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差异性性网络连通性为细菌性阴道病患病率的人群水平差异提供了一种简洁的解释:一个数据驱动、模型支持的假说。

Differential sexual network connectivity offers a parsimonious explanation for population-level variations in the prevalence of bacterial vaginosis: a data-driven, model-supported hypothesis.

作者信息

Kenyon Chris R, Delva Wim, Brotman Rebecca M

机构信息

STI Unit, Institute of Tropical Medicine, Nationalestraat 155, 2000, Antwerp, Belgium.

The South African DST-NRF Centre of Excellence in Epidemiological, Modelling and Analysis (SACEMA), Stellenbosch, South Africa.

出版信息

BMC Womens Health. 2019 Jan 10;19(1):8. doi: 10.1186/s12905-018-0703-0.

Abstract

BACKGROUND

The prevalence of bacterial vaginosis (BV) and vaginal microbiota types varies dramatically between different populations around the world. Understanding what underpins these differences is important, as high-diversity microbiotas associated with BV are implicated in adverse pregnancy outcomes and enhanced susceptibility to and transmission of sexually transmitted infections.

MAIN TEXT

We hypothesize that these variations in the vaginal microbiota can, in part, be explained by variations in the connectivity of sexual networks. We argue: 1) Couple-level data suggest that BV-associated bacteria can be sexually transmitted and hence high sexual network connectivity would be expected to promote the spread of BV-associated bacteria. Epidemiological studies have found positive associations between indicators of network connectivity and the prevalence of BV; 2) The relationship between BV prevalence and STI incidence/prevalence can be parsimoniously explained by differential network connectivity; 3) Studies from other mammals are generally supportive of the association between network connectivity and high-diversity vaginal microbiota.

CONCLUSION

To test this hypothesis, we propose a combination of empirical and simulation-based study designs.

摘要

背景

细菌性阴道病(BV)的患病率和阴道微生物群类型在世界各地不同人群之间差异巨大。了解这些差异的根源很重要,因为与BV相关的高多样性微生物群与不良妊娠结局以及性传播感染易感性增加和传播有关。

正文

我们假设,阴道微生物群的这些差异部分可由性网络连通性的差异来解释。我们认为:1)夫妻层面的数据表明,与BV相关的细菌可通过性传播,因此,性网络连通性高有望促进与BV相关细菌的传播。流行病学研究发现网络连通性指标与BV患病率之间存在正相关;2)BV患病率与性传播感染发病率/患病率之间的关系可通过不同的网络连通性得到简洁解释;3)来自其他哺乳动物的研究总体上支持网络连通性与高多样性阴道微生物群之间的关联。

结论

为验证这一假设,我们提出了实证研究设计与基于模拟的研究设计相结合的方法。

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