Evidence map›Paper›PMID 38615138›Full record

ArticleScientific reports2024

A reassessment of trends and rural-urban/regional differences in the total fertility rate in China, 2000-2020: analyses of the 2020 national census data.

Long Li, Guangzhao Jin, Xiaozhen Lai, Rize Jing, He Zhu

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2024. 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
9.3field-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

4 citing papers in PubMed, 10 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.

Long Li *Center for Population and Development Studies, Renmin University of China, Beijing, 100872, China.
Guangzhao Jin *Center for Population and Development Studies, Renmin University of China, Beijing, 100872, China.
Xiaozhen LaiChina Center for Health Development Studies, Peking University, Beijing, 100871, China.
Rize JingSchool of Public Administration and Policy, Renmin University of China, No. 59, Zhongguancun Street, Haidian District, Beijing, 100872, China. rzjing@ruc.edu.cn.
He ZhuChina Center for Health Development Studies, Peking University, Beijing, 100871, China. he.zhu@pku.edu.cn.
Renmin University of China · CNPeking University · CN

Funding

Fundamental Research Funds for the Central Universities 22XNQJ04
6 · The paper itself

Abstract

The decline in the total fertility rate (TFR) is a key driver of population change and has important implications for population health and social development. However, China's TFR has been a considerable controversy due to a lack of high-quality data. Therefore, this study used the 2020 national population census of China (NPCC) data and reverse survival method to reassess temporal trends in the TFRs and to reexamine rural-urban differences and regional variations in TFRs from 2000 to 2020 in China. Overall, there were significant gaps between the estimated and reported TFRs before 2020, and the estimated TFRs based on the 2020 NPCC data remained higher than the reported TFRs from government statistics. Although TFRs rebounded shortly in the years after the two-child policy, they have shown a wavelike decline since 2010. Additionally, the estimated TFRs fluctuated below 1.5 children per woman in urban areas compared to above 1.8 in rural areas, but the rural-urban differences continued to decrease. Regarding geographic regional variations, the estimated TFRs in all regions displayed a declining trend during 2010-2020, especially in rural areas. Large decreases of over 25% in TFRs occurred in the north, east, central, and northwest regions. In addition to changing the birth policy, the government and society should adopt comprehensive strategies, including reducing the costs of marriage, childbearing, and child education, as well as promoting work-family balance, to encourage and increase fertility levels.

Indexed as

Birth RateCensusesChinaData AccuracyFemaleFertilityHumans

Identifiers

PMID38615138
PMCPMC11016060
OpenAlexW4394783068

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LicenceCC BY
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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.