THE NUTRITIONAL STATUS OF SOUTH AFRICANS A Review of the Literature

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2 THE NUTRITIONAL STATUS OF SOUTH AFRICANS A Review of the Literature FROM By Hester H Vorster, Welma Oosthuizen, Johann C Jerling, Frederick J Veldman & Hester M Burger The Nutrition Research Group, Potchefstroom University for Christian Higher Education, Potchefstroom 2520 South Africa For the S H HEALTH SYSTEMS TRUST T

3 Published by the Health Systems Trust S H T 504 General Building cnr. Smith and Field Streets Durban 4001 South Africa ISBN # Date of publication: March 1997 This publication is also available electronically in Portable Document Format. Access via our Web Site Designed, typeset and printed by Kwik Kopy Printing, Durban

4 PREFACE In this review, the Nutrition Research Group provides a timely and useful overview of the state of knowledge about nutritional status and the causes of malnutrition in South Africa. The review covers a period of 21 years, from 1975 to Due to shortcomings in the data, it is unfortunately not possible to analyse trends over this period. The review should prove useful to policy makers and programme directors, to establish the key nutritional problems we need to address. The data shows that nutrition problems occur in specific groups and geographical areas. Targeting interventions is therefore critical. The review is as illuminating regarding the gaps in our knowledge. For effective policy development and planning, researchers are challenged to focus on conducting research in these areas. Overall, there is an absence of definitive work on the underlying causes of malnutrition in various circumstances. In depth, small scale studies, linked to planned interventions could make an important contribution in this regard. There are gaps in our knowledge regarding the dietary practices of certain groups, including rural black children under two years of age, and rural adults, particularly in some provinces. The nutritional status and dietary practices of teenage girls, a potentially vulnerable group, also appears as an area in need of study. Nutrition researchers have an opportunity to ensure that the gaps identified in this study are filled. When a review is done, in five or ten years time, we must have the data to be able to indicate improvements in key indicators. Researchers should also seize the opportunity to use the available information to advocate for immediate action to improve the nutritional status of the population. Milla McLachlan Chairperson: Nutrition Society. November 1996 ACKNOWLEDGEMENTS The research, writing and publication of this report were made possible by a grant from the Health Systems Trust. Dr. LA Greyvenstein assisted with the language editing of the report, and Mrs. JM van Rensburg did the typing. Dr. HM McLachlan reviewed the manuscript. Her useful recommendations were incorporated into the text with the hope that it will contribute to a widespread application of the report in the planning of nutrition strategies and programmes in South Africa. We would like to thank all our colleagues (Dr. ARP Walker, Dr. AJS Benade, Prof. N Cameron and members of the SANSS group) for assistance in the collection of the relevant literature. i

5 1. The problem of malnutrition EXECUTIVE SUMMARY As in most other developing countries, recent literature indicates that South Africa has a problem of malnutrition. However, the exact nature and extent of this problem, as well as the vulnerability of different groups of South Africans, are not known. 2. Ineffectiveness of present programmes There is, at present, a perception that the few national Government programmes, and the many efforts from nongovernment programmes and organisations aimed at addressing malnutrition are not effective. One of the main reasons is probably because these programmes are not based on an analysis and understanding of the real problem and are not targeted at the most needy. To design strategy, policy and programmes to tackle the problem of malnutrition, more should be known about the nutritional status of South Africans. 3. Objectives of the review The objective of this review is to integrate results from four national studies and a large number of ad hoc studies by individual researchers and groups in a scientifically responsible manner, in order to evaluate and describe the existing nutritional status of South Africans. 4. Data used Results from published and unpublished reports which give information on the anthropometry, biochemical profiles, dietary patterns, nutrient intakes, and clinical signs of malnutrition were used to compile 84 tables. Results are stratified for ethnic group, age, gender, and province of domicile. Data which describes the impact of various determinants of nutritional status (food security, poverty, urbanisation, family unity and cohesion, physical environment, pregnancy, breast feeding and weaning practices, education, parasitic infections and alcohol intake) are summarised in a separate chapter. A number of studies concerning the cultural influences on eating patterns of South Africans are also included in this review. 5. Results The results indicate that on a national level % of preschool children and at least 20 % of primary school children are stunted and therefore suffer from chronic undernutition. Prevalences of wasting and underweight in school children are low. The vitamin A, iron and folate deficiencies observed in pre-school and primary school children, are also seen in adolescents and adults. Rural black and coloured children are the most vulnerable groups. The calculated mean prevalences of stunting in pre-school and primary school children observed in a large number of ad hoc studies, were in agreement or slightly higher for particular groups than found in the national surveys. However, there were wide ranges reported, varying, for example, from 3-64 % in urban black preschool children to 0-12 % in white primary school children. This clearly indicates that there are pockets or areas with more serious problems of undernutrition than others. The dietary and nutrient intake data supported the anthropometric and biochemical observations. In addition to low intakes of several micronutrients (calcium, iron, magnesium, zinc, riboflavin, vitamins A, B6, C and folate), the low fibre intakes and increases in total fat intake are of concern. An analysis of dietary patterns and determinants of malnutrition showed that, although cultural influences may explain some differences in nutrient intakes between ethnic groups, other factors such as poverty, food insecurity, disruption of the family unit, parasitic infections and lack of education are probably more important determinants. In all reports which examined dietary patterns, there was consensus that the low energy density of weaning foods and the low intake of milk (or milk products), fruits, vegetables and legumes by many South Africans are responsible for most of the nutrient imbalances in the diets. ii

6 6. Recommendations It is suggested that the major findings of this review should be considered in the design of strategies, policies and programmes to address the problem of malnutrition. The wide range of prevalences of stunting in pre-school and primary school children indicates that programmes should be flexible and based on real and specific needs in specific areas. The co-existence of under- and overnutrition suggests that programmes should not only focus on adequacy of diets, but also on prudency. Education towards healthier food choices should form part of all intervention programmes. Although some of the micronutrient deficiencies can be addressed by fortification programmes, it is suggested that the question of iron fortification should be examined in depth by an expert committee. Fortification of weaning foods is an option to consider. The limited information on the nutritional status of adult South Africans, not normally regarded as a high priority target group, indicates that their nutritional status is far from optimal. It is essential that to ensure maximum benefit from development programmes, the nutritional status of many adults should also be improved. A major observation in this review is the many gaps in our knowledge regarding nutritional status of specific age and ethnic groups and also regarding specific nutrients. There is no information on how many South Africans suffer from hunger. Very little is known about the impact of the rapid urbanisation on nutritional status and its determinants in people living in informal housing areas. The biochemical information on nutritional status is limited to a few nutrients in selected groups. Much more information on, for example zinc, calcium and iodine status is needed. Clearly, all these areas require urgent research to support intervention programmes. iii

7 PREFACE CONTENTS ACKNOWLEDGEMENTS EXECUTIVE SUMMARY CHAPTER 1 INTRODUCTION 1.1 BACKGROUND 1.2 MOTIVATION AND AIMS OF THIS REVIEW 1.3 EVALUATION OF NUTRITIONAL STATUS 1.4 STRUCTURE OF THIS REVIEW CHAPTER 2 METHODS 2.1 COLLECTION AND SELECTION OF STUDIES/DATA 2.2 CODING OF DATA: COMPILATION OF TABLES 2.3 DIETARY DATA 2.4 UNCODED DATA CHAPTER 3 RESULTS 3.1 ANTHROPOMETRY Introduction Definition and Terminology Reference Population (Standards, Cutpoints) Infants and Children, 0-6 years Primary School Children Adolescents Adults Comments 3.2 BIOCHEMICAL VARIABLES Introduction Infants and Children aged 0-6 years Primary School Children Adolescents Adults Comments iv

8 CHAPTER 4 DETERMINANTS OF NUTRITIONAL STATUS 4.1 INTRODUCTION 4.2 CAUSES OF UNDERNUTRITION 4.3 RISK FACTORS FOR UNDERNUTRITION IN SOUTH AFRICA Food Security Poverty Urbanisation Family Unity and Cohesion Physical Environment Pregnancy Breastfeeding and Weaning Practices Education, Ignorance and Psychological Factors Parasitic Infections Alcohol Intake 4.4 COMMENTS CHAPTER 5 CULTURAL INFLUENCES ON DIETARY PATTERNS 5.1 INTRODUCTION 5.2 WHITE SOUTH AFRICANS 5.3 COLOURED SOUTH AFRICANS 5.4 SOUTH AFRICAN INDIANS 5.5 BLACK SOUTH AFRICANS 5.6 COMMENTS CHAPTER 6 DISCUSSION, CONCLUSIONS AND RECOMMENDATIONS 6.1 LIMITATIONS OF THE REVIEW 6.2 MAIN FINDINGS: CONCLUSIONS Preschool Children Primary School Children Adolescents Adults Determinations of Malnutrition Dietary Patterns and Nutrient Intakes 6.3 DISCUSSION AND RECOMMENDATIONS v

9 INTRODUCTION CHAPTER BACKGROUND Our health and well-being, quality of life and ability to learn, work and play depend on how well we are nourished. Good nutrition or nutritional status is the outcome of many complex and interrelated determinants such as access to adequate, safe, affordable and nutritious food, care and health services. Although good nutrition is universally accepted as a basic human right, it is estimated that globally, more than 800 million people suffer from malnutrition and that in developing countries, more than 20 % of the populations are hungry. Grant (1993) estimated that in 1990, 193 million preschool children were underweight South Africa is a middle-income, developing country. According to the literature widespread outspoken hunger may not a major problem, but the health and nutritional status of millions of South Africans are far from optimal. A recent comparison of a few health indicators (infant mortality rate, life expectancy at birth and incidence of tuberculosis) and the money spent on health services compared with those of other countries at similar levels of economic development (McIntyre et al. 1995), indicate that we are not using our resources optimally. The high rates of malnutrition among South African children reported by a number of authors during the past 20 years (Kotzé, 1978; Wyndham & Irwig, 1979; Hansen, 1984; Richardson, 1986; Coovadia, 1993) have motivated the Department of Health to implement various national nutrition intervention programmes. These are the National Nutrition and Social Development Programme (NNSDP), the Protein Energy Malnutrition Scheme (PEM) and the Primary School Nutrition Programme (PSNP). In addition, several non-government organisations also implemented intervention programmes. Although the outcome of these programmes have never been evaluated in a scientific and satisfactory way, there is a perception that they are not cost-effective and do not contribute to general improvement of nutritional status and health. The reasons for their failure have been discussed in detail by McLachlan & Marshall (1995). These include inter alia that they were designed without adequate information, that their designs reflect a limited understanding of the problems of malnutrition, that goals were ill-defined and activities unfocused, that the emphasis on delivering of specific services such as the handing out of food was wrong, that they were not targeted to the most needy and that participation and involvement of communities were inadequate. However, in 1994 a nutrition committee appointed by the Minister of Health compiled a draft report on an integrated nutrition strategy for South Africa, which addresses these problems in a constructive and positive manner (Nutrition Committee, 1994). 1.2 MOTIVATION AND AIMS OF THIS REVIEW It is obvious from the above that in order to design better and more effective nutrition intervention programmes that will lead to improved nutritional status and health, we need adequate information on the existing nutritional status and specific nutritional problems of South Africans. We also need to know which of the many interrelated determinants of nutritional status contribute most to malnutrition in South Africa. To target programmes effectively we need to know more about the most vulnerable and disadvantaged. In addition, we need to know where the gaps in our knowledge are to plan more effective and relevant research in nutrition. The main objective of this review is to provide baseline data on the existing nutritional status of South Africans. Except for four national studies from 1980 to 1994, which provided data on the anthropometry of young children and of which one gave information on vitamin A and iron status of preschool children, the only other available scientific data on nutritional status are results from small regional ad hoc studies published by individual researchers. This review therefore aims to combine, integrate and interpret the results of these studies. Because of the structure of the South African population, as well as previous political policies, most of the above mentioned studies stratified and reported results for specific ethnic groups. To identify the most vulnerable and needy it was thought that further stratifications for gender, age, province and rural or urban locality in the case of Africans would be necessary, and were therefore made in the compilation of the tables. 1

10 1.3 EVALUATION OF NUTRITIONAL STATUS The nutritional status of an individual depends on how well requirements for energy and more than 50 different nutrients are met. Requirements and eating behaviour (what, where, when and how often specific foods are eaten) are determined by a large number of physiological, pathological, psychological, cultural and socio-economic factors. Because of this, there is no single measurement that will give comprehensive information on nutritional status. Therefore, a combination of methods, including anthropometric measurements, biochemical analyses, nutrient intakes and clinical signs of malnutrition is usually used. The interpretation of these variables and conclusions reached will depend on the norms or standards used for comparison. 1.4 STRUCTURE OF THIS REVIEW In addition to the executive summary and this introduction, (Chapter 1), the methods used to collect, select, code and integrate the available literature are discussed in Chapter 2. In Chapter 3 the results consisting of 84 tables and 6 figures are given. These are divided into four sections, namely anthropometry, biochemistry, nutrient intakes and clinical signs. Data from these tables and figures are discussed briefly and salient observations highlighted. Reports on the determinants of nutritional status which have been examined in several studies by individual researchers and groups are given in Chapter 4. In Chapter 5, the limited information on how culture influences eating patterns in South Africa is summarised. Cultural influences may be seen as a determinant of nutritional status. However, it is difficult to conclude from the available literature whether it contributes to malnutrition in South Africa. Because it probably should influence dietary recommendations, and also because it should be taken into account in nutrition programming, the available literature on cultural influences on eating patterns is summarised in this separate chapter. Chapter 6 consists of an integrated discussion of the results and some recommendations on how the problem of malnutrition could be tackled. The bibliography and acknowledgements are given in Chapters 7 and 8. 2

11 METHODS 2.1 COLLECTION AND SELECTION OF STUDIES/DATA CHAPTER 2 Both published and unpublished data are included in this review. Published titles screened for inclusion were obtained from several electronic data bases (MEDLINE, REPORTORIUM), as well as South African medical and nutrition journals not included in these data bases. Articles, books and reports were obtained from the Ferdinand Postma Library in Potchefstroom and its inter-library services. Unpublished manuscripts, dissertations, theses, research reports and other documents (policy and briefing papers, technical reports, etc.) were obtained from the Medical Research Council, several universities, Government Departments, the Health Systems Trust, UNICEF, WHO, FAO and RDP offices, as well as individual colleagues and researchers. It is possible that, despite all these efforts, there may be publications and reports with valuable information on nutritional status of South Africans that were missed. After screening and selecting all available titles, some documents (especially postgraduate theses) could not be traced and are therefore not included in the review. Literature that measured the nutritional status of patients or subjects included in a study because of a specific disease or condition such as kwashiorkor, marasmus, diabetes or hypertension, were not included in the review. 2.2 CODING OF DATA: COMPILATION OF TABLES After collection of the literature, four researchers read the relevant sections and transferred the data to specially designed coding forms for either anthropometry, biochemistry, nutrient intakes or clinical signs. At the same time, short summaries of data pertaining to determinants of nutritional status and eating patterns were made. The coding forms helped to stratify information for date of the study (or published date), province, randomisation of subjects, ethnic group, urban/rural, gender, age, number of subjects, variables measured, means with standard deviations or confidence intervals, percentage of subjects with abnormal values and reference range. These data were then computerised and organised by computer into Tables Because of differences in study design, selection of subjects and presentation of results, it was not possible to integrate and combine data on anthropometry, biochemistry and clinical signs of malnutrition in a meta-analysis. These data are therefore summarized in separate tables. Available nutrient intake data were combined in a metaanalysis by SANSS (1994) and are presented as such. For coding, urban and rural classification were used, as reported by the authors. Where appropriate, for example in the prevalence of stunting in preschool children, means from the different individual studies were calculated (without weighting of studies for numbers, etc.) and compared with the recent national surveys. Data from these surveys (SALDRU/World Bank 1994; Department of Health 1994; SAVACG, 1995) were included in the tables where appropriate, or given separately. 2.3 DIETARY DATA Nutrient intake data depends to a large extent on methods used to obtain information on dietary habits and intakes. The 24-hour recall method tends to measure lower intakes than, for example, the diet history and food frequency questionnaire. A survey of the South African literature on dietary intakes (SANSS, 1995) showed that the 24-hour recall method was mostly used in larger surveys while the diet history or food frequency questionnaire methods were used in smaller studies with limited numbers of subjects. Therefore, it was decided to present the 24-hour recall data separately, as explained in Chapter UNCODED DATA Not all sources such as review papers, opinions, editorials and policy or briefing papers gave data in a form that could be coded and included into the tables. If relevant, these were used in Chapters 4 and 5 to describe determinants of nutritional status or mentioned in the brief discussions of the different tables. 3

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13 RESULTS CHAPTER ANTHROPOMETRY INTRODUCTION In this section, reported anthropometric measurements and indices of South Africans, stratified for age, gender and ethnic group, are used as indicators to evaluate nutritional status of specific groups. Anthropometric measurements are used to assess body size, proportions and composition. They reflect inadequate or excess food intake, insufficient exercise, growth of children, disease, and overall health and welfare. Because anthropometry is the single most portable, universally applicable, inexpensive and non-invasive method to obtain information on nutritional status (De Onis & Habicht, 1996), it is often used to evaluate the outcomes of policies and nutrition intervention programmes, or to select individuals whom should be targeted in such programmes. Therefore, repeated cross-sectional or longitudinal measurements of anthropometry will monitor changes in nutritional indicators over time, giving warning of impending crises and identify at risk populations DEFINITIONS AND TERMINOLOGY The definitions of different concepts and the terminology used in this section are in agreement with recent recommendations of an expert committee on the use and interpretation of anthropometry of the World Health Organisation (WHO, 1995) Measurements The basic nutritional anthropometric measurements are weight (mass), height, body circumferences (waist, hip, head and upper arm), as well as skinfolds Indices These are combinations of measurements necessary for interpretation of the measurements. Examples are body mass index [weight (kg)/height (m 2 )], weight-for-age (W-a), height-for-age (H-a) or weight-for-height (W-H). The indices can be expressed in terms of Z-scores, percentiles or percent of median. These expressions can be used to compare an individual or a group with a reference population. * Z-scores: This is a standard deviation score and is defined by WHO (1995) as the deviation of the value for an individual from the median value of the reference population, divided by the standard deviation for the reference population. Therefore: Z-score = (observed value) - (median reference value) standard deviation of reference population * Percentiles This is the rank position of an individual on a given reference distribution, stated in terms of what percentage of the group is equalled or exceeded by the individual. Therefore, a child of a specific age, whose weight falls in the 10th percentile, weighs the same or more than 10 % of the reference population of children of the same age. * Percent of median This is the ratio of a measured value in an individual such as weight or height to the median value of the reference data for the same age, expressed as a percentage Indicators These are applications of indices to evaluate nutritional status. In this analysis, the percentage of children below a defined cutpoint (level) for a particular index (W-a, H-a, W-H), was used to evaluate the extent and magnitude of 5

14 malnutrition in a particular group of children. Therefore, studies which reported percentages of subjects under a specific cutpoint were included in the tables. Many studies did not report data in this way, but did, however, make important observations regarding the nutritional status and anthropometry of South Africans. These studies were also incorporated in the results and discussion sections, but not in the tables. In agreement with the World Health Organisation s recommendations (WHO, 1986; 1995), the anthropometric indices and indicators were used in this analysis as follows: * Weight-for-age (W-a) A low W-a is indicative of underweight. If % of a population or group is underweight, the population or group is moderately affected. If more than 40 % is underweight, a severe problem exists. * Height-for-age (H-a) Low H-a is indicative of stunting, which is a result of chronic, long-term dietary inadequacy, reflecting socioeconomic deprivation. The WHO (1986) regards a population to be moderately affected if % of its children under 5 years of age are stunted, and severely affected if more than 50 % are stunted. * Weight-for-height (W-H) A low W-H reflects wasting, a result of acute nutritional stress and severe food shortages or serious illness. A figure of 5-10 % wasting in a population or group is regarded as a moderate prevalence and more than 10 % as a severe problem (WHO 1986; 1995), which would need immediate nutritional support (Solarsh et al., 1994). Because one of the main aims of this analysis is to evaluate the extent of malnutrition among South Africans, the focus in the tables on children is on the percentage of children with low anthropometric indices. However, if data on overnutrition (obesity) was published, this was also included in the tables REFERENCE POPULATION (STANDARDS, CUTPOINTS) The measured frequency, magnitude or extent of malnutrition in a particular population or group will be influenced by the anthropometric criteria employed. WHO (1995) defines a reference as a tool for grouping and analysing data which provides a common basis for comparing populations. No inferences should be made about the meaning of observed differences. The same source further states that a standard embraces the notion of a norm or desirable target and thus involves a value judgement. There has been considerable debate in the literature regarding the use of international reference data and the desirability of national norms that would reflect growth patterns of South African black children (Walker et al., 1978; Kotzé et al., 1982; Cameron, 1992; Cameron & Kgamphe, 1993). De Onis and Habicht (1996) maintain that although differences of genetic origin are evident for some comparisons, these variations are relatively minor compared with the large worldwide variation in growth related to health and nutrition. Cameron and Kgamphe (1993) state that secular trends towards greater heights and weights and earlier pubertal development can only be assessed by using international norms. But, if the growth of an individual child is monitored, the child should be compared with his peers who are living under the same environmental circumstances. However, no national norms exist and almost all the studies on children included in this analysis used the reference data collected from healthy, wellnourished American children by the National Center for Health Statistics (NCHS) and recommended by the WHO for international use. The cutpoints used in this analysis for children and adolescents were the percentages of children given below: * -2 Z-score (< 2.28th percentile) * 3rd percentile (< 5th if the 3rd was not available) * 80 % of the median (50th percentile) weight-for-age * 90 % of the median height-for-age * 90 % of the median height-for-weight In a population with reference values following a normal (Gaussian) distribution, the -2 Z-score, 3rd percentile and % of the median are very close to each other (WHO, 1995). To evaluate prevalence of underweight and obesity in adults, cutpoints of < 20 kg/m 2 and > 30 kg/m 2 for body mass index were used. In children, obesity was evaluated by using either > +2 Z -score or > 120 % of ideal weight as cutpoints. However, obesity results in children should be interpreted with care. De Onis & Habicht (1996) recently observed that in the NCHS reference curves, the 6

15 distributions of weight-for-age and weight-for-height are markedly skewed toward the higher end, reflecting a substantial level of childhood obesity. This skewness, reflecting an unhealthy characteristic of the reference sample may result in the misclassification of overweight children as normal INFANTS AND CHILDREN, 0-6 YEARS The percentages of infants and children who fell under the cutpoints as discussed above regarding W-a, H-a and W-H are given in Tables 1 to 7. The data were collected by several researchers from 1976 to 1996 from more than children, divided into approximately 140 subgroups based on age, gender, ethnic group and geographical location. In addition to tables for white, coloured and Indian children, there are three tables for black children, giving data for urban and rural children separately and one (Table 6) with data from a study of Solarsh et al. (1994) which did not distinguish between rural and urban children in the same manner as the other studies. Table 7 gives data from national studies which did not stratify for ethnicity. This table consists mainly of data from the 1994 national study on vitamin A status of preschool children (SAVACG, 1995), which also reported on the anthropometric status of these children. The table further includes H-a data from the SALDRU/World Bank study of In all 7 tables, the available data for the different provinces are grouped together. Table 8 summarises some of the information in Tables 1 to 7, and also gives calculated means of percentages of children under the given cutpoints. These means were not corrected for number of children in each subgroup. The means given at the bottom of this table are from the SAVACG (1995) study. From these tables it is clear that the groups most extensively researched and reported on (although not in proportion to total numbers of South African children) are rural and urban black infants and children, while less research has been done on Indian, white and coloured children. An important observation is that within each ethnic group there is a wide range of percentages of children under a given cutpoint, illustrating that the prevalence and severity of malnutrition differs from area to area and that pockets of malnourished children exist. This wide range was especially noticeable in rural black children. A direct comparison between rural and urban black children on the available data is not possible. The SAVACG (1995) study reported slightly higher prevalences of rural children under the -2 Z-score of the three anthropometric indices than urban children, indicating that on a national basis and where data is not stratified for ethnic group, the rural areas probably have a larger incidence of malnutrition than urban areas. Except for the SALDRU and SAVACG studies, not enough comparable data were available to evaluate the extent of malnutrition in different provinces in the under 6 year old group of children. From Table 8 it can also be seen that both coloured and Indian children had higher prevalences of low W-a and low H-a than black children. Unfortunately, especially in the Indian group, no recent data were available. Generally, the percentages of children who had low W-H were small. Therefore, except for some isolated areas, wasting or acute malnutrition was not reported as a problem. The SAVACG (1995) study confirmed these results. In the white, coloured and Indian groups, mean prevalences of children with low W-a were higher than those with low H-a. This indicates that in these three groups underweight was a more serious problem than stunting. In contrast, in black children the percentages of children who were stunted exceeded those who were underweight. In the national survey (SAVACG, 1995), the prevalence of stunting (22.9 %) was also much higher than that of underweight (9.3 %). The same pattern of much lower degrees of underweight than underheight-for-age, in the absence of wasting, was observed by Solarsh et al. (1994) in infants and preschool children in KwaZulu-Natal. These authors mention that this pattern suggests that a substantial number of children are relatively overweight-for-height. Dannhauser et al. (1996) found that approximately 10 % of the black children in their sample from a rural area in the Free State had a Z-score of +2 and higher. Gross & Monteiro (1989) also described differences in prevalences of stunting and wasting in infants and preschool children in Brazil. They concluded that the high stunting (10-15 % of children) and low wasting (2-5 %) indicated that malnutrition was caused not by hunger, but by poor sanitation and health facilities. The growth pattern of South African infants and children has been studied in some detail by several authors on children from different parts of the country showing very similar results. Coovadia et al. (1977) reported on urban black children aged 0-12 years from KwaZulu-Natal. Compared to Harvard reference standards, the younger children were generally heavier than the international standard. The heights of children aged 0-2 years were similar to the international standard, but children older than two years were shorter (stunted). Richardson and Sinwell (1984) monitored the growth of Tswana infants in the rural North West Province. They found that these babies were short at birth (mean 43 cm, NCHS reference: 50 cm); but that the mean birth weight of 3.3 kg was comparable to the international standard. Weights were maintained for 7 months but faltered thereafter, despite continuous breastfeeding, indicating that breastmilk alone was not sufficient and that weaning practices were not adequate. 7

16 A direct comparison of the results from the SALDRU/World Bank and the 1994 National Survey (SAVACG, 1995; Table 8) with the compilation (calculated means) of the smaller studies done from 1976 to 1996 is not possible. Changing circumstances over 20 years such as droughts, economic recession, improved health services, changed political structures, as well as an absence of proper randomisation or selection bias in the smaller studies, could be responsible for observed differences. However, looking at calculated means, the same overall pattern of low prevalence of underweight, moderate to high prevalences of stunting in the absence of wasting, emerged. The wide range of percentages of children under a specific cutpoint for all three indices (W-a, H-a and W-H) as summarised in Table 8 further emphasises that there are areas with high prevalences of malnutrition PRIMARY SCHOOL CHILDREN Tables 9 to 14 give information on the anthropometric indices of primary school children, as well as percentages of children under the 3rd or 5th percentile of these indices. Most children were between 6 and 12 years old, but some studies included slightly older children. The data were collected from 1975 to 1996 and children were weighed and measured. For this analysis, the children were divided into 111 subgroups based on age, gender, ethnicity and geographical area. The data include children aged 6 to 9 years who were measured in the 1980 National Survey (Kotzé et al., 1982). Without this group, the anthropometry of only primary school children were studied by individual researchers over a period of 20 years. However, Table 15 gives data on the 1994 National Survey (Department of Health, 1994). This study included children or 4.9 % of all school entrants in the Republic of South Africa. These children were randomly selected from schools using 10 schools per magisterial district in the four Education Departments (Houses of Assembly, Representatives, Delegates and Education and Training) of the previous Government to represent children from all four population groups. For the purpose of this analysis, the assumption was made that these would represent the white, coloured, Indian and black children respectively. Table 16 summarises some of the data contained in Tables For comparison, the mean figures obtained in the 1994 National Survey for each ethnic group are also given in this table. The mean percentages were calculated from all studies except the 1994 National Survey. No corrections for the number or distribution of subjects in the smaller studies were done. The data should therefore be interpreted with care. Nevertheless, the prevalences of underweight and stunting in all population groups seemed to be higher in the smaller studies than in the 1994 National Survey. Both sets of data indicate that wasting (low W-H) is not a serious problem on a national basis, although the wide range in prevalence reported in different studies, indicates that it is a serious problem in several areas and in particular groups of children. One reason for the differences in prevalences of underweight and stunting is probably that in the smaller studies some groups of children were examined because it was suspected that they were malnourished, leading to selection bias. For example, the Indian children studied by Van Rensburg et al. (1977) were from a socio-economically deprived area in Durban and they were selected on a basis of scoring during aptitude tests. This study showed that the majority of children were growth retarded and that they could be classified as slow learners. These authors remarked that despite the low weights and heights of the Indian children, their skinfold thickness was close to normal, as judged by conventional standards. The normal or thicker skinfolds of Indian children were also observed in other studies (Kotzé et al., 1986; Vorster et al., 1994). Comparing weights and heights and weight and height increases in the 6, 7, 8 and 9 year old children of the 1980 National Survey, Kotzé et al. (1982) observed that white children had the highest growth rate. Indian boys initially had the lowest weight, and put on weight later than the coloured and black boys. But they grew faster in height than the boys of the other two ethnic groups. Black children weighed more than the Indian and coloured children but they had the slowest growth rate (in weight and height) over this age period. In Table 17, the prevalences of stunting (low H-a) obtained in the three recent National Surveys on preschool (SALDRU/World Bank 1993/1994; SAVACG 1995) and primary school children (Department of Health, 1994) are given. On a national level, the percentages of stunted preschool children were 25.4 and 22.9, while the percentage of stunted school entrants was This 10 % difference is difficult to explain. It is possible that undernourished children are kept at home and sent to school later, but both studies on preschool children had an age cutpoint (60 and 72 months). All three studies were randomised and included children from the previous Homelands. However, differences in the provinces that did not have Homelands, such as the Western Cape, Northern Cape and Gauteng, were smaller than the provinces that included the Transkei (Eastern Cape), Bophutatswana (Free State and North West Province) and Venda (Northern Province). Therefore, it seems that insufficient randomisation of subjects could be a possible reason. The prevalences of stunting obtained in the SALDRU/World Bank study for the different provinces are generally higher than those of the SAVACG study. Due to measurement error, the body weights of children in the SALDRU/World Bank study could not be used (Harrison, 1995). The possibility that heights and ages were not accurate cannot, therefore, be ruled out. 8

17 Table 17 shows that the Northern Cape, Eastern Cape and Northern Province have the highest stunting prevalences, followed by the North West Province, KwaZulu-Natal, Free State and Mpumalanga. Gauteng and the Western Cape, the two most urban provinces, had the lowest prevalences ADOLESCENTS The anthropometric indices of adolescent boys and girls measured by several authors from 1978 to 1993 are given in Tables No national study of a representative group of adolescents has been done, probably because they are not generally seen to be a vulnerable group for malnutrition. The data in Tables are from children of different ages and different variables were measured. It is, therefore, difficult to compare the different population groups or to obtain an indication of the general level of nutritional status. However, three groups of researchers including Walker, Richardson and Cameron, studied the anthropometry and secondary sexual development of South African adolescents. Walker et al. (1982) compared 16 year old children from all four population groups and found that Afrikaans speaking white boys and girls were the tallest and heaviest (also taller than English speaking and Jewish boys and girls), while rural black boys and Indian girls were the shortest and lightest. In another study, Walker et al. (1980) demonstrated that 16 and 17 year old rural black children were on average 1 cm shorter and 2 kg lighter than urban black children. However, in a series of studies Cameron (1992) and Cameron et al. (1991; 1992; 1993; 1994) found that rural children of farm labourers and subsistence farmers had superior growth compared with average urban children. They concluded that black children of good socio-economic status have growth patterns similar to those of NCHS norms. The same authors consistently found that rural black children were delayed in the age at which they entered events of puberty, but that urban black children from good socio-economic backgrounds were slightly ahead of European children. Richardson & Pieters (1977) and Richardson et al. (1983) described the same pattern of late menarche in rural black girls despite normal breast development and adequate body fat composition. Their average weight-forheight was, in fact, greater than the average minimum required for white girls to menstruate. Cameron et al. (1991; 1992; 1993; 1994) observed a secular trend of a decrease in age of menarche in black girls since 1943 of 0.34 years for rural girls and 0.73 years for urban girls. Cameron et al. (1994) also described the fat patterning of rural black children. The girls showed a rapid gain in fatness after peak height velocity which differed from male centralised patterning. They hypothesised that this fat gain may be a physiological adaptation to an environment of suboptimal energy availability to buffer the energy cost of reproduction ADULTS Tables 23 to 26 give anthropometric indices of South African adults. Table 27 summarises reported heights of the men and women from the different population groups. Table 28 gives an analysis which Walker (1995) made of the prevalences of obesity among adult men and women, stratified for age and ethnic group. The data used to compile this table came from four large studies on whites (CORIS: Jooste et al., 1988), coloureds (CRISIC: Steyn et al., 1990), Indians (Seedat et al., 1990) and blacks (BRISK: Steyn et al., 1991). Table 27 indicates that black and coloured men and women are on average shorter than white men and women. Woods et al. (1978) also showed that coloured primigravidas delivering at term in the Western Cape, were shorter, lighter and thinner than white primigravidas. They related this phenomenon to childhood undernutrition and an inadequate diet during pregnancy. But Cameron and Kgamphe (1993) maintain that heights of African men and women (except the Pygmy and Bushmen) fell within or above European standards, showing that catchup growth took place where children were short for their age. Tobias (1989) examined secular trends in heights (statures) of Africans. He showed that no increase in height of Africans in Johannesburg took place from 1919 to However, the Kalahari San (Bushmen) has a secular trend towards increased adult mean stature. Table 28 shows that obesity (BMI > 30 k/g/m2) is common among South A frican women. The highest prevalence of 59 % was observed among black women aged years in the BRISK study. Coloured women of the same age had a prevalence of 42.6 %, Indian women 40 % and white women 23.8 %. The black women aged also had the highest mean prevalence of 34.4 %. The prevalences for men are much lower. The group with the highest prevalence was the black men aged 55 to 64 years (28.6 %), but the white men had a higher mean prevalence (14.7 %) than the other ethnic groups COMMENTS The trends or patterns observed from the nutritional anthropometry are that although only moderate prevalences of stunting, relatively low levels of underweight and low levels of wasting exist on a national level, there are pockets 9

18 of high prevalences, indicating that there are areas where undernutrition is a severe and serious problem. Rural black and coloured children seemed to be the most vulnerable. At the same time, relatively high prevalences of obesity, especially among black and coloured women were observed. This coexistence of under and overnutrition in developing countries has been described by several authors (Gross & Monteiro, 1989; Popkin, 1994). It has also been observed in the same families. Steyn et al. (1994) examined the caretakers of 57 underweight Pedi preschool children. They found that 4 % of the caretakers were underweight, 20 % overweight and 11 % were obese. More than 50 % of siblings were stunted. It seems that in these families there was enough diet energy available, but that it was difficult for young children to eat enough food to meet energy needs. The low energy density of the diet was therefore a contributing factor to the high prevalence of underweight. Steyn et al. (1994) also mention that parasitic infections in the children, as well as unhygienic feeding practices which lead to illness, may be responsible for the undernutrition of children, despite the availability of enough food and energy. There are other hypotheses that try to explain the coexistence of under and overnutrition in the same communities or families. The one is the Barker hypothesis (Barker, 1992) which states that foetal nourishment will influence health in later life. The other is the thrifty gene hypothesis, recently reviewed by Swinburn (1995). This hypothesis maintains that a process of natural selection of survivors of hunger, famine and starvation is responsible for the high incidence of obesity in developing populations. Both are beyond the scope of this report, but are mentioned to make the point that many mysteries and problems in the field of community nutrition will only be solved through research on a genetic and molecular level. 3.2 BIOCHEMICAL VARIABLES INTRODUCTION The concentration of many variables in body fluids (blood, plasma, serum, urine) or tissues (blood cells, muscle, adipose, etc.) can give useful information on the dynamics of a particular physiological or pathological process and also on nutritional status. Unfortunately, no single biochemical variable will reflect total nutritional status and a number of variables are generally used in conjunction with other measures of nutritional status (anthropometry, nutrient intakes and clinical signs of deficiencies). It should be kept in mind that the concentration of a specific nutrient variable will be influenced not only by intakes, but also by all factors which influence turnover (absorption, transport, metabolism and excretion). Moreover, several homeostatic mechanisms are responsible for maintaining many blood variables within narrow ranges. The blood (plasma or serum) concentration of a particular variable therefore does not necessarily reflect body stores. Another problem in the interpretation of biochemical variables is often their poor correlations with other measures of nutritional status. For example, Badenhorst et al (1993) found in 296 rural black children that, while 25 % were underweight and 23 % stunted according to anthropometric indices, none had serum albumin or glucose values outside the reference range, only 3 % had low phosphorus values, but 38 % had abnormal alkaline phosphatase levels. In a group of primary school black children from a remote rural area in the North West Province, Schmidt & Vorster (1995) also found that, although more than 50 % of the sample were stunted, total protein, albumin, prealbumin, retinol, ß-carotene and several other vitamins and minerals fell within normal ranges. Poor dietary intakes are often better reflected by anthropometry than by biochemical measurements. However, the opposite can also be true. Jooste et al. (1994) demonstrated in a group of 380 black primary school children in the Caprivi that, although 43.9 % of the girls and 33.7 % of the boys were biochemically anaemic, less than 1 % showed clinical signs of anaemia. The above emphasises the fact that while anthropometric measurements reflect growth and total nutritional status, biochemical measurements should be used to evaluate specific nutrient deficiencies. In this section, mean biochemical variables and in some instances, percentages outside normal ranges, reported during the past 10 years on South Africans stratified for age and ethnic group, are given in Tables 30 to 43. The normal reference ranges used to evaluate these variables are given in Table INFANTS AND CHILDREN AGED 0-6 YEARS The data obtained from 8 different studies in six provinces and in 1947 coloured and black children are given in Tables 30 to 33. The only national study in which biochemical variables were measured is the SAVACG (1995) study and it did not stratify for ethnic group. Data from this study are given in Table 33. The mean values reported for groups of coloured children (Table 30) were all within normal ranges, except for mean serum phosphorus values which were slightly raised and haemoglobin concentrations which were in the low normal range. 10