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瑞典饮食指南指数、肠道微生物α多样性与代谢综合征患病率——瑞典心肺生物影像研究(SCAPIS)中的观察结果

A Swedish dietary guideline index, gut microbial α-diversity and prevalence of metabolic syndrome - observations in the Swedish CArdioPulmonary bioImage Study (SCAPIS).

作者信息

Ericson Ulrika, Hellstrand Sophie, Larsson Anna, Miari Mariam, Sayols-Baixeras Sergi, Dekkers Koen F, Bergström Göran, Malinovschi Andrei, Engström Gunnar, Ärnlöv Johan, Fall Tove, Orho-Melander Marju

机构信息

Department of Clinical Sciences in Malmö, Diabetes and Cardiovascular Disease, Lund University, Malmö, Sweden.

Molecular Epidemiology, Department of Medical Sciences, Uppsala University, Uppsala, Sweden.

出版信息

Food Nutr Res. 2024 Nov 28;68. doi: 10.29219/fnr.v68.10547. eCollection 2024.

DOI:10.29219/fnr.v68.10547
PMID:39691688
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11650442/
Abstract

BACKGROUND

Metabolic syndrome (MetS) is characterized by coexisting risk factors for type 2 diabetes and cardiovascular disease. Diet is of importance in their aetiology, and gut microbiota (GM) may constitute a link between diet and metabolic health. Understanding the interplay between diet and GM could contribute novel insights for future dietary guidelines, and aid in preventive actions to motivate adherence to dietary guidelines.

OBJECTIVE

We intended to create a Swedish dietary guideline index (SweDGI) measuring adherence to 12 Swedish dietary guidelines and examine whether SweDGI and its components are associated with GM α-diversity (Shannon index) and prevalent MetS, and if the association between the Shannon index and MetS differs depending on SweDGI.

DESIGN

SweDGI was based on food-frequency data assessed 2014-2018 in 10,396 diabetes-free participants from the Malmö and Uppsala-sites of the Swedish CArdioPulmonary bioImage Study (SCAPIS) (50-64 y, 53% women). We estimated the Shannon index from shotgun metagenomic sequencing-data to assess microbial richness and evenness. We used a general linear model to examine cross-sectional SweDGI-Shannon associations and logistic regression for associations with MetS.

RESULTS

Most guidelines were followed by less than half of the participants. Men showed poorer adherence. Higher SweDGI was linked to higher Shannon index (-trend across five SweDGI-groups = 1.7 × 10). Most guidelines contributed to this observation. Higher SweDGI and Shannon index were associated with lower MetS-prevalence, where the lowest prevalence was observed among those with both high SweDGI and high Shannon index (odds ratio:0.43; 95% confidence interval:0.35, 0.52). Both the Shannon index and SweDGI were associated with MetS, independently of the level of the other factor (-interaction = 0.82).

CONCLUSIONS

We created a new index to comprehensively reflect adherence to the Swedish dietary guidelines in sub-cohorts within the large multicentre SCAPIS study. Better adherence was associated with a richer and more even GM and lower prevalence of MetS. The inverse association between the Shannon index and MetS was consistent at different levels of adherence to dietary guidelines.

摘要

背景

代谢综合征(MetS)的特征是存在2型糖尿病和心血管疾病的共存危险因素。饮食在其病因中具有重要作用,而肠道微生物群(GM)可能构成饮食与代谢健康之间的联系。了解饮食与GM之间的相互作用可为未来的饮食指南提供新的见解,并有助于采取预防措施以促进对饮食指南的遵守。

目的

我们旨在创建一个瑞典饮食指南指数(SweDGI),以衡量对12条瑞典饮食指南的遵守情况,并研究SweDGI及其组成部分是否与GMα多样性(香农指数)和普遍存在的MetS相关,以及香农指数与MetS之间的关联是否因SweDGI而异。

设计

SweDGI基于2014年至2018年在瑞典心肺生物图像研究(SCAPIS)的马尔默和乌普萨拉站点的10396名无糖尿病参与者(50 - 64岁,53%为女性)中评估的食物频率数据。我们从鸟枪法宏基因组测序数据中估计香农指数,以评估微生物的丰富度和均匀度。我们使用一般线性模型来检查横断面SweDGI与香农指数的关联,并使用逻辑回归分析与MetS的关联。

结果

大多数指南的遵循者不到一半的参与者。男性的遵守情况较差。较高的SweDGI与较高的香农指数相关(五个SweDGI组的趋势 = 1.7×10)。大多数指南都促成了这一观察结果。较高的SweDGI和香农指数与较低的MetS患病率相关,在SweDGI和香农指数都高的人群中患病率最低(优势比:0.43;95%置信区间:0.35,0.52)。香农指数和SweDGI都与MetS相关,且独立于另一个因素的水平(交互作用 = 0.82)。

结论

我们创建了一个新的指数,以全面反映大型多中心SCAPIS研究中亚队列对瑞典饮食指南的遵守情况。更好的遵守与更丰富、更均匀的GM以及更低的MetS患病率相关。在不同的饮食指南遵守水平下,香农指数与MetS之间的负相关是一致的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4678/11650442/e7ef0fcd9e80/FNR-68-10547-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4678/11650442/24bf03e155eb/FNR-68-10547-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4678/11650442/435ef84cea3b/FNR-68-10547-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4678/11650442/040f2f4d0ec5/FNR-68-10547-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4678/11650442/e7ef0fcd9e80/FNR-68-10547-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4678/11650442/24bf03e155eb/FNR-68-10547-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4678/11650442/435ef84cea3b/FNR-68-10547-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4678/11650442/040f2f4d0ec5/FNR-68-10547-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4678/11650442/e7ef0fcd9e80/FNR-68-10547-g004.jpg

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