The need to address the growing prevalence of non-communicable diseases through changing the lifestyle behaviours that contribute to them has become a global priority. Settings-based health promotion strategies such as workplace health promotion programmes are growing in an attempt to start meeting this need. In order for settings-based health promotion programmes to be successful, they need to be based on the specific risk profiles of the population for whom they are designed. Workplace health promotion programmes are becoming popular in South Africa, but there are currently few data available about the health risks and lifestyle behaviours of the South African employed population. In order to obtain such data and reward workplace health promotion initiatives, Discovery Health initiated healthy company campaigns in South Africa and the UK. These campaigns took the form of a competition to assess the healthiest companies in each country. Through these campaigns, an extensive data set was collected encompassing UK and South African employees' lifestyle behaviours and health risks. In this article, we used these data to compare self-reported physical activity levels, self-reported fruit and vegetable consumption, calculated BMI, self-reported smoking, mental health indicators, and health screening status of the UK and South African employee samples. We found significant differences across all measures, with the exception of self-reported fruit and vegetable consumption. The findings emphasise the importance of using local data to tailor workplace health promotion programmes for the population for which the programmes have been designed.

South Africa has amongst the highest rates of homicide in the world, yet little is known about the contexts that shape fatal violence. One frequently feared context is robbery. We examine 68,801 robberies reported between 2003 and 2014 to predict risk factors for cases resulting in victim death. Robbery-homicide is rare in South Africa and its risk factors differ from the country’s overall homicide profile. Significant correlates include day of the week, time of the day and the victim’s race. These findings demonstrate how context-sensitive understandings of violence are crucial to advancing research on homicide in low- and middle-income countries.

Using routinely collected police data is valuable for investigating the situational dimensions of violence, thereby enhancing our understanding of contexts that shape violence and its injury outcomes. Such an approach can advance contextually sensitive violence prevention strategies.

This open-access article is distributed under Creative Commons licence CC-BY-NC 4.0.

Road traffic accidents (RTA) are a major cause of death and injury around the world. The use of Supervised learning (SL) methods to understand the frequency and injury-severity of RTAs are of utmost importance in designing appropriate interventions. Data on RTAs that occurred in the city of Cape Town during 2015-2017 are used for this study. The data contain the injury-severity (no injury, slight, serious and fatal injury) of the RTAs as well as several accident-related variables. Additional locational and situational variables were added to the dataset. Four training datasets were analysed: the original imbalanced data, data with the minority class over-sampled, data with the majority class under-sampled and data with synthetically created observations. The performance of different SL methods were compared using accuracy, recall, precision and F1 score evaluation metrics and based on the average recall the ANN was selected as the best performing model on the validation data.