Using confirmatory factor analysis to explore associated factors of intimate partner violence in a sample of Chinese rural women: a cross-sectional study.BMJ Open. 2018 02 02; 8(2):e019465.BO
To estimate the prevalence of intimate partner violence (IPV) among a sample of rural Chinese women and to explore associated factors.
Rural areas of Guangyuan City, Sichuan, China.
We recruited 1501 women, aged 16 years and older, who had been living locally for at least 2 years and reported being married or in a relationship during the past 12 months. They were among a sample of 1898 potential participants from our larger parent study on the prevalence of depressive-distress symptoms.
Participants completed demographic and social economic measures, the Short Form of the Revised Conflict Tactics Scale and the Duke Social Support Index. We applied χ2 test, analysis of variance and confirmatory factor analysis for analysis.
The overall prevalence of IPV in the past 12 months was 29.05%; the prevalence of physical, psychological and sexual violence was 7.66%, 26.58% and 3.20%, respectively. The overall prevalence was highest among women aged 16-29 years, and was more common among those without a high school diploma and who saw their family's financial status as very poor or stagnant. Women who were not victims of IPV had higher levels of social support. Confirmatory factor analysis showed that the total effects of social support on physical, psychological and sexual violence were -0.12, -0.35 and -0.12, respectively. The indirect effects of objective economic status on physical, psychological and sexual violence were -0.047, -0.014 and -0.047, respectively, but the total effect was not significant. The indirect effect of education on psychological violence was -0.056.
IPV is common in rural Guangyuan. Our data are comparable with the findings from north-west of China. Social support is an important protective factor. Future work is needed to develop, test and later disseminate potential IPV interventions, with a focus on building actual and perceived supportive social networks.