Evidence mapPaperPMID 40933416Full record

ArticleFrontiers in public health2025

Trends of domestic violence against women in China: an age-period-cohort analysis.

Hui Shen, Yongxiang Xie

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Hui ShenDepartment of Sociology, Fudan University, Shanghai, China.
Yongxiang XieSchool of Educational Science, Anhui Normal University, Wuhu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Domestic violence (DV) against women is a worldwide public health problem. This study explored the dynamics of DV in China from 1990 to 2010. Methods: Based on nationally representative data from the 1990, 2000, and 2010 China Women's Social Status Survey (CWSS) involving 29,995 women, we employed the Hierarchical APC-Cross-Classified Random Effects Models (HAPC-CCREM) to disentangle the effects of age, period and cohort on DV trends. Results: The reported overall prevalence of DV substantially declined from 26.7% in 1990 to 5.4% in 2010. The decline was more pronounced in rural areas (from 31.9 to 7.8%) than in urban areas (from 21.4 to 3.2%). The highest prevalence of reported violence occurred among women aged 30-34. However, among rural women, the risk increased with age. The period effect revealed a consistent decline in women's risk of DV over time, with rural areas showing a faster reduction than urban areas. The cohort effect indicated a significant decrease in risk for women born between 1976 and 1990 compared to earlier cohorts. Among urban women, the risk remained relatively stable across cohorts, whereas rural women experienced a marked decline. Conclusions: Overall, the risk of DV against women showed a downward trend. Distinct age, period, and cohort effects were observed, with a higher risk among women aged 30-34 and a lower risk among those born after 1975. The disparity in DV risk between urban and rural women narrowed over time and across birth cohorts. These patterns may be linked to broader shifts such as anti-domestic violence legislation, public health education, and improvements in women's socio-economic status.

Indexed as

Domestic ViolenceAdolescentAdultAge FactorsChinaCohort StudiesFemaleHumansMiddle AgedPrevalenceRural PopulationUrban PopulationYoung Adultage-period-cohort effectdomestic violenceruralurbanwomen

Identifiers

PMID40933416
PMCPMC12417488

What Socratic 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 Socratic graph.