Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-31T13:44:20.188Z Has data issue: false hasContentIssue false
  • English
  • Français

Calibration of the dietary questionnaire for the Canadian Study of Diet, Lifestyle and Health cohort

Published online by Cambridge University Press:  16 October 2007

Meera G Jain ,
Thomas E Rohan ,
Colin L Soskolne  and
Nancy Kreiger
Meera G Jain*
Affiliation:
Department of Public Health Sciences, 12 Queen's Park Crescent West, University of Toronto, Toronto, Ontario, M5S 1A8, Canada
Thomas E Rohan
Affiliation:
Department of Epidemiology and Social Medicine, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, USA
Colin L Soskolne
Affiliation:
Department of Public Health Sciences, 13–103 Clinical Sciences Building, University of Alberta, Edmonton, Alberta, T6G 2G3, Canada
Nancy Kreiger
Affiliation:
Research Unit, Division of Preventive Oncology, Cancer Care Ontario, 620 University Avenue, Toronto, Ontario, M5G 2L7, Canada
*
*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:

For proper interpretation of results from epidemiological studies that use food-frequency questionnaires (FFQs), it is necessary to know the relationship between reported intakes from the FFQ and true usual intake. In this paper, we report a calibration study conducted to investigate the performance of the FFQ used in a cohort study, the Canadian Study of Diet, Lifestyle and Health.

Methods:

Over a 1-year period, 151 men and 159 women completed a full set of questionnaires including a self-administered baseline FFQ, three 24-hour diet recalls administered by telephone, and a second FFQ self-administered subsequently. The association between the nutrient estimates derived from the FFQs and the diet recalls was evaluated by calculating deattenuated Pearson's correlation coefficients.

Results:

The FFQs estimated mean daily nutrient intakes higher than the diet recalls. When the log-transformed and energy-adjusted nutrient intakes from the average of three 24-hour recalls were compared against the baseline FFQ, the following deattenuated correlations were obtained in men and women, respectively: total energy 0.44 and 0.32, total fat 0.64 and 0.68, saturated fat 0.68 and 0.70, dietary fibre 0.65 and 0.44, vitamin E 0.32 and 0.37, vitamin C 0.40 and 0.37, β-carotene 0.34 and 0.29, alcohol 0.74 and 0.67, caffeine 0.81 and 0.76, with a median correlation of 0.49 and 0.53. Correlations between the second FFQ and diet recalls were similar. The correlations between the two FFQs as a test of reliability had a median value 0.64 for men and 0.63 for women for selected nutrients.

Conclusions:

The study suggests that the FFQ method gives acceptable levels of nutrients or food component estimates, as assessed by this calibration study against diet recalls, when limited to energy-adjusted and deattenuated values.

Keywords

CalibrationDiet methodsFood-frequency questionnairesValidation
Type
Research Article
Information
Public Health Nutrition , Volume 6 , Issue 1 , February 2003 , pp. 79 - 86
Copyright
Copyright © CABI Publishing 2003

References

1Stram, DO, Hankin, JH, Wilkens, LR, et al. Calibration of the dietary questionnaire for a multiethnic cohort in Hawaii and Los Angeles. Am. J. Epidemiol. 2000; 151: 358–70.CrossRefGoogle ScholarPubMed
2Carroll, RJ, Pee, D, Freedman, LS, et al. Statistical design of calibration studies. Am. J Clin. Nutr. 1997; 65(Suppl.): 1187S–9S.CrossRefGoogle ScholarPubMed
3. Willett, W. Nutritional Epidemiology. New York: Oxford University Press, 1998.CrossRefGoogle Scholar
4Stram, DO, Longnecker, MP, Shames, L, et al. Cost effective design of a diet validation study. Am. J. Epidemiol. 1995; 142: 353–62.CrossRefGoogle Scholar
5Kaaks, R, Riboli, E. Validation and calibration of dietary intake measurements in the EPIC project: methodological considerations. Int. J. Epidemiol. 1997; 26(Suppl. 1): S15–25.CrossRefGoogle ScholarPubMed
6Jain, M, Harrison, L, Howe, GR, et al. Evaluation of a selfadministered dietary questionnaire for use in a cohort study. Am. J. Clin. Nutr. 1982; 36: 931–5.CrossRefGoogle ScholarPubMed
7Miller, AB, Howe, GR, Wall, C. The national study of breast cancer screening. Clin. Invest. Med. 1981; 4: 227–58.Google ScholarPubMed
8Jain, M, Howe, GR, Rohan, T. Dietary assessment in epidemiology: comparison of a food frequency and a diet history questionnaire with 7-day food records. Am. J. Epidemiol. 1996; 143: 953–60.CrossRefGoogle Scholar
9 Health Canada. Canadian Nutrient File. Ottawa: Nutrition Research Division, Health Canada, 1997.Google Scholar
10Mangels, AR, Holden, JM, Beecher, GR, et al. The carotenoid content of fruits and vegetables: an evaluation of analytic data. J. Am. Diet. Assoc. 1993; 93: 284–96.CrossRefGoogle ScholarPubMed
11 National Cancer Institute. NFCS Classification System. National Food Consumption Survey. US Department of Agriculture. Bethesda, MD: National Cancer Institute, 1993.Google Scholar
12Willett, WC, Stampfer, MJ. Total energy intake: implications for epidemiologic analyses. Am. J. Epidemiol. 1986; 124: 17–27.CrossRefGoogle ScholarPubMed
13Rosner, 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
14Hu, FB, Rimm, E, Smith-Warner, SA, et al. Reproducibility and validity of dietary patterns associated with a food-frequency questionnaire. Am. J. Clin. Nutr. 1999; 69: 243–9.CrossRefGoogle Scholar
15 Statistics Canada. Personal health practices: smoking, drinking, physical activity and weight. Health Reports 1999; 11: 83–90.Google Scholar
16Bright-See, E, Catlin, G, Godin, G. Assessment of the relative validity of the Ontario Health Survey Food Frequency Questionnaire. J. Can. Diet. Assoc. 1994; 55: 33–8.Google Scholar
17Willett, WC, Sampson, L, Stampfer, MJ, et al. Reproducibility and validity of a semiquantitative food frequency questionnaire. Am. J. Epidemiol. 1985; 122(1): 51–65.CrossRefGoogle ScholarPubMed
18Kroke, A, Klipstein-Grobusch, K, Voss, S, et al. Validation of a self-administered food-frequency questionnaire administered in the European Prospective Investigation into Cancer and Nutrition (EPIC) Study: comparison of energy, protein, and macronutrient intakes estimated with the doubly labeled water, urinary nitrogen, and repeated 24-h dietary recall methods. Am. J. Clin. Nutr. 1999; 70(4): 439–47.CrossRefGoogle Scholar
19Kaaks, R, Slamani, N, Riboli, E. Pilot phase studies on the accuracy of dietary intake measurements in the EPIC project: overall evaluation of results. Int. J. Epidemiol. 1997; 26: S26–36.CrossRefGoogle ScholarPubMed
20Black, AE. Physical activity levels from a meta-analysis of doubly labeled water studies for validating energy intake as measured by dietary assessment. Nutr. Rev. 1996; 54: 170–4.CrossRefGoogle ScholarPubMed
21Martínez, ME, Marshall, JR, Graver, E, et al. Reliability and validity of a self-administered food frequency questionnaire in a chemoprevention trial of adenoma recurrence. Cancer Epidemiol. Biomark. Prev. 1999; 8: 941–6.Google Scholar
22Subar, AF, Thompson, FE, Kipnis, V, et al. Comparative validation of the Block, Willett, and National Cancer Institute food frequency questionnaires: the Eating at America's Table Study. Am. J. Epidemiol. 2001; 154(12): 1089–99.CrossRefGoogle Scholar
23Rimm, EB, Giovannucci, EL, Stampfer, MJ, et al. Reproducibility and validity of an expanded self-administered semiquantitative food frequency questionnaire among male health professionals. Am. J. Epidemiol. 1992; 135: 1114–26.CrossRefGoogle ScholarPubMed
24Hankin, JH, Wilkens, LR, Kolonel, LN, et al. Validation of a quantitative diet history method in Hawaii. Am. J. Epidemiol. 1991; 133: 616–28.CrossRefGoogle ScholarPubMed
25Lee, J. Use of regression adjustment for ascertaining nutrient intakes. J. Am. Diet. Assoc. 1981; 78: 245–9.CrossRefGoogle ScholarPubMed
26Thomas, D, Stram, D, Dwyer, J. Exposure measurement error: influence on exposure–disease relationships and methods of correction. Ann. Public Health 1993; 14: 69–93.CrossRefGoogle ScholarPubMed
27Black, AE, Prentice, AM, Goldberg, G, et al. Measurements of total energy expenditure provide insights into the validity of dietary measurements of energy intake. J. Am. Diet. Assoc. 1993; 93: 572–9.CrossRefGoogle ScholarPubMed
28Schaefer, EJ, Augustin, JL, Schaefer, MM, et al. Lack of efficacy of a food-frequency questionnaire in assessing dietary macronutrient intakes in participants consuming diets of known composition. Am. J. Clin. Nutr. 2000; 71: 746–51.CrossRefGoogle Scholar
29Kaaks, R, Riboli, E, van Staveren, W. Calibration of dietary intake measurements in prospective cohort studies. Am. J. Epidemiol. 1995; 142(5): 548–56.CrossRefGoogle ScholarPubMed
30Rosner, B, Willett, W, 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
31Jain, M, McLaughlin, J. Validity of nutrient estimates by food frequency questionnaires based either on exact frequencies or categories. Ann. Epidemiol. 2000; 10: 354–60.CrossRefGoogle ScholarPubMed
32Kipnis, V, Carroll, RJ, Freedman, LS, et al. Implications of a new dietary measurement error model for estimation of relative risk: application to four calibration studies. Am. J. Epidemiol. 2000; 152(5): 494–6.Google Scholar
33Kipnis, V, Midthune, D, Freedman, LS, et al. Empirical evidence of correlated biases in dietary assessment instruments and its implications. Am. J. Epidemiol. 2001; 153(4): 394–403.CrossRefGoogle ScholarPubMed