Association of Body Mass Index and Dysmenorrhea : A systematic Review and Meta Analysis of Observation Studies
CURRENT WOMENS HEALTH REVIEWS(2022)
摘要
Background: Dysmenorrhea or menstrual pain is a commonly occurring disorder in re-productive age women with different proposed risk factors including body mass index. Objective: This study aimed to investigate the association of body mass index and dysmenorrhea using a systematic review and meta-analysis approach. Methods: Academic databases Scopus, PubMed CENTRAL, Embase, ProQuest, Science Direct, and ISI Web of Science as well as Google Scholar-were searched systematically from inception un-til the end of February, 2020. Original researches published in English with observational designs were included to examine the association of body mass index and dysmenorrhea as a primary out-come. Newcastle Ottawa scale was used to evaluate the methodological quality of the studies. Due to the variation of reported data across studies, all data were converted to Pearson correlation coeffi-cient and corrected by transforming to fisher's Z score. Then meta-analysis was performed using a random-effects model with Der-Simonian and Laird method. Results: A total of 61 studies with 57,079 participants, of which 25,044 reported having dysmenor-rhea were included. The pooled estimated effect size of correlation showed trivial to small correla-tion between body mass index and dysmenorrhea with corrected fisher's z score of 0.12 (95% CI: 0.08; 0.17, I2=95%). While publication bias was probable, results were corrected using the fill & trim method. The corrected results based on this method showed that pooled Fisher's z-score for the association of body mass index and dysmenorrhea was 0.04 (95% CI:-0.009; 0.085). Conclusion: No association was found between body mass index and dysmenorrhea. But this find-ing should be interpreted with caution considering the included studies' limitations.
更多查看译文
关键词
Body mass index,dysmenorrhea,systematic review,meta-analysis,Fisher's z-score,body mass index
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要