Evidence map›Paper›PMID 32471396›Full record

ArticleBMC psychiatry2020

Number of children and the prevalence of later-life major depression and insomnia in women and men: findings from a cross-sectional study of 0.5 million Chinese adults.

Hanyu Wang, Minne Chen, Tong Xin, Kun Tang

Open access · goldAbstract read
In one paragraph

Article in BMC psychiatry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
6.5field-weighted citation impact, top 3% 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

14 citing papers in PubMed, 28 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Observational
  5. Article
  6. Do mothers or females without children have better health-related quality of life across their reproductive years?Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2023
    Article
  7. Article
  8. Article
  9. Review
  10. Number of Births and Later-Life Depression in Older Adults: Evidence from China.International journal of environmental research and public health · 2022
    Article
  11. Article
  12. Article
  13. Article
  14. Article
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

4 authors at 3 institutions in 2 countries.

Hanyu WangResearch Center for Public Health, School of Medicine, Tsinghua University, Haidian District, Beijing, China.
Minne ChenDepartment of Sociology, University of North Carolina at Chapel Hill, 103 S Bldg Cb 9100, Chapel Hill, United States.
Tong XinDepartment of Global Health, Peking University Health Science Center, No. 38 Xueyuan Road, Beijing, 100191, China.
Kun TangResearch Center for Public Health, School of Medicine, Tsinghua University, Haidian District, Beijing, China. tangkun@post.harvard.edu.ORCID 0000-0002-5444-186X
Peking University · CNTsinghua University · CNUniversity of North Carolina at Chapel Hill · US

Funding

Kadoorie Charitable Foundation 088158/Z/09/ZNational Key Research and Development Program of China 2016YFC0900501National Key Research and Development Program of China 2016YFC0900504the National Key Research and Development Program of China 2016YFC0900500Wellcome Trust 104085/Z/14/Z
6 · The paper itself

Abstract

backgroundPregnancy and parenthood have been associated with physical and mental health. Previous literature concerning the impacts of parity on mental health was inconsistent and lack epidemiolocal evidence. China, with growing mental health problems and changing fertility patterns, faces unique challenges. This study aims to examine the relationship between parity and the prevalence of major depression and insomnia among men and women in the Chinese population.

methodsBaseline data from a Chinese population-based study of 512,891 adults (59.01% women) from 10 areas, aged 30-79 were analyzed. Number of children was based on self-report by the participants. Major depression (MD) was assessed using the Composite International Diagnostic Inventory. Insomnia symptoms were accessed by a questionnaire comparable to that used in the Diagnostic and Statistical Manual of Mental Disorders. Logistic regression was used to assess the relationship between MD/Insomnia and number of children, after stratifications and adjustments.

resultsFor women, each additional child was associated with a 9% decreased odds of MD (OR: 0.91, 95%CI: 0.88-0.96), with the associations significant for those who lived in urban areas (OR: 0.76, 95%CI: 0.70-0.83), or had a lower education (OR: 0.90, 95%CI: 0.85-0.94), or had lower household income (OR: 0.89, 95%CI: 0.85-0.94), or had ever used alcohol (OR: 0.89, 95%CI: 0.84-0.93). The association between per additional children and MD was not significant in men (OR: 1.02, 95%CI: 0.97-1.07), but a decreased odd of MD with per additional child was found in men who lived in urban areas (OR: 0.81, 95%CI: 0.71-0.96). For women, each additional child was associated with a 4% decreased odds of insomnia (OR: 0.96, 95%CI: 0.95-0.96). Each additional child was also associated with a 2% decreased odds of insomnia in men (OR: 0.98, 95%CI: 0.97-1.00).

conclusionsMD and insomnia were inversely associated with number of children in women while the association was not overall significant in men. The association was mediated by socioeconomic and lifestyle factors. Future mental health public health programs should address parity and sex differences when designing interventions.

Indexed as

ParitySleep Initiation and Maintenance DisordersAdultAgedAsian PeopleChildChinaCross-Sectional StudiesFemaleHumansMajor Depressive DisorderMaleMiddle AgedPregnancyPrevalenceChinaInsomniaMajor depressionParitySex differences

Identifiers

PMID32471396
PMCPMC7260797
OpenAlexW3031245805

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.