Association between dietary branched-chain amino acids and multiple chronic conditions among older adults in Chinese communities.

IF 3.9 2区医学 Q2 NUTRITION & DIETETICS

Nutrition & Metabolism Pub Date : 2024-07-30 DOI:10.1186/s12986-024-00825-9

Yuanfeng Song, Ji Zhang, Ziqiang Luo, Lanlan Wu, Zhaopei Cai, Xiaoqi Zhong, Xiaoxue Zeng, Tingxi Cao, Hong-En Chen, Shan Xu, Chang-Yi Wang

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引用次数: 0

Abstract

Background: The association of BCAAs (isoleucine, leucine, and valine) with cardiovascular and cerebrovascular diseases has been widely recognized by researchers, but there is limited evidence to support the relationship between BCAAs and multiple chronic conditions (MCCs) in older adults. This study aimed to explore the correlation between BCAA levels in the diets of older adults and MCCs.

Methods: Based on a health management cohort project in Nanshan District of Shenzhen, 4278 individuals over 65 years old were selected as participants via multi-stage stratified sampling from May 2018 to December 2019. Data were collected using a validated semi-quantitative food frequency questionnaire, as well as anthropometric and chronic disease reports. MCC was defined as the coexistence of two or more chronic diseases, namely, hypertension, dyslipidemia, diabetes, CAD, stroke, CKD, and CLD. Multivariate unconditional logistic regression analysis was used to analyze the relationship between dietary BCAAs and MCCs in older adults, and then, gender stratification analysis was performed. A restricted cubic spline model (a fitted smooth curve) was used to determine the dose-response relationship of isoleucine with MCCs.

Results: A total of 4278 older adults aged 65 and above were included in this study, with an average age of 72.73 ± 5.49 years. The cohort included 1861 males (43.50%). Regardless of whether confounding factors were corrected, isoleucine was a risk factor for MCCs (OR = 3.388, 95%CI:1.415,8.109). After gender stratification, the relationships between dietary isoleucine and MCCs (OR = 6.902, 95%CI:1.875,25.402) and between leucine (OR = 0.506,95%CI:0.309,0.830) and MCCs were significant in women, but not in men. No significant association between valine and MCCs was observed. In addition, isoleucine was a risk factor for MCCs when its intake was greater than 4.297 g/d.

Conclusion: Isoleucine may play an important role in regulating age-related diseases. BCAAs such as isoleucine can be used as risk markers for MCCs in older adults.

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中国社区老年人膳食支链氨基酸与多种慢性病之间的关系。

背景：BCAAs（异亮氨酸、亮氨酸和缬氨酸）与心脑血管疾病的关系已得到研究人员的广泛认可，但支持BCAAs与老年人多种慢性疾病（MCCs）之间关系的证据却很有限。本研究旨在探讨老年人饮食中 BCAA 含量与 MCCs 之间的相关性：基于深圳市南山区健康管理队列项目，从2018年5月至2019年12月，通过多阶段分层抽样选取了4278名65岁以上的老年人作为参与者。数据收集采用经过验证的半定量食物频率问卷，以及人体测量和慢性病报告。MCC定义为同时患有两种或两种以上慢性疾病，即高血压、血脂异常、糖尿病、CAD、中风、慢性肾脏病和慢性肺病。多变量无条件逻辑回归分析用于分析老年人膳食中 BCAAs 与 MCC 之间的关系，然后进行性别分层分析。使用限制性立方样条模型（拟合平滑曲线）确定异亮氨酸与 MCCs 的剂量-反应关系：本研究共纳入了 4278 名 65 岁及以上的老年人，平均年龄为 72.73 ± 5.49 岁。其中包括 1861 名男性（43.50%）。无论是否对混杂因素进行校正，异亮氨酸都是 MCCs 的风险因素（OR = 3.388，95%CI:1.415,8.109）。性别分层后，膳食中的异亮氨酸与 MCCs（OR = 6.902，95%CI:1.875,25.402）和亮氨酸与 MCCs（OR = 0.506，95%CI:0.309,0.830）之间的关系在女性中显著，但在男性中不显著。缬氨酸与 MCCs 之间没有明显的关联。此外，当异亮氨酸的摄入量超过 4.297 克/天时，异亮氨酸是导致 MCCs 的风险因素：结论：异亮氨酸可能在调节与年龄有关的疾病方面发挥着重要作用。异亮氨酸等 BCAAs 可作为老年人罹患 MCCs 的风险指标。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Nutrition & Metabolism 医学-营养学

CiteScore

8.40

自引率

0.00%

发文量

审稿时长

4-8 weeks

期刊介绍： Nutrition & Metabolism publishes studies with a clear focus on nutrition and metabolism with applications ranging from nutrition needs, exercise physiology, clinical and population studies, as well as the underlying mechanisms in these aspects. The areas of interest for Nutrition & Metabolism encompass studies in molecular nutrition in the context of obesity, diabetes, lipedemias, metabolic syndrome and exercise physiology. Manuscripts related to molecular, cellular and human metabolism, nutrient sensing and nutrient–gene interactions are also in interest, as are submissions that have employed new and innovative strategies like metabolomics/lipidomics or other omic-based biomarkers to predict nutritional status and metabolic diseases. Key areas we wish to encourage submissions from include: -how diet and specific nutrients interact with genes, proteins or metabolites to influence metabolic phenotypes and disease outcomes; -the role of epigenetic factors and the microbiome in the pathogenesis of metabolic diseases and their influence on metabolic responses to diet and food components; -how diet and other environmental factors affect epigenetics and microbiota; the extent to which genetic and nongenetic factors modify personal metabolic responses to diet and food compositions and the mechanisms involved; -how specific biologic networks and nutrient sensing mechanisms attribute to metabolic variability.