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Validation and calibration of food-frequency questionnaire measurements in the Northern Sweden Health and Disease cohort

Published online by Cambridge University Press:  02 January 2007

Ingegerd Johansson*
Affiliation:
Department of Nutritional Research, Umeå University, Sweden
Göran Hallmans
Affiliation:
Department of Nutritional Research, Umeå University, Sweden
Åsa Wikman
Affiliation:
Department of Nutritional Research, Umeå University, Sweden
Carine Biessy
Affiliation:
Unit of Analytical Epidemiology, Program of Nutrition and Cancer, International Agency for Research on Cancer, Lyon, France
Elio Riboli
Affiliation:
Unit of Analytical Epidemiology, Program of Nutrition and Cancer, International Agency for Research on Cancer, Lyon, France
Rudolf Kaaks
Affiliation:
Unit of Analytical Epidemiology, Program of Nutrition and Cancer, International Agency for Research on Cancer, Lyon, France
*
*Corresponding author: Email ingegerd.johansson@odont.umu.se
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Abstract

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Objectives:

To evaluate the reproducibility of, and to compare and calibrate, diet measures by the Northern Sweden 84-item food-frequency questionnaire (FFQ) with measures from 24-hour diet recalls (24-HDR).

Design:

Randomly selected respondents (n=246) from the EPIC (diet-cancer) and MONICA (diet-cardiovascular disease) study cohort in Northern Sweden were invited to answer the FFQ twice over a one-year interval (FFQ1 and FFQ2), and to complete ten 24-hour recalls (reference method) in the months between. Plasma β-carotene concentrations were determined from a subset of 47 participants.

Setting:

Vasterbotten and Norrbotten, Northern Sweden.

Participants:

Ninety-six men and 99 women, who completed the study.

Results:

The reproducibility of the FFQ was high in terms of both mean energy and nutrient intakes and relative ranking of participants by intake levels (median Pearson correlation of 0.68). Moderately higher food intake frequencies were recorded by FFQ1 compared with 24-hour recalls for dairy products, bread/cereals, vegetables, fruits and potato/rice/pasta, whereas meat, fish, sweet snacks and alcoholic beverage intakes were lower. The median Spearman coefficient of correlation between FFQ1 and the average of ten 24-HDR measurements was 0.50. Daily energy and nutrient intakes were similar for FFQ1 and 24-HDR measurements, except for fibre, vitamin C, β-carotene and retinol (FFQ1<24-HDR) and sucrose and cholesterol (FFQ1>4-HDR). Pearson coefficients of correlation between FFQ1 and 24-HDR corrected for attenuation due to residual day-to-day variation in the 24-HDR measurements ranged from 0.36 to 0.79 (median 0.54). Adjustment for energy had only very moderate effects on the correlation estimates. Calibration coefficients estimated by linear regression of the 24-HDR on the FFQ1 measurements varied between 0.30 and 0.59 for all nutrients except alcohol, which had calibration coefficients close to 1.0. These low calibration coefficients indicate that relative risk estimates corresponding to an absolute difference in dietary intake levels measured by the FFQ will generally be biased towards 1.0. Plasma β-carotene levels had a Pearson coefficient of correlation of 0.47 with the 24-HDR measurements, and of 0.23 with FFQ1 measurements.

Conclusions:

The Northern Sweden FFQ measurements have good reproducibility and an estimated level of validity similar to that of FFQ measurements in other prospective cohort studies. The results from this study will form the basis for the correction of attenuation and regression dilution biases in relative risk estimates, in future studies relating FFQ measurements to disease outcomes.

Type
Research Article
Copyright
Copyright © CABI Publishing 2002

References

1Bingham, SA, Gill, C, Welch, A, Cassidy, A, Runswick, SA, Oakes, S, Lubin, R, Thurnham, DI, Key, TJ, Roe, L, Khaw, KT, Day, NE. 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: S13751.Google Scholar
2Ocke, MC, Bueno de Mesquita, HB, Goddijn, HE, Jansen, A, Pols, MA, van Staveren, WA, Kromhout, D. The Dutch EPIC food frequency questionnaire. I. Description of the questionnaire, and relative validity and reproducibility for food groups. Int. J. Epidemiol. 1997; 26: S3748.CrossRefGoogle ScholarPubMed
3Ocke, MC, Bueno de Mesquita, HB, Pols, MA, Smit, HA, van Staveren, WA, Kromhout, D. The Dutch EPIC food frequency questionnaire. II. Relative validity and reproducibility for nutrients. Int. J. Epidemiol. 1997; 26: S4958.CrossRefGoogle ScholarPubMed
4Bohlscheid-Thomas, S, Hoting, I, Boeing, H, Wahrendorf, J. Reproducibility and relative validity of energy and macronutrient intake of a food frequency questionnaire developed for the German part of the EPIC project. European Prospective Investigation into Cancer and Nutrition. Int. J. Epidemiol. 1997; 26: S7181.Google Scholar
5Willett, WC, Sampson, L, Stampfer, MJ, Rosner, B, Bain, C, Witschi, J, Hennekens, CH, Speizer, FE. Reproducibility and validity of a semiquantitative food frequency questionnaire. Am. J. Epidemiol. 1985; 122: 5165.Google Scholar
6Kroke, A, Klipstein-Grobusch, K, Voss, S, Moseneder, J, Thielecke, F, Noack, R, Boeing, H. 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: 439–47.CrossRefGoogle Scholar
7Pietinen, P, Hartman, AM, Haapa, E, Räsänen, L, Haapakoski, J, Palmgren, J, Albanes, D, Virtamo, J, Huttunen, JK. Reproducibility and validity of dietary assessment instruments. I. A self-administered food use questionnaire with a portion size picture booklet. Am. J. Epimiol. 1988; 128: 655–66.CrossRefGoogle Scholar
8Klipstein-Grobusch, K, den Breeijen, JH, Goldbohm, RA, Geleijnse, JM, Hofman, A, Grobbee, DE, Witteman, JC. Dietary assessment in the elderly: validation of a semiquantitative food frequency questionnaire. Eur. J. Clin. Nutr. 1998; 52: 588–96.CrossRefGoogle ScholarPubMed
9Riboli, E, Kaaks, R. The EPIC project: rationale and study design. European Prospective Investigation into Cancer and Nutrition. Int. J. Epidemiol. 1997; 26: S614.CrossRefGoogle ScholarPubMed
10MONICA Principal Investigators. WHO MONICA Project: geographic variation in mortality from cardiovascular diseases. Baseline data on selected population characteristics and cardiovascular mortality. World Health Statist. Quart. 1987; 40: 171–84.Google Scholar
11Brännström, I, Rosèn, M, Wall, S, Weinehall, L. Local health planning and intervention – the case of a Swedish municipality. Scand. J. Prim. Health Care 1988; (Suppl. 1) 5764.Google Scholar
12Weinehall, L. Partnership for health. On the role of primary health care in a community intervention programme. Thesis, Umeå University, Sweden, 1997.Google Scholar
13Bergström, L, Kylberg, E, Hagman, U, Eriksson, H, Bruce, Å. The food composition data base system (KOST-systemet) - its use for nutrient values [in Swedish]. Vär. Föda 1991; 43: 439–47.Google Scholar
14Livsmedelsverket. Weight Tables [in Swedish]. Uppsala: Livsmedelsverkets repro, 1999.Google Scholar
15Johansson, G, Wikman, Å, Åhrèn, A-M, Hallmans, G, Johansson, I. Underreporting of energy intake in repeated 24-hour recalls related to gender, age, weight status, day of interview, educational level, reported food intake, smoking habits and area of living. Public Health Nutr. 2001; 4(4): 919–27.CrossRefGoogle ScholarPubMed
16Krantzler, NJ, Mullen, BJ, Schutz, HG, Grivetti, LE, Holden, CA, Meiselman, HL. Validity of telephone diet recalls and records for assessment of individual food intake. Am. J. Clin. Nutr. 1982; 36: 1234–42.Google Scholar
17Tran, KM, Johnson, RK, Soultanakis, RP, Matthews DE, J. In-person vs telephone-administered multiple-pass 24-hour recalls in women: validation with doubly labeled water. J. Am. Diet. Assoc. 2000; 100: 777–83.Google Scholar
18Bergström, L. Illustrations of food items [in Swedish]. Vår Föda 1979; 31(Suppl. 4): 401–3.Google Scholar
19Håglin, L, Hagman, U, Nilsson, M. Evaluation of the meal model ‘matmallen’. A means of estimating consumed amounts of food. Scand. J. Nutr. 1995; 39: 7983.Google Scholar
20Epler, KS, Ziegler, RG, Craft, NE. Liquid-chromatographic method for the determination of carotenoids, retinoids, tocopherols in human serum and food. J. Chromatogr. 1993; 619: 3748.CrossRefGoogle Scholar
21FAO/WHO/UNU. Energy and Protein Requirements. Report of a Joint Expert Consultation. WHO Technical Report Series No. 724. Geneva: World Health Organization (WHO), 1985.Google Scholar
22Goldberg, GR, Black, AE, Jebb, SA, Cole, TJ, Murgatroyd, PR, Coward, 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 ScholarPubMed
23Rosner, 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: 37786.Google Scholar
24Rosner, 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.Google Scholar
25Kaaks, R, Riboli, E, van Staveren, W. Calibration of dietary intake measurements in prospective cohort studies. Am. J. Epidemiol. 1995; 142: 548–56.CrossRefGoogle ScholarPubMed
26Peltonen, M, Huhtasaari, F, Stegmayr, B, Lundberg, V, Asplund, K. Secular trends in cardiovascular risk factor levels in Sweden. The Northern Sweden MONICA study. J. Intern. Med. 1998; 244: 19.CrossRefGoogle ScholarPubMed
27Basiotis, PP, Welsh, SO, Cronin, FJ, Kelsay, JL, Mertz, W. Number of days of food intake records required to estimate individual and group nutrient intakes with defined confidence. J. Nutr. 1987; 117: 1638–41.Google Scholar
28Black, AE, Goldberg, GR, Jebb, SA, Livingstone, MB, 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 ScholarPubMed
29Kaaks, R, Riboli, E, Esteve, J, van Kappel, AL, van Staveren, WA. Estimating the accuracy of dietary questionnaire assessments: validation in terms of structural equation models. Stat. Med. 1994; 13: 127–42.Google Scholar
30Chow, CK, Thacker, RR, Changchit, C, Bridges, RB, Rehm, SR, Humble, J, Turbek, J. Lower levels of vitamin C and carotenes in plasma of cigarette smokers. J. Am. Coll. Nutr. 1986; 5: 305–12.CrossRefGoogle ScholarPubMed
31Kipnis, V, Freedman, LS, Brown, CC, Hartman, AM, Schatzkin, A, Wacholder, S. Effect of measurement error on energy-adjustment models in nutritional epidemiology. Am. J. Epidemiol. 1997; 146: 842–55.CrossRefGoogle ScholarPubMed