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Validation of a quantitative food-frequency questionnaire for use in Western Mali

Published online by Cambridge University Press:  02 January 2007

Liv E Torheim*
Affiliation:
Akershus University College, Ringstabekkveien 105, N-1356 Bekkestua, Norway
Ingrid Barikmo
Affiliation:
Akershus University College, Ringstabekkveien 105, N-1356 Bekkestua, Norway
Anne Hatløy
Affiliation:
Fafo Institute for Applied Social Science, Oslo, Norway
Moro Diakité
Affiliation:
Aideb, Bafoulabé, Mali
Kari Solvoll
Affiliation:
Institute for Nutrition Research, University of Oslo, Norway
Modibo M Diarra
Affiliation:
CPS, Ministère de la Sante, Bamako, Mali
Arne Oshaug
Affiliation:
Akershus University College, Ringstabekkveien 105, N-1356 Bekkestua, Norway
*
*Corresponding author: Email [email protected]
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Abstract

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Objective:

The purpose of this study was to validate a quantitative food-frequency questionnaire (QFFQ) created for assessing the usual intake of foods and nutrients in the prevailing season in Western Mali.

Design:

Intake of foods and nutrients over the week preceding the interview was measured with a 69-item QFFQ. Intakes were compared with intakes as measured with 2-day combined weighed and recalled diet records.

Setting:

A rural village in Western Mali, West Africa.

Subjects:

Twenty-seven men and 48 women (15–59 years of age) representing 18 households.

Results:

Spearman rank correlations between intake of food groups from the QFFQ and the diet record ranged from 0.09 (meat/fish) to 0.58 (tea/coffee). Median coefficient was 0.37. Median Spearman correlation coefficient for nutrient intake was 0.40. Men had higher median correlation coefficients than did women. The proportion of subjects being classified into the same quartile of food intake was on median 33%, while a median of 7% was misclassified into extreme quartiles. Correct classification into the same quartile for intake of nutrients was on median 34% while a median of 4% was grossly misclassified. Intakes of most food groups and nutrients as measured by the QFFQ were higher than those measured by the diet records. However, while men had higher estimated intakes for foods eaten in-between meals, women in general had higher intake of foods eaten in the main meals.

Conclusion:

This QFFQ can be used for comparing the intake of foods and nutrients between groups within this study population. It therefore represents a useful tool in the surveillance of food intake in the population, both in identifying vulnerable groups and for tracking food intake over time. The differences between men and women in overestimating food intake need to be taken into account when using the method.

Type
Research Article
Copyright
Copyright © CABI Publishing 2001

References

1FAO/WHO. Nutrition and Development – A Global Assessment. International Conference on Nutrition. Rome: Food and Agriculture Organization of the United Nations/World Health Organization, 1992.Google Scholar
2Hatløy, A, Torheim, LE, Oshaug, A. Food variety – a good indicator of nutritional adequacy of the diet? A case study from an urban area in Mali, West Africa. Eur. J. Clin. Nutr. 1998; 52: 891–8.CrossRefGoogle Scholar
3Dop, MC, Milan, C, Milan, C, N'Diaye, AM. Use of the multiple-day weighed record for Senegalese children during the weaning period: a case of the ‘instrument effect’. Am. J. Clin. Nutr. 1994; 59: 266S–8S.Google Scholar
4Ferguson, EL, Gibson, RS, Opare-Obisaw, C, Osei-Opare, F, Lamba, C, Ounpuu, S. Seasonal food consumption patterns and dietary diversity of rural preschool Ghanaian and Malawian children. Ecol. Food Nutr. 1993; 29: 219–34.CrossRefGoogle Scholar
5Ferguson, EL, Gibson, RS, Opare-Obisaw, C. The relative validity of the repeated 24 h recall for estimating energy and selected nutrient intakes of rural Ghanaian children. Eur. J. Clin. Nutr. 1994; 48: 241–52.Google Scholar
6Kigutha, HN. Assessment of dietary intake in rural communities in Africa: experiences in Kenya. Am. J. Clin. Nutr. 1997; 65: 1168S–72S.CrossRefGoogle ScholarPubMed
7FAO/WHO. World Declaration and Plan of Action for Nutrition. International Conference on Nutrition. Rome: Food and Agriculture Organization of the United Nations/World Health Organization, 1992.Google Scholar
8FAO/WHO. Preparation and Use of Food-based Dietary Guidelines. WHO Technical Report Series. Geneva: WorldHealth Organization, 1998.Google Scholar
9Willett, WC, Sampson, L, Stampfer, MJ, Rosner, B, Bain, C, Witschi, J, et al. Reproducibility and validity of a semi-quantitative food-frequency questionnaire. Am. J. Epidemiol. 1985 122: 5165.CrossRefGoogle Scholar
10Kushi, LH. Gaps in epidemiologic research methods: design considerations for studies that use food-frequency questionnaires. Am. J. Clin. Nutr. 1994. 59: 180S–4S.Google Scholar
11Hebert, JR, Gupta, PC, Bhonsle, RB, Sinor, PN, Mehta, H, Mehta, FS. Development and testing of a quantitative food frequency questionnaire for use in Gujarat, India. Public Health Nutr. 1999; 2: 3950.CrossRefGoogle ScholarPubMed
12Hebert, JR, Gupta, PC, Bhonsle, RB, Murti, PR, Mehta, H, Verghese, F, et al. Development and testing of a quantitative food frequency questionnaire for use in Kerela, India. Public Health Nutr. 1998; 1: 123–30.Google Scholar
13Sharma, S, Cade, J, Jackson, M, Mbanya, JC, Chungong, S, Forrester, T, et al. Development of food frequency questionnaires in three population samples of African origin from Cameroon, Jamaica and Caribbean migrants to the UK. Eur. J. Clin. Nutr. 1996; 50: 479–86.Google Scholar
14Hatløy, A, Hallund, J, Diarra, MM, Oshaug, O. Food variety, socioeconomic status and nutritional status in urban and rural areas in Koutiala (Mali). Public Health Nutr. 2000; 3: 5765.Google Scholar
15Cassidy, CM. Walk a mile in my shoes: culturally sensitive food-habit research. Am. J. Clin. Nutr. 1994; 59: 190S–7S.Google Scholar
16Nes, M, Andersen, LF, Solvoll, K, Sandstad, B, Hustvedt, BE, Løvø, A, et al. Accuracy of a quantitative food frequency questionnaire applied in elderly Norwegian women. Eur. J. Clin. Nutr. 1992; 46: 809–21.Google Scholar
17Bingham, SA, Gill, C, Welch, A, Day, K, Cassidy, A, Khaw, KT, et al. Comparison of dietary assessment methods in nutritional epidemiology: weighed records v. 24 h recalls, food-frequency questionnaires and estimated-diet records. Br. J. Nutr. 1994; 72: 619–43.Google Scholar
18Andersen, LF. Evaluation of food frequency questionnaires used among different groups of the Norwegian population. Dissertation, Institute for Nutrition Research, University of Oslo, 1998.Google Scholar
19Nordeide, MB. Table de Composition d'Aliments du Mali. Annex No. 9. Rapport d'Etape Sécurité Alimentaire/Femme. Projet de Recherche SSE. Environnement et Développement au Mali. Oslo: CNRST/Université d'Oslo, 1997.Google Scholar
20Goldberg, GR, Black, AE, Jebb, SA, Cole, TJ, Murgatroyd, PR, Coward, WA. 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
21Goldberg, GR, Black, AE. Assessment of the validity of reported energy intakes – review and recent developments. Scand. J. Nutr. 1998; 42: 69.Google Scholar
22FAO/WHO/UNU. Energy and Protein Requirements. Technical Report Series 724. Geneva: World Health Organization, 1985.Google Scholar
23SPSS, Inc. SPSS 8.0 for Windows. Chicago, IL: SPSS, Inc, 1997.Google Scholar
24Burema, J, van Staveren, WA, Feunekes, GIJ. Guidelines for reports on validation studies. Eur. J. Clin. Nutr. 1995; 49: 932–3.Google Scholar
25Bland, JM, Altman, DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986; 1: 307–10.Google Scholar
26Oshaug, A, Diarra, M, Torheim, LE, Diallo, F, Diakité, M, Sissoko, F, et al. Etude qualitative des besoins de la population à Bafoulabé. Programme de collaboration PIDEB/INRSP/Université de Oslo, Oslo, 1997.Google Scholar
27Kaaks, R, Riboli, E, van Staveren, W. Calibration of dietary intake measurements in prospective cohort studies. Am. J. Epidemiol. 1995; 142: 548–56.CrossRefGoogle ScholarPubMed
28Willett, WC. Nutritional Epidemiology. Oxford: Oxford University Press, 1990.Google Scholar
29Adams, AM. Seasonal variations in energy balance among agriculturalists in central Mali: compromise or adaptation? Eur. J. Clin. Nutr. 49: 809–23.Google Scholar
30Pietinen, P, Hartman, AM, Haapa, E, Räsänen, L, Haapakoski, J, Palmgren, J, et al. Reproducibility and validity of dietary assessment instruments. II. A qualitative food frequency questionnaire. Am. J. Epidemiol. 1988; 128: 667–76.Google Scholar
31Goldbohm, RA, van den Brandt, PA, Brants, HA, van't Veer, P, Al, M, Sturmans, F, et al. Validation of a dietary questionnaire used in a large-scale prospective cohort study on diet and cancer. Eur. J. Clin. Nutr. 1994; 48: 253–65.Google Scholar
32Bonifacj, C, Gerber, M, Scali, J, Daures, JP. Comparison of dietary assessment methods in a Southern French population: use of weighed records, estimated-diet records and a food-frequency questionnaire. Eur. J. Clin. Nutr. 1997; 51: 217–31.CrossRefGoogle Scholar
33Andersen, LF, Nes, M, Lillegaard, IT, Sandstad, B, Bjørneboe, GEA, Drevon, CA. Evaluation of a quantitative food frequency questionnaire used in a group of Norwegian adolescents. Eur. J. Clin. Nutr. 1995; 49: 543–54.Google Scholar
34Elmståhl, S, Riboli, E, Lindgärde, F, Gullberg, B, Saracci, R. The Malmö food study: the relative validity of a modified diet history method and an extensive food frequency questionnaire for measuring food intake. Eur. J. Clin. Nutr. 1996; 50: 143–51.Google Scholar
35Salvini, S, Hunter, DJ, Sampson, L, Stampfer, MJ, Colditz, GA, Rosner, B, et al. Food-based validation of dietary questionnaire: the effects of week-to-week variation in food consumption. Int. J. Epidemiol. 1989; 18: 858–66.CrossRefGoogle ScholarPubMed
36Beaton, GH. Approaches to analysis of dietary data: relationship between planned analysis and choice of methodology. Am. J. Clin. Nutr. 1994; 59: 253S–61S.CrossRefGoogle ScholarPubMed
37Nelson, M. The validity of dietary assessment. In: Margetts, MB, Nelson, M, eds. Design Concepts in Nutritional Epidemiology. 2nd ed. Oxford: Oxford University Press, 1997; 241–72.CrossRefGoogle Scholar
38Bingham, SA, Day, NE. Using biochemical markers to assess the validity of prospective dietary assessment methods and the effect of energy adjustment. Am. J. Clin. Nutr. 1997; 65: 1130S–7S.Google Scholar