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Reproducibility and validity of a food frequency questionnaire among fourth to seventh grade inner-city school children: implications of age and day-to-day variation in dietary intake

Published online by Cambridge University Press:  02 January 2007

Alison E Field ,
Karen E Peterson ,
Steve L Gortmaker ,
Lilian Cheung ,
Helaine Rockett ,
Mary Kay Fox  and
Graham A Colditz
Alison E Field*
Affiliation:
Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, USA
Karen E Peterson
Affiliation:
Department of Nutrition, Harvard School of Public Health, USA Department of Maternal and Child Health, Harvard School of Public Health, USA
Steve L Gortmaker
Affiliation:
Department of Health and Social Behavior, Harvard School of Public Health, USA
Lilian Cheung
Affiliation:
Department of Nutrition, Harvard School of Public Health, USA
Helaine Rockett
Affiliation:
Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, USA
Mary Kay Fox
Affiliation:
Abt Associates, USA
Graham A Colditz
Affiliation:
Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, USA Department of Epidemiology, Harvard School of Public Health, USA
*
*Corresponding author: Email: [email protected]
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Abstract

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Objective

To assess the reproducibility and validity of a semiquantitative food frequency questionnaire (FFQ) to classify children and adolescents in terms of daily servings of fruits and vegetables and intake of calories, protein, fat, carbohydrate, dietary fibre, vitamin C, phosphorous, calcium and iron.

Design

FFQs were collected in the autumn of 1993 and 1994. Four 24-hour diet recalls were collected during the same 1-year period and their mean was compared to the FFQ diet estimates.

Setting

Low income, inner-city state schools.

Subjects

A sample of 109 inner-city fourth to seventh grade students.

Results

The 1-year reproducibility of the FFQ, assessed with Spearman correlations, was lower among the fourth and fifth (range: r = −0.26 to 0.40) than the sixth and seventh grade students (range: r = 0.18–0.47). After adjusting for day-to-day variation in dietary intake, for most nutrients and foods the correlations between the FFQ and the 24-hour recalls remained greater among the junior high school students (fourth to fifth grade range: r = 0.0–0.42; sixth to seventh grade range: = 0.07–0.76).

Conclusions

Inner-city sixth and seventh grade students demonstrated the ability to provide valid estimates of intake of calories, carbohydrate, calcium, phosphorous, iron and vitamin C over the past year. However, children in the fourth and fifth grades experienced some difficulty in completing the FFQ. Our results suggest that, before using this instrument with fourth and fifth grade children, investigators should assess whether study participants can think abstractly and are familiar with the concept of ‘average intake’.

Keywords

DietChildrenDiet assessment
Type
Research Article
Information
Public Health Nutrition , Volume 2 , Issue 3 , March 1999 , pp. 293 - 300
Copyright
Copyright © CABI Publishing 1999

References

1Randall, E. Measuring food use in school-aged children. J. School Health 1991; 61: 201–3.CrossRefGoogle ScholarPubMed
2 Consensus workshop on dietary assessment: nutrition monitoring and tracking the year 2000 objectives. US Department of Health and Human Services, Public Health Service/Centers for Disease Control and Prevention, National Center for Health Statistics, 1993.Google Scholar
3Nicklas, TA. Dietary studies of children and young adults (1973–1988): the Bogalusa Heart Study. Am. J. Med. Sci. 1995; 310(Suppl. 1): S101–8.CrossRefGoogle Scholar
4Kimm, SYS, Gergen, PJ, Malloy, M, Dresser, C, Carroll, M. Dietary patterns of U.S. children: implications for disease prevention. Prev. Med. 1990; 19: 432–42.CrossRefGoogle ScholarPubMed
5Nicklas, TA, Farris, RP, Srinivasan, SR, Webber, LS, Berenson, GS. Nutritional studies in children and implications for change: the Bogalusa Heart Study. J. Adv. Med. 1989; 2: 451–74.Google Scholar
6Farris, R, Nicklas, T. Characterizing children's eating behavior. In: Suskind, R, Suskind, L, eds. Textbook of Pediatric Nutrition, 2nd edn.New York: Raven Press, 1993: 505–16.Google Scholar
7Luepker, RV, Perry, CL, McKinlay, SM, et al. Outcome of a field trial to improve children's dietary patterns and physical activity. JAMA 1996; 275: 768–76.CrossRefGoogle ScholarPubMed
8Merzenich, HBoeing, H, Wahrendorf, J. Dietary fat and sports activity as determinants of menarche. Am. J. Epidemiol. 1993; 138: 217–24.CrossRefGoogle ScholarPubMed
9Field, AE, Wolf, AM, Herzog, DB, Cheung, LColditz, GA. The relationship of caloric intake to frequency of dieting among preadolescent and adolescent girls. J. Am. Acad. Child. Adolesc. Psychiatry 1993; 32: 1246–52.CrossRefGoogle ScholarPubMed
10Rockett, HRH, Wolf, AM, Colditz, GA. Development and reproducibility of a food frequency questionnaire to assess diets of older children and adolescents. J. Am. Diet. Assoc. 1995; 95: 336–40.CrossRefGoogle ScholarPubMed
11Rockett, HR, Colditz, GA. Assessing diets of children and adolescents. Am. J. Clin. Nutr. 1997; 65: S1116–22.CrossRefGoogle ScholarPubMed
12US Department of Agriculture. Composition of Foods. Agriculture Handbooks Nos. 8–1 to 8–21. Washington, DC: US Department of Agriculture, 1976–92.Google Scholar
13Paul, AA, Southgate, DAT. McCance and Widdowson's The Composition of Foods, 4th edn.London: HMSO, 1976.Google Scholar
14Holland, B, Welch, AA, Unwin, ID, Buss, DH, Paul, AA, Southgate, DAT. McCance and Widdowson's The Composition of Foods, 5th edn.Cambridge, UK: Royal Chemical Society and Ministry of Agriculture, Fisheries and Food, 1991.Google Scholar
15Willett, WC, Sampson, L, Stampfer, MJ, et al. Reproducibility and validity of a semiquantitative food frequency questionnaire. Am. J. Epidemiol. 1985; 122: 51–65.CrossRefGoogle ScholarPubMed
16 Nutrition Coordinating Center, University of Minnesota. Minnesota Nutrition Data System (NDS) v. 2.0. Minneapolis: University of, Minnesota, 1993.Google Scholar
17Havas, S, Heimendinger, J, Reynolds, K, et al. 5 a Day for Better Health: a new research initiative. J. Am. Diet. Assoc. 1994; 94: 32–6.CrossRefGoogle Scholar
18Smith, SA, Campbell, DR, Elmer, PJ, Martini, MC, Slavin, J, Potter, JD. The University of Minnesota Cancer Prevention Research Unit vegetable and fruit classification scheme. Cancer Causes Control 1995; 6: 292–302.CrossRefGoogle ScholarPubMed
19Rosner, 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
20SAS Institute. SAS User's Guide: Statistics, 5th edn.Cary, NC: SAS Institute, 1980.Google Scholar
21US Public Health Service. Healthy People 2000: National Health Promotion and Disease Prevention Objectives. DHHS Publication No. PHS 91–50212. Washington, DC: US Department of Health and Human Services, 1991.Google Scholar
22Domel, SB, Baranowski, T, Davis, H, Leonard, SB, Riley, P, Baranowski, J. Fruit and vegetable food frequencies by fourth and fifth grade students: validity and reproducibility. J. Am. Coll. Nutr. 1994; 13: 33–9.CrossRefGoogle Scholar
23Knuiman, JT, Rasanen, L, Ahola, M, West, CE, van der Snoek, L. The relative validity of reports of food intake of Dutch and Finnish boys aged 8 and 9 years. J. Am. Diet. Assoc. 1987; 87: 303–7.CrossRefGoogle ScholarPubMed
24Baranowski, T, Domel, SB. A cognitive model of children's reporting food intake. Am. J. Clin. Nutr. 1994; 59(Suppl.): S212–17.CrossRefGoogle Scholar
25Flavell, JH, Miller, PH, Miller, SA. Cognitive Development, 3rd edn.Englewood Cliffs, NJ: Prentice-Hall, 1993.Google Scholar
26Krebs-Smith, SM, Cook, A, Subar, A, Cleveland, L, Friday, J. US adults' fruit and vegetable intakes, 1989 to 1991: a revised baseline for the Healthy People 2000 objective. Am. J. Public Health 1995; 85: 1623–9.CrossRefGoogle ScholarPubMed
27Nelson, 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.CrossRefGoogle ScholarPubMed
28Rockett, HRH, Breitenbach, M, Frazier, AL, et al. Validation of a youth/adolescent food frequency questionnaire. Prev. Med. 1997; 26: 808–16.CrossRefGoogle ScholarPubMed
29Crockett, EG, Clancy, KL, Bowering, J. Comparing the cost of a thrifty food plan market basket in three areas of New York state. J. Nutr. Educ. 1992; 24: S72–9.CrossRefGoogle Scholar
30Smith, PK, Hoerr, SL. A comparison of current food bank users, non-users, and past users in populations of low income single mothers. J. Nutr. Educ. 1992; 24: S59–66.CrossRefGoogle Scholar
31 Anon. Improving federal efforts to assess hunger and food insecurity. Fam. Econ. Nutr. Rev. 1996; 9: 56–7.Google Scholar
32Jenner, DA, Neylon, K, Croft, S, Beilin, LJ. Vandongen, R. A comparison of methods of dietary assessment in Australian children aged 11–12 years. Eur. J. Clin. Nutr. 1989; 43: 663–73.Google ScholarPubMed