Author/s: Winnie Sambu & Katharine HallDate: February 2014
A child is considered underweight if the child’s weight-for-age measurement is less than two standard deviations from the globally accepted reference cut-off point, or three standard deviations in the case of severe underweight.
The effects of poor nutrition on children are far reaching. It is estimated that more than 200 million children under five years globally will not realise their full cognitive development due to poverty, lack of proper care, poor health and inadequate nutrition.1 Research suggests that poor nutrition affects the educational outcomes of children, adult working capacity and economic productivity.2 Under-nutrition in childhood could therefore lead to lower wages in adulthood, perpetuating intergenerational cycles of poverty and exacerbating poverty rates.
Globally, undernutrition contributes to more than a third of deaths in children under five.3 A local study of child deaths in audited hospitals indicated that 34% of children who died between 2005 and 2009 were severely malnourished and another 30% were underweight for their age.4 Early childhood is a critical period for growth and development, and nutritional deficits may be irreversible after the second year.5 The effects of early undernutrition are long-reaching, and are associated with life-threatening diseases such as diabetes, cardiovascular disease and hypertension in adult life.6
UNICEF distinguishes between the immediate, underlying and basic causes of malnutrition.7 Immediate causes of malnutrition include inadequate dietary intake and illness. This can lead to a potentially vicious cycle of illness and malnutrition, where malnutrition impairs children’s immunity leading to recurrent bouts of illness, which further undermine children’s nutritional status.8 Underlying causes include household food insecurity, inadequate maternal care, poor access to services and unhealthy living environments, which in turn are driven by the unequal distribution of resources in society.9
Efforts to monitor malnutrition in South Africa are constrained by the shortage of regular and reliable anthropometric data (measures of height and weight, for example). Nationally representative surveys that have yielded usable data on the height and weight of children are the Project for Statistics on Living Standards and Development (PSLSD) of 1993, the Demographic and Health Survey of 1998, the National Food Consumption Survey of 2005 and the National Income Dynamics Study (NIDS) of 2008.
It is notoriously difficult to collect anthropometric data of good quality. Statistics South Africa’s Living Conditions Survey of 2008/09 collected anthropometric data from a large sample but did not publish it because the quality was too poor. Subsequent iterations of the NIDS panel survey have collected anthropometric data, but although changes in children’s nutritional status over time are plausible,10 the representivity of the sample diminishes after the first wave. The analyses presented here are therefore based on the most recent reliable and nationally representative data: NIDS 2008. A more recent survey, the South African National Health and Nutrition Examination Survey,11 was undertaken in 2012, and may provide more up-to-date data for analysis of child anthropometry. The data have not yet been made available.
Underweight is an indicator of both chronic and acute malnutrition.13 In 2008, nearly 10% of children aged six months to nine years were underweight. About 4% were severely underweight. Children living in rural areas were more likely to be underweight, while 13% and 10% of children in rural formal and tribal areas were underweight compared to 8% and 9% in the urban formal and urban informal areas respectively. Rates were lowest amongst children in relatively wealthy households (5%), compared to 11% amongst children in the poorest quintile.
The proportion of underweight children under five years decreased from 15% in 1993 to 9% in 2008, and may have declined further to 5.2%, according to the SAHANES-1 report.14
NIDS attempts to follow individuals and changes that occur in their well-being over a period of time. Wave 1 data collection began in February 2008, and involved 7,305 households and 28, 255 individuals. The study used a two-stage cluster sampling approach, where in the first stage; primary sampling units were selected from Stats SA’s master sample. During the survey, data collected included household demographics, income and expenditure patterns, living conditions, anthropometric measurements among other indicators. While it is a nationally representative survey, further disaggregation is limited due to the small sample size used.