Probing secondary exposure and health data as a tool to improve public health in South Africa

Abstract

The usefulness of secondary exposure and health data to improve public health in South Africa will be assessed. Given the tremendous health impact of air pollution exposure the focus of this thesis is on primary prevention, that is the identification of outdoor air pollution and the use of dirty fuels (wood, animal dung, crop residues, coal, paraffin) for cooking and heating as risk factors, whilst controlling for confounding. Hourly averaged outdoor PM10 mass, NO2, NO, SO2, O3 data (1 August 1998 - 31 July 2003) from Cape Town were analysed in a nonparametric Spearman’s Rho correlation analysis to determine the seasonal spatial correlation between the monitoring sites. Trend and descriptive analyses were conducted on the outdoor hourly and daily PM10 mass data to investigate the current and future health implications in the Khayelitsha sub-district, Cape Town. The 1998 South African Demographic and Health Survey (SADHS) data were analysed. The survey involved 13 826 individuals in 12763 households. Univariate and multivariate logistic regression analyses generated crude and adjusted odds ratios and 95% confidence intervals in order to assess the influence of dirty fuel use for cooking and heating on adult (> 15 years) respiratory health, childhood (< 59 months) respiratory health and 1-59 month mortality. It was found that outdoor air pollution is not homogenously distributed in Cape Town during all seasons. Elevated PM10 mass concentrations are frequently present in the Khayelitsha sub-district. There is a strong case for acknowledging the large public health risk arising from air pollution exposure in South Africa, despite the limitations of the 1998 SADHS data. Not much progress has been made in air pollution epidemiology in the country during this investigation due to the identified limitations. Secondary exposure and health data are thus only useful in improving public health in South Africa by supplying baseline data for trend analysis or hypotheses generation. It is recommended that the country must develop environmental public health tracking networks, which incorporates various data sources from multi-sectoral collaborative intervention projects with analytic study designs, in all major cities in the country.