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

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Linear Mixed Models for Longitudinal Data

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Reproducibility and Validity of an Expanded Self-Administered Semiquantitative Food Frequency Questionnaire among Male Health Professionals

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The US Department of Agriculture Automated Multiple-Pass Method reduces bias in the collection of energy intakes

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Comparative Validation of the Block, Willett, and National Cancer Institute Food Frequency Questionnaires

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Measurement error in nonlinear models: a modern perspective

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Using Intake Biomarkers to Evaluate the Extent of Dietary Misreporting in a Large Sample of Adults: The OPEN Study

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Measurement Characteristics of the Women’s Health Initiative Food Frequency Questionnaire

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Dietary Assessment Methodology

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Controversy and Debate: Memory Based Methods Paper 3: Nutrition's ‘Black Swans’: Our reply

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Invited Commentary: The Contribution to the Field of Nutritional Epidemiology of the Landmark 1985 Publication by Willett et al.

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Associations Among Food Security, Diet Quality, and Dietary Intake During Pregnancy in a Predominantly African American Group of Women from North Carolina

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Effectiveness of a Theory-Informed Documentary to Reduce Consumption of Meat and Animal Products: Three Randomized Controlled Experiments

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Comparison of dietary intake measured by a web-based FFQ and repeated 24-hour dietary recalls: the Hordaland Health Study

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The impact of stratification by implausible energy reporting status on estimates of diet‐health relationships

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Comparing Interviewer-Administered and Web-Based Food Frequency Questionnaires to Predict Energy Requirements in Adults

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Use of Online Dietary Recalls among Older UK Adults: A Feasibility Study of an Online Dietary Assessment Tool

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Development and validation of a Brief Diet Quality Assessment Tool in the French-speaking adults from Quebec

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Assessing Validity of Self-Reported Dietary Intake within a Mediterranean Diet Cluster Randomized Controlled Trial among US Firefighters

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Strategies to Address Misestimation of Energy Intake Based on Self-Report Dietary Consumption in Examining Associations Between Dietary Patterns and Cancer Risk

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Reply to LS Freedman et al.

Archer, E., & Blair, S. N. (2015) · Advances in Nutrition · doi:10.3945/an.115.009183 · Cited by 18

The Self-Control of Eating

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Accuracy and Cost-effectiveness of Technology-Assisted Dietary Assessment Comparing the Automated Self-administered Dietary Assessment Tool, Intake24, and an Image-Assisted Mobile Food Record 24-Hour Recall Relative to Observed Intake: Protocol for a Randomized Crossover Feeding Study

Whitton, C., Healy, J. D., Collins, C. E., Mullan, B. A., Rollo, M. E., Dhaliwal, S. S., Norman, R., Boushey, C. J., Delp, E. J., Zhu, F. M., et al. (2021) · JMIR Research Protocols · doi:10.2196/32891 · Cited by 21

Dietary Intake, Adherence to Mediterranean Diet and Lifestyle-Related Factors in People with Schizophrenia

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On the Use of Regression Calibration in a Complex Sampling Design With Application to the Hispanic Community Health Study/Study of Latinos

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Portion Sizes from 24-Hour Dietary Recalls Differed by Sex among Those Who Selected the Same Portion Size Category on a Food Frequency Questionnaire

Kang, M., Park, S., Boushey, C. J., Wilkens, L. R., Monroe, K. R., Marchand, L. L., Kolonel, L. N., Murphy, S. P., & Paik, H. Y. (2018) · Journal of the Academy of Nutrition and Dietetics · doi:10.1016/j.jand.2018.02.014 · Cited by 19

Is the Canadian Healthy Eating Index 2007 an Appropriate Diet Indicator of Metabolic Health? Insights from Dietary Pattern Analysis in the PREDISE Study

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Associations between intuitive eating, overall diet quality, and physical health indicators: Results of the PREDISE study

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The Canadian Food Intake Screener for assessing alignment of adults’ dietary intake with the 2019 Canada’s Food Guide healthy food choices recommendations: scoring system and construct validity

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Validation of Total Water Intake from the Automated Self-Administered 24-h Recall, 4-d Food Records, and a Food Frequency Questionnaire Using Doubly Labeled Water

Chang, D. C., Stinson, E. J., Dodd, K. W., Bowles, H. R., Herrick, K., Schoeller, D. A., Barrett, B., Votruba, S. B., Krakoff, J. A., & Kavouras, S. A. (2023) · Journal of Nutrition · doi:10.1016/j.tjnut.2023.08.027 · Cited by 16

A comparison of dietary estimates from the National Aboriginal and Torres Strait Islander Health Survey to food and beverage purchase data

McMahon, E., Wycherley, T. P., O’Dea, K., & Brimblecombe, J. K. (2017) · Australian and New Zealand Journal of Public Health · doi:10.1111/1753-6405.12718 · Cited by 16

Objective Physiological Measurements but Not Subjective Reports Moderate the Effect of Hunger on Choice Behavior

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Dairy intake is not associated with improvements in bone mineral density or risk of fractures across the menopause transition: data from the Study of Women's Health Across the Nation

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The association between dairy intake and risk of cardiovascular disease and mortality in patients with stable angina pectoris

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Energy Intake in Socially Vulnerable Women Living in Brazil: Assessment of the Accuracy of Two Methods of Dietary Intake Recording Using Doubly Labeled Water

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Retrospectively Estimating Energy Intake and Misreporting From a Qualitative Food Frequency Questionnaire: An Example Using Australian Cohort and National Survey Data

Goode, J. P., Smith, K. J., Kilpatrick, M., Breslin, M. C., Oddy, W. H., Dwyer, T., Venn, A., & Magnussen, C. G. (2021) · Frontiers in Nutrition · doi:10.3389/fnut.2021.624305 · Cited by 19

Automated Self-Administered 24-H Dietary Assessment Tool (ASA24) recalls for parent proxy-reporting of children’s intake (> 4 years of age): a feasibility study

Sharpe, I., Kirkpatrick, S. I., Smith, B. T., Keown‐Stoneman, C. D. G., Omand, J. A., Vanderhout, S. M., Maguire, J. L., Birken, C. S., & Anderson, L. N. (2021) · Pilot and Feasibility Studies · doi:10.1186/s40814-021-00864-6 · Cited by 15

Predictors of change in BMI over 10 years among midlife and older adults: Associations with gender, CVD risk status, depressive symptoms, and social support

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Proportions of Polyunsaturated Fatty Acids in Umbilical Cord Blood at Birth Are Related to Atopic Eczema Development in the First Year of Life

Barman, M., Stråvik, M., Bröberg, K., Sandin, A., Wold, A. E., & Sandberg, A. (2021) · Nutrients · doi:10.3390/nu13113779 · Cited by 16

Use of a Doubly Robust Machine-Learning–Based Approach to Evaluate Body Mass Index as a Modifier of the Association Between Fruit and Vegetable Intake and Preeclampsia

Bodnar, L. M., Cartus, A. R., Kennedy, E. H., Kirkpatrick, S. I., Parisi, S. M., Himes, K. P., Parker, C. B., Grobman, W. A., Simhan, H. N., Silver, R. M., et al. (2022) · American Journal of Epidemiology · doi:10.1093/aje/kwac062 · Cited by 15

Greater adherence to the 2019 Canada’s Food Guide recommendations on healthy food choices reduces the risk of cardiovascular disease in adults: a prospective analysis of UK Biobank data

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Validation and Comparison of Nutrient Intakes from Two Dietary Questionnaires Developed for the Multiethnic Cohort Study

Wilkens, L. R., Kang, M., Park, S., Sawyer, A., Boushey, C. J., Au, D., Paik, H. Y., Marchand, L. L., Haiman, C. A., Kolonel, L. N., et al. (2022) · Journal of the Academy of Nutrition and Dietetics · doi:10.1016/j.jand.2022.09.016 · Cited by 15

Augmented gut hormone response to feeding in older adults exhibiting low appetite.

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A statistical model for measurement error that incorporates variation over time in the target measure, with application to nutritional epidemiology

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Associations between self-reported vegetable and fruit intake assessed with a new web-based 24-h dietary recall and serum carotenoids in free-living adults: a relative validation study

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Dietary pattern analysis among stone formers: resemblance to a DASH-style diet

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Differences in Population-Based Dietary Intake Estimates Obtained From an Interviewer-Administered and a Self-Administered Web-Based 24-h Recall

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Administering a combination of online dietary assessment tools, the Automated Self-Administered 24-Hour Dietary Assessment Tool, and Diet History Questionnaire II, in a cohort of adults in Alberta's Tomorrow Project

Solbak, N. M., Robson, P. J., Siou, G. L., Rajabi, A. A., Paek, S., Vena, J. E., & Kirkpatrick, S. I. (2021) · Journal of the Academy of Nutrition and Dietetics · doi:10.1016/j.jand.2021.01.014 · Cited by 15

Objective measures are complementary to, rather than a replacement for, self-reported methods

Satija, A., Yu, E., Willett, W. C., & Hu, F. B. (2015) · International Journal of Obesity · doi:10.1038/ijo.2015.80 · Cited by 15

Introducing menus of three weekly insect- or plant-based dinner meals slightly reduced meat consumption in Danish families: Results of a randomized intervention study

Maya, C., Wilderspin, D. E., Costa, A. I. A., Cunha, L. M., & Roos, N. (2024) · Appetite · doi:10.1016/j.appet.2024.107689 · Cited by 14

New approaches in assessing food intake in epidemiology

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Improving the nutritional intake of hospital patients: how far have we come? A re‐audit

Beavan, S., Baker, R., Sadler, H., & Collinson, A. (2018) · Journal of Human Nutrition and Dietetics · doi:10.1111/jhn.12607 · Cited by 14

Reply to E Archer and SN Blair

Freedman, L. S., Carroll, R. J., Neuhouser, M. L., Prentice, R. L., Spiegelman, D. L., Subar, A. F., Tinker, L. F., & Willett, W. C. (2015) · Advances in Nutrition · doi:10.3945/an.115.009118 · Cited by 14

A Comparison of the Australian Dietary Guidelines to the NOVA Classification System in Classifying Foods to Predict Energy Intakes and Body Mass Index

Grech, A. L., Rangan, A., Allman-Farinelli, M. A., Simpson, S. J., Gill, T. P., & Raubenheimer, D. (2022) · Nutrients · doi:10.3390/nu14193942 · Cited by 14

Maternal Mediterranean Diet Adherence and Its Associations with Maternal Prenatal Stressors and Child Growth

Gonzalez-Nahm, S., Marchesoni, J., Maity, A., Maguire, R. L., House, J. S., Tucker, R., Atkinson, T., Murphy, S. K., & Hoyo, C. (2022) · Current Developments in Nutrition · doi:10.1093/cdn/nzac146 · Cited by 16

Impact of a farmers’ market healthy food subsidy on the diet quality of adults with low incomes in British Columbia, Canada: a pragmatic randomized controlled trial

Aktary, M. L., Dunn, S., Sajobi, T. T., O'Hara, H., Leblanc, P., McCormack, G. R., Caron-Roy, S., Ball, K., Lee, Y. Y., Nejatinamini, S., et al. (2023) · American Journal of Clinical Nutrition · doi:10.1016/j.ajcnut.2023.01.017 · Cited by 13

Supervision during resistance training positively influences muscular adaptations in resistance-trained individuals

Coleman, M., Burke, R., Benavente, C., Piñero, A., Augustin, F., Maldonado, J., Fisher, J. P., Oberlin, D. J., Vigotsky, A. D., & Schoenfeld, B. J. (2023) · Journal of Sports Sciences · doi:10.1080/02640414.2023.2261090 · Cited by 13

Anorexia of ageing is associated with elevated fasted and lower post-prandial ghrelin, independent of ghrelin O-acyltransferase

Holliday, A., Warner, J., Hulston, C. J., Corfe, B. M., & Crabtree, D. R. (2024) · Appetite · doi:10.1016/j.appet.2024.107259 · Cited by 13

Examining the diversity of ultra-processed food consumption and associated factors in Canadian adults

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Dietary intake of tyrosine and phenylalanine, and p-cresyl sulfate plasma levels in non-dialyzed patients with chronic kidney disease

Fernandes, A. L. F., Borges, N. A., Black, A. P., dos Anjos, J. S., da Silva, G. S., Nakao, L. S., & Mafra, D. (2020) · Brazilian Journal of Nephrology · doi:10.1590/2175-8239-jbn-2018-0214 · Cited by 13

Using enhanced regression calibration to combine dietary intake estimates from 24 h recall and FFQ reduces bias in diet–disease associations

Looman, M., Boshuizen, H. C., Feskens, E. J. M., & Geelen, A. (2019) · Public Health Nutrition · doi:10.1017/s1368980019001563 · Cited by 13

Biomarker-predicted sugars intake compared with self-reported measures in US Hispanics/Latinos: results from the HCHS/SOL SOLNAS study

Beasley, J. M., Jung, M., Tasevska, N., Wong, W. W., Siega‐Riz, A. M., Sotres‐Alvarez, D., Gellman, M. D., Kizer, J., SHAW, P. A., Stamler, J., et al. (2016) · Public Health Nutrition · doi:10.1017/s1368980016001580 · Cited by 13

Overview of Nutritional Epidemiology

Villaseñor, A., Cadmus‐Bertram, L., & Patterson, R. E. (2017) · Elsevier eBooks · doi:10.1016/b978-0-12-802928-2.00007-2 · Cited by 13

Pecan‐enriched diets increase energy expenditure and fat oxidation in adults at‐risk for cardiovascular disease in a randomised, controlled trial

Guarneiri, L. L., Paton, C. M., & Cooper, J. A. (2021) · Journal of Human Nutrition and Dietetics · doi:10.1111/jhn.12966 · Cited by 12

Leveraging Observational Cohorts to Study Diet and Nutrition in Older Adults: Opportunities and Obstacles

Shea, M. K., Korat, A. V. A., Jacques, P. F., Sebastiani, P., Cohen, R., LaVertu, A. E., & Booth, S. L. (2022) · Advances in Nutrition · doi:10.1093/advances/nmac031 · Cited by 13

Explaining Racial/Ethnic Dietary Patterns in Relation to Type 2 Diabetes: An Analysis of NHANES 2007-2012

Nowlin, S. Y., Cleland, C. M., Vadiveloo, M. K., Melkus, G. D., Parekh, N., & Hagan, H. (2016) · Ethnicity & Disease · doi:10.18865/ed.26.4.529 · Cited by 12

Intentional weight gain efforts among young Canadian adults aged 17–32 years

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Integration of an Image-Based Dietary Assessment Paradigm into Dietetic Training Improves Food Portion Estimates by Future Dietitians

Ho, D. K. N., Chiu, W., Lee, Y., Su, H.-Y., Chang, C., Yao, C., Hua, K., Chu, H., Hsu, C., & Chang, J. (2021) · Nutrients · doi:10.3390/nu13010175 · Cited by 12

Diet Composition, Anthropometrics, and Mortality Risk

Krakauer, N. Y., & Krakauer, J. C. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph191912885 · Cited by 12

Comparison between Self-Completed and Interviewer-Administered 24-Hour Dietary Recalls in Cancer Survivors: Sampling Bias and Differential Reporting

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Association between dietary factors and plasma fetuin-A concentrations in the general population

Nimptsch, K., Janke, J., Pischon, T., & Linseisen, J. (2015) · British Journal Of Nutrition · doi:10.1017/s0007114515002639 · Cited by 12

A Potential Tool for Clinicians; Evaluating a Computer-Led Dietary Assessment Method in Overweight and Obese Women during Weight Loss

Widaman, A. M., Keim, N. L., Burnett, D. J., Miller, B. T., Witbracht, M. G., Widaman, K. F., & Laugero, K. D. (2017) · Nutrients · doi:10.3390/nu9030218 · Cited by 14

Evaluation of the dietary intake data coding process in a clinical setting: Implications for research practice

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Risk of metabolic syndrome and metabolic phenotypes in relation to biomarker-calibrated estimates of energy and protein intakes: an investigation from the Women’s Health Initiative

Vasbinder, A. L., Tinker, L. F., Neuhouser, M. L., Pettinger, M. B., Hale, L. E., Di, C., Zaslavsky, O., Hayman, L. L., Lin, X., Eaton, C. B., et al. (2020) · American Journal of Clinical Nutrition · doi:10.1093/ajcn/nqaa334 · Cited by 12

Limitações na comparação dos Inquéritos Nacionais de Alimentação de 2008–2009 e 2017–2018

Rodrigues, R. D. R. M., Carli, E. D., Araújo, M. C., Verly, E., Marchioni, D. M. L., Bezerra, I. N., Souza, A. D. M., Yokoo, E. M., Pereira, R. A., & Sichieri, R. (2021) · Revista de Saúde Pública · doi:10.11606/s1518-8787.2021055003365 · Cited by 12

Are French Canadians able to accurately self-rate the quality of their diet? Insights from the PREDISE study

Carbonneau, É., Lamarche, B., Lafrenière, J., Robitaille, J., Provencher, V., Desroches, S., Corneau, L., & Lemieux, S. (2018) · Applied Physiology Nutrition and Metabolism · doi:10.1139/apnm-2018-0293 · Cited by 12

Reply to E Archer and SN Blair

Hébert, J. R., Hurley, T. G., Steck, S. E., Miller, D. R., Tabung, F. K., Kushi, L. H., & Frongillo, E. A. (2015) · Advances in Nutrition · doi:10.3945/an.114.007831 · Cited by 12

Applying Artificial Intelligence and machine learning in precision nutrition

Massara, P., Kirkland, J., Pagani, I., Huey, S. L., Hirsh, H., McDonald, D. T., Patel, L., Finkelstein, J. L., Gantz, M. G., Wang, F., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-75004-w · Cited by 15

Diet Quality and Pancreatic Cancer Incidence in the Multiethnic Cohort

Steel, H., Park, S., Lim, T., Stram, D. O., Boushey, C. J., Hébert, J. R., Marchand, L. L., Wu, A. H., & Setiawan, V. W. (2022) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-22-0564 · Cited by 11

The relative validity of a semiquantitative food frequency questionnaire among pregnant women in the United Arab Emirates: The Mutaba’ah study

Almulla, A. A., Ahmed, L. A., Hesselink, A., Augustin, H., & Bärebring, L. (2024) · Nutrition and Health · doi:10.1177/02601060231224010 · Cited by 12

Weight resilience and fruit and vegetable intake among African-American women in an obesogenic environment

Parisi, S., Bodnar, L. M., & Dubowitz, T. (2017) · Public Health Nutrition · doi:10.1017/s1368980017002488 · Cited by 13

Adjustment Factors Can Improve Estimates of Food Group Intake Assessed Using a Short Dietary Assessment Instrument

Hendrie, G. A., Rebuli, M. A., Golley, R. K., & Noakes, M. (2018) · Journal of the Academy of Nutrition and Dietetics · doi:10.1016/j.jand.2018.02.018 · Cited by 11

Advanced Dietary Analysis and Modeling: A Deep Dive into the National Cancer Institute Method

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Nutritional Epidemiology and Dietary Assessment for Patients With Kidney Disease: A Primer

Sullivan, V. K., & Rebholz, C. M. (2023) · American Journal of Kidney Diseases · doi:10.1053/j.ajkd.2022.11.014 · Cited by 11

Serum and Erythrocyte Biomarkers of Nutrient Status Correlate with Short-Term Α-Carotene, Β-Carotene, Folate, and Vegetable Intakes Estimated by Food Frequency Questionnaire in Military Recruits

Lutz, L. J., Nakayama, A. T., Karl, J. P., McClung, J. P., & Gaffney‐Stomberg, E. (2018) · Journal of the American College of Nutrition · doi:10.1080/07315724.2018.1490215 · Cited by 11

Examining the Advantages of Using Multiple Web-Based Dietary Assessment Instruments to Measure Population Dietary Intake: The PREDISE Study

Brassard, D., Fulgoni, V. L. I., Robitaille, J., Lemieux, S., & Lamarche, B. (2019) · Current Developments in Nutrition · doi:10.1093/cdn/nzz014 · Cited by 11

Adhering to Canada’s Food Guide Recommendations on Healthy Food Choices Increases the Daily Diet Cost: Insights from the PREDISE Study

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Government Dietary Guidelines: Uncertain Science Leads to Questionable Public Health PolicyPreprint

Archer, E., Marlow, M. L., & Williams, R. A. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3211651 · Cited by 11

Using SHAP and LIME to Explain Machine Learning Models Predicting Comorbid Depression and Stroke From Daily Dietary Nutrient Intake in a US Population‐Based Study

Liu, H., Wu, M., Wei, P., Fan, H., & Hou, M. (2025) · Food Science & Nutrition · doi:10.1002/fsn3.71401 · Cited by 10

Using food frequency questionnaires to measure traits: A case study of human consumption of animals and animal products

Feltz, A., Caton, J. N., Cogley, Z., Engel, M., Feltz, S., Ilea, R. C., Johnson, L. S. M., & Offer-Westort, T. (2023) · Psychology of Human-Animal Intergroup Relations · doi:10.5964/phair.10145 · Cited by 10

What is the Validity of Questionnaires Assessing Fruit and Vegetable Consumption in Children when Compared with Blood Biomarkers? A Meta-Analysis

Collese, T. S., Vatavuk‐Serrati, G., Ferreira, M. V. N., de Moraes, A. C. F., & Carvalho, H. B. (2018) · Nutrients · doi:10.3390/nu10101396 · Cited by 10

Design and characterization of dietary assessment in the German National Cohort

Knüppel, S., Clemens, M., Conrad, J., Gastell, S., Michels, K. B., Leitzmann, M. F., Krist, L., Pischon, T., Krause, G., Ahrens, W., et al. (2019) · European Journal of Clinical Nutrition · doi:10.1038/s41430-018-0383-8 · Cited by 10

Validation of energy intake recorded by a 7-day pre-coded food diary against measured energy expenditure in a group of Norwegian adults

Johansen, A. M. W., Myhre, J. B., Hjartåker, A., & Andersen, L. F. (2019) · PLoS ONE · doi:10.1371/journal.pone.0215638 · Cited by 11

Opportunities for Examining Child Health Impacts of Early-Life Nutrition in the ECHO Program: Maternal and Child Dietary Intake Data from Pregnancy to Adolescence

Bragg, M. G., Westlake, M., Alshawabkeh, A. N., Bekelman, T. A., Camargo, C. A., Catellier, D., Comstock, S. S., Dabelea, D., Dunlop, A. L., Hedderson, M. M., et al. (2023) · Current Developments in Nutrition · doi:10.1016/j.cdnut.2023.102019 · Cited by 10

Dieting attempts modify the association between quality of diet and obesity

Sares‐Jäske, L., Knekt, P., Lundqvist, A., Heliövaara, M., & Männistö, S. (2017) · Nutrition Research · doi:10.1016/j.nutres.2017.08.001 · Cited by 13

Comparison of Methods Used to Correct Self-Reported Protein Intake for Systematic Variation in Reported Energy Intake Using Quantitative Biomarkers of Dietary Intake

Korth, A., Bhutani, S., Neuhouser, M. L., Beresford, S. A. A., Snetselaar, L. G., Tinker, L. F., & Schoeller, D. A. (2020) · Journal of Nutrition · doi:10.1093/jn/nxaa007 · Cited by 10

Cord Blood Levels of EPA, a Marker of Fish Intake, Correlate with Infants’ T- and B-Lymphocyte Phenotypes and Risk for Allergic Disease

Barman, M., Rabe, H., Hesselmar, B., Johansen, S., Sandberg, A., & Wold, A. E. (2020) · Nutrients · doi:10.3390/nu12103000 · Cited by 10

Estimating human energy intake using mathematical models , ,

Hall, K. D. (2014) · American Journal of Clinical Nutrition · doi:10.3945/ajcn.114.094441 · Cited by 10

Intake biomarkers and the chronic disease nutritional epidemiology research agenda

Prentice, R. L. (2018) · American Journal of Clinical Nutrition · doi:10.1093/ajcn/nqy206 · Cited by 10

Sugar types, genetic predictors of the gut microbiome, and the risk of chronic kidney disease: a prospective cohort study

Zheng, G., Zhang, Y., Ou, F., Chang, Q., Ji, C., Yang, H., Chen, L., Xia, Y., & Zhao, Y. (2024) · Food & Function · doi:10.1039/d4fo00724g · Cited by 9

Beyond the family's cooking frequency: The influence of cooking techniques on vegetable and fruit consumption among the U.S. population

Baraldi, L. G., Grilo, M. F., Landert, M. D., & Martins, C. A. (2024) · Appetite · doi:10.1016/j.appet.2024.107757 · Cited by 9

Improving the dietary quality of food parcels leads to improved dietary intake in Dutch food bank recipients—effects of a randomized controlled trial

Neter, J. E., Dijkstra, S. C., Twisk, J. W. R., Visser, M., & Brouwer, I. A. (2020) · European Journal of Nutrition · doi:10.1007/s00394-020-02182-8 · Cited by 9

Development, validity and reproducibility of a whole grain food frequency questionnaire in Malaysian children

Koo, H. C., Lim, G. P., Kaur, S., Chan, K. Q., Tan, Y. X. F., Pang, X. J., & Tang, L. (2020) · Nutrition Journal · doi:10.1186/s12937-020-00588-y · Cited by 9

Relative validation of a pre-coded food diary in a group of Norwegian adults – Comparison of underreporters and acceptable reporters

Myhre, J. B., Johansen, A. M. W., Hjartåker, A., & Andersen, L. F. (2018) · PLoS ONE · doi:10.1371/journal.pone.0202907 · Cited by 9

Appetite responses to pecan-enriched diets

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The Accuracy of Portion Size Reporting on Self-Administered Online 24-Hour Dietary Recalls Among Women With Low Incomes

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Total energy expenditure as assessed by doubly labeled water and all-cause mortality in a cohort of postmenopausal women

Prentice, R. L., Aragaki, A. K., Manson, J. E., Schoeller, D. A., Tinker, L. F., Mossavar‐Rahmani, Y., Wallace, R. B., LaMonte, M. J., Tooze, J. A., Johnson, K., et al. (2023) · American Journal of Clinical Nutrition · doi:10.1016/j.ajcnut.2023.02.023 · Cited by 9

Relationships between misreported energy intake and pregnancy in the pregnancy, infection and nutrition study: new insights from a dynamic energy balance model

Thomas, D. M., Bredlau, C. E., Islam, S., Armah, K. A., Kunnipparampil, J., Patel, K., Redman, L. M., Misra, D. P., & Salafia, C. (2016) · Obesity Science & Practice · doi:10.1002/osp4.29 · Cited by 9

Diet quality as assessed by Healthy Eating Index-2015 among Hungarian Roma living in settlements of Northeast Hungary

Bárdos, H., Llanaj, E., Vincze, F., Diószegi, J., Pikó, P., Kósa, Z., Sándor, J., & Ádány, R. (2022) · Scientific Reports · doi:10.1038/s41598-022-23670-3 · Cited by 8

Combining a Food Frequency Questionnaire With 24-Hour Recalls to Increase the Precision of Estimation of Usual Dietary Intakes—Evidence From the Validation Studies Pooling Project

Freedman, L. S., Midthune, D., Arab, L., Prentice, R. L., Subar, A. F., Willett, W., Neuhouser, M. L., Tinker, L. F., & Kipnis, V. (2018) · American Journal of Epidemiology · doi:10.1093/aje/kwy126 · Cited by 116

Comparison of self-reported dietary intakes from the Automated Self-Administered 24-h recall, 4-d food records, and food-frequency questionnaires against recovery biomarkers

Park, Y., Dodd, K. W., Kipnis, V., Thompson, F. E., Potischman, N., Schoeller, D. A., Baer, D. J., Midthune, D., Troiano, R. P., Bowles, H., et al. (2018) · The American Journal of Clinical Nutrition · doi:10.1093/ajcn/nqx002 · Cited by 367

Evaluation of the 24-Hour Recall as a Reference Instrument for Calibrating Other Self-Report Instruments in Nutritional Cohort Studies: Evidence From the Validation Studies Pooling Project

Freedman, L. S., Commins, J. M., Willett, W. C., Tinker, L. F., Spiegelman, D. L., Rhodes, D. G., Potischman, N. A., Neuhouser, M. L., Moshfegh, A. J., Kipnis, V., et al. (2017) · American Journal of Epidemiology · doi:10.1093/aje/kwx039 · Cited by 63

Using Intake Biomarkers to Evaluate the Extent of Dietary Misreporting in a Large Sample of Adults: The OPEN Study

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Evaluation and Comparison of Food Records, Recalls, and Frequencies for Energy and Protein Assessment by Using Recovery Biomarkers

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