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Procedures for screening out inaccurate reports of dietary energy intake

Published online by Cambridge University Press:  22 December 2006

Megan A Mccrory*
The Energy Metabolism Laboratory, Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, 711 Washington Street, Boston, MA 02111-1524, USA
Cheryl L Hajduk
The Energy Metabolism Laboratory, Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, 711 Washington Street, Boston, MA 02111-1524, USA
Susan B Roberts
The Energy Metabolism Laboratory, Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, 711 Washington Street, Boston, MA 02111-1524, USA
*Corresponding author: Email
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To review existing methods and illustrate the use of a new, simple method for identifying inaccurate reports of dietary energy intake (rEI).


Comparison of rEI with energy requirements estimated by using total energy expenditure predicted (pTEE) from age, weight, height and sex using a previously published equation. Propagation of error calculations was performed and cut-offs for excluding rEI at plus or minus two standard deviations (±2 SD) and ±1 SD for the agreement between rEI and pTEE were established.


Dietary survey in a US national cohort: the Continuing Survey of Food Intakes by Individuals (CSFII), 1994–96.


Men and non-pregnant, non-lactating women aged 21–45 years in the CSFII who provided two multiple-pass 24-hour recalls, height and weight(n = 3755).


Average rEI was 77% of pTEE in men, and 64% of pTEE in women. Calculated cut-offs were rEI <40% or >160% of pTEE (±2 SD) and <70% or >130% of pTEE (±1 SD), respectively. Use of only the ±1 SD cut-offs, not the ±2 SD cut-offs, resulted in a relationship between rEI and body weight similar to what was expected (based on an independently calculated relationship between rEI and measured TEE). Exclusion of rEI outside either the ±2 SD (11% of subjects) or ±1 SD (57% of subjects) cut-offs did not affect mean reported macronutrient intakes, but did markedly affect relationships between dietary composition and body mass index.


When examining relationships between diet and health, use of ±1 SD cut-offs may be preferable to ±2 SD cut-offs for excluding inaccurate dietary reports.

Research Article
Copyright © CAB International 2002


1Schoeller, Da, Bandini, LG, Dietz, WH. Inaccuracies in self-reported intake identified by comparison with the doubly labelled water method. Can. J. Physiol. Pharmacol. 1990; 68: 941–9.Google Scholar
2Schoeller, DA. Limitations in the assessment of dietary energy intake by self-report. Metabolism. 1995; 44: 1822.Google Scholar
3Bingham, SA, Cassidy, A, Cole, TJ, Welch, A, Runswick, SA, Black, AE, et al. Validation of weighed records and other methods of dietary assessment using the 24 h urine nitrogen technique and other biological markers. Br. J. Nutr. 1995; 73: 531–50.Google Scholar
4Briefel, RR, Sempos, CT, McDowell, MA, Chien, SC-, Alaimo, K. Dietary methods research in the third National Health and Nutrition Examination Survey: underreporting of energy intake. Am. J. Clin. Nutr. 1997; 65(Suppl.): 1203S–9S.Google Scholar
5Lafay, L, Basdevant, A, Charles, MA, Vray, M, Balkau, B, Borys, JM, et al. Determinants and nature of dietary underreporting in a free-living population: the Fleurbaix Laventie Ville Sante (FLVS) study. Int. J. Obes. 1997; 21: 567–73.Google Scholar
6Adams, SJ. The dietary intake of people with non-insulin-dependent diabetes (NIDDM): how valid is self-reported intake?. J. Hum. Nutr. Diet. 1998; 11: 295306.Google Scholar
7Voss, S, Kroke, A, Klipstein-Grobusch, K, Boeing, H. Is macronutrient composition of dietary intake data affected by underreporting? Result from the EPIC–Potsdam Study. European Prospective Investigation into Cancer and Nutrition. Eur. J. Clin. Nutr. 1998; 52: 119–26.Google Scholar
8Pomerleau, J, Ostbye, T, Bright-See, E. Potential underreporting of energy intake in the Ontario Health Survey and its relationship with nutrient and food intakes. Eur. J. Clin. Nutr. 1999; 15: 553–7.Google Scholar
9Samaras, K, Kelly, PJ, Campbell, LV. Dietary underreporting is prevalent in middle-aged British women and is not related to adiposity (percentage body fat). Int. J. Obes. 1999; 23: 881–8.Google Scholar
10Goris, AHC, Westerterp-Plantenga, MS, Westerterp, KR. Undereating and underrecording of habitual food intake in obese men: selective underreporting of fat intake. Am. J. Clin. Nutr. 2000; 71: 130–4.Google Scholar
11Saltzman, E, Roberts, SB. The role of energy expenditure in energy regulation: findings from a decade of research. Nutr. Rev. 1995; 53: 209–20.Google Scholar
12Bray, G, Popkin, BM. Dietary fat intake does affect obesity!. Am. J. Clin. Nutr. 1998; 68: 1157–73.Google Scholar
13Roberts, SB, Pi-Sunyer, FX, Dreher, M, Hahn, R, Hill, JO, Kleinman, RE, et al. Physiology of fat replacement and fat reduction: effects of dietary fat and fat substitutes on energy regulation. Nutr. Rev. 1998; 56: S29–49.Google Scholar
14Willett, WC. Dietary fat and obesity: an unconvincing relation. Am. J. Clin. Nutr. 1998; 68: 1149–50.Google Scholar
15Prentice, AM, Cole, TJ. The Doubly-Labelled Water Method for Measuring Energy Expenditure. Technical Recommendations for Use in Humans: A Consensus Report. Vienna: Section of Nutritional and Health-Related Environmental Studies, International Atomic Energy Agency, International Dietary Energy Consultancy Group, 1990.Google Scholar
16Speakman, JR. Doubly Labelled Water: Theory and Practice, 1st ed. London: Chapman & Hall. 1997.Google Scholar
17Black, AE. The sensitivity and specificity of the Goldberg cut-off for EI:BMR for identifying diet reports of poor validity. Eur. J. Clin. Nutr. 2000; 54: 395404.Google Scholar
18US Department of Agriculture, Agricultural Research Service. CSFII/DHKS 1994–96 Data Set and Documentation: The 1994–96 Continuing Survey of Food Intakes by Individuals and the 1994–96 Diet and Health Knowledge Survey. Springfield, VA: National Technical Information Service, 1998; data tables.Google Scholar
19Beaton, GH, Milner, J, Corey, P, McGuire, V, Cousins, M, Stewart, E, et al. Sources of variance in 24-hour dietary recall data: implications for nutrition study design and interpretation. Am. J. Clin. Nutr. 1979; 32: 2546–9.Google Scholar
20Black, AE. Critical evaluation of energy intake using the Goldberg cut-off for energy intake:basal metabolic rate. A practical guide to its calculation, use and limitations. Int. J. Obes. 2000; 24: 1119–30.Google Scholar
21Marr, JW, Heady, JA. Within- and between-person variation in dietary surveys: number of days needed to classify individuals. Hum. Nutr. Appl. Nutr. 1986; 40A: 347–64.Google Scholar
22Nelson, M, Black, AE, Morris, JA, Cole, TJ. Between- and within-subject variation in nutrient intake from infancy to old age: estimating the number of days required to rank dietary intakes with desired precision. Am. J. Clin. Nutr. 1989; 50: 155–67.Google Scholar
23Prentice, RL. Measurement error and results from analytic epidemiology: dietary fat and breast cancer. J. Natl. Cancer Inst. 1996; 88: 1738–47.Google Scholar
24Paeratakul, S, Popkin, BM, Kohlmeier, L, Hertz-Picciotto, I, Guo, X, Edwards, LJ. Measurement error in dietary data: implications for the epidemiologic study of the diet–disease relationship. Eur. J. Clin. Nutr. 1998; 52: 722–7.Google Scholar
25Prentice, AM, Black, AE, Coward, WA, Davies, HL, Goldberg, GR, Murgatroyd, PR, et al. High levels of energy expenditure in obese women. Br. Med. J. 1986; 292: 983–7.Google Scholar
26Bandini, LG, Schoeller, DA, Cyr, HN, Dietz, WH. Validity of reported energy intake in obese and nonobese adolescents. Am. J. Clin. Nutr. 1990; 52: 421–5.Google Scholar
27Lichtman, SW, Pisarska, K, Berman, ER, Pestone, M, Dowling, H, Offenbacher, E, et al. Discrepancy between self-reported and actual caloric intake and exercise in obese subjects. N. Engl. J. Med. 1992; 327: 1893–8.Google Scholar
28Bathalon, GP, Tucker, KL, Hays, NP, Vinken, AG, Greenberg, AS, McCrory, MA, et al. Psychological measures of eating behavior and the accuracy of 3 common dietary assessment methods in healthy postmenopausal women. Am. J. Clin. Nutr. 2000; 71: 739–45.Google Scholar
29Goris, AHC, Westerterp, KR. Underreporting of habitual food intake is explained by undereating in highly motivated lean women. J. Nutr. 1999; 129: 878–82.Google Scholar
30Stunkard, AJ, Messick, S. The three-factor eating questionnaire to measure dietary restraint, disinhibition and hunger. J. Psychosom. Res. 1985; 29: 7183.Google Scholar
31Pryer, JA, Vrijheid, M, Nichols, R, Kiggins, M, Elliott, P. Who are the ‘low energy reporters’ in the Dietary and Nutritional Survey of British Adults?. Int. J. Epidemiol. 1997; 26: 146–54.Google Scholar
32Johnson, 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.Google Scholar
33Braam, LA, Ocké, MC, Bueno-de-Mesquita, HB, Seidell, JC. Determinants of obesity-related underreporting of energy intake. Am. J. Epidemiol. 1998; 147: 1081–6.Google Scholar
34Kretsch, MJ, Fong, AKH, Green, MW. Behavioral and body size correlates of energy intake underreporting by obese and normal-weight women. J. Am. Diet. Assoc. 1999; 99: 300–6.Google Scholar
35Tomoyasu, NJ, Toth, MJ, Poehlman, ET. Misreporting of total energy intake in older men and women. J. Am. Geriatr. Soc. 1999; 47: 710–5.Google Scholar
36Mennen, LI, Jackson, M, Cade, J, Mbanya, JC, Lafay, L, Sharma, S. Underreporting of energy intake in four populations of African origin. Int. J. Obes. 2000; 24: 882–7.Google Scholar
37Macdiarmid, J, Blundell, J. Assessing dietary intake: who, what and why of under-reporting. Nutr. Res. Rev. 1998; 11: 231–53.Google Scholar
38Goldberg, 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.Google Scholar
39Black, AE, Coward, WA, Cole, TJ, Prentice, AM. Human energy expenditure in affluent societies: an analysis of 574 doubly-labelled water measurements. Eur. J. Clin. Nutr. 1996; 50: 7292.Google Scholar
40Black, AE, Goldberg, GR, Jebb, SA, Livingstone, MBE, Cole, TJ, Prentice, AM. Critical evaluation of energy intake data using fundamental principles of energy physiology: 2. Evaluating the results of published surveys. Eur. J. Clin. Nutr. 1991; 45: 583–99.Google Scholar
41Warwick, PM, Baines, J. Energy expenditure in free-living smokers and nonsmokers: comparison between factorial, intake-balance, and doubly labeled water measures. Am. J. Clin. Nutr. 1996; 63: 1521.Google Scholar
42FAO/WHO/UNU. Energy and Protein Requirements: Report of a Joint FAO/WHO/UNU Expert Consultation. Geneva: World Health Organization, 1965.Google Scholar
43Vinken, AG, Bathalon, GP, Sawaya, AL, Dallal, GE, Tucker, KL, Roberts, SB. Equations for predicting the energy requirements of healthy adults aged 18–81 y. Am. J. Clin. Nutr. 1999; 69: 920–6.Google Scholar
44Shetty, PS, Henry, CJK, Black, AE, Prentice, AM. Energy requirements of adults: an update on basal metabolic rates (BMRs) and physical activity levels (PALs). Eur. J. Clin. Nutr. 1996; 50(Suppl. 1): S11–23.Google Scholar
45Roberts, SB, Heyman, MB, Evans, WJ, Fuss, P, Tsay, R, Young, VR. Dietary energy requirements of young adult men, determined by using the doubly labeled water method. Am. J. Clin. Nutr. 1991; 54: 499505.Google Scholar
46Roberts, SB, Young, VR, Fuss, P, Heyman, MB, Fiatarone, M, Dallal, GE, et al. What are the dietary energy needs of elderly adults?. Int. J. Obes. 1992; 16: 969–76.Google Scholar
47Prentice, AM, Black, AE, Coward, WA, Cole, TJ. Energy expenditure in overweight and obese adults in affluent societies: an analysis of 319 doubly-labelled water measurements. Eur. J. Clin. Nutr. 1996; 50: 93–7.Google Scholar
48Goldberg, GR. From individual variation in energy intakes…to variations in energy requirements and adaptations to them. Br. J. Nutr. 1997; 78(Suppl. 2): S81–94.Google Scholar
49Macdiarmid, JI, Vail, A, Cade, JE, Blundell, JE. The sugar–fat relationship revisited: differences in consumption between men and women of varying BMI. Int. J. Obes. 1998; 22: 1053–61.Google Scholar
50Stallone, DD, Brunner, EJ, Bingham, SA, Marmot, MG. Dietary assessment in Whitehall II: the influence of reporting bias on apparent socioeconomic variation in nutrient intakes. Eur. J. Clin. Nutr. 1997; 51: 815–25.Google Scholar