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Secondary data analyses of dietary surveys undertaken in South Africa to determine usual food consumption of the population

Published online by Cambridge University Press:  22 December 2006

Nelia Patricia steyn ,
Johanna Helena Nel  and
Annette Casey
Nelia Patricia steyn*
Affiliation:
Chronic Diseases of Lifestyle Unit, South African Medical Research Council, PO Box 19070, Tygerberg, Cape Town 7505, South Africa
Johanna Helena Nel
Affiliation:
Chesham House, Hermanus, Western Cape, South Africa
Annette Casey
Affiliation:
Directorate Food Control, Department of Health, Pretoria, South Africa
*
*Corresponding author: Email nelia.steyn@mrc.ac.za
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Abstract

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Objective:

The primary objective of this study was to generate a reference table of food items and average amounts of these items consumed by South Africans, for the Department of Health. The reference table was required to be representative of foods and beverages eaten frequently by children and adults from all age and ethnic groups in order for the Department of Health to test for contaminants in these foods.

Design:

The National Food Consumption Survey (NFCS) served as a framework for compiling data on children since this was a national representative survey of 1–9-year-old children undertaken in South Africa in 1999. However, there has never been a national dietary survey on adults in South Africa. Consequently the data had to be extrapolated from existing isolated surveys on adults. Secondary data analysis was conducted on existing dietary databases (raw data) obtained from surveys undertaken on adults in South Africa between 1983 and 2000. Available datasets were regional and independent, and were not individually representative of the South African diet. It was therefore necessary to use different statistical methods, including factor analyses, weighting and correlations, to generate ethnic and geographic representative data for adults. Two methods were used: Method 1, which corresponded with results of the NFCS (over-sampled for low socio-economic status), and Method 2, which was based on ethnic proportions of the population.

Results:

The secondary data analyses generated food items most commonly consumed by the South African adult population (Method 1) in descending frequency of usage and average (mean) amount per day: maize porridge (78%/848 g), white sugar (77%/27 g), tea (68%/456 g), brown bread (55%/165 g), white bread (28%/163 g), non-dairy creamer (25%/6 g), brick margarine (21%/19 g), chicken meat (19%/111 g), full-cream milk (19%/204 g) and green leaves (17%/182 g). In 6–9-year-olds, maize porridge (72%/426 g), sugar (76%/23 g), tea (51%/258 g), full-cream milk (35%/171 g) and white bread (33%/119 g) were eaten most frequently. Similarly, in 1–5-year-olds, the foods consumed most frequently were maize porridge (80%/426 g), sugar (76%/21 g), tea (44%/224 g), full-cream milk (39%/186 g) and white bread (24%/83 g). In order to evaluate the validity of the adult data generated, kilojoule values of the individual food items (per capita) were compared with food balance sheets (FBSs). The comparison was favourable except that the FBSs had a higher overall energy intake per capita of between 22 and 28%.

Conclusion:

Reference tables of commonly consumed foods and beverages were generated at minimal cost based on secondary data analyses of past dietary surveys in different South African populations.

Keywords

Nutrition surveyValidationFood balance sheetsFood intakeDietary intakeSouth Africa
Type
Research Article
Information
Public Health Nutrition , Volume 6 , Issue 7 , October 2003 , pp. 631 - 644
Copyright
Copyright © CABI Publishing 2003

References

1World Health Organization (WHO). Guidelines for the Study of Dietary Intakes of Chemical Contaminants. WHO Offset Publication No. 87. Geneva: WHO, 1985.Google Scholar
2World Health Organization (WHO). Guidelines for Predicting Dietary Intake of Pesticide Residues (Revised). Prepared by the Global Environment Monitoring System/Food Contamination Monitoring and Assessment Programme (GEMS/Food) in collaboration with Codex Committee on Pesticide Residues. WHO Programme of Food Safety and Food Aid. WHO/FSF/FOS/97.7. Geneva: WHO, 1997.Google Scholar
3World Health Organization (WHO). GEMS/Food Regional Diets. Regional Per Capita Consumption of Raw and Semi-processed Agricultural Commodities. Prepared by the Global Environment Monitoring System/Food Contamination Monitoring and Assessment Programme (GEMS/Food). Food Safety Unit, WHO Programme of Food Safety and Food Aid. WHO/FSF/FOS/98.3. Geneva: WHO, 1998.Google Scholar
4World Health Organization (WHO). Food Consumption and Exposure Assessment of Chemicals. Report of a Food and Agriculture Organization/WHO Consultation held at Geneva, Switzerland on 10–14 February 1997. WHO/FSF/FOS/97.5. Geneva: WHO, 1997.Google Scholar
5World Health Organization (WHO). GEMS/Food Total Diet Studies. Report of a Joint US Food and Drug Administration/WHO International Workshop on Total Diet Studies in co-operation with the Pan American Health Organization held at Kansas City, MO, USA on 26 July–6 August 1999. WHO/SDE/PHE/FOS/99.9. Geneva: WHO, 1999.Google Scholar
6Labadarios, D, Steyn, NP, Maunder, E, MacIntyre, U. Swart, R, Gerike, G, et al. The National Food Consumption Survey (NFCS): Children aged 1–9 years, South Africa, 1999. Stellenbosch: The National Food Consumption Survey (NFCS), 2000.Google Scholar
7Steyn, NP, Badenhorst, CJ, Nel, JH, Jooste, PL. The nutritional status of Pedi preschool children in two rural areas of Lebowa. South African Journal of Food Science and Nutrition 1992; 4(2): 24–8.Google Scholar
8Steyn, NP, Badenhorst, CJ, Nel, JH. The meal pattern and snacking habits of schoolchildren in two rural areas of Lebowa. South African Journal of Food Science and Nutrition 1993; 5(4): 5–9.Google Scholar
9Steyn, NP, Badenhorst, CJ, Nel, JH, Ladzani, R. Breast-feeding and weaning practices of Pedi mothers and the dietary intakes of their preschool children. South African Journal of Food Science and Nutrition 1993; 5(4): 10–13.Google Scholar
10Badenhorst, CJ, Steyn, NP, Jooste, PL, et al. Nutritional status of Pedi schoolchildren aged 6–14 years in two rural areas of Lebowa: a comprehensive nutritional survey of dietary intake, anthropometric, biochemical, haematological and clinical measurements. South African Journal of Food Science and Nutrition 1993; 5(4): 112–9.Google Scholar
11Steyn, NP, Burger, S, Monyeki, KD, Alberts, M, Nthangeni, G. Dietary Intake of the Adult Population of Dikgale 1998. Sovenga: University of the North, 1998.Google Scholar
12Steyn, NP, Burger, S, Monyeki, KD, Alberts, M, Nthangeni, G. Seasonal variation in the dietary intake of the adult population of Dikgale. South African Journal of Clinical Nutrition 2001; 14(4): 140–5.Google Scholar
13Steyn, NP, MacIntyre, U, Olwagon, R, Alberts, M. Validation of multiple 24-hour recalls in a rural adult population using energy intake and estimated basal metabolic ratios. South African Journal of Epidemiology and Infection 2001; 16(1): 23–6.Google Scholar
14Bourne, LT, Langenhoven, ML, Steyn, K, Jooste, PL, Laubscher, JA, Van der Vyfer, E. Nutrient intake in the urban African population of the Cape Peninsula, South Africa. The BRISK Study. Central African Journal of Medicine 1993; 39(12): 238–47.Google ScholarPubMed
15Bourne, LT, Langenhoven, ML, Steyn, K, Jooste, PL, Laubscher, JA. The food and meal pattern in the black population of the Cape Peninsula. The BRISK Study. Central African Journal of Medicine 1994; 40(6): 140–8.Google ScholarPubMed
16Bourne, LT, Langenhoven, ML, Steyn, K, Jooste, PL, Laubscher, JA, Bourne, DE. Nutritional status of 3–6 year-old children in the Cape Peninsula. The BRISK Study. East African Medical Journal 1994; 7: 695–702.Google Scholar
17Venter, CS, MacIntyre, UE, Vorster, HH. The development and testing of a food portion photograph book for use in an African population. Journal of Human Nutrition and Dietetics 2000; 13: 205–18.CrossRefGoogle Scholar
18Vorster, HH, Wissing, MP, Venter, CS, et al. The impact of urbanization on physical, physiological and mental health of Africans in the North West Province of South Africa: the THUSA study. South African Journal of Science 2000; 96: 505–14.Google Scholar
19MacIntyre, UE, Venter, CS, Vorster, HH. A culture-sensitive quantitative food frequency questionnaire used in an African population: 1. Development and reproducibility. Public Health Nutrition 2000; 4(1): 53–62.CrossRefGoogle Scholar
20MacIntyre, 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 Nutrition 2000; 4(1): 63–71.CrossRefGoogle Scholar
21MacIntyre, UE, Venter, CS, Vorster, HH, Steyn, HS. A combination of statistical methods for the analysis of the relative validation data of the quantitative food frequency questionnaire used in the THUSA study. Public Health Nutrition 2000; 4(1): 45–51.CrossRefGoogle Scholar
22MacIntyre, EE, Kruger, HS, Venter, CS, Vorster, HH. Dietary intakes of an African population in different stages of transition in the North West Province, South Africa: the THUSA study. Nutrition Research 2002; 22: 239–56.CrossRefGoogle Scholar
23Underhay, C, de Ridder, JH, van Rooyen, JM, Kruger, HS. The effect of urbanisation on the relationship between physical activity and obesity among 10–15 year-old children in the North West Province, South Africa: the THUSA study. Presented at The Southern Africa Congress of Sport ScienceStellenbosch5–9 November 2001.Google Scholar
24Kruger, HS, de Ridder, JH, Pienaar, AE. Overweight among children 10–15 years old in the North West Province: prevalence and associated factors [abstract]. Journal of Endocrinology, Metabolism and Diabetes of South Africa 2002; 7(1): 37.Google Scholar
25Steyn, NP, Senekal, M, Brits, S, Nel, J. Urban and rural differences in dietary intake, weight status and nutrition knowledge of black female students. Asia Pacific Journal of Clinical Nutrition 2000; 9(1): 53–9.CrossRefGoogle Scholar
26Steyn, NP, Senekal, M, Brits, S, Alberts, M, Mashego, T, Nel, JH. Weight and health status of black female students. South African Medical Journal 2000; 90(2): 146–52.Google ScholarPubMed
27Senekal, M, Steyn, NP, Mashego, TA, Nel, JH. Evaluation of body shape, eating disorders and weight management related parameters in black female students. South African Journal of Psychology 2001; 31: 45–53.CrossRefGoogle Scholar
28Senekal, M, Steyn, NP. Development of a Nutrition and Health Monitor. Sovenga: University of the North, 1997.Google Scholar
29Senekal, M, Steyn, NP, Nel, JH. Factors associated with overweight/obesity in economically active South African populations. Ethnicity and Disease 2003; 13: 109–15.Google ScholarPubMed
30Wolmarans, P, Langenhoven, ML, Van Eck, M, Swanepoel, ASP. The contribution of different food groups to the energy, fat and fibre intake of the Coronary Risk Factor Study (CORIS) population. South African Medical Journal 1989; 75: 167–71.Google Scholar
31Steyn, K, Fourie, J, Benade, AJ, Rossouw, JE, Langenhoven, ML, Joubert, G, et al. Factors associated with high density lipoprotein cholesterol in a population with high high density lipoprotein cholesterol levels. Arteriosclerosis 1989; 9: 390–7.CrossRefGoogle Scholar
32Steyn, K, Steyn, M, Swanepoel, AS, Jordaan, PC, Jooste, PL, Fourie, JM, et al. Twelve-year results of the Coronary Risk Factor Study (CORIS). International Journal of Epidemiology 1997; 26: 964–71.CrossRefGoogle ScholarPubMed
33Steyn, NP, Abercrombie, R, Labadarios, D. Food security – an update for health professionals. South African Journal of Clinical Nutrition 2001; 14(3): 98–102.Google Scholar
34Bourne, LT. A liquid consumption survey of individuals in greater Cape Town. MSc Med (Community Health) thesis, University of Cape Town, 1986.Google Scholar
35Food and Nutrition Board NAS–NRC (USA). Recommended Dietary Allowances, revised 1989. Journal of the American Dietetics Association 1989; 89: 1748–52.CrossRefGoogle Scholar
36Nel, JH. Intakes of foods most commonly consumed: secondary data analyses of South African food consumption studies (1983–2000). MBA thesis, University of Stellenbosch, 2002.Google Scholar
37Langenhoven, ML, Kruger, M, Gouws, E, Faber, M. Medical Research Council Food Composition Tables, 3rd ed. Parow: Research Institute for Nutritional Diseases, South African Medical Research Council, 1991.Google Scholar
38Medical Research Council. Food Composition Tables [software]. Developed by the Nutrition Intervention Programme. Tygerberg: South African Medical Research Council, 1999.Google Scholar
39 Eurocode. Core Classification Version 99/2 [online]. Available at http://www.ianunwin.demon.co.uk/eurocode/docmn/ec99/ecmg01ct.htm. Accessed 1 October 2001.Google Scholar
40 Central Statistical Services. Census '96. Pretoria: Central Statistical Services, 1999.Google Scholar