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Association between body mass index and endometriosis risk: a meta-analysis.


ABSTRACT:

Background

Epidemiological studies have sought to establish a relationship between a woman's current body mass index and endometriosis, but with varying results. This meta-analysis was to summarize the current epidemiological evidence.

Methods

Pertinent studies were identified by searching PubMed and Web of Science through November 2016. Study-specific risk estimates were combined using fixed or random effects models depending on whether significant heterogeneity was detected.

Results

A total of 11 studies (two cohort studies and nine case-control studies) was included in the meta-analysis. The pooled relative risk of endometriosis was 0.67 (95% CI: 0.53, 0.84) for each 5 kg/m2 increase in current body mass index, with statistical significant heterogeneity across the studies (P <0.001, I2 =86.9%). Compared with normal weight women, the pooled relative risk for obese women was 0.89 (95% CI: 0.83, 0.96), which was lower than that for overweight women (relative risk =0.97; 95% CI: 0.91, 1.05). The combined estimate was robust across subgroup and sensitivity analyses and no observed publication bias was detected.

Conclusion

This study suggested that higher body mass index may be associated with lower risk of endometriosis. Further work will need to focus on elucidating underlying biologic mechanism that contribute to the initiation of endometriosis.

SUBMITTER: Liu Y 

PROVIDER: S-EPMC5564533 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Association between body mass index and endometriosis risk: a meta-analysis.

Liu Yong Y   Zhang Weiyuan W  

Oncotarget 20170701 29


<h4>Background</h4>Epidemiological studies have sought to establish a relationship between a woman's current body mass index and endometriosis, but with varying results. This meta-analysis was to summarize the current epidemiological evidence.<h4>Methods</h4>Pertinent studies were identified by searching PubMed and Web of Science through November 2016. Study-specific risk estimates were combined using fixed or random effects models depending on whether significant heterogeneity was detected.<h4>  ...[more]

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