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The impact of body composition on the degree of misreporting of food diaries

European Journal of Clinical Nutrition volume 78, pages 209–216 (2024)Cite this article

Subjects

Abstract

Background/Objectives

Accurate assessments of energy intake (EI) are needed in lifestyle interventions to guarantee a negative energy balance (EB), thereby losing weight. This study aimed (1) to compare objectively measured and self-reported EI and (2) to determine the predictors of underreporting divided by sex, adiposity and BMI category.

Methods

Seventy-three participants [mean (SD): 43.7 (9.2) years, BMI = 31.5 (4.5) kg/m2, 37% females] of the Champ4Life intervention were included in this study. EI was measured using the “intake-balance method” and self-reported through 3-day food records. Fat mass (FM) and fat-free mass (FFM) were measured by dual-energy X-ray absorptiometry. Bland–Altman analysis was performed to compare both EI assessments.

Results

Self-reported EI was lower than measured EI during both neutral (–355 kcal/d) and negative EB (–570 kal/day). While no significant trends were observed for EI evaluation in either neutral (p = 0.315) or negative EB (p = 0.611), limits of agreement were wide (–1720 to 1010 and –1920 to 779 kcal/day, respectively). In females, the degree of misreporting (kcal/day and %) was predicted by weight (p = 0.032 and p = 0.039, respectively) and FM (p = 0.029 and p = 0.037, respectively). In males, only BMI (p = 0.036) was a predictor of misreporting (kcal/day).

Conclusion

Self-reported EI did not agree with measured EI. Our results show that larger body size was associated with higher levels of underestimation for EI (females only). Nevertheless, misreporting EI is a complex issue involving more associations than merely body composition. A deeper understanding could inform counseling for participants filling out food records in other to reduce misreporting and improve validity.

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Fig. 1: Schematic presentation of the study.
Fig. 2: Association and agreement between measured (intake-balance method) and self-reported EI (food records).
Fig. 3: Associations between the magnitude of weight and fat mass loss and the degree of misreporting at 4 months.

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Data availability

The data that support the findings of this study are available from the corresponding author, AMS, upon reasonable request.

References

  1. Dahle JH, Ostendorf DM, Zaman A, Pan Z, Melanson EL, Catenacci VA. Underreporting of energy intake in weight loss maintainers. Am J Clin Nutr. 2021;114:257–66. https://doi.org/10.1093/ajcn/nqab012

    Article  PubMed  PubMed Central  Google Scholar 

  2. Westerterp KR. Doubly labelled water assessment of energy expenditure: principle, practice, and promise. Eur J Appl Physiol. 2017;117:1277–85. https://doi.org/10.1007/s00421-017-3641-x.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Speakman JR, Yamada Y, Sagayama H, Berman ESF, Ainslie PN, Andersen LF, et al. A standard calculation methodology for human doubly labeled water studies. Cell Rep Med. 2021;2:100203. https://doi.org/10.1016/j.xcrm.2021.100203.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. de Jonge L, DeLany JP, Nguyen T, Howard J, Hadley EC, Redman LM, et al. Validation study of energy expenditure and intake during calorie restriction using doubly labeled water and changes in body composition. Am J Clin Nutr. 2007;85:73–9. https://doi.org/10.1093/ajcn/85.1.73.

    Article  PubMed  Google Scholar 

  5. Poslusna K, Ruprich J, de Vries JH, Jakubikova M, van’t Veer P. Misreporting of energy and micronutrient intake estimated by food records and 24 h recalls, control and adjustment methods in practice. Br J Nutr. 2009;101:S73–85. https://doi.org/10.1017/s0007114509990602

    Article  CAS  PubMed  Google Scholar 

  6. Pisanu S, Deledda A, Loviselli A, Huybrechts I, Velluzzi F. Validity of accelerometers for the evaluation of energy expenditure in obese and overweight individuals: a systematic review. J Nutr Metab. 2020;2020:2327017. https://doi.org/10.1155/2020/2327017.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Ravelli MN, Schoeller DA. Traditional self-reported dietary instruments are prone to inaccuracies and new approaches are needed. Front Nutr. 2020;7:90. https://doi.org/10.3389/fnut.2020.00090.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Burrows TL, Ho YY, Rollo ME, Collins CE. Validity of dietary assessment methods when compared to the method of doubly labeled water: a systematic review in adults. Front Endocrinol. 2019;10:850. https://doi.org/10.3389/fendo.2019.00850.

    Article  Google Scholar 

  9. Bawadi H, Akasheh RT, Kerkadi A, Haydar S, Tayyem R, Shi Z. Validity and reproducibility of a food frequency questionnaire to assess macro and micro-nutrient intake among a convenience cohort of healthy adult qataris. Nutrients. 2021;13:2002. https://doi.org/10.3390/nu13062002.

  10. Maurer J, Taren DL, Teixeira PJ, Thomson CA, Lohman TG, Going SB, et al. The psychosocial and behavioral characteristics related to energy misreporting. Nutr Rev. 2006;64:53–66. https://doi.org/10.1301/nr.2006.feb.53-66

    Article  PubMed  Google Scholar 

  11. Dhurandhar NV, Schoeller D, Brown AW, Heymsfield SB, Thomas D, Sørensen TI, et al. Energy balance measurement: when something is not better than nothing. Int J Obes (Lond). 2015;39:1109–13. https://doi.org/10.1038/ijo.2014.199.

    Article  CAS  PubMed  Google Scholar 

  12. Capling L, Beck KL, Gifford JA, Slater G, Flood VM, O’Connor H. Validity of dietary assessment in athletes: a systematic review. Nutrients. 2017;9:1313. https://doi.org/10.3390/nu9121313.

  13. Banna JC, Fialkowski MK, Townsend MS. Misreporting of dietary intake affects estimated nutrient intakes in low-income Spanish-speaking women. J Acad Nutr Diet. 2015;115:1124–33. https://doi.org/10.1016/j.jand.2014.06.358.

    Article  PubMed  Google Scholar 

  14. Ravelli MN, Schoeller DA. An objective measure of energy intake using the principle of energy balance. Int J Obes (Lond). 2021;45:725–32. https://doi.org/10.1038/s41366-021-00738-0.

    Article  PubMed  Google Scholar 

  15. Shook RP, Hand GA, O’Connor DP, Thomas DM, Hurley TG, Hébert JR, et al. Energy intake derived from an energy balance equation, validated activity monitors, and dual X-ray absorptiometry can provide acceptable caloric intake data among young adults. J Nutr. 2018;148:490–6. https://doi.org/10.1093/jn/nxx029.

    Article  PubMed  Google Scholar 

  16. Gilmore LA, Ravussin E, Bray GA, Han H, Redman LM. An objective estimate of energy intake during weight gain using the intake-balance method. Am J Clin Nutr. 2014;100:806–12. https://doi.org/10.3945/ajcn.114.087122.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Silva AM, Nunes CL, Matias CN, Jesus F, Francisco R, Cardoso M, et al. Champ4life study protocol: a one-year randomized controlled trial of a lifestyle intervention for inactive former elite athletes with overweight/obesity. Nutrients. 2020;12:286. https://doi.org/10.3390/nu12020286.

  18. Michie S, Abraham C, Whittington C, McAteer J, Gupta S. Effective techniques in healthy eating and physical activity interventions: a meta-regression. Health Psychol. 2009;28:690–701. https://doi.org/10.1037/a0016136.

    Article  PubMed  Google Scholar 

  19. World Medical Association. Declaration of Helsinki – ethical principles for medical research involving human subjects. WMJ. 2008;54:122–5.

    Google Scholar 

  20. Compher C, Frankenfield D, Keim N, Roth-Yousey L, Group EAW. Best practice methods to apply to measurement of resting metabolic rate in adults: a systematic review. J Am Diet Assoc. 2006;106:881–903.

    Article  PubMed  Google Scholar 

  21. Merril A, Watt B. Energy value of foods, basis and derivation. Agriculture Handbook No. 74. Washington, DC: ARS United States Department of Agriculture; 1973. p. 2.

  22. Dulloo AG, Jacquet J. The control of partitioning between protein and fat during human starvation: its internal determinants and biological significance. Br J Nutr. 1999;82:339–56. https://doi.org/10.1017/s0007114599001580.

    Article  CAS  PubMed  Google Scholar 

  23. Rosenbaum M, Ravussin E, Matthews DE, Gilker C, Ferraro R, Heymsfield SB, et al. A comparative study of different means of assessing long-term energy expenditure in humans. Am J Physiol. 1996;270:R496–504. https://doi.org/10.1152/ajpregu.1996.270.3.R496.

    Article  CAS  PubMed  Google Scholar 

  24. Racette SB, Das SK, Bhapkar M, Hadley EC, Roberts SB, Ravussin E, et al. Approaches for quantifying energy intake and %calorie restriction during calorie restriction interventions in humans: the multicenter CALERIE study. Am J Physiol Endocrinol Metab. 2012;302:E441–8. https://doi.org/10.1152/ajpendo.00290.2011.

    Article  CAS  PubMed  Google Scholar 

  25. Goldberg GR, Black AE, Jebb SA, Cole TJ, Murgatroyd PR, Coward WA, et al. Critical evaluation of energy intake data using fundamental principles of energy physiology: 1. Derivation of cut-off limits to identify under-recording. Eur J Clin Nutr. 1991;45:569–81.

    CAS  PubMed  Google Scholar 

  26. Silva AM, Nunes CL, Jesus F, Francisco R, Matias CN, Cardoso M, et al. Effectiveness of a lifestyle weight-loss intervention targeting inactive former elite athletes: the Champ4Life randomised controlled trial. Br J Sports Med. 2022;56:394–401. https://doi.org/10.1136/bjsports-2021-104212.

  27. Johnson RK, Soultanakis RP, Matthews DE. Literacy and body fatness are associated with underreporting of energy intake in US low-income women using the multiple-pass 24-hour recall: a doubly labeled water study. J Am Diet Assoc. 1998;98:1136–40. https://doi.org/10.1016/s0002-8223(98)00263-6.

    Article  CAS  PubMed  Google Scholar 

  28. Poppitt SD, Swann D, Black AE, Prentice AM. Assessment of selective under-reporting of food intake by both obese and non-obese women in a metabolic facility. Int J Obes Relat Metab Disord. 1998;22:303–11. https://doi.org/10.1038/sj.ijo.0800584.

    Article  CAS  PubMed  Google Scholar 

  29. Koebnick C, Wagner K, Thielecke F, Dieter G, Höhne A, Franke A, et al. An easy-to-use semiquantitative food record validated for energy intake by using doubly labelled water technique. Eur J Clin Nutr. 2005;59:989–95. https://doi.org/10.1038/sj.ejcn.1602200

    Article  CAS  PubMed  Google Scholar 

  30. de Vries JH, Zock PL, Mensink RP, Katan MB. Underestimation of energy intake by 3-d records compared with energy intake to maintain body weight in 269 nonobese adults. Am J Clin Nutr. 1994;60:855–60. https://doi.org/10.1093/ajcn/60.6.855.

    Article  PubMed  Google Scholar 

  31. Barnard JA, Tapsell LC, Davies PS, Brenninger VL, Storlien LH. Relationship of high energy expenditure and variation in dietary intake with reporting accuracy on 7 day food records and diet histories in a group of healthy adult volunteers. Eur J Clin Nutr. 2002;56:358–67. https://doi.org/10.1038/sj.ejcn.1601341.

    Article  CAS  PubMed  Google Scholar 

  32. McKenzie BL, Coyle DH, Santos JA, Burrows T, Rosewarne E, Peters SAE, et al. Investigating sex differences in the accuracy of dietary assessment methods to measure energy intake in adults: a systematic review and meta-analysis. Am J Clin Nutr. 2021;113:1241–55. https://doi.org/10.1093/ajcn/nqaa370

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. World Bank. Global adult literacy rate aged 15 years and older from 1976 to 2019 by gender [Graph]. In: Statista; 2020.

  34. Nutbeam D, McGill B, Premkumar P. Improving health literacy in community populations: a review of progress. Health Promot Int. 2018;33:901–11. https://doi.org/10.1093/heapro/dax015.

    Article  PubMed  Google Scholar 

  35. Schoeller DA. Limitations in the assessment of dietary energy intake by self-report. Metabolism. 1995;44:18–22. https://doi.org/10.1016/0026-0495(95)90204-x.

    Article  CAS  PubMed  Google Scholar 

  36. Livingstone MB, Black AE. Markers of the validity of reported energy intake. J Nutr. 2003;133:895s–920. https://doi.org/10.1093/jn/133.3.895S.

    Article  CAS  PubMed  Google Scholar 

  37. Ortega RM, Perez-Rodrigo C, Lopez-Sobaler AM. Dietary assessment methods: dietary records. Nutri Hosp. 2015;31:38–45. https://doi.org/10.3305/nh.2015.31.sup3.8749.

    Article  Google Scholar 

  38. Cade JE, Warthon-Medina M, Albar S, Alwan NA, Ness A, Roe M, et al. DIET@NET: Best Practice Guidelines for dietary assessment in health research. BMC Med. 2017;15:202. https://doi.org/10.1186/s12916-017-0962-x.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Sedgwick P, Greenwood N. Understanding the Hawthorne effect. BMJ. 2015;351:h4672. https://doi.org/10.1136/bmj.h4672.

    Article  PubMed  Google Scholar 

  40. Hartmann-Boyce J, Johns DJ, Jebb SA, Aveyard P. Effect of behavioural techniques and delivery mode on effectiveness of weight management: systematic review, meta-analysis and meta-regression. Obes Rev. 2014;15:598–609. https://doi.org/10.1111/obr.12165.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Funding

Financial support was provided by the Portuguese Institute of Sports and Youth and by the International Olympic Committee, under the Olympic Solidarity Promotion of the Olympic Values Unit (Sports Medicine and Protection of Clean Athletes Programme). The current work was also supported by national funding from the Portuguese Foundation for Science and Technology within the R&D units UIDB/00447/2020. CLN and FJ were supported with a PhD scholarship from the Portuguese Foundation for Science and Technology (SFRH/BD/143725/2019 and 2021.07122.BD, respectively).

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Authors and Affiliations

  1. Exercise and Health Laboratory, CIPER, Faculdade Motricidade Humana, Universidade Lisboa, Estrada da Costa, 1499-002, Cruz-Quebrada, Portugal

    Catarina L. Nunes, Filipe Jesus, Mariana V. Oliveira, Luís B. Sardinha, Cláudia S. Minderico & Analiza M. Silva

  2. Atlântica, Instituto Universitário, Fábrica da Pólvora de Barcarena, 2730-036, Barcarena, Portugal

    Catarina L. Nunes

  3. Department of Mathematical Sciences, United States Military Academy West Point, New York, NY, USA

    Diana M. Thomas

  4. Laboratory of Sport Psychology, Faculdade de Motricidade Humana da Universidade de Lisboa, 1499-002, Cruz-Quebrada, Portugal

    Paulo Martins

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Contributions

The Champ4Life project led by Primary Investigator AMS obtained funding for the research. CLN conceptualized and designed the study. CLN and FJ acquired the data. CLN performed the data analysis and interpretation. CLN and MVO wrote the first draft of the manuscript. All authors revised the manuscript critically and contributed to the final approval of the version to be submitted.

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Correspondence to Analiza M. Silva.

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Nunes, C.L., Jesus, F., Oliveira, M.V. et al. The impact of body composition on the degree of misreporting of food diaries. Eur J Clin Nutr 78, 209–216 (2024). https://doi.org/10.1038/s41430-023-01382-9

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