The association between vitamin E intake and hepatic steatosis in general and obese populations.

IF 3.9 2区医学 Q2 NUTRITION & DIETETICS Nutrition & Metabolism Pub Date : 2024-07-30 DOI:10.1186/s12986-024-00830-y

Bin Chen, Li Han, Xingxing Chen

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Abstract

Purpose: Using data from the National Health and Nutrition Examination Survey (NHANES) and employing Controlled Attenuation Parameter (CAP) measures, this study explores the correlation between vitamin E (VE) intake and hepatic steatosis and its impact on different subsets.

Materials and methods: We selected 5757 participants with CAP data from the 2017-2020 NHANES dataset. Daily VE intake was assessed by a 24-hour dietary recall. Hepatic fat content was quantified using transient elastography to measure CAP. Stratified multivariable regression analysis investigated relationships in different subsets, and a generalized additive model identified nonlinear relationships and thresholds.

Results: After adjusting for confounders, higher VE intake correlated with lower CAP levels. Subgroup analyses and tests for interaction revealed a significantly stronger negative correlation between VE intake and CAP in obese individuals. Further analysis indicated a curvilinear relationship between VE intake and the severity of liver fat degeneration in both the general study population and the obese subgroup, demonstrating a threshold effect. In the general population, VE intake below the threshold (6.58 mg/day) is positively correlated with CAP levels, whereas intake above this threshold shows a negative correlation. For obese individuals, the threshold is set at 7.37 mg/day, above which the negative correlation with CAP is even more pronounced.

Conclusion: Our study revealed a negative correlation between VE intake and hepatic fat content, highlighting the potentially crucial role VE plays in obese fatty liver patients. Importantly, we identified threshold effects of VE intake in both general and obese populations. Our results support clinical nutritional interventions, personalized dietary guidance, and the development of drugs to combat fatty liver.

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普通人群和肥胖人群维生素 E 摄入量与肝脏脂肪变性之间的关系。

目的：本研究利用美国国家健康与营养调查（NHANES）的数据，并采用受控衰减参数（CAP）测量方法，探讨维生素 E（VE）摄入量与肝脂肪变性之间的相关性及其对不同亚群的影响：我们从 2017-2020 年 NHANES 数据集中选取了 5757 名有 CAP 数据的参与者。每日 VE 摄入量通过 24 小时饮食回忆进行评估。使用瞬态弹性成像技术对肝脏脂肪含量进行量化，以测量 CAP。分层多变量回归分析调查了不同子集中的关系，广义相加模型确定了非线性关系和阈值：结果：在对混杂因素进行调整后，较高的 VE 摄入量与较低的 CAP 水平相关。分组分析和交互作用检验显示，肥胖者的 VE 摄入量与 CAP 之间的负相关性明显更强。进一步的分析表明，在一般研究人群和肥胖亚组中，VE 摄入量与肝脏脂肪变性的严重程度呈曲线关系，表明存在阈值效应。在一般人群中，低于阈值（6.58 毫克/天）的 VE 摄入量与 CAP 水平呈正相关，而高于该阈值的摄入量则呈负相关。对于肥胖者，阈值设定为 7.37 毫克/天，超过这一阈值，与 CAP 的负相关性更加明显：我们的研究揭示了 VE 摄入量与肝脏脂肪含量之间的负相关性，突出了 VE 在肥胖脂肪肝患者中的潜在关键作用。重要的是，我们在普通人群和肥胖人群中都发现了VE摄入的阈值效应。我们的研究结果支持临床营养干预、个性化膳食指导和防治脂肪肝药物的开发。

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.