水果和蔬菜摄入量可改变超加工食品与代谢综合征之间的关联。

IF 3.9 2区 医学 Q2 NUTRITION & DIETETICS
Somayeh Hosseinpour-Niazi, Hanieh Malmir, Parvin Mirmiran, Maryam Shabani, Mitra Hasheminia, Fereidoun Azizi
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引用次数: 0

摘要

背景:这项前瞻性队列研究旨在调查超加工食品(UPF)与代谢综合征(MetS)风险之间的关系,并评估水果和蔬菜摄入量以及体重变化是否会改变这种关系:我们纳入了 1915 名参加德黑兰血脂和血糖研究(TLGS)的健康参与者,他们都有完整的人口统计学、人体测量和饮食测量数据。根据诺瓦(NOVA)分类系统,使用经过验证的食物频率问卷评估 UPF 消费量。MetS是根据联合临时声明定义的。多变量调整 Cox 回归用于估算不同 UPF 百分位数的 MetS 事件危险比 (HRs)。使用 Cox 回归联合分类法评估了水果和蔬菜摄入量及体重变化对这一关联的影响:结果:在对混杂因素进行调整后,UFP摄入量与MetS风险没有关联。然而,在对膳食纤维、水果和蔬菜进行调整后,与最低三分位数相比,UPF 消费量的最高三分位数与 MetS 风险呈正相关。在 MetS 风险方面,水果、蔬菜和膳食纤维摄入量与 UPF 摄入量之间存在明显的交互作用(所有 P 值均为结论):多吃水果和蔬菜可减轻 UPF 对 MetS 患病风险的不利影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fruit and vegetable intake modifies the association between ultra-processed food and metabolic syndrome.

Background: This prospective cohort study aimed to investigate the association between ultra-processed food (UPF) and the risk of metabolic syndrome (MetS), as well as to assess whether fruit and vegetable intake and weight change modify this association.

Methods: We included 1915 healthy participants who participated in the Tehran Lipid and Glucose Study (TLGS), all of whom had complete demographic, anthropometric, and dietary measurements. A validated food frequency questionnaire was used to assess UPF consumption based on the NOVA classification system. MetS was defined according to the Joint Interim Statement. Multivariable adjusted Cox regression was used to estimate hazard ratios (HRs) for MetS events across tertiles of UPF. The effect of fruit and vegetable consumption and weight change on this association was assessed using joint classification by Cox regression.

Results: UFP consumption showed no association with MetS risk after adjusting for confounders. However, after adjustment for dietary fiber, fruits, and vegetables, the highest tertile of UPF consumption was positively linked to MetS risk, compared to the lowest tertile. There was a significant interaction between fruit, vegetable, and dietary fiber intake and UPF consumption concerning the risk of MetS (All P values < 0.05). Among individuals consuming less than 248 g/day of fruit, the risk of MetS increased by 54% (confidence interval: 1.13-2.10) in the highest UPF tertile. Consuming vegetables and dietary fiber below the median (258 g/day and 42.2 g/day, respectively) increased the risk of MetS in the third tertile of UPF. However, consuming vegetables and fiber ≥ median intake, reduced the risk of MetS among those with the lowest UPF consumption. Furthermore, the risk of MetS was observed in the third tertile of UPF consumption among individuals with fruit and vegetable consumption < 537 g/day. UPF consumption was not associated with the risk of MetS in different weight change statuses.

Conclusions: Consuming more fruits and vegetables mitigated the adverse effect of UPF on the risk of developing MetS.

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来源期刊
Nutrition & Metabolism
Nutrition & Metabolism 医学-营养学
CiteScore
8.40
自引率
0.00%
发文量
78
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.
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