Evidence map›Paper›PMID 35836246›Full record

ArticleBMC public health2022

Global trends in total fertility rate and its relation to national wealth, life expectancy and female education.

Haoyue Cheng, Wenliang Luo, Shuting Si, Xing Xin, Zhicheng Peng, Haibo Zhou, Hui Liu, Yunxian Yu

Abstract read
In one paragraph

Article in BMC public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing 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

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

43 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

8 authors.

Haoyue ChengDepartment of Epidemiology & Health Statistics, School of Public Health, School of Medicine, Zhejiang University, Hangzhou, China.
Wenliang LuoDepartment of Epidemiology & Health Statistics, School of Public Health, School of Medicine, Zhejiang University, Hangzhou, China.
Shuting SiDepartment of Epidemiology & Health Statistics, School of Public Health, School of Medicine, Zhejiang University, Hangzhou, China.
Xing XinDepartment of Epidemiology & Health Statistics, School of Public Health, School of Medicine, Zhejiang University, Hangzhou, China.
Zhicheng PengDepartment of Epidemiology & Health Statistics, School of Public Health, School of Medicine, Zhejiang University, Hangzhou, China.
Haibo ZhouDepartment of Epidemiology & Health Statistics, School of Public Health, School of Medicine, Zhejiang University, Hangzhou, China.
Hui LiuSir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
Yunxian YuDepartment of Epidemiology & Health Statistics, School of Public Health, School of Medicine, Zhejiang University, Hangzhou, China. yunxianyu@zju.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesAlong with the development of the times and progress of the society, the total fertility rate (TFR) markedly changed in each country. Therefore, it is critical to describe the trend of TFR and explore its influencing factors. However, previous studies did not consider the time lag and cumulative effect in the associations between the influencing factors and TFR. Thus, our study aimed to analyze the associations from a new dimension.

methodsThe study was employed using national-level data from the World Bank and United Nations Development Programme. Distributed lag non-linear models with 5-year lag were used to examine the independent associations between the relevant factors and TFR.

resultsThe cumulative exposure-TFR curves were inverted U-shaped for log gross domestic product (GDP) per capita and life expectancy at birth, while the cumulative exposure-response curves were approximately linear for female expected years of schooling and human development index (HDI). However, it is worth noting that in the developed regions, TFR increased slightly with the high level of GDP per capita, female expected years of schooling and HDI.

conclusionsNowadays, with the growth of GDP per capita, life expectancy at birth, female expected years of schooling and HDI, TFR are on a drastic downward trend in most regions. Besides, with the development of society, when levels of the factors continued to increase, TFR also showed a slight rebound. Therefore, governments, especially those in developing countries, should take measures to stimulate fertility and deal with a series of problems caused by declining TFR.

Indexed as

Birth RateLife ExpectancyDeveloping CountriesEducational StatusFemaleFertilityGross Domestic ProductHumansInfant, NewbornSocioeconomic FactorsDLNMEconomyEducationHealthHuman development indexTotal fertility rate

Identifiers

PMID35836246
PMCPMC9284852

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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.