Cited by 528Nutritional Studies and DietNutrition and Health StudiesStatistical Methods in Epidemiology

The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.

Pooled Results From 5 Validation Studies of Dietary Self-Report Instruments Using Recovery Biomarkers for Energy and Protein Intake

Open access

Freedman, Laurence S., Commins, John M., Moler, James E., Arab, Lenore, Baer, David J., Kipnis, Victor, Midthune, Douglas, Moshfegh, Alanna J., Neuhouser, Marian L., Prentice, Ross L., Schatzkin, Arthur, Spiegelman, Donna, Subar, Amy F., Tinker, Lesley F., Willett, Walter·2014·American Journal of Epidemiology

DOI 10.1093/aje/kwu116PMC PMC4082341

Open this paper in CoChat — free account Open PDF

Abstract

We pooled data from 5 large validation studies of dietary self-report instruments that used recovery biomarkers as references to clarify the measurement properties of food frequency questionnaires (FFQs) and 24-hour recalls. The studies were conducted in widely differing US adult populations from 1999 to 2009. We report on total energy, protein, and protein density intakes. Results were similar across sexes, but there was heterogeneity across studies. Using a FFQ, the average correlation coefficients for reported versus true intakes for energy, protein, and protein density were 0.21, 0.29, and 0.41, respectively. Using a single 24-hour recall, the coefficients were 0.26, 0.40, and 0.36, respectively, for the same nutrients and rose to 0.31, 0.49, and 0.46 when three 24-hour recalls were averaged. The average rate of under-reporting of energy intake was 28% with a FFQ and 15% with a single 24-hour recall, but the percentages were lower for protein. Personal characteristics related to under-reporting were body mass index, educational level, and age. Calibration equations for true intake that included personal characteristics provided improved prediction. This project establishes that FFQs have stronger correlations with truth for protein density than for absolute protein intake, that the use of multiple 24-hour recalls substantially increases the correlations when compared with a single 24-hour recall, and that body mass index strongly predicts under-reporting of energy and protein intakes.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Integrity signals

Registry

Crossref · 10.1093/aje/kwu116

Cites

34 of 34 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Quantifying heterogeneity in a meta‐analysis
Higgins, J. P. T., & Thompson, S. G. (2002) · Statistics in Medicine · doi:10.1002/sim.1186 · Cited by 36,763
Reproducibility and validity of a semiquantitative food frequency questionnaire
WILLETT, W. C., SAMPSON, L., STAMPFER, M. J., ROSNER, B., BAIN, C., WITSCHI, J., HENNEKENS, C. H., & SPEIZER, F. E. (1985) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a114086 · Cited by 4,274
Self-citation
Linear Mixed Models for Longitudinal Data
Verbeke, G. (1997) · Lecture Notes in Statistics · doi:10.1007/978-1-4612-2294-1_3 · Cited by 3,506
Reproducibility and Validity of an Expanded Self-Administered Semiquantitative Food Frequency Questionnaire among Male Health Professionals
Rimm, E. B., Giovannucci, E. L., Stampfer, M. J., Colditz, G. A., Litin, L. B., & Willett, W. C. (1992) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a116211 · Cited by 2,104
Self-citation
The US Department of Agriculture Automated Multiple-Pass Method reduces bias in the collection of energy intakes
Moshfegh, A. J., Rhodes, D. G., Baer, D. J., Murayi, T., Clemens, J. C., Rumpler, W. V., Paul, D. R., Sebastian, R. S., Kuczynski, K. J., Ingwersen, L. A., et al. (2008) · American Journal of Clinical Nutrition · doi:10.1093/ajcn/88.2.324 · Cited by 1,988
Self-citation
Comparative Validation of the Block, Willett, and National Cancer Institute Food Frequency Questionnaires
Subar, A. F., Thompson, F. E., Kipnis, V., Midthune, D., Hurwitz, P. E., McNutt, S., McIntosh, A., & Rosenfeld, S. (2001) · American Journal of Epidemiology · doi:10.1093/aje/154.12.1089 · Cited by 1,401
Self-citation
Measurement error in nonlinear models: a modern perspective
Carroll, R. J. (2006) · Cited by 1,374
Using Intake Biomarkers to Evaluate the Extent of Dietary Misreporting in a Large Sample of Adults: The OPEN Study
Subar, A. F. (2003) · American Journal of Epidemiology · doi:10.1093/aje/kwg092 · Cited by 1,070
Self-citation
Measurement Characteristics of the Women’s Health Initiative Food Frequency Questionnaire
Patterson, R. E., Kristal, A. R., Tinker, L. F., Carter, R. A., Bolton, M. P., & Agurs‐Collins, T. (1999) · Annals of Epidemiology · doi:10.1016/s1047-2797(98)00055-6 · Cited by 1,021
Self-citation
Dietary Assessment Methodology
Thompson, F. E., & Subar, A. F. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-802928-2.00001-1 · Cited by 978
Self-citation

Flagged first, then by citations

Show all 34 references

Research works printed but not linked: 4

2013, Nutritional Epidemiology
United States Department of Agriculture, Food and Nutrient Database for Dietary Studies: Foods, Portions/Weights, Nutrients for Analyzing Dietary Data
2002, The impact of categorization of continuous exposure measured with error [abstract], Am J Epidemiol, 155, S28
SAS Institute Inc, 2008, Statistical Analysis System (SAS) Software, Version 9.2

Sorted by citations

Items 301–400 of 528

Relationship between Adherence to the 2019 Canada’s Food Guide Recommendations on Healthy Food Choices and Nutrient Intakes in Older Adults
Brassard, D., & Chevalier, S. (2023) · Journal of Nutrition · doi:10.1016/j.tjnut.2023.07.005 · Cited by 8
Assessing daily energy intake in adult women: validity of a food-recognition mobile application compared to doubly labelled water
Serra, M., Alceste, D., Hauser, F., Hulshof, P. J. M., Meijer, H. A. J., Thalheimer, A., Steinert, R. E., Gerber, P. A., Spector, A. C., Gerö, D., et al. (2023) · Frontiers in Nutrition · doi:10.3389/fnut.2023.1255499 · Cited by 7
NutritionVerse: Empirical Study of Various Dietary Intake Estimation Approaches
Tai, C.-E. A., Keller, M., Nair, S., Chen, Y., Wu, Y., Markham, O., Parmar, K., Xi, P., Keller, H., Kirkpatrick, S. I., et al. (2023) · International Workshop on Multimedia Assisted Dietary Management (MADiMa) · doi:10.1145/3607828.3617799 · Cited by 8
Effects of basic carbohydrate counting versus standard dietary care for glycaemic control in type 2 diabetes (The BCC Study): a randomised, controlled trial
Ewers, B., Blond, M. B., Bruun, J. M., & Vilsbøll, T. (2024) · Nutrition and Diabetes · doi:10.1038/s41387-024-00307-0 · Cited by 9
Addition of food group equivalents to the Canadian Diet History Questionnaire II for the estimation of the Canadian Healthy Eating Index-2005
McInerney, M., Ho, V., Koushik, A., Massarelli, I., Rondeau, I., McCormack, G. R., & Csizmadi, I. (2018) · Health Promotion and Chronic Disease Prevention in Canada · doi:10.24095/hpcdp.38.3.03 · Cited by 8
Salt/Sodium Intake Estimation in Children and Adolescents of Costa Rica
Núñez-Rivas, H. P., Holst-Schumacher, I. I., Blanco‐Metzler, A., Montero-Campos, M. D. L. Á., Campos-Saborío, N., & Benavides-Aguilar, K. (2020) · Food and Nutrition Sciences · doi:10.4236/fns.2020.1110065 · Cited by 8
Validation of an automated self-administered 24-hour dietary recall web application against urinary recovery biomarkers in a sample of French-speaking adults of the province of Québec, Canada
Paradis, F., Lamarche, B., Robitaille, J., Couillard, C., Lafrenière, J., Tremblay, A. J., Corneau, L., & Lemieux, S. (2022) · Applied Physiology, Nutrition, and Metabolism · doi:10.1139/apnm-2021-0445 · Cited by 8
Ten-Year Changes in Global Warming Potential of Dietary Patterns Based on Food Consumption in Ontario, Canada
Topcu, B., Dias, G. M., & Mollaei, S. (2022) · Sustainability · doi:10.3390/su14106290 · Cited by 8
Differences in Dietary Intake Exist among U.S. Adults by Diabetic Status Using NHANES 2009–2016
Lin, L., Zhu, F. M., Delp, E. J., & Eicher‐Miller, H. A. (2022) · Nutrients · doi:10.3390/nu14163284 · Cited by 11
Is the Association Between Fruits and Vegetables and Preeclampsia Due to Higher Dietary Vitamin C and Carotenoid Intakes?
Bodnar, L. M., Kirkpatrick, S. I., Roberts, J. M., Kennedy, E. H., & Naimi, A. I. (2023) · American Journal of Clinical Nutrition · doi:10.1016/j.ajcnut.2023.06.007 · Cited by 9
Manual de marketing
Sánchez, M. D. G. (2008) · Dialnet (Universidad de la Rioja) · Cited by 8
Intervening on Calorie Intake or Eating Timing in Older Adults: Lessons Learned in the Healthy Aging and Late-Life Outcomes Randomized Controlled Pilot Trial
Fanning, J. T., Rejeski, W. J., Nicklas, B. J., Kritchevsky, S. B., Miller, M. E., Houston, D. K., Walkup, M. P., Kennedy, K., Stowe, C. L., Ford, S. A., et al. (2025) · Clinical Interventions in Aging · doi:10.2147/cia.s520273 · Cited by 8
Sarcopenia, Muscle Mass and Protein Intake in Adults Older Than 65 Years After Earlier Bariatric Surgery
Eksteen, G., Vanuytsel, T., Vangoitsenhoven, R., Mertens, A. C., Lannoo, M., Deleus, E., der Schueren, B. V., & Matthys, C. (2025) · Journal of Cachexia Sarcopenia and Muscle · doi:10.1002/jcsm.13839 · Cited by 7
Objective and Subjective Aspects of the Drive to Eat in Obesogenic Environments
Lieberman, L. S. (2016) · Springer eBooks · doi:10.1007/978-3-319-44103-0_10 · Cited by 7
Hunger and satiety responses to diets enriched with cottonseed oil vs. olive oil
Prater, M. C., Scheurell, A. R., Paton, C. M., & Cooper, J. A. (2022) · Physiology & Behavior · doi:10.1016/j.physbeh.2022.114041 · Cited by 7
Development of the Canadian Food Intake Screener to assess alignment of adults’ dietary intake with the 2019 Canada's Food Guide healthy food choices recommendations
Hutchinson, J. M., Williams, T. E., Westaway, A. M., Bédard, A., Pitre, C., Lemieux, S., Dodd, K. W., Lamarche, B., Guenther, P. M., Haines, J., et al. (2023) · Applied Physiology, Nutrition, and Metabolism · doi:10.1139/apnm-2023-0019 · Cited by 7
Revisiting Protein Restriction in Early CKD: Did We Get it Wrong?
Workeneh, B., Moore, L. W., & Mitch, W. E. (2025) · American Journal of Kidney Diseases · doi:10.1053/j.ajkd.2025.01.004 · Cited by 7
Assessment of nationally representative dietary studies in the Gulf Cooperation Council: a scoping review
Hoque, R., Strotheide, E., Saquib, J., & Saquib, N. (2020) · PeerJ · doi:10.7717/peerj.10163 · Cited by 7
Diets high in glycemic index and glycemic load are associated with an increased risk of metabolic syndrome among Korean women
Jun, S., Lee, S., Lee, J., & Kim, J. (2022) · Nutrition Metabolism and Cardiovascular Diseases · doi:10.1016/j.numecd.2022.01.017 · Cited by 8
Fast food consumption in adults living in Canada: alternative measurement methods, consumption choices, and correlates
Seale, E., de Groh, M., & Greene-Finestone, L. S. (2022) · Applied Physiology Nutrition and Metabolism · doi:10.1139/apnm-2022-0252 · Cited by 7
The Association of Prenatal Dietary Factors with Child Autism Diagnosis and Autism-Related Traits Using a Mixtures Approach: Results from the Environmental Influences on Child Health Outcomes Cohort
Bragg, M. G., Rando, J., Carroll, K. N., Eick, S. M., Karagas, M. R., Lin, P. D., Schmidt, R. J., Lyall, K., Smith, P. B., Newby, L. K., et al. (2025) · Journal of Nutrition · doi:10.1016/j.tjnut.2025.02.025 · Cited by 6
Dietary misreporting: a comparative study of recalls vs energy expenditure and energy intake by doubly-labeled water in older adults with overweight or obesity
Baez, L. S. S., Ravelli, M. N., Díaz‐Rizzolo, D. A., Popp, C. J., Gallagher, D., Cheng, B., Schoeller, D. A., & Laferrère, B. (2025) · BMC Medical Research Methodology · doi:10.1186/s12874-025-02568-4 · Cited by 6
Issues in Implementing Regression Calibration Analyses
Boe, L. A., Shaw, P. A., Midthune, D., Gustafson, P., Kipnis, V., Park, E., Sotres‐Alvarez, D., & Freedman, L. S. (2022) · PubMed Central · doi:10.1093/aje/kwad098 · Cited by 6
Self-citation
Animal and plant protein usual intakes are not adversely associated with all-cause, cardiovascular disease–, or cancer-related mortality risk: an NHANES III analysis
Papanikolaou, Y., Phillips, S. M., & Fulgoni, V. L. I. (2025) · Applied Physiology, Nutrition, and Metabolism · doi:10.1139/apnm-2023-0594 · Cited by 6
Photo-Assisted Dietary Method Improves Estimates of Dietary Intake Among People with Sleeve Gastrectomy
Al‐Ozairi, E., AlAwadhi, M. M., Kandari, J. A., Taghadom, E., Abdullah, M., & le Roux, C. W. (2019) · Obesity Surgery · doi:10.1007/s11695-019-03736-4 · Cited by 6
The effect of different methods to identify, and scenarios used to address energy intake misestimation on dietary patterns derived by cluster analysis
Siou, G. L., Akawung, A. K., Solbak, N. M., McDonald, K., Rajabi, A. A., Whelan, H. K., & Kirkpatrick, S. I. (2021) · Nutrition Journal · doi:10.1186/s12937-021-00696-3 · Cited by 6
Prospective dietary polyunsaturated fatty acid intake is associated with trajectories of fatty liver disease: an 8 year follow-up study from adolescence to young adulthood
Wan, F., Pan, F., Ayonrinde, O. T., Adams, L. A., Mori, T. A., Beilin, L. J., O’Sullivan, T. A., Olynyk, J. K., & Oddy, W. H. (2022) · European Journal of Nutrition · doi:10.1007/s00394-022-02934-8 · Cited by 6
Urinary Sucrose and Fructose From Spot Urine May Be Used as a Predictive Biomarker of Total Sugar Intake–Findings From a Controlled Feeding Study
Tasevska, N., Palma-Duran, S. A., Sági‐Kiss, V., Commins, J. M., Barrett, B., Kipnis, V., Midthune, D., O’Brien, D. M., & Freedman, L. S. (2023) · Journal of Nutrition · doi:10.1016/j.tjnut.2023.04.002 · Cited by 6
Self-citation
Relative Validity and Reproducibility of a Web-Based Semi-Quantitative Food Frequency Questionnaire in the Danish Diet, Cancer, and Health—Next Generations MAX Study
Rostgaard‐Hansen, A. L., Rosthøj, S., Brunius, C. F., Olsen, S. F., Bjerregaard, A. A., Cade, J. E., Tjønneland, A. M., Landberg, R., & Halkjær, J. (2023) · Nutrients · doi:10.3390/nu15102389 · Cited by 6
Dietary Intake of Athletes at the World Masters Athletics Championships as Assessed by Single 24 h Recall
Leonhardt, T. P. M., Bristol, A., McLaurin, N., Forbes, S. C., Tanaka, H., Frings‐Meuthen, P., Pesta, D. H., Rittweger, J., & Chilibeck, P. D. (2024) · Nutrients · doi:10.3390/nu16040564 · Cited by 8
An Assessment of the Validity of an Audio-Video Method of Food Journaling for Dietary Quantity and Quality
Jago, E., Gauthier, A. P., Pegoraro, A. L., & Dorman, S. C. (2019) · Journal of Nutrition and Metabolism · doi:10.1155/2019/9839320 · Cited by 6
Validity and Reproducibility of a Semi-Quantitative Food-Frequency Questionnaire Designed to Measure the Nutrient Intakes of Canadian South Asian Infants at 12 Months of Age
de Souza, R. J., Williams, N. C., Sockalingam, L., Wahi, G., Desai, D., Dehghan, M., Schulze, K. M., Gupta, M., & Anand, S. S. (2020) · Canadian Journal of Dietetic Practice and Research · doi:10.3148/cjdpr-2020-011 · Cited by 6
Effectiveness of a combined New Zealand green-lipped mussel and Antarctic krill oil supplement on markers of exercise-induced muscle damage and inflammation in untrained men
Barenie, M. J., Freemas, J. A., Baranauskas, M. N., Goss, C. S., Freeman, K. L., Chen, X., Dickinson, S., Fly, A. D., Kawata, K., Robert F. Chapman, P., et al. (2020) · Journal of Dietary Supplements · doi:10.1080/19390211.2020.1853649 · Cited by 6
Stress-Related Poor Diet Quality Does Not Explain Socioeconomic Inequities in Health: A Structural Equation Mediation Analysis of Gender-Specific Pathways
Olstad, D. L., Nejatinamini, S., Kirkpatrick, S. I., Vanderlee, L., Livingstone, K. M., Campbell, D. J. T., Tang, K. L., Minaker, L. M., & Hammond, D. G. (2021) · Journal of the Academy of Nutrition and Dietetics · doi:10.1016/j.jand.2021.09.018 · Cited by 6
Holter monitoring in the prognosis of sudden cardiac death.
Erdoğan, O. (2007) · PubMed · Cited by 6
Energy intake is associated with dietary macronutrient densities: inversely with protein and monounsaturated fat and positively with polyunsaturated fat and carbohydrate among postmenopausal females
Prentice, R. L., Aragaki, A. K., Zheng, C., Manson, J. E., Tinker, L. F., Schoeller, D. A., Ravelli, M. N., Raftery, D., Gowda, G. A. N., Navarro, S. L., et al. (2025) · American Journal of Clinical Nutrition · doi:10.1016/j.ajcnut.2025.03.011 · Cited by 5
Self-citation
Advances and opportunities in measuring dietary intake: from omics to AI
Cohen, Y., Jansen, T., Onwuka, S., & Elinav, E. (2026) · Nature Metabolism · doi:10.1038/s42255-026-01494-z · Cited by 5
Identifying the Leading Sources of Saturated Fat and Added Sugar in U.S. Adults
Taylor, C. A., Madril, P., Weiss, R., Thomson, C. A., Dunton, G. F., Jospe, M. R., Richardson, K. M., Bedrick, E. J., & Schembre, S. M. (2024) · Nutrients · doi:10.3390/nu16152474 · Cited by 5
Metabolic outcomes in women 6 months and 2 years after preeclampsia versus normotensive pregnancy: A P4 study
Esber, Y., Gow, M. L., McLennan, S., Sushil, S., Roberts, L. M., Brown, M. A., Mangos, G., Pettit, F. M., Davis, G. K., O’Sullivan, A., et al. (2024) · Clinical Obesity · doi:10.1111/cob.12706 · Cited by 7
Rice and Prevention of Type 2 Diabetes: Narrative Review of Epidemiologic Evidene
Sasaki, S. (2019) · Journal of Nutritional Science and Vitaminology · doi:10.3177/jnsv.65.s38 · Cited by 5
A pecan-enriched diet reduced postprandial appetite intensity and enhanced peptide YY secretion: A randomized control trial
Cogan, B., Pearson, R. C., Jenkins, N. T., Paton, C. M., & Cooper, J. A. (2023) · Clinical Nutrition ESPEN · doi:10.1016/j.clnesp.2023.05.002 · Cited by 5
Fifty shades of grain - Increasing whole grain consumption through daily messages.
Weingarten, N., & Hartmann, M. (2023) · Appetite · doi:10.1016/j.appet.2023.106608 · Cited by 6
Validation Study of Physical Activity and Sedentary Behavior in African-American Men and Women
Hicks, J., Adams-Campbell, L. L., Lu, J., Mills, M. G., & Dash, C. (2023) · Journal of Racial and Ethnic Health Disparities · doi:10.1007/s40615-023-01734-y · Cited by 5
Relative validity of the Chrono-Nutrition Behavior Questionnaire (CNBQ) against 11-day event-based ecological momentary assessment diaries of eating
Murakami, K., Shinozaki, N., McCaffrey, T. A., Livingstone, M. B. E., Masayasu, S., & Sasaki, S. (2025) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-025-01740-9 · Cited by 6
Breastfeeding and Protein Intake Influence Body Mass Index from 2 Months to 22 Years in the Cebu Longitudinal Health and Nutrition Survey
Wright, M., Méndez, M. A., Sotres‐Alvarez, D., & Adair, L. S. (2016) · Journal of Nutrition · doi:10.3945/jn.116.232470 · Cited by 5
Adjusting diet–outcome associations for random error: comparison of associations based on observed and estimated usual intakes
Verly, E., Sichieri, R., & Baltar, V. T. (2017) · European Journal of Clinical Nutrition · doi:10.1038/ejcn.2017.120 · Cited by 5
Energy intake and expenditure in children and adolescents, contributions of biological maturity
Silva, A. L., Teles, J. M. V., Olivares, L. A. F., & Fragoso, I. J. (2020) · American Journal of Human Biology · doi:10.1002/ajhb.23529 · Cited by 5
Predicting energy intake with an accelerometer-based intake-balance method
Hibbing, P. R., Shook, R. P., Panda, S., Manoogian, E. N. C., Mashek, D. G., & Chow, L. S. (2022) · British Journal Of Nutrition · doi:10.1017/s0007114522003312 · Cited by 5
Is the energy balance explanation of the obesity epidemic wrong?
Stroebe, W. (2023) · Appetite · doi:10.1016/j.appet.2023.106614 · Cited by 5
Considerations for a protein-focused screening instrument in clinical nutrition assessment
Contillo, A. T., Chun, O. K., & Rodriguez, N. R. (2023) · Clinical Nutrition ESPEN · doi:10.1016/j.clnesp.2023.09.915 · Cited by 4
Dietary inflammatory index and Alzheimer's disease mortality in a prospective cohort
Liao, R., Yang, J., Huang, X., Xu, Y., Ji, Q., Liu, Q., Xu, S., Liu, P., & Zhan, Y. (2025) · Experimental Gerontology · doi:10.1016/j.exger.2025.112770 · Cited by 4
Dietary sugar intake, genetic susceptibility, and risk of dementia: A prospective cohort study
An, Y., Cao, L., Zheng, G., Liu, Y., Yang, H., Chen, L., Zhao, Y., Zhang, X., & Xia, Y. (2025) · The Journal of Prevention of Alzheimer s Disease · doi:10.1016/j.tjpad.2025.100312 · Cited by 4
Different types of sweetened coffee consumption, genetic predictor of gut microbe, and the risk of metabolic dysfunction-associated steatotic liver disease
Liu, W., Xu, X., Chang, Q. H., Yang, H., Ma, Z., Zhang, T., Zhao, Y., Zhao, L., & Xia, Y. (2026) · Nutrition Journal · doi:10.1186/s12937-026-01289-8 · Cited by 4
Evaluation of a digital FFQ using 24 h recalls as reference method, for assessment of habitual diet in women with South Asian origin in Norway
Carlsen, M. H., Totland, T. H., Kumar, R., Lensnes, T. M., Sharma, A., Suntharalingam, A. A., Tran, A. T., Birkeland, K. I., & Sommer, C. (2024) · Public Health Nutrition · doi:10.1017/s1368980024000302 · Cited by 4
Validity and reproducibility of a web-based dietary assessment tool: a cross-sectional study in an adult Danish population
Kisi, S. B., Petersen, C. F., Andersen, R. S., Rasmussen, S. I. I., Parlesak, A., Christensen, S. H., Petersen, H. L., Geiker, N. R. W., Hitz, M. F., & Tetens, I. (2025) · Journal of Nutritional Science · doi:10.1017/jns.2025.10010 · Cited by 6
Criterion validity of wrist accelerometry for assessing energy intake via the intake-balance technique
Hibbing, P. R., Welk, G. J., Ries, D., Yeh, H., & Shook, R. P. (2023) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-023-01515-0 · Cited by 3
Adesão à dieta EAT-Lancet e sua relação com insegurança alimentar e renda em uma amostra de base populacional brasileira
Ferreira, M. A., Silva, A. M., Marchioni, D. M. L., & Carli, E. D. (2023) · Cadernos de Saúde Pública · doi:10.1590/0102-311xpt247222 · Cited by 4
Adherence to the EAT-Lancet diet and its relation with food insecurity and income in a Brazilian population-based sample
Ferreira, M. A., Silva, A. M., Marchioni, D. M. L., & Carli, E. D. (2023) · Cadernos de Saúde Pública · doi:10.1590/0102-311xen247222 · Cited by 4
Challenges for Predictive Modeling With Neural Network Techniques Using Error‐Prone Dietary Intake Data
Spicker, D., Nazemi, A., Hutchinson, J. M., Fieguth, P., Kirkpatrick, S. I., Wallace, M., & Dodd, K. W. (2025) · Statistics in Medicine · doi:10.1002/sim.70013 · Cited by 7
Nutrition Assessment of the Athlete
Larson‐Meyer, D. E. (2019) · Current Sports Medicine Reports · doi:10.1249/jsr.0000000000000586 · Cited by 4
Validity of Absolute Intake and Nutrient Density of Protein, Potassium, and Sodium Assessed by Various Dietary Assessment Methods: An Exploratory Study
Trijsburg, L. E., Geelen, A., Hulshof, P. J. M., Veer, P. V., Boshuizen, H. C., Hollman, P. C. H., van Dijk, G., Feskens, E. J. M., & de Vries, J. H. M. (2019) · Nutrients · doi:10.3390/nu12010109 · Cited by 4
Mortality Associated with Healthy Eating Index Components and an Empirical-Scores Healthy Eating Index in a Cohort of Postmenopausal Women
Prentice, R. L., Aragaki, A. K., Horn, L. V., Thomson, C. A., Tinker, L. F., Manson, J. E., Mossavar‐Rahmani, Y., Huang, Y., Zheng, C., Beresford, S. A. A., et al. (2022) · Journal of Nutrition · doi:10.1093/jn/nxac068 · Cited by 3
Self-citation
Associations Between Weight Talk and Biopsychosocial Outcomes in Children from Racially/Ethnically Diverse Households
Trofholz, A. C., Tate, A. D., Telke, S. E., Loth, K. A., Buchanan, G. J. R., & Berge, J. M. (2022) · Journal of Child and Family Studies · doi:10.1007/s10826-022-02351-9 · Cited by 4
Evaluating self‐reported retrospective average daily fruit, vegetable, and egg intake: Trustworthy—Sometimes!
Egele, V. S., Klopp, E., & Stark, R. (2022) · Applied Psychology Health and Well-Being · doi:10.1111/aphw.12430 · Cited by 4
Dairy Food Consumption Is Associated with Reduced Risk of Heart Disease Mortality, but Not All-Cause and Cancer Mortality in US Adults
Papanikolaou, Y., & Fulgoni, V. L. I. (2023) · Nutrients · doi:10.3390/nu15020394 · Cited by 4
Experiences of Racial Discrimination and Periconceptional Diet Quality
Bodnar, L. M., Odoms‐Young, A. M., Kirkpatrick, S. I., Naimi, A. I., Petersen, J. M., & Martin, C. L. (2023) · Journal of Nutrition · doi:10.1016/j.tjnut.2023.05.028 · Cited by 4
No association between dietary markers and incident hypertension in a population-based sample
Fidalgo, A. S. Q., Vollenweider, P., & Marques-Vidal, P. M. (2018) · Clinical Nutrition ESPEN · doi:10.1016/j.clnesp.2018.07.013 · Cited by 6
Dietary vitamins A and K are inversely associated with visceral adiposity in US adults: NHANES 2011–2018
Villa, T. H. C., Ruiz‐Vivanco, G., Porchia, L. M., Torres‐Rasgado, E., López‐Bayghen, E., & Gonzalez-Mejia, M. E. (2025) · Nutrition Research · doi:10.1016/j.nutres.2025.12.001 · Cited by 4
Convergent Validity of Multiple 24‐h Dietary Recalls and Food Frequency Questionnaire in Calculating the Dietary Inflammatory Index Score in Community‐Dwelling Older Adults
Linton, C., Schaumberg, M. A., & Wright, H. (2026) · Food Science & Nutrition · doi:10.1002/fsn3.71501 · Cited by 3
The (ab)use of food frequency questionnaire data in substitution modelling in nutritional epidemiology: a critique
Louie, J. C. Y., & Bhowmik, J. (2026) · European Journal of Clinical Nutrition · doi:10.1038/s41430-026-01712-7 · Cited by 4
Postprandial appetite responses to a pecan enriched meal: A randomized crossover trial
Prater, M. C., Guadagni, A. J., & Cooper, J. A. (2024) · Appetite · doi:10.1016/j.appet.2024.107598 · Cited by 3
Protein Adequacy in Europe: Adjusting Crude Intakes Using the Protein Adequacy and Quality Score (PAQS)
Heerschop, S. N., Biesbroek, S., Daas, M. C., Kuijsten, A., Gurinović, M. A., Geleijnse, J. M., & Veer, P. V. ’. (2025) · Current Developments in Nutrition · doi:10.1016/j.cdnut.2025.107539 · Cited by 3
Development of an Assessment Tool to Measure Healthy Eating in Navajo Children and Their Families
Beresford, S. A. A., Rillamas‐Sun, E., Rudd, K., Bishop, S. K., Deschenie, D., Ornelas, I. J., Bauer, M. C., & Lombard, K. A. (2023) · Current Developments in Nutrition · doi:10.1016/j.cdnut.2023.100074 · Cited by 3
Association between dietary macronutrient composition and plasma one-carbon metabolites and B-vitamin cofactors in patients with stable angina pectoris
Bråtveit, M., Parys, A. V., Olsén, T., Strand, E., Marienborg, I., Laupsa‐Borge, J., Haugsgjerd, T. R., McCann, A., Dhar, I., Ueland, P. M., et al. (2024) · British Journal Of Nutrition · doi:10.1017/s0007114524000473 · Cited by 3
Does the Inclusion of Free Sugars as Opposed to Total Sugars in Nutrient Profiling Models Improve Their Performance? A Cross-sectional Analysis From the PREDISE Study
Corriveau, A., Turcotte, M., Bergeron, A., Lemieux, S., & Labonté, M. (2025) · Journal of Nutrition · doi:10.1016/j.tjnut.2025.05.038 · Cited by 3
Assessment of dietary intake in young populations using new approaches and technologies
Svensson, Å. (2014) · KTH Publication Database DiVA (KTH Royal Institute of Technology) · Cited by 3
An Unjustified Conclusion from Self-report-based Estimates of Energy Intake
Levitsky, D. A., Brown, A. W., HANSEN, B. C., Atkinson, R. L., Byrne, N. M., Cheskin, L. J., & Allison, D. B. (2014) · The American Journal of Medicine · doi:10.1016/j.amjmed.2014.08.029 · Cited by 3
The Future of Sport and Exercise Science Research in the Female Athlete
Kelly, R. K., & Ackerman, K. E. (2023) · Springer eBooks · doi:10.1007/978-3-031-21881-1_23 · Cited by 2
Influence of physical activity measurement on the association between Life’s Essential 8 and incident cardiovascular disease in older women
Hyde, E. T., Nguyen, S., LaMonte, M. J., Di, C., Bellettiere, J., Tinker, L. F., Foraker, R. E., Tindle, H. A., Stefanick, M. L., & LaCroix, A. Z. (2024) · Preventive Medicine Reports · doi:10.1016/j.pmedr.2024.102904 · Cited by 2
Self-citation
Plant-Based Dietary Protein Is Associated with Lower Metabolic Syndrome Risk in Division III Female Athletes: A Pilot Study
Kotarsky, C. J., Frenett, M. L., Hoerle, W. F., Kim, J., Lockwood, J., Cryer, L., & Ives, S. J. (2024) · Nutrients · doi:10.3390/nu16203486 · Cited by 2
Efficacy of a 24-month behavioral intervention focused on sugary beverage reduction for Latino mother-infant dyads: evidence from a randomized controlled trial
Machle, C. J., Berger, P. K., Salvy, S., Rios, C., Durazo-Arvizú, R., & Goran, M. I. (2025) · American Journal of Clinical Nutrition · doi:10.1016/j.ajcnut.2024.11.009 · Cited by 2
Ultra-processed food consumption: an exploration of social determinants among Black children of African and Caribbean descent in Ottawa
Levacher, V., Batal, M., Giroux, I., Sanou, D., & Blanchet, R. (2025) · Applied Physiology, Nutrition, and Metabolism · doi:10.1139/apnm-2024-0525 · Cited by 2
The need and strategies for increasing whole-grain intake: a narrative review focused on the UK and Ireland
Boyle, N. B., Dye, L., & Seal, C. J. (2025) · British Journal Of Nutrition · doi:10.1017/s0007114525105059 · Cited by 4
EAT-Lancet reference diet and nutritional adequacy in children: examining the planetary health diet index for children (PHDI-C)
Fabios, E., Zazpe, I., Santiago, S., García, S., Martínez‐González, M. Á., & Martín‐Calvo, N. (2025) · European Journal of Nutrition · doi:10.1007/s00394-025-03858-9 · Cited by 2
Carbon Isotope Ratios as Biomarkers for Added Sugar Intake: Fundamental Limitations that Constrain Valid Application
Louie, J. C. Y. (2026) · Journal of Nutrition · doi:10.1016/j.tjnut.2026.101575 · Cited by 2
Reducing bias and enhancing equity in AI-enabled precision nutrition: addressing measurement error across wearables, multiomics, and dietary data
Mai, A., Luan, Y., Loy, S. L., Qin, C., Ji, H., Obeng, A., Oladuti, M., Ejima, K., Mok, K. T., Kaur, S., et al. (2026) · Frontiers in Digital Health · doi:10.3389/fdgth.2026.1805704 · Cited by 4
Development of a Multibiomarker Panel of Healthy Eating Index in United States Adults: A Machine Learning Approach
Liang, S., Li, A., & Skilton, M. R. (2022) · Journal of Nutrition · doi:10.1016/j.tjnut.2022.11.004 · Cited by 2
Avoidable diet-related deaths and cost-of-illness with culturally optimized modifications in diet: The case of Brazil
Verly, E., Machado, Í. E., Meireles, A. L., & Nilson, E. A. F. (2023) · PLoS ONE · doi:10.1371/journal.pone.0288471 · Cited by 2
No Observed Difference in Inflammatory and Coagulation Markers Following Diets Rich in n-6 Polyunsaturated Fat vs Monounsaturated Fat in Adults With Untreated Hypercholesterolemia: A Randomized Trial
Prater, M. C., Scheurell, A. R., Paton, C. M., & Cooper, J. A. (2023) · Journal of the Academy of Nutrition and Dietetics · doi:10.1016/j.jand.2023.08.127 · Cited by 2
The Use of Three-Dimensional Images and Food Descriptions from a Smartphone Device Is Feasible and Accurate for Dietary Assessment
Schenk, J. M., Boynton, A., Kulik, P., Zyuzin, A., Neuhouser, M. L., & Kristal, A. R. (2024) · Nutrients · doi:10.3390/nu16060828 · Cited by 2
Self-citation
Depression is associated with lower diet quality in both pre- and post-menopausal U.S. women: NHANES 2007-2018
Owens, B. A., Larcom, A. B., & Vadiveloo, M. K. (2024) · Nutrition Research · doi:10.1016/j.nutres.2024.11.007 · Cited by 2
Dietary and Physical Activity Outcomes Determine Energy Balance in U.S. Adults Aged 50–74 Years
Patterson, M. A., Wang, W., & Ortíz, A. (2017) · Journal of Aging and Physical Activity · doi:10.1123/japa.2017-0304 · Cited by 2
FoodSampler
Romero, N. A., Davis, K., van Oers, S. M. D., de van der Schueren, M. A. E., Alberts, J. W., & Vastenburg, M. H. (2018) · International Conference on Pervasive Computing Technologies for Healthcare · doi:10.1145/3240925.3240948 · Cited by 3
Methods and tools used to describe and quantify the associations between diet, inflammation, and health
Hébert, J. R. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-822130-3.00005-3 · Cited by 2
Association between objective measures and parent-reported measures of child tobacco smoke exposure: A secondary data analysis of four trials
Bitan, M., Steinberg, D. M., Wilson, S. R., Kalkbrenner, A. E., Lanphear, B. P., Hovell, M. F., Gamliel, V. M., & Rosen, L. (2022) · Tobacco Induced Diseases · doi:10.18332/tid/150296 · Cited by 2
Feilkilder i ernæringsepidemiologi
Lysne, V., & Olsén, T. (2018) · Norsk tidsskrift for ernæring · doi:10.18261/ntfe.16.2.6 · Cited by 2
Reply to NV Dhurandhar et al.
Subar, A. F., Freedman, L. S., Kirkpatrick, S. I., Boushey, C. J., Potischman, N. A., Guenther, P. M., & Krebs‐Smith, S. M. (2016) · Journal of Nutrition · doi:10.3945/jn.116.230854 · Cited by 2
Self-citation
10-Year Changes of Food Consumption and Carbon Footprint in Ontario
Topcu, B. (2018) · UWSpace (University of Waterloo) · Cited by 2
Interventions to reduce meat consumption by appealing to animal welfare: Meta-analysis and evidence-based recommendationsPreprint
Mathur, M. B., Peacock, J., Reichling, D. B., Nadler, J., Bain, P. A., Gardner, C. D., & Robinson, T. N. (2021) · OSF Preprints (OSF Preprints) · doi:10.31219/osf.io/bc2wy · Cited by 6
High red blood cell folate is associated with an increased risk of diabetes death among a hypertensive cohort
Twum, F., Cowan, L., Yu, L., Afriyie-Gyawu, E., & Zhang, J. (2024) · Nutrition Research · doi:10.1016/j.nutres.2024.04.005 · Cited by 1

Authors: Freedman, L. S., Commins, J. M., Moler, J. E., Arab, L., Baer, D. J., Kipnis, V., Midthune, D., Moshfegh, A. J., Neuhouser, M. L., Prentice, R. L., Schatzkin, A., Spiegelman, D., Subar, A. F., Tinker, L. F., & Willett, W.
Affiliations: Sheba Medical Center (IL)
ORCID: Freedman, Laurence S.
Moler, James E.
Arab, Lenore
Baer, David J.
Midthune, Douglas
Moshfegh, Alanna J.
Neuhouser, Marian L.
Prentice, Ross L.
Spiegelman, Donna
Tinker, Lesley F.
Willett, Walter
Venue: American Journal of Epidemiology
Publisher: Oxford University Press (OUP)
Published: 2014-06-10
Volume: 180
Issue: 2
Pages: 172-188
ISSN: 0002-9262 (ISSN-L)
1476-6256
DOI: 10.1093/aje/kwu116
PMC: PMC4082341
OpenAlex: W2128117277
Cited by: 528
References: 34
Citations by year: 2026: 57 · 2025: 36 · 2024: 29 · 2023: 43 · 2022: 50 · 2021: 43 · 2020: 47 · 2019: 43 · 2018: 52 · 2017: 44 · 2016: 41 · 2015: 34 · 2014: 6
FWCI: 6.53
Type: journal article
Language: en
Open access: bronze
doi.org
Locations: American Journal of Epidemiology (publishedVersion)
Europe PMC (PubMed Central) (publishedVersion, public-domain)
PubMed Central (publishedVersion, public-domain)
PubMed (publishedVersion)
Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
Funders: National Institutes of Health (HHSN268201100004C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C)
National Institute on Aging (HHSN-271-2011-00004C,)
National Heart, Lung, and Blood Institute (HHSN2682011-00001I, HHSN2682011-00002I, HHSN2682011‐00004I, HHSN268201100046C, HHSN2682011-00003I)
National Cancer Institute (P01CA053996, R01CA119171, P30CA015704)
Topics: Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Nutritional Studies and Diet
Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Nutrition and Health Studies
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Keywords: food frequency questionnaire, 24-hour dietary recall, energy intake, protein intake, protein density, underreporting, body mass index, calibration equations, measurement validity
MeSH terms: Adult, Aged, Calibration, Energy Intake, Diet, Dietary Proteins, Female, Humans, Male, Middle Aged, Nitrogen, Surveys and Questionnaires, Mental Recall, Biomarkers, Diet Records, Validation Studies as Topic, Self Report

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Pooled Results From 5 Validation Studies of Dietary Self-Report Instruments Using Recovery Biomarkers for Energy and Protein Intake

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks