Hostname: page-component-8448b6f56d-qsmjn Total loading time: 0 Render date: 2024-04-16T13:35:19.180Z Has data issue: false hasContentIssue false

Statistical approaches for assessing the relative validity of a food-frequency questionnaire: use of correlation coefficients and the kappa statistic

Published online by Cambridge University Press:  02 January 2007

LF Masson
Affiliation:
Department of Public Health, University of Aberdeen, Polwarth Building, Foresterhill, Aberdeen AB25 2ZD, UK:
G MCNeill*
Affiliation:
Department of Medicine & Therapeutics, University of Aberdeen, Polwarth Building, Foresterhill, Aberdeen AB25 2ZD, UK:
JO Tomany
Affiliation:
Department of Medicine & Therapeutics, University of Aberdeen, Polwarth Building, Foresterhill, Aberdeen AB25 2ZD, UK:
JA Simpson
Affiliation:
Department of General Practice & Primary Care, University of Aberdeen, Foresterhill Health Centre, Westburn Road, Aberdeen AB25 2AY, UK:
HS Peace
Affiliation:
Department of Medicine & Therapeutics, University of Aberdeen, Polwarth Building, Foresterhill, Aberdeen AB25 2ZD, UK:
L Wei
Affiliation:
Department of Medicine & Therapeutics, University of Aberdeen, Polwarth Building, Foresterhill, Aberdeen AB25 2ZD, UK:
DA Grubb
Affiliation:
Rowett Research Institute, Bucksburn, Aberdeen AB21 9SB, UK:
C Bolton-Smith
Affiliation:
Medical Research Council Human Nutrition Research, Elsie Widdowson Laboratory, Fulbourn Road, Cambridge CB1 9NL, UK
*
*Corresponding author: Email g.mcneill@abdn.ac.uk.
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 compare different statistical methods for assessing the relative validity of a self-administered, 150-item, semi-quantitative food-frequency questionnaire (FFQ) with 4-day weighed diet records (WR).

Design:

Subjects completed the Scottish Collaborative Group FFQ and carried out a 4-day WR. Relative agreement between the FFQ and WR for energy-adjusted nutrient intakes was assessed by Pearson and Spearman rank correlation coefficients, the percentages of subjects classified into the same and opposite thirds of intake, and Cohen's weighted kappa.

Subjects:

Forty-one men, mean age 36 (range 21-56) years, and 40 women, mean age 33 (range 19-58) years, recruited from different locations in Aberdeen, Scotland.

Results:

Spearman correlation coefficients tended to be lower than Pearson correlation coefficients, and were above 0.5 for 10 of the 27 nutrients in men and 17 of the 27 nutrients in women. For nutrients with Spearman correlation coefficients above 0.5, the percentage of subjects correctly classified into thirds ranged from 39 to 78%, and weighted kappa values ranged from 0.23 to 0.66.

Conclusions:

Both Spearman correlation coefficients and weighted kappa values are useful in assessing the relative validity of estimates of nutrient intake by FFQs. Spearman correlation coefficients above 0.5, more than 50% of subjects correctly classified and less than 10% of subjects grossly misclassified into thirds, and weighted kappa values above 0.4 are recommended for nutrients of interest in epidemiological studies.

Type
Research Article
Copyright
Copyright © CAB International 2003

References

1Willett, WC. Future directions in the development of food frequency questionnaires. Am. J. Clin. Nutr. 1994; 59(Suppl.): 171S–4S.Google Scholar
2Sempos, CT. Some limitations of semiquantitative food frequency questionnaires [invited commentary]. Am. J. Epidemiol. 1992; 135: 1127–32.CrossRefGoogle Scholar
3Bland, JM, Altman, DG. Statistical methods for assessing agreement between two methods of measurement. Lancet 1986; 1(8476): 307–10.CrossRefGoogle Scholar
4Herbert, JR, Miller, DR. The inappropriateness of conventional use of the correlation coefficient in assessing validity and reliability of dietary assessment methods. Eur. J. Epidemiol. 1991; 7(4): 339–43.Google Scholar
5Burema, J, van Staveren, WA, Feunekes, GIJ. Guidelines for reports on validation studies [letter to the editor]. Eur. J. Clin. Nutr. 1995; 49: 932–3.Google ScholarPubMed
6Cohen, J. Weighted kappa: nominal scale agreement with provision for scaled disagreement or partial credit. Psychol. Bull. 1968; 70: 213–20.CrossRefGoogle ScholarPubMed
7Garrow, JS. Validation of methods for estimating habitual diet: proposed guidelines [editorial]. Eur. J. Clin. Nutr. 1995; 49: 231–2.Google Scholar
8Burley, V, Cade, J, Margetts, B, Thomson, R, Warm, D. Consensus Document on the Development, Validation and Utilisation of Food Frequency Questionnaires [online]. Available at http://www.leeds.ac.uk/nuffield/pubs/ffq.pdf. Accessed September 2001.Google Scholar
9Smith, WCS, Crombie, IC, Tavendale, R, Irving, JM, Kenicer, MB, Tunstall-Pedoe, H. The Scottish Heart Health Study – objectives and development of methods. Health Bull. 1987; 45(4): 211–7.Google ScholarPubMed
10Yarnell, JWG, Fehily, AM, Milbank, JE, Sweetnam, PM, Walker, CL. A short dietary questionnaire for use in an epidemiological survey: comparison with weighed dietary records. Hum. Nutr. Appl. Nutr. 1983; 37A: 103–12.Google Scholar
11Holland, B, Welch, AA, Unwin, ID, Buss, DH, Paul, AA, Southgate, DAT. McCance & Widdowson's The Composition of Foods, 5th ed. Cambridge: Royal Society of Chemistry, 1991.Google Scholar
12Holland, B, Welch, AA, Buss, DH. Cereals and Cereal Products. Third Supplement to McCance & Widdowson's The Composition of Foods, 4th ed. Cambridge: Royal Society of Chemistry, 1988.Google Scholar
13Holland, B, Welch, AA, Buss, DH. Milk Products and Eggs. Fourth Supplement to McCance & Widdowson's The Composition of Foods, 4th ed. Cambridge: Royal Society of Chemistry, 1989.Google Scholar
14Holland, B, Welch, AA, Buss, DH. Vegetables, Herbs and Spices. Fifth Supplement to McCance & Widdowson's The Composition of Foods, 4th ed. Cambridge: Royal Society of Chemistry, 1991.Google Scholar
15Holland, B, Welch, AA, Buss, DH. Fruit and Nuts. First Supplement to McCance & Widdowson's The Composition of Foods, 5th ed. Cambridge: Royal Society of Chemistry, 1992.Google Scholar
16Holland, B, Welch, AA, Buss, DH. Vegetable Dishes. Second Supplement to McCance & Widdowson's The Composition of Foods, 5th ed. Cambridge: Royal Society of Chemistry, 1992.Google Scholar
17Holland, B, Brown, J, Buss, DH. Fish and Fish Products. Third Supplement to McCance & Widdowson's The Composition of Foods, 5th ed. Cambridge: Royal Society of Chemistry, 1993.Google Scholar
18Chan, W, Brown, J, Buss, DH. Miscellaneous Foods. Fourth Supplement to McCance & Widdowson's The Composition of Foods, 5th ed. Cambridge: Royal Society of Chemistry, 1994.CrossRefGoogle Scholar
19Chan, W, Brown, J, Lee, SM. Meat, Poultry and Game. Fifth Supplement to McCance & Widdowson's The Composition of Foods, 5th ed. Cambridge: Royal Society of Chemistry, 1995.Google Scholar
20Chan, W, Brown, J, Church, SM, Buss, DH. Meat Products and Dishes. Sixth Supplement to McCance & Widdowson's The Composition of Foods, 5th ed. Cambridge: Royal Society of Chemistry, 1996.Google Scholar
21Willett, WC, Stampfer, MJ. Total energy intake: implications for epidemiologic analyses. Am. J. Epidemiol. 1986;124: 1727.CrossRefGoogle ScholarPubMed
22Altman, DG. Practical Statistics for Medical Research. London: Chapman and Hall, 1991; 404–9Google Scholar
23Department of Health. Dietary Reference Values for Food Energy and Nutrients for the United Kingdom. Report of the Panel on Dietary Reference Values of the Committee on Medical Aspects of Food Policy. London: The Stationery Office, 1991.Google Scholar
24Goldberg, GR, Black, AE, Jebb, SA, Cole, TJ, Murgatroyd, WA, Prentice, AM. 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
25Brunner, E, Stallone, D, Juneja, M, Bingham, S, Marmot, M. Dietary assessment in Whitehall II: comparison of 7d diet diary and food-frequency questionnaire and validity against biomarkers. Br. J. Nutr. 2001; 86: 405–14.CrossRefGoogle Scholar
26Nelson, 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
27Bingham, 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): S13751.CrossRefGoogle ScholarPubMed
28Willett, W. Nutritional Epidemiology, 2nd ed. New York: Oxford University Press, 1998.CrossRefGoogle Scholar
29McKeown-Eyssen, GC, Tibshirani, R. Implications of measurement error in exposure for the sample sizes of case-control studies. Am. J. Epidemiol. 1994; 139: 415–21.CrossRefGoogle ScholarPubMed