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一项横断面研究表明,按性别和年龄划分的成年人健康饮食指数模式可预测心血管代谢风险因素。

Healthy eating index patterns in adults by sex and age predict cardiometabolic risk factors in a cross-sectional study.

作者信息

Artegoitia Virginia M, Krishnan Sridevi, Bonnel Ellen L, Stephensen Charles B, Keim Nancy L, Newman John W

机构信息

Obesity and Metabolism Research Unit, United States Department of Agriculture-Agricultural Research Services-Western Human Nutrition Research Center, 430 West Health Sciences Drive, Davis, CA, 95616, USA.

Department of Nutrition, University of California Davis, Davis, CA, USA.

出版信息

BMC Nutr. 2021 Jun 22;7(1):30. doi: 10.1186/s40795-021-00432-4.

Abstract

BACKGROUND

Associations between diet and cardiometabolic disease (CMD) risk may vary in men and women owing to sex differences in eating habits and physiology. The current secondary analysis sought to determine the ability of sex differences in dietary patterns to discriminate groups with or without CMD risk factors (CMDrf) in the adult population and if this was influenced by age.

METHODS

Diet patterns and quality were evaluated using 24 h recall-based Healthy Eating Index (HEI-2015) in free-living apparently healthy men (n = 184) and women (n = 209) 18-65 y of age with BMIs of 18-44 kg/m. Participants were stratified into low- and high-CMDrf groups based on the presence/absence of at least one CMDrf: BMI > 25 kg/m; fasting triglycerides > 150 mg/dL; HDL cholesterol < 50 mg/dL-women or < 40 mg/dL-men; HOMA > 2; HbA1c > 5.7. Sex by age dietary patterns were stratified by multivariate analyses, with metabolic variable associations established by stepwise discriminant analysis.

RESULTS

Diet quality increased with age in both sexes (P < 0.01), while women showed higher fruit, vegetable and saturated fat intake as a percentage of total energy (P < 0.05). The total-HEI score (i.e. diet quality) was lower in the high-CMDrf group (P = 0.01), however, diet quality parameters predicted CMDrf presence more accurately when separated by sex. Lower 'total vegetable' intake in the high-CMDrf group in both sexes, while high-CMDrf men also had lower 'total vegetables', 'greens and beans' intake, and high-CMDrf women had lower 'total fruits', 'whole-fruits', 'total vegetables', 'seafood and plant-proteins', 'fatty acids', and 'saturated fats' intakes (P < 0.05). Moreover, 'dairy' intake was higher in high-CMDrf women but not in men (sex by 'dairy' interaction P = 0.01). Sex by age diet pattern models predicted CMDrf with a 93 and 89% sensitivity and 84 and 92% specificity in women and men, respectively.

CONCLUSIONS

Sex and age differences in dietary patterns classified participants with and without accepted CMDrfs, supporting an association between specific diet components and CMD risk that differs by sex. Including sex specific dietary patterns into health assessments may provide targeted nutritional guidance to reduce the burden of cardiovascular disease.

TRIAL REGISTRATION

ClinicalTrials.gov : NCT02367287 . ClinicalTrials.gov : NCT02298725 .

摘要

背景

由于饮食习惯和生理机能方面的性别差异,饮食与心血管代谢疾病(CMD)风险之间的关联在男性和女性中可能有所不同。当前的二次分析旨在确定饮食模式中的性别差异对区分成年人群中有无CMD风险因素(CMDrf)群体的能力,以及这是否受年龄影响。

方法

采用基于24小时回忆法的健康饮食指数(HEI - 2015)对年龄在18 - 65岁、体重指数(BMI)为18 - 44kg/m²的自由生活、表面健康的男性(n = 184)和女性(n = 209)的饮食模式和质量进行评估。根据是否存在至少一种CMDrf将参与者分为低CMDrf组和高CMDrf组:BMI > 25kg/m²;空腹甘油三酯> 150mg/dL;高密度脂蛋白胆固醇< 50mg/dL(女性)或< 40mg/dL(男性);稳态模型评估(HOMA)> 2;糖化血红蛋白(HbA1c)> 5.7。通过多变量分析对按年龄分层的性别饮食模式进行分层,通过逐步判别分析建立代谢变量关联。

结果

男女两性的饮食质量均随年龄增长而提高(P < 0.01),而女性摄入的水果、蔬菜和饱和脂肪占总能量的百分比更高(P < 0.05)。高CMDrf组的总HEI得分(即饮食质量)较低(P = 0.01),然而,按性别分开时,饮食质量参数能更准确地预测CMDrf的存在。高CMDrf组中男女的“蔬菜总量”摄入量均较低,而高CMDrf组男性的“蔬菜总量”、“绿叶蔬菜和豆类”摄入量也较低,高CMDrf组女性的“水果总量”、“完整水果”、“蔬菜总量”、“海鲜和植物蛋白”、“脂肪酸”和“饱和脂肪”摄入量较低(P < 0.05)。此外,高CMDrf组女性的“乳制品”摄入量较高,而男性则不然(“乳制品”的性别交互作用P = 0.01)。按年龄分层的性别饮食模式模型预测CMDrf的敏感性在女性和男性中分别为93%和89%,特异性分别为84%和92%。

结论

饮食模式中的性别和年龄差异对有和没有公认CMDrf的参与者进行了分类,支持特定饮食成分与CMD风险之间的关联存在性别差异。将特定性别的饮食模式纳入健康评估可能会提供有针对性的营养指导,以减轻心血管疾病的负担。

试验注册

ClinicalTrials.gov:NCT02367287。ClinicalTrials.gov:NCT02298725。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/938a/8218401/a3d9d11782b4/40795_2021_432_Fig1_HTML.jpg

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