Cancer Epidemiology Division, Cancer Council Victoria, Level 8, 200 Victoria Parade, East Melbourne, Melbourne, VIC, 3002, Australia.
Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.
Eur J Nutr. 2024 Dec;63(8):3207-3221. doi: 10.1007/s00394-024-03501-z. Epub 2024 Sep 17.
Macronutrient intakes vary across people and economic status, leading to a disparity in diet-related metabolic diseases. This study aimed to provide insight into this by: (1) identifying dietary patterns in adults using reduced rank regression (RRR), with macronutrients as response variables, and (2) investigating the associations between economic status and macronutrient based dietary patterns, and between dietary patterns with central obesity (waist circumference) and systemic inflammation (C-reactive protein [CRP]).
41,849 US participants from the National Health and Nutrition Examination Survey (NHANES), 1999-2018 were included. The percentages of energy from protein, carbohydrates, saturated fats, and unsaturated fats were used as response variables in RRR. Multivariable generalized linear models with Gaussian distribution were employed to investigate the associations.
Four dietary patterns were identified. Economic status was positively associated with both the high fat, low carbohydrate [β = 0.22; 95% CI: 0.16, 0.28] and high protein patterns [β = 0.07; 95% CI: 0.03, 0.11], and negatively associated with both the high saturated fat [β = -0.06; 95% CI: -0.08, -0.03] and the low alcohol patterns [β = -0.08; 95% CI; -0.10, -0.06]. The high saturated fat pattern was positively associated with waist circumference [β = 1.71; 95% CI: 0.97, 2.44] and CRP [β = 0.37; 95% CI: 0.26, 0.47].
Macronutrient dietary patterns, which varied by economic status and were associated with metabolic health markers, may explain associations between economic status and health.
由于人们的宏量营养素摄入量存在差异，且这种差异与经济地位有关，因此导致了与饮食相关的代谢性疾病的发生存在差异。本研究旨在通过以下方法来深入了解这一现象：（1）使用降秩回归（RRR），以宏量营养素作为因变量，确定成年人的饮食模式；（2）研究经济地位与宏量营养素为基础的饮食模式之间的关系，以及饮食模式与中心性肥胖（腰围）和全身炎症（C 反应蛋白 [CRP]）之间的关系。
纳入了来自 1999 年至 2018 年美国国家健康和营养调查（NHANES）的 41849 名美国参与者。RRR 中使用的因变量为蛋白质、碳水化合物、饱和脂肪和不饱和脂肪的能量百分比。采用具有正态分布的多变量广义线性模型来研究相关性。
确定了四种饮食模式。经济地位与高脂肪、低碳水化合物模式呈正相关[β=0.22；95%置信区间：0.16，0.28]，与高蛋白模式呈正相关[β=0.07；95%置信区间：0.03，0.11]，与高饱和脂肪模式呈负相关[β=-0.06；95%置信区间：-0.08，-0.03]，与低酒精模式呈负相关[β=-0.08；95%置信区间：-0.10，-0.06]。高饱和脂肪模式与腰围[β=1.71；95%置信区间：0.97，2.44]和 CRP[β=0.37；95%置信区间：0.26，0.47]呈正相关。
宏量营养素饮食模式因经济地位而异，且与代谢健康标志物相关，可能可以解释经济地位与健康之间的关系。
