Evidence map›Paper›PMID 40088973›Full record

Trial reportThe American journal of clinical nutrition2025

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, Ga Nagana Gowda, Sandi L Navarro and 6 more

Registry-linked trialAbstract readClinical Trial, Phase IIIRandomized Controlled Trial
In one paragraph

Trial report in The American journal of clinical nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT00000611 (Women's Health Initiative), which is not on this map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT00000611 phase3completednot on this map

Women's Health Initiative (WHI)

TypeinterventionalSponsorNational Heart, Lung, and Blood Institute (NHLBI)ConditionsBone Diseases, Breast Neoplasms, Cardiovascular Diseases, Colonic NeoplasmsArmshormone replacement therapy, estrogens, progestins, estrogen replacement therapy, diet, fat-restricted
3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Ross L PrenticeDivision 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. Electronic address: rprentic@whi.org.
Aaron K AragakiDivision of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, United States.
Cheng ZhengDepartment of Biostatistics, University of Nebraska Medical Center, Omaha, NE, United States.
JoAnn E MansonDepartment of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States.
Lesley F TinkerDivision of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, United States.
Dale A SchoellerBiotech Center and Nutritional Sciences Department, University of Wisconsin, Madison, WI, United States.
Michele N RavelliBiotech Center and Neurology Department, University of Wisconsin, Madison, WI, United States.
Daniel RafteryDepartment of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, United States.
Ga Nagana GowdaDepartment of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, United States.
Sandi L NavarroDivision of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, United States.
Ying HuangDivision 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.
Yasmin Mossavar-RahmaniDepartment of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United States.
Robert B WallaceDepartment of Epidemiology, College of Public Health, University of Iowa, Iowa City, IA, United States.
Karen C JohnsonDepartment of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN, United States.
Johanna W LampeDivision of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, United States; Department of Epidemiology School of Public Health, University of Washington, Seattle, WA, United States.
Marian L NeuhouserDivision of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, United States; Department of Epidemiology School of Public Health, University of Washington, Seattle, WA, United States.

Funding

Pulmonary Toxicology Facility CoreP30ES005605 · NIEHS · UNIVERSITY OF IOWA · PI Jong Sung Kim · 1990 to 2026
$40.5M
Nutrition and Physical Activity Assessment Study (NPAAS)R01CA119171 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Marian L Neuhouser · 2006 to 2026
$14.3M
NCI NIH HHS R01 CA119171NIEHS NIH HHS P30 ES005605
6 · The paper itself

Abstract

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.

objectivesWe 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.

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 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.

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 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.

conclusionsAmong 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. CLINICAL TRIAL REGISTRY: This study is registered with clinicaltrials.gov identifier: NCT00000611.

Indexed as

DietDietary CarbohydratesDietary Fats, UnsaturatedDietary ProteinsEnergy IntakeFatty Acids, MonounsaturatedNutrientsPostmenopauseAgedBiomarkersDietary FatsFemaleHumansMiddle AgedUnited StatesBiomarkersDietary CarbohydratesDietary FatsDietary Fats, UnsaturatedDietary ProteinsFatty Acids, MonounsaturatedNutrientsbiomarkerdietary assessmentenergy intakeenergy underreportingmacronutrient density

Identifiers

PMID40088973
PMCPMC12107488

What OpenQuestion holds

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.