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中国农村老年女性不健康生活方式与代谢综合征的关系。

Associations of unhealthy lifestyles with metabolic syndrome in Chinese rural aged females.

机构信息

Henan Provincial People's Hospital, Zhengzhou, Henan, P.R. China.

Zhengzhou University People's Hospital, Zhengzhou, Henan, P.R. China.

出版信息

Sci Rep. 2020 Feb 17;10(1):2718. doi: 10.1038/s41598-020-59607-x.

DOI:10.1038/s41598-020-59607-x
PMID:32066855
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7026414/
Abstract

The purpose of this study is to update the prevalence of metabolic syndrome (MetS) and explore to identify the susceptible populations. A total of 38208 subjects aged 18 to 79 years were obtained from the Henan Rural Cohort Study (n = 39259). Five criteria (ATP β, IDF, JIS, CDS, EGIR) were used to estimate the prevalence of MetS. Multivariate logistic regression analysis was used to assess odds ratios (ORs) and 95% confidence interval (CI) of potential risk factors with MetS. The age-standardized prevalence of MetS were 27.87%, 24.63%, 27.40%, 18.00% and 8.91% according to the standard of ATP β, IDF, JIS, CDS, and EGIR, respectively. After adjusted for the potential confounding factors, aging, females, physical activity and the state of drinking were independent risk factors of MetS. MetS is positively associated with stroke and coronary heart disease in all five criteria (P < 0.01). The current data identify a high prevalence of MetS among Chinese rural adults. Especially for aged females with unhealthy lifestyle had a higher risk for MetS.

摘要

本研究旨在更新代谢综合征（MetS）的患病率，并探讨识别易感人群的方法。我们从河南农村队列研究中获得了 38208 名年龄在 18 至 79 岁的受试者（n=39259）。使用了 5 项标准（ATP β、IDF、JIS、CDS、EGIR）来估计 MetS 的患病率。使用多变量逻辑回归分析评估了具有 MetS 的潜在危险因素的比值比（ORs）和 95%置信区间（CI）。根据 ATP β、IDF、JIS、CDS 和 EGIR 的标准，年龄标准化的 MetS 患病率分别为 27.87%、24.63%、27.40%、18.00%和 8.91%。在调整了潜在的混杂因素后，年龄、女性、体力活动和饮酒状况是 MetS 的独立危险因素。MetS 与所有五项标准中的中风和冠心病均呈正相关（P<0.01）。目前的数据表明，中国农村成年人的 MetS 患病率较高。特别是对于年龄较大、生活方式不健康的女性，MetS 的风险更高。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1f63/7026414/b301cb715e0e/41598_2020_59607_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1f63/7026414/1718dc69890c/41598_2020_59607_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1f63/7026414/326b03a316a2/41598_2020_59607_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1f63/7026414/033224c4564f/41598_2020_59607_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1f63/7026414/b301cb715e0e/41598_2020_59607_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1f63/7026414/1718dc69890c/41598_2020_59607_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1f63/7026414/326b03a316a2/41598_2020_59607_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1f63/7026414/033224c4564f/41598_2020_59607_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1f63/7026414/b301cb715e0e/41598_2020_59607_Fig4_HTML.jpg

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