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

Published online by Cambridge University Press:  02 January 2007

Christine L Parr ,
Ingrid Barikmo ,
Liv E Torheim ,
Fatimata Ouattara ,
Assitan Kaloga  and
Arne Oshaug
Christine L Parr*
Affiliation:
Center for Sami Health Research, University of Tromsø, PO Box 71, N-9735 Karasjok, Norway
Ingrid Barikmo
Affiliation:
Akershus University College, Ringstabekkveien 105, N-1356 Bekkestua, Norway
Liv E Torheim
Affiliation:
Akershus University College, Ringstabekkveien 105, N-1356 Bekkestua, Norway
Fatimata Ouattara
Affiliation:
Institut National de Recherche en Santé Publique, PO Box 1771 Bamako, Mali
Assitan Kaloga
Affiliation:
Institut National de Recherche en Santé Publique, PO Box 1771 Bamako, Mali
Arne Oshaug
Affiliation:
Akershus University College, Ringstabekkveien 105, N-1356 Bekkestua, Norway
*
*Corresponding author: Email christine.parr@bigfoot.com
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Abstract

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Objective:

To assess the relative validity of the second version of a quantitative food-frequency questionnaire (QFFQ), designed to measure the habitual food and nutrient intake in one season in rural populations in Western Mali, West Africa.

Design:

The dietary intake during the previous week was assessed with the 164-item QFFQ administered by interview. This was compared with the intake from a 2-day weighed record (WR) with weighed recipes.

Setting:

The village of Ouassala in the Kayes region, Western Mali.

Subjects:

Thirty-four women and 36 men aged 15–45 years, from 29 households.

Results:

The QFFQ gave a lower intake of lunch and dinner and a higher intake of snacks than the WR. The discrepancies were larger for women than for men. The median proportion of subjects classified in the same quartile of intake was 29% for food groups and 36% for energy and nutrients. For classification into extreme opposite quartiles, the median proportion was 6% for food groups and 7% for energy and nutrients. Spearman's rank correlation for energy and nutrients ranged from 0.16 (% energy from protein) to 0.62 (retinol equivalents).

Conclusions:

The second version of the QFFQ tends to underestimate total food weight. The methods used for estimating food portion size should therefore be applied with caution. The changes made from the first version had little effect. The ability to rank subjects according to dietary intake is similar with both versions. The improved layout of the new QFFQ makes it a more user-friendly tool for comparing dietary intake between population groups and for measuring changes over time.

Keywords

Evaluation studiesNutrition surveysQuestionnairesFood frequencyValidityAdultMaliAfrica
Type
Research Article
Information
Public Health Nutrition , Volume 5 , Issue 6 , December 2002 , pp. 769 - 781
Copyright
Copyright © CABI Publishing 2002

References

1Willett, WC, Stampfer, MJ, Colditz, GA, Rosner, BA, Hennekens, CH, Speizer, FE. Dietary fat and the risk of breast cancer. N. Engl. J. Med. 1987; 316(1): 22–8.CrossRefGoogle ScholarPubMed
2Bingham, SA, Welch, AA, McTaggart, A, Mulligan, AA, Runswick, SA, Luben, R, et al. Nutritional methods in the European Prospective Investigation of Cancer in Norfolk. Public Health Nutr. 2001; 4(3): 847–58.Google Scholar
3Torheim, LE, Barikmo, I, Hatløy, A, Diakité, M, Solvoll, K, Diarra, M, et al. Validation of a quantitative food-frequency questionnaire for use in Western Mali. Public Health Nutr. 2001; 4(6): 1267–77.Google Scholar
4Kushi, LH. Gaps in epidemiologic research methods: design considerations for studies that use food-frequency questionnaires. Am. J. Clin. Nutr. 1994; 59(Suppl. 1): 180S–4S.CrossRefGoogle ScholarPubMed
5Cassidy, CM. Walk a mile in my shoes: culturally sensitive food-habit research. Am. J. Clin. Nutr. 1994; 59(Suppl. 1): 190S–7S.Google Scholar
6Lewandowski, S, Rodgers, A, Schloss, I. The influence of a high-oxalate/low-calcium diet on calcium oxalate renal stone risk factors in non-stone-forming black and white South African subjects. BJU Int. 2001; 87(4): 307–11.Google Scholar
7Louw, L, Dannhauser, A. Keloids in rural black South Africans. Part 2: Dietary fatty acid intake and total phospholipid fatty acid profile in the blood of keloid patients. Prostaglandins Leukot. Essent. Fatty Acids 2000; 63(5): 247–53.Google Scholar
8MacKeown, JM, Cleaton-Jones, PE, Edwards, AW. Energy and macronutrient intake in relation to dental caries incidence in urban black South African preschool children in 1991 and 1995: the Birth-to-Ten study. Public Health Nutr. 2000; 3(3): 313–9.Google Scholar
9van Rooyen, JM, Kruger, HS, Huisman, HW, Wissing, MP, Margetts, BM, Venter, CS, et al. An epidemiological study of hypertension and its determinants in a population in transition: the THUSA study. J. Hum. Hypertens. 2000; 14(12): 779–87.Google Scholar
10Dannhauser, A, van Staden, AM, van der Ryst, E, Nel, M, Marais, N, Erasmus, E, et al. Nutritional status of HIV-1 seropositive patients in the Free State Province of South Africa: anthropometric and dietary profile. Eur. J. Clin. Nutr. 1999; 53(3): 165–73.Google Scholar
11Faber, M, Smuts, CM, Benade, AJ. Dietary intake of primary school children in relation to food production in a rural area in KwaZulu-Natal, South Africa. Int. J. Food Sci. Nutr. 1999; 50(1): 57–64.Google Scholar
12O'Keefe, SJ, Kidd, M, Espitalier-Noel, G, Owira, P. Rarity of colon cancer in Africans is associated with low animal product consumption, not fiber. Am. J. Gastroenterol. 1999; 94(5): 1373–80.Google Scholar
13Mennen, LI, Mbanya, JC, Cade, J, Balkau, B, Sharma, S, Chungong, S, et al. The habitual diet in rural and urban Cameroon. Eur. J. Clin. Nutr. 2000; 54(2): 150–4.Google Scholar
14Ojofeitimi, EO, Adelekan, DA, Adeoye, A, Ogungbe, TG, Imoru, AO, Oduah, EC. Dietary and lifestyle patterns in the aetiology of cataracts in Nigerian patients. Nutr. Health 1999; 13(2): 61–8.Google Scholar
15Gharbi, M, Hani, AB, Aouidet, A, Akrout, M, Nasraoui, A, Tritar, B. Dietary intake in the urban and rural populations of the Cap-Bon [in French]. Rev. Epidemiol. Sante Publique 1998; 46(3): 164–75.Google Scholar
16Allain, TJ, Wilson, AO, Gomo, ZA, Adamchak, DJ, Matenga, JA. Diet and nutritional status in elderly Zimbabweans. Age Ageing 1997; 26(6): 463–70.Google Scholar
17MacIntyre, UE, Venter, CS, Vorster, HH. A culture-sensitive quantitative food frequency questionnaire used in an African population: 1: Development and reproducibility. Public Health Nutr. 2001; 4(1): 53–62.Google Scholar
18MacIntyre, UE, Venter, CS, Vorster, HH. A culture-sensitive quantitative food frequency questionnaire used in an African population: 2: Relative validation by 7-day weighed records and biomarkers. Public Health Nutr. 2001; 4(1): 63–71.CrossRefGoogle Scholar
19Sloan, NL, Rosen, D, de la Paz, T, Arita, M, Temalilwa, C, Solomons, NW. Identifying areas with vitamin A deficiency: the validity of a semiquantitative food frequency method. Am. J. Public Health 1997; 87(2): 186–91.Google Scholar
20Sharma, 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(7): 479–86.Google Scholar
21Diallo, F, Diarra, M, Ouattara, F, Hatløy, A, Oshaug, A, Torheim, LE, et al. Rapport de l'enquête de base. Oussoubidiania et Ouassala, Bafoulabé Cercle, 1997 [unpublished]. Oslo: Programme de collaboration PIDEB/INRSP/Université d'Oslo Mali/Norvège 1997–2000, 1998.Google Scholar
22United Nations. National Household Survey Capability Programme. Annexe 1: Summary Procedures. How to Weigh and Measure Children: Assessing the Nutritional Status of Young Children in Household Surveys. New York: United Nations, Department of Technical Co-operation for Development and Statistical Office, 1986.Google Scholar
23Black, AE. Critical evaluation of energy intake using the Goldberg cut-off for energy intake:basal metabolic rate. A practical guide to its calculation, use and limitations. Int. J. Obes. Relat. Metab. Disord. 2000; 24(9): 1119–30.Google Scholar
24Black, AE, Coward, WA, Cole, TJ, Prentice, AM. Human energy expenditure in affluent societies: an analysis of 574 doubly-labelled water measurements. Eur. J. Clin. Nutr. 1996; 50(2): 72–92.Google ScholarPubMed
25World Health Organization (WHO). Energy and Protein Requirements. Report of a Joint FAO/WHO/UNU Expert Consultation. Technical Report Series No. 742. Geneva: WHO, 1985.Google Scholar
26Lauritsen, J FoodCalc version 1.3, 1998 [computer program]. Available from: http://www.ibt.ku.dk/jesper/FoodCalc. Accessed 15 May 2002.Google Scholar
27Nordeide, MB. Table de composition d'aliments du Mali. Oslo: Programme de Recherche SSE, Mali-Norvège, 1995.Google Scholar
28Leung, W-TW. Food Composition Table for Use in Africa. Bethesda, MD: US Department of Health, Education and Welfare/Food Consumption and Planning Branch, FAO, 1968.Google Scholar
29Salvini, S, Parpinel, M, Gnagnarella, P, Maisonneuve, P, Turruni, A. Banca dati di composizione degli alimenti per studi epidemiologici in Italia. Milan: Instituto Europeo di Oncologia, 1998.Google Scholar
30Rimestad, AH, Blaker, B, Flåten, A-M, Nordbotten, A. Den store matvaretabellen 1995: Oslo: Universitetsforlaget, 1995.Google Scholar
31Nelson, M. The validation of dietary assessment. In: Margetts, BM, Nelson, M, eds. Design Concepts in Nutritional Epidemiology. Oxford: Oxford University Press, 1997; 241–72.Google Scholar
32SPSS, Inc. SPSS version 10.0 for Windows [computer program]. Chicago, IL: SPSS, Inc., 1999.Google Scholar
33Burema, J, van Staveren, WA, Feunekes, GI. Guidelines for reports on validation studies [letter; comment]. Eur. J. Clin. Nutr. 1995; 49(12): 932–3.Google ScholarPubMed
34Bland, JM, Altman, DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986; 1(8476): 307–10.Google Scholar
35Barikmo, I. Elaboration d'un questionnaire de fréquence pour les enquêtes nutrionelles dans les zones rurales de l'ouest de Mali. Oslo: Programme de Recherche SSE, Mali-Norvège, 1997.Google Scholar
36Dop, 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(Suppl. 1): 266S–8S.Google Scholar
37Kigutha, HN. Assessment of dietary intake in rural communities in Africa: experiences in Kenya. Am. J. Clin. Nutr. 1997; 65(Suppl. 4): 1168S–72S.Google Scholar
38Venter, CS, MacIntyre, UE, Vorster, HH. The development and testing of a food portion photograph book for use in an African population. J. Hum. Nutr. Diet. 2000; 13(3): 205–18.Google Scholar
39Johnson, RK, Soultanakis, RP, Matthews, DE. Literacy and body fatness are associated with underreporting of energy intake in US low-income women using the multiple-pass 24-hour recall: a doubly labeled water study. J. Am. Diet. Assoc. 1998; 98(10): 1136–40.Google Scholar
40Briefel, RR, Sempos, CT, McDowell, MA, Chien, S, Alaimo, K. Dietary methods research in the third National Health and Nutrition Examination Survey: underreporting of energy intake. Am. J. Clin. Nutr. 1997; 65(Suppl. 4): 1203S–9S.Google Scholar
41Hirvonen, T, Mannisto, S, Roos, E, Pietinen, P. Increasing prevalence of underreporting does not necessarily distort dietary surveys. Eur. J. Clin. Nutr. 1997; 51(5): 297–301.Google Scholar
42Johnson, RK, Goran, MI, Poehlman, ET. Correlates of over- and underreporting of energy intake in healthy older men and women. Am. J. Clin. Nutr. 1994; 59(6): 1286–90.Google Scholar
43Goldbohm, 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(4): 253–65.Google Scholar
44Nes, M, Frost, AL, Solvoll, K, Sandstad, B, Hustvedt, BE, Lovo, A, et al. Accuracy of a quantitative food frequency questionnaire applied in elderly Norwegian women. Eur. J. Clin. Nutr. 1992; 46(11): 809–21.Google Scholar
45Salvini, S, Hunter, DJ, Sampson, L, Stampfer, MJ, Colditz, GA, Rosner, B, et al. Food-based validation of a dietary questionnaire: the effects of week-to-week variation in food consumption. Int. J. Epidemiol. 1989; 18(4): 858–67.Google Scholar
46Andersen, LF, Nes, M, Lillegaard, IT, Sandstad, B, Bjorneboe, GE, Drevon, CA. Evaluation of a quantitative food frequency questionnaire used in a group of Norwegian adolescents. Eur. J. Clin. Nutr. 1995; 49(8): 543–54.Google Scholar
47Bingham, 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(4): 619–43.Google Scholar
48Hebert, 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(1): 39–50.Google Scholar
49Hebert, 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 Kerala, India. Public Health Nutr. 1998; 1(2): 123–30.Google Scholar
50Bonifacj, 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(4): 217–31.CrossRefGoogle Scholar