Prentice Ross L, Aragaki Aaron K, Zheng Cheng, Manson JoAnn E, Tinker Lesley F, Schoeller Dale A, Ravelli Michele N, Raftery Daniel, Gowda Ga Nagana, Navarro Sandi L, Huang Ying, Mossavar-Rahmani Yasmin, Wallace Robert B, Johnson Karen C, Lampe Johanna W, Neuhouser Marian L
Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, United States; Department of Biostatistics School of Public Health, University of Washington, Seattle, WA, United States.
Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, United States.
Am J Clin Nutr. 2025 May;121(5):1165-1175. doi: 10.1016/j.ajcnut.2025.03.011. Epub 2025 Mar 13.
Associations of the macronutrient composition of the diet with total energy intake (EI) are uncertain, as are associations of macronutrient composition with self-reported energy underreporting.
We aimed to estimate the associations of biomarker-assessed EI with both biomarker-assessed and self-reported macronutrient component densities in a Women's Health Initiative (WHI) subcohort of postmenopausal females in the United States. Secondarily, we examined energy underreporting using food records, recalls, and frequencies, for association with macronutrient densities.
We used a previously proposed EI biomarker equation based on doubly labeled water (DLW) and updated biomarker equations for several macronutrient component densities, to estimate EI and macronutrient component densities in a WHI nutritional biomarkers subcohort (n = 436; 2007-2009). We used linear regression of EI biomarker values on biomarker and self-reported macronutrient component densities, and of EI underreporting values on biomarker densities, to examine targeted associations.
Using biomarker assessments, the geometric mean (95% CI) for EI corresponding to a 20% increment in carbohydrate density was 2.0% (0.1%, 3.9%) higher, and for a 20% protein density increment was 2.1% (0.5%, 3.7%) lower. The former was attributable to added sugars. Similarly, EI values for 20% increments in polyunsaturated (PUFA), and monounsaturated (MUFA) fatty acid densities were 1.4% (0.3%, 2.6%) higher and 1.5% (0.1%, 2.9%) lower, respectively. Pertinent associations were either not detected or were substantially attenuated if instead self-reported macronutrient densities were used. Also, EI underreporting was strongly related to self-reported macronutrient densities using food records, recalls, or frequencies.
Among postmenopausal females in the United States lower EI was associated with diets relatively high in protein or MUFA, and higher EI was associated with diets relatively high in PUFA or added sugars. These associations are of public health importance but are mostly missed using self-reported dietary density assessments. Self-reported energy underestimation is substantially associated with self-reported macronutrient densities.
This study is registered with clinicaltrials.gov identifier: NCT00000611.
饮食中宏量营养素组成与总能量摄入(EI)之间的关联尚不确定,宏量营养素组成与自我报告的能量摄入不足之间的关联也是如此。
我们旨在评估在美国女性健康倡议(WHI)绝经后女性亚队列中,生物标志物评估的EI与生物标志物评估和自我报告的宏量营养素成分密度之间的关联。其次,我们使用食物记录、回忆和频率来检查能量摄入不足情况,以探讨其与宏量营养素密度的关联。
我们使用先前提出的基于双标水(DLW)的EI生物标志物方程以及几种宏量营养素成分密度的更新生物标志物方程,来估算WHI营养生物标志物亚队列(n = 436;2007 - 2009年)中的EI和宏量营养素成分密度。我们使用EI生物标志物值对生物标志物和自我报告的宏量营养素成分密度进行线性回归,以及EI摄入不足值对生物标志物密度进行线性回归,以检验目标关联。
使用生物标志物评估,碳水化合物密度增加20%时,EI的几何均值(95%CI)高2.0%(0.1%,3.9%);蛋白质密度增加20%时,EI低2.1%(0.5%,3.7%)。前者归因于添加糖。同样,多不饱和脂肪酸(PUFA)和单不饱和脂肪酸(MUFA)密度增加20%时,EI值分别高1.4%(0.3%,2.6%)和低1.5%(0.1%,2.9%)。如果使用自我报告的宏量营养素密度,相关关联要么未被检测到,要么显著减弱。此外,使用食物记录、回忆或频率,EI摄入不足与自我报告的宏量营养素密度密切相关。
在美国绝经后女性中,较低的EI与蛋白质或MUFA含量相对较高的饮食有关,较高的EI与PUFA或添加糖含量相对较高的饮食有关。这些关联具有公共卫生重要性,但使用自我报告的饮食密度评估大多会遗漏这些关联。自我报告的能量低估与自我报告的宏量营养素密度密切相关。
本研究已在clinicaltrials.gov注册,标识符为:NCT00000611。