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Assessment of a narrative approach to the diet history

Published online by Cambridge University Press:  02 January 2007

LC Tapsell ,
K Pettengell  and
SL Denmeade
LC Tapsell*
Affiliation:
Department of Biomedical Science, University of Wollongong, Northfields Avenue, Wollongong, NSW 2522, Australia
K Pettengell
Affiliation:
Department of Biomedical Science, University of Wollongong, Northfields Avenue, Wollongong, NSW 2522, Australia
SL Denmeade
Affiliation:
Department of Biomedical Science, University of Wollongong, Northfields Avenue, Wollongong, NSW 2522, Australia
*
*Corresponding author: Email linda_tapsell@uow.edu.au
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Abstract:

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Objective:

To assess the quality of a narrative form diet history (DH).

Design:

Reproducibility assessed with data obtained at 6-week intervals. Criterion validity assessed using energy intake to estimated energy expenditure (EI: BMR) cut-off limits. Relative validity assessed by comparing results for energy and macronutrients at baseline and month 2 of an intervention trial with those obtained from 3-day food records (FR).

Setting:

Community-based dietary intervention trials for the study of metabolic syndrome in the Illawarra region of New South Wales, Australia.

Subjects:

Reproducibility: 43 healthy female volunteers. Mean age 58.72 years (range 50–67), mean body mass index (BMI) 25.79 (range 21–36). Validity: 45 healthy volunteers—18 males (mean age 46.9 years, mean BMI 27.8), and 27 females (mean age 45.7 years, mean BMI 26.2), attending a study on the effect of diet on metabolic variables.

Results:

Reproducibility: wide SD values indicated a high degree of intraindividual variation, but correlation coefficients were comparable to those of similar studies. Validity: underreporting was inconsistent with individuals, but was greater with the DH than the FR at each stage of the dietary trial (significant at month 1, P > 0.01). Underreporters indicated higher intakes of protein during the trial (P > 0.05). Weaker associations were found between the DH and FR data for energy values, but there was strong agreement for per cent fat consumed as saturated and monounsaturated fat at each stage of the trial.

Conclusions:

The narrative form DH performs as well as standardized interviews, but more work needs to be done at the micro level, focusing on aspects which deal with foods likely to be underreported in the particular study context. This can be achieved through continued research using combined methodologies.

Keywords

Dietary methodologyDiet historyCommunicationValidityReliability
Type
Research Article
Information
Public Health Nutrition , Volume 2 , Issue 1 , January 1999 , pp. 61 - 68
Copyright
Copyright © CABI Publishing 1999

References

1Burke, BS. The dietary history as a tool in research. J. Am. Diet. Assoc. 1947; 23: 1041–46.Google Scholar
2Pao, EM, Cypel, YS. Estimation of dietary intake. In: Ziegler, E, Filer, LJ, eds. Present Knowledge in Nutrition. Washington DC: ILSI Press, 1996: 498–508.Google Scholar
3Tapsell, LC The dietetic interview: towards a critical social pedagogy. PhD thesis, Wollongong: University of Wollongong, 1995.Google Scholar
4Block, G, Hartman, AM. Issues in reproducibility and validity of dietary studies. Am. J. Clin. Nutr. 1989; 50: 113–8.CrossRefGoogle ScholarPubMed
5Nelson, M. The validation of dietary assessment. In: Margetts, BM, Nelson, M, eds. Design Concepts in Nutritional Epidemiology, second edition. Oxford: Oxford University Press, 1997: 241–72.CrossRefGoogle Scholar
6Burema, J, van Staveren, W, Feunekes, GIJ. Letter to the editor: guidelines for reports on validation studies. Eur. J. Clin. Nutr. 1995; 49: 932–3.Google Scholar
7Mertz, W. Food intake measurements: is there a ‘gold standard’? J. Am. Diet. Assoc. 1992; 92: 1463–5.CrossRefGoogle ScholarPubMed
8Bingham, S, Day, N. Using biochemical markers to assess the validity of prospective dietary assessment methods and the effect of energy adjustment. Am. J. Clin. Nutr. 1997; 65 (suppl): 1130S–1137S.Google Scholar
9Goldberg, GR, Black, AE, Jebb, SA, et al. 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
10Bellach, B. Remarks on the use of Pearson's correlation co-efficient and other association measures in assessing validity and reliability of dietary assessment methods. Eur. J. Clin. Nutr. 1993; 47 (suppl): S42–S45.Google Scholar
11Kristal, AR, Beresford, SA, Lazovich, D. Assessing change in diet-intervention research. Am. J. Clin. Nutr. 1994; 59 (suppl): 185S–189S.Google Scholar
12Gibson, RS. Qualitative dietary assessment. In: Gibson, RS. Nutritional Assessment: a Laboratory Manual. Oxford: Oxford University Press, 1993: 15–22.Google Scholar
13Schofield, WN. Predicting basal metabolic rate. New standards and review of previous work. Hum. Nutr. Clin. Nutr. 1985; 39 (suppl 1): 5–41.Google ScholarPubMed
14Mahalko, JK, Johnson, LK, Gallagher, SK, Milne, DB. Comparison of diet histories and seven day food records in a nutri-tional assessment of older adults. Am. J. Clin. Nutr. 1985; 42: 542–53.Google Scholar
15Bland, JM, Altman, DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986; 1: 307–10.CrossRefGoogle ScholarPubMed
16Bittoni, MA, Wilkens, JR. Assessment of the reliability of a diet history questionnaire. Nutr. Cancer 1994; 21: 143–55.Google Scholar
17Nelson, M, Bingham, SA. Assessment of food consumption and nutrient intake. In: Margetts, BM and Nelson, M, eds. Design Concepts in Nutritional Epidemiology, second edition. Oxford: Oxford University Press, 1997: 123–69.CrossRefGoogle Scholar
18Hebert, JL, Clemow, L, Pobert, L, Ockene, IS, Ockene, JK. Social desirability bias in dietary self-report may compromise validity intake measures. Int. J. Epidemiol. 1995; 24: 389–98.Google Scholar
19Morgan, S, O'Dea, K, Sinclair, AL. A low-fat diet supplemented with monounsaturated fat results in less HDL-C lowering than a very-low-fat diet. J. Am. Diet. Assoc. 1997; 97: 151–56.CrossRefGoogle ScholarPubMed
20Black, AS, Bingham, S, et al. 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
21Buzzard, IM, Faucett, CL, Jeffrey, RW. Monitoring dietary change in a low fat diet intervention study: advantages of using 24-h dietary recalls vs food records. J. Am. Diet. Assoc. 1996; 60: 574–9.CrossRefGoogle Scholar
22Grace, C, Summerbell, C. Does provision of additional dietary information affect actual or only reported compliance to a low-fat diet over 12 weeks in hyperlipidaemic individuals? Report of a pilot study. J. Hum. Nutr. Diet. 1996; 9: 303–7.Google Scholar
23Macintyre, S, Anderson, A. Socio-demographic and psycho-social variables. In: Margetts, BM, Nelson, M, eds. Design Concepts in Nutritional Epidemiology, second edition. Oxford: Oxford University Press, 1997: 273–88.Google Scholar
24Mertz, W, Tsui, JC, Judd, JT. What are people really eating? The relation between energy intake derived from estimated diet records and intake determined to maintain body weight. Am. J. Clin. Nutr. 1991; 54: 291–5.CrossRefGoogle ScholarPubMed
25Buzzard, IM, Sievert, YA. Research priorities and recommendations for dietary assessment methodology. Am. J. Clin. Nutr. 1994; 59 (suppl): 275S–80S.Google Scholar
26Kohlmeier, L. Gaps in dietary assessment methodology: meal- vs list-based methods. Am. J. Clin. Nutr. 1994: 59 (suppl): 175S–179S.Google Scholar
27Knapper, J, Tredger, J, Webb, D. Substitution of dietary monounsaturated acids for saturated fatty acids in a free-living population: a feasibility study. J. Hum. Nutr. Diet. 1996; 9: 273–82.Google Scholar
28Means, B, Swan, GE, Jobe, JB, Esposito, JL. An alternative approach to obtaining personal history data. In: Biemer, PP, Groves, RM et al. , eds. Measurement Errors in Surveys. New York: Wiley Interscience, 1991: 167–84.Google Scholar
29Beaton, GH. Approaches to analysis of dietary data: relationship between planned analyses and choice of methodology. Am. J. Clin. Nutr. 1994; 59 (suppl): 253S–61S.CrossRefGoogle ScholarPubMed
30Schaeffer, NC. Conversation with a purpose—or conversation? Interaction in the standardized interview. In: Biemer, PP, Groves, RM et al. , eds. Measurement Errors in Surveys. New York: Wiley Interscience, 1991: 367–92.Google Scholar
31Barrett-Connor, E. Nutrition epidemiology: how do we know what they ate? Am. J. Clin. Nutr. 1991; 54 (suppl): 182S–187S.Google Scholar
32Cassidy, CM. Walk a mile in my shoes: culturally sensitive food-habit research. Am. J. Clin. Nutr. 1994; 59 (suppl): 190S–197S.CrossRefGoogle Scholar