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Energy intake is associated with dietary macronutrient densities: inversely with protein and monounsaturated fat and positively with polyunsaturated fat and carbohydrate among postmenopausal females
Journal article   Peer reviewed

Energy intake is associated with dietary macronutrient densities: inversely with protein and monounsaturated fat and positively with polyunsaturated fat and carbohydrate among postmenopausal females

Ross L Prentice, Aaron K Aragaki, Cheng Zheng, JoAnn E Manson, Lesley F Tinker, Dale A Schoeller, Michele N Ravelli, Daniel Raftery, G A Nagana Gowda, Sandi L Navarro, …
The American journal of clinical nutrition, Vol.121(5), pp.1165-1175
05/2025
DOI: 10.1016/j.ajcnut.2025.03.011
PMCID: PMC12107488
PMID: 40088973
url
https://pmc.ncbi.nlm.nih.gov/articles/PMC12107488/View
Open Access

Abstract

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.BACKGROUNDAssociations 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 aim to estimate associations of biomarker-assessed EI with both biomarker-assessed and self-reported macronutrient component densities in a Women's Health Initiative (WHI) sub-cohort of postmenopausal U.S. females. Secondarily, we examine energy underreporting using food records, recalls and frequencies, for association with macronutrient densities.OBJECTIVESWe aim to estimate associations of biomarker-assessed EI with both biomarker-assessed and self-reported macronutrient component densities in a Women's Health Initiative (WHI) sub-cohort of postmenopausal U.S. females. Secondarily, we examine 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 sub-cohort (n=436; 2007-2009). We used linear regression of EI biomarker values on biomarker and self-reported macronutrient component densities, and of log-EI underreporting values on biomarker densities, to examine targeted associations.DESIGN AND METHODSWe 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 sub-cohort (n=436; 2007-2009). We used linear regression of EI biomarker values on biomarker and self-reported macronutrient component densities, and of log-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 acids densities were respectively 1.4% (0.3%, 2.6%) higher, and 1.5% (0.1%, 2.9%) lower. 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.RESULTSUsing 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 acids densities were respectively 1.4% (0.3%, 2.6%) higher, and 1.5% (0.1%, 2.9%) lower. 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 U.S. postmenopausal females 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.CONCLUSIONSAmong U.S. postmenopausal females 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.
 biomarker dietary assessment energy intake energy underreporting macronutrient density

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