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饮食习惯、生活方式和昼夜节律与老年人代谢综合征的关联——基于人群的汉堡城市健康研究的启示。

Association of Dietary Pattern, Lifestyle and Chronotype with Metabolic Syndrome in Elderly-Lessons from the Population-Based Hamburg City Health Study.

机构信息

Institute for Occupational and Maritime Medicine (ZfAM), University Medical Center Hamburg-Eppendorf (UKE), 20459 Hamburg, Germany.

Department of Cardiology, University Heart and Vascular Center, 20251 Hamburg, Germany.

出版信息

Int J Environ Res Public Health. 2021 Dec 30;19(1):377. doi: 10.3390/ijerph19010377.

DOI:10.3390/ijerph19010377
PMID:35010639
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8744785/
Abstract

In aging populations, the increasing prevalence of metabolic syndrome and the resulting elevated risk of developing non-communicable diseases is a major challenge for worldwide health care. The elderly population-based Hamburg City Health Study (HCHS) allows investigating the association in the relevant age group 45-74 years. For 3513 of 10,000 participants, self-reported information on dietary patterns (DASH, MEDAS), chronotype, lifestyle, and data on metabolic syndrome parameters was available. Overall, having a "low" DASH score was a statistically significant risk factor (OR 1.23; 95% CI 1.01-1.48). Only for "late" chronotype, a slightly elevated OR (1.06) was found, but no statistically significant effect on the outcome of metabolic syndrome. Still, considering chronotype vastly improved the model. However, a trend of an increasing predicted probability from early to late chronotype was found for participants with low adherence to the DASH diet. Future research should focus on options for prevention in persons with late chronotype, so they can be supported better in adherence to, e.g., DASH diet to lower their risk.

摘要

在老龄化人口中,代谢综合征的患病率不断上升,由此导致的非传染性疾病发病风险增加,是全球医疗保健的一个主要挑战。基于老年人群的汉堡城市健康研究(HCHS)允许在相关年龄组 45-74 岁之间进行调查。对于 10000 名参与者中的 3513 名,有关于饮食模式(DASH、MEDAS)、昼夜型、生活方式和代谢综合征参数的数据的自我报告信息可用。总体而言,DASH 评分较低是一个具有统计学意义的风险因素(OR 1.23;95%CI 1.01-1.48)。只有对于“晚”昼夜型,发现了略微升高的 OR(1.06),但对代谢综合征的结果没有统计学意义。尽管如此,考虑昼夜型大大改进了模型。然而,对于低 DASH 饮食依从性的参与者,发现从早到晚昼夜型的预测概率呈上升趋势。未来的研究应侧重于为晚昼夜型人群提供预防选择,以便更好地支持他们遵守 DASH 饮食等,以降低他们的风险。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba42/8744785/af330bf04f58/ijerph-19-00377-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba42/8744785/af330bf04f58/ijerph-19-00377-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba42/8744785/af330bf04f58/ijerph-19-00377-g001.jpg

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