Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-26T16:47:44.393Z Has data issue: false hasContentIssue false

Bias in dietary-report instruments and its implications for nutritional epidemiology

Published online by Cambridge University Press:  22 December 2006

Victor Kipnis*
Affiliation:
Biometry Research Group, Division of Cancer Prevention, National Cancer Institute, Bethesda, MD 20892-7354, USA
Douglas Midthune
Affiliation:
Biometry Research Group, Division of Cancer Prevention, National Cancer Institute, Bethesda, MD 20892-7354, USA
Laurence Freedman
Affiliation:
Bar Ilan University, Ramat Gan, Israel and Gertner Institute for Epidemiology and Health Policy Research, Tel Hashomer, Israel
Sheila Bingham
Affiliation:
Medical Research Council, Dunn Human Nutrition Unit, Cambridge, UK
Nicholas E Day
Affiliation:
Strangeways Research Laboratory, University of Cambridge, Cambridge, UK
Elio Riboli
Affiliation:
Unit of Nutrition and Cancer, International Agency for Research on Cancer, Lyon, France
Pietro Ferrari
Affiliation:
Unit of Nutrition and Cancer, International Agency for Research on Cancer, Lyon, France
Raymond J Carroll
Affiliation:
Department of Statistics, Texas A&M University, College Station, TX, USA
*
*Corresponding author: Email [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Objective:

To evaluate measurement error structure in dietary assessment instruments and to investigate its implications for nutritional studies, using urinary nitrogen excretion as a reference biomarker for protein intake.

Design:

The dietary assessment methods included different food-frequency questionnaires (FFQs) and such conventional dietary-report reference instruments as a series of 24-hour recalls, 4-day weighed food records or 7-day diaries.

Setting:

Six original pilot validation studies within the European Prospective Investigation of Cancer (EPIC), and two validation studies conducted by the British Medical Research Council (MRC) within the Norfolk cohort that later joined as a collaborative component cohort of EPIC.

Subjects:

A sample of approximately 100 to 200 women and men, aged 35–74 years, from each of eight validation studies.

Results:

In assessing protein intake, all conventional dietary-report reference methods violated the critical requirements for a valid reference instrument for evaluating, and adjusting for, dietary measurement error in an FFQ. They displayed systematic bias that depended partly on true intake and partly was person-specific, correlated with person-specific bias in the FFQ. Using the dietary-report methods as reference instruments produced substantial overestimation (up to 230%) of the FFQ correlation with true usual intake and serious underestimation (up to 240%) of the degree of attenuation of FFQ-based log relative risks.

Conclusion:

The impact of measurement error in dietary assessment instruments on the design, analysis and interpretation of nutritional studies may be much greater than has been previously estimated, at least regarding protein intake.

Type
Part E. New statistical approaches to dealing with bias associated with dietary data
Copyright
Copyright © CAB International 2002

References

1Hunter, Dj, Spiegelman, D, Adami, H-O, Beeson, L, Van den Brandt, PA, Folsom, AR, et al. Cohort studies of fat intake and the risk of breast cancer – a pooled analysis. N. Engl. J. Med. 1996; 334: 356–61.CrossRefGoogle ScholarPubMed
2Fuchs, CS, Giovannucci, EL, Colditz, GA, Hunter, DJ, Stampfer, MJ, Rosner, B, et al. Dietary fiber and the risk of colorectal cancer and adenoma in women. N. Engl. J. Med. 1999; 340: 169–76.CrossRefGoogle ScholarPubMed
3Michels, KB, Giovannucci, E, Joshipura, KJ, Rosner, BA, Stampfer, MJ, Fuchs, CS, et al. Prospective study of fruit and vegetable consumption and incidence of colon and rectal cancers. J. Natl. Cancer Inst. 2000; 92: 1740–52.CrossRefGoogle ScholarPubMed
4Beaton, 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.CrossRefGoogle ScholarPubMed
5Freudenheim, JL, Marshall, JR. The problem of profound mismeasurement and the power of epidemiological studies of diet and cancer. Nutr. Cancer. 1988; 11: 243–50.CrossRefGoogle ScholarPubMed
6Freedman, LS, Schatzkin, A, Wax, J. The impact of dietary measurement error on planning sample size required in a cohort study. Am. J. Epidemiol. 1990; 132: 1185–95.CrossRefGoogle ScholarPubMed
7Kipnis, V, Carroll, RJ, Freedman, LS, Li, L. Implications of a new dietary measurement error model for estimation of relative risk: application to four calibration studies. Am. J. Epidemiol. 1999; 150: 642–51.CrossRefGoogle ScholarPubMed
8Willett, W. Nutritional Epidemiology. New York: Oxford University Press, 1990.Google Scholar
9Rosner, B, Willett, WC. Interval estimates for correlation coefficients corrected for within-person variation: implications for study design and hypothesis testing. Am. J. Epidemiol. 1988; 127: 377–86.CrossRefGoogle ScholarPubMed
10Rosner, B, Willett, WC, Spiegelman, D. Correction of logistic regression relative risk estimates and confidence intervals for systematic within-person measurement error. Stat. Med. 1989; 8: 1051–69.CrossRefGoogle ScholarPubMed
11Bandini, 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.CrossRefGoogle ScholarPubMed
12Livingstone, MBE, Prentice, AM, Strain, JJ, Coward, WA, Black, AE, Barker, ME, et al. Accuracy of weighed dietary records in studies of diet and health. Br. Med. J. 1990; 300: 708–12.CrossRefGoogle ScholarPubMed
13Heitmann, BL. The influence of fatness, weight change, slimming history and other lifestyle variables on diet reporting in Danish men and women aged 35–65 years. Int. J. Obes. 1993; 17: 329–36.Google ScholarPubMed
14Heitmann, BL, Lissner, L. Dietary underreporting by obese individuals – is it specific or non-specific?. Br. Med. J. 1995; 311: 986–9.CrossRefGoogle ScholarPubMed
15Martin, LJ, Su, W, Jones, PJ, Lockwood, GA, Tritchler, DL, Boyd, NF. Comparison of energy intakes determined by food records and doubly labeled water in women participating in a dietary-intervention trial. Am. J. Clin. Nutr. 1996; 63: 483–90.CrossRefGoogle Scholar
16Sawaya, AL, Tucker, K, Tsay, R, Willett, W, Saltzman, E, Dallal, GE, et al. Evaluation of four methods for determining energy intake in young and older women: comparison with doubly labeled water measurements of total energy expenditure. Am. J. Clin. Nutr. 1996; 63: 491–9.CrossRefGoogle Scholar
17Black, AE, Bingham, SA, Johansson, G, Coward, WA. Validation of dietary intakes of protein and energy against 24 hour urinary N and DLW energy expenditure in middle-aged women, retired men and post-obese subjects: comparisons with validation against presumed energy requirements. Eur. J. Clin. Nutr. 1997; 51: 405–13.CrossRefGoogle ScholarPubMed
18Prentice, RL. Measurement error and results from analytic epidemiology: dietary fat and breast cancer. J. Natl. Cancer Inst. 1996; 88: 1738–47.CrossRefGoogle ScholarPubMed
19Kipnis, V, Midthune, D, Freedman, LS, Bingham, S, Schatzkin, A, Subar, A, et al. Empirical evidence of correlated biases in dietary assessment instruments and its implications. Am. J. Epidmiol. 2001; 153: 394403.CrossRefGoogle ScholarPubMed
20Carroll, RJ, Ruppert, D, Stefanski, LA. Measurement Error in Nonlinear Models. London: Chapman & Hall, 1995.CrossRefGoogle Scholar
21Kaaks, R, Riboli, E, van Staveren, W. Calibration of dietary intake measurements in prospective cohort studies. Am. J. Epidemiol. 1995; 142: 548–56.CrossRefGoogle ScholarPubMed
22Freedman, LS, Carroll, RJ, Wax, Y. Estimating the relation between dietary intake obtained from a food frequency questionnaire and true average intake. Am. J. Epidemiol. 1991; 134: 310–20.CrossRefGoogle ScholarPubMed
23Kaaks, RJ. Biochemical markers as additional measurements in studies of the accuracy of dietary questionnaire measurements: conceptional issues. Am. J. Clin. Nutr. 1997; 65(Suppl.): 1232S–9S.CrossRefGoogle Scholar
24Bingham, SA, Cummings, JH. Urine nitrogen as an independent validatory measure of dietary intake: a study of nitrogen balance in individuals consuming their normal diet. Am. J. Clin. Nutr. 1985; 42: 1276–89.CrossRefGoogle ScholarPubMed
25Kaaks, R, Slimani, N, Riboli, E. Pilot phase studies on the accuracy of dietary intake measurements in the EPIC project: overall evaluation of results. European Prospective Investigation into Cancer and Nutrition. Int. J. Epidemiol. 1997; 26(Suppl. 1): s26–36.CrossRefGoogle ScholarPubMed
26Bingham, SA, Gill, C, Welch, A, Cassidy, A, Runswick, SA, Oakes, S, et al. Validation of dietary assessment methods in the UK arm of EPIC using weighed records and 24-hour urinary nitrogen and potassium and serum vitamin C and carotenoids as biomarkers. Int. J. Epidemiol. 1997; 26(Suppl. 1): S137–51.CrossRefGoogle ScholarPubMed
27Day, N, Oakes, S, Luben, R, Khaw, KT, Bingham, S, Welch, A, et al. EPIC–Norfolk: study design and characteristics of the cohort. Br. J. Cancer 1999; 80(Suppl. 1): 95103.Google Scholar
28Campbell, WW, Crim, MC, Dallal, GE, Young, VR, Evans, WJ. Increased protein requirements in elderly people: new data and retrospective reassessments. Am. J. Clin. Nutr. 1994; 60: 501–9.CrossRefGoogle ScholarPubMed
29Zanni, E, Calloway, DH, Zezulka, AY. Protein requirements of elderly men. J. Nutr. 1979; 109: 513–24.CrossRefGoogle ScholarPubMed
30Oddoye, EA, Margen, S. Nitrogen balance studies in humans: long-term effect of high nitrogen intake on nitrogen accretion. J. Nutr. 1979; 109: 363–77.CrossRefGoogle ScholarPubMed
31Weller, LA, Calloway, DH, Margen, S. Nitrogen balance of men fed amino acid mixtures based on Rose's requirements, egg white protein, and serum free amino acid patterns. J. Nutr. 1971; 101: 1499–508.CrossRefGoogle ScholarPubMed
32Bunker, VW, Lawson, MS, Stansfield, MF, Clayton, BE. Nitrogen balance studies in apparently healthy elderly people and those who are housebound. Br. J. Nutr. 1987; 57: 211–21.CrossRefGoogle ScholarPubMed
33Uauy, R, Scrimshaw, NS, Young, VR. Human protein requirements: nitrogen balance response to graded levels of egg protein in elderly men and women. Am. J. Clin. Nutr. 1978; 31: 779–85.CrossRefGoogle ScholarPubMed
34Castaneda, C, Charnley, JM, Evans, WJ, Crim, MC. Elderly women accommodate to a low-protein diet with losses of body cell mass, muscle function, and immune response. Am. J. Clin. Nutr. 1995; 62: 30–9.CrossRefGoogle ScholarPubMed
35Cheng, AHR, Gomez, A, Bergan, JG, Lee, TC, Monckeberg, F, Chichester, CO. Comparative nitrogen balance study between young and aged adults using three levels of protein intake from a combination wheat–soy–milk mixture. Am. J. Clin. Nutr. 1978; 31: 1222.CrossRefGoogle Scholar
36Atinmo, T, Mbofung, CMF, Egun, G, Osotimehin, B. Nitrogen balance study in young Nigerian adult males using four levels of protein intake. Br. J. Nutr. 1988; 60: 451–8.CrossRefGoogle ScholarPubMed
37Rand, WM, Scrimshaw, NS, Young, VR. Retrospective analysis of data from five long-term, metabolic balance studies: implications for understanding dietary nitrogen and energy utilization. Am. J. Clin. Nutr. 1985; 42: 1339–50.CrossRefGoogle ScholarPubMed
38Tarnopolsky, MA, Atkinson, SA, MacDougall, JD, Chesley, A, Phillips, S, Schwarcz, HP. Evaluation of protein requirements for trained strength athletes. J. Appl. Physiol. 1992; 73: 1986–95.CrossRefGoogle ScholarPubMed
39Pannemans, DLE, Wagenmakers, AJM, Westerterp, KR, Schaafsma, G, Halliday, D. Effect of protein source and quantity on protein metabolism in elderly women. Am. J. Clin. Nutr. 1998; 68: 1228–35.CrossRefGoogle ScholarPubMed
40Wayler, A, Queiroz, E, Scrimshaw, NS, Steinke, FH, Rand, WM, Young, VR. Nitrogen balance studies in young men to assess the protein quality of an isolated soy protein in relation to meat proteins. J. Nutr. 1983; 113: 2485–91.CrossRefGoogle ScholarPubMed
41Young, VR, Wayler, A, Garza, C, Steinke, FH, Murray, E, Rand, WM, et al. A long-term metabolic balance study in young men to assess the nutritional quality of an isolated soy protein and beef proteins. Am. J. Clin. Nutr. 1984; 39: 815.CrossRefGoogle ScholarPubMed
42Matthews, DE. Proteins and amino acids. In: Shils, ME, Olson, JA, Shike, M, Ross, AC, eds. Modern Nutrition in Health and Disease, 9th ed. Baltimore, MD: Williams & Wilkins, 1999; 1148.Google Scholar