming, Yunnan, China.
Guangping GuoHealth Care Centre, Yunnan Maternal and Child Health Care Hospital, Kunming, Yunnan, China yanli20021965@21cn.com guoguangping68@126.com.
Yan LiSchool of Public Health, Kunming Medical University, Kunming, Yunnan, China yanli20021965@21cn.com guoguangping68@126.com.
Kunming Medical University · CNYunnan Maternal and Child Health · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo inform the impacts of health programmes which aimed at preventing women and children from being trapped in or returning to poverty because of illness in Yunnan, the main battlefield against poverty in China.

designThe longitudinal comparative evaluation design. DATA COLLECTION AND ANALYSIS: National and Yunnan policy documents related to maternal and child health programmes for poverty alleviation during 2015-2020 were analysed. The changes in disparities in maternal and child health system inputs, service coverage, and health outcomes between poor and non-poor areas, as well as out-of-pocket payments between poor and non-poor populations were assessed before and after 2017.

resultsIn total 12 policies and 15 programmes related to poverty alleviation for poor women and children in Yunnan were summarised. As a result of health system strengthening in Yunnan, the densities of licensed doctors, nurses, obstetricians, midwives, township health workers and female village doctors had been increased substantially in poor areas, with the annual rates of 14.3%, 22.5%, 21.8%, 23.9%, 14.1% and 7.1% separately. Although disparities existed in some of service coverage between poor and non-poor areas, the health programmes had narrowed the gaps in utilisation of facility birth, caesarean section, prenatal screening and newborn screening across Yunnan (p<0.01). The out-of-pocket payments for inpatient care for serious illnesses among women and children with poverty registration had been considerably decreased to 10.0%. Paralleling the universal coverage, maternal deaths per 100 000 livebirths and child deaths per 1000 livebirths had further declined in both poor and non-poor areas, and the impacts of health programmes on closing the gaps in child survivals across Yunnan were significant (p<0.01).

conclusionsRemarkable progress in equitable maternal and child survival has been achieved in Yunnan. The practices in Yunnan have shown the Chinese model in ending poverty by strengthening health system and implementing universal coverage with firm commitment, determined leadership, detailed blueprint and social participation.

Indexed as

Child HealthChild Health ServicesCesarean SectionChildChinaFemaleHumansInfant, NewbornPovertyPregnancyhealth economicshealth policypublic health

Identifiers

PMID37821133
PMCPMC10583063
OpenAlexW4387527240

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

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.