Evidence map›Paper›PMID 37236662›Full record

ArticleBMJ open2023

Rising trend of childlessness in China: analysis of social and regional disparities with 2010 and 2020 census data.

Quanbao Jiang, Cuiling Zhang, Yaer Zhuang, Yu Jiang, Xuying Zhang

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 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
8.1field-weighted citation impact, top 2% 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

7 citing papers in PubMed, 18 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

5 authors at 2 institutions in 1 country.

Quanbao JiangInstitute for Population and Development Studies, Xi'an Jiaotong University, Xi'an, China recluse_jqb@126.com.ORCID 0000-0002-1696-7393
Cuiling ZhangChina Population and Development Research Center, Beijing, China.
Yaer ZhuangChina Population and Development Research Center, Beijing, China.
Yu JiangChina Population and Development Research Center, Beijing, China.
Xuying ZhangChina Population and Development Research Center, Beijing, China.
China Population and Development Research Center · CNXi'an Jiaotong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionIn recent decades, there has been a significant increase in childlessness. This paper analysed childlessness in China, specifically examining its socio and regional disparities.

methodsWith data from China's 2020 population census, supplemented with data from China's 2010 population census and 2015 inter-censual 1% population sample survey, we used a basic indicator of age-specific childlessness proportion, a decomposition method, and probability distribution models to analyse, fit and project childlessness.

resultsWe presented age-specific childlessness proportions for women as a whole and by socioeconomic features, decomposition and projection results. The childlessness proportion increased markedly from 2010 to 2020, reaching 5.16% for women aged 49. The proportion is highest for city women, followed by township women, and is lowest among village women, at 6.29%, 5.50% and 3.72 % for women aged 49, respectively. The proportion for women aged 49 with high college education or above was 7.98%, and only 4.42% for women with junior high school education. The proportion also exhibits marked provincial discrepancies, and the total fertility rate is negatively correlated with childlessness at the province level. The decomposition results distinguished the different contribution of change in educational structure and change in childlessness proportion for subgroups to the total childlessness proportion change. It is projected that city women, women with high education will have higher childlessness proportion, and the proportion will further increase with the rapid increase in education level and urbanisation.

conclusionsChildlessness has risen to a relatively high level, and varies among women with different characteristics. This should be taken into consideration in China's countermeasures to reduce childlessness and curtail further fertility decline accordingly.

Indexed as

CensusesFertilityBirth RateChinaDemographyDeveloping CountriesEconomicsFemaleHumansPopulation Dynamicsdemographypublic healthsubfertility

Identifiers

PMID37236662
PMCPMC10231016
OpenAlexW4378471669

What OpenQuestion holds

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LicenceCC BY-NC
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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.