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评估膳食宏量营养素与心血管代谢疾病之间的直接效应,并考虑肥胖和身体活动的中介作用。

Estimating the Direct Effect between Dietary Macronutrients and Cardiometabolic Disease, Accounting for Mediation by Adiposity and Physical Activity.

作者信息

Pomares-Millan Hugo, Atabaki-Pasdar Naeimeh, Coral Daniel, Johansson Ingegerd, Giordano Giuseppe N, Franks Paul W

机构信息

Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital, 21428 Malmö, Sweden.

Department of Public Health and Clinical Medicine, Umeå University, 90187 Umeå, Sweden.

出版信息

Nutrients. 2022 Mar 13;14(6):1218. doi: 10.3390/nu14061218.

Abstract

Assessing the causal effects of individual dietary macronutrients and cardiometabolic disease is challenging because distinguish direct effects from those mediated or confounded by other factors is difficult. To estimate these effects, intake of protein, carbohydrate, sugar, fat, and its subtypes were obtained using food frequency data derived from a Swedish population-based cohort (n~60,000). Data on clinical outcomes (i.e., type 2 diabetes (T2D) and cardiovascular disease (CVD) incidence) were obtained by linking health registry data. We assessed the magnitude of direct and mediated effects of diet, adiposity and physical activity on T2D and CVD using structural equation modelling (SEM). To strengthen causal inference, we used Mendelian randomization (MR) to model macronutrient intake exposures against clinical outcomes. We identified likely causal effects of genetically predicted carbohydrate intake (including sugar intake) and T2D, independent of adiposity and physical activity. Pairwise, serial- and parallel-mediational configurations yielded similar results. In the integrative genomic analyses, the candidate causal variant localized to the established T2D gene . These findings may be informative when considering which dietary modifications included in nutritional guidelines are most likely to elicit health-promoting effects.

摘要

评估个体膳食常量营养素与心血管代谢疾病之间的因果关系具有挑战性,因为很难将直接影响与其他因素介导或混淆的影响区分开来。为了估计这些影响,我们使用来自瑞典人群队列(约60,000人)的食物频率数据,获取了蛋白质、碳水化合物、糖、脂肪及其亚型的摄入量。通过链接健康登记数据,获得了临床结局(即2型糖尿病(T2D)和心血管疾病(CVD)发病率)的数据。我们使用结构方程模型(SEM)评估了饮食、肥胖和身体活动对T2D和CVD的直接和介导影响的大小。为了加强因果推断,我们使用孟德尔随机化(MR)对临床结局的常量营养素摄入暴露进行建模。我们确定了遗传预测的碳水化合物摄入量(包括糖摄入量)与T2D之间可能的因果关系,独立于肥胖和身体活动。成对、序列和平行介导配置产生了相似的结果。在综合基因组分析中,候选因果变异定位于已确定的T2D基因。在考虑营养指南中包含的哪些饮食调整最有可能产生促进健康的效果时,这些发现可能会提供信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d719/8949537/cbc723f8d98a/nutrients-14-01218-g001.jpg

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