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Joint effects of HPV-related knowledge and socio-demographic factors on HPV testing behaviour among females in Shenzhen

医学 住所 逻辑回归 优势比 宫颈癌 置信区间 人口 人口学 环境卫生 癌症 内科学 社会学
作者
Wei Lin,Bin Chen,Haiyan Hu,Shixin Yuan,Bo Wu,Chuyan Zhong,Weikang Huang,Zhihua Liu,Yueyun Wang
出处
期刊:European journal of public health [Oxford University Press]
卷期号:31 (3): 582-588 被引量:7
标识
DOI:10.1093/eurpub/ckab049
摘要

Abstract Background Limited population-based studies explore the utilization and associated barriers or facilitators to cervical cancer screening in China. We attempted to investigate the associations of socio-demographic factors, HPV specific knowledge with HPV testing behaviour in Shenzhen, China. Methods A citywide cross-sectional survey was conducted from January to June 2015 in Shenzhen city by using a multistage stratified cluster sampling method. Socio-demographic information, awareness and specific knowledge of HPV, practice of HPV testing, and HPV vaccination-related attitude were collected. Multivariate logistic regression model was used to analyse possible associations. Results Approximately one third of total 8639 women aged from 30 to 60 years old had ever received HPV testing. Overall, 67.6% of all participants demonstrated low knowledge level of HPV. High HPV knowledge level was significantly associated with HPV testing behaviour (odds ratio: 3.792, 95% confidence interval: 3.400–4.230). The impact of residence and education on testing behaviour only turned to be significant if women had low level of HPV knowledge (P for multiplicative interactions: 0.001 and <0.001, respectively), whereas monthly income exerted promotion effects apparently among those with high knowledge level (P for multiplicative interaction: 0.037). Conclusions Our study revealed gaps in HPV knowledge and screening participation among Chinese women, and provided novel clues that women with high HPV knowledge level would be more appeal to involve in HPV testing behaviour. The influence of HPV-related knowledge on HPV testing also lies in the joint effects with socio-demographic factors, including residence, education and monthly income.
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