Monitoring the levels of important nutrients in the food supply

A food supply that delivers energy-dense products with high levels of salt, saturated fats and trans fats, in large portion sizes, is a major cause of non-communicable diseases (NCDs). The highly processed foods produced by large food corporations are primary drivers of increases in consumption of these adverse nutrients. The objective of this paper is to present an approach to monitoring food composition that can both document the extent of the problem and underpin novel actions to address it. The monitoring approach seeks to systematically collect information on high-level contextual factors influencing food composition and assess the energy density, salt, saturated fat, trans fats and portion sizes of highly processed foods for sale in retail outlets (with a focus on supermarkets and quick-service restaurants). Regular surveys of food composition are proposed across geographies and over time using a pragmatic, standardized methodology. Surveys have already been undertaken in several high- and middle-income countries, and the trends have been valuable in informing policy approaches. The purpose of collecting data is not to exhaustively document the composition of all foods in the food supply in each country, but rather to provide information to support governments, industry and communities to develop and enact strategies to curb food-related NCDs

Fine resolution mapping of population age-structures for health and development applications

The age-group composition of populations varies considerably across the world, and obtaining accurate, spatially detailed estimates of numbers of children under 5 years is important in designing vaccination strategies, educational planning or maternal healthcare delivery. Traditionally, such estimates are derived from population censuses, but these can often be unreliable, outdated and of coarse resolution for resource-poor settings. Focusing on Nigeria, we use nationally representative household surveys and their cluster locations to predict the proportion of the under-five population in 1 × 1 km using a Bayesian hierarchical spatio-temporal model. Results showed that land cover, travel time to major settlements, night-time lights and vegetation index were good predictors and that accounting for fine-scale variation, rather than assuming a uniform proportion of under 5 year olds can result in significant differences in health metrics. The largest gaps in estimated bednet and vaccination coverage were in Kano, Katsina and Jigawa. Geolocated household surveys are a valuable resource for providing detailed, contemporary and regularly updated population age-structure data in the absence of recent census data. By combining these with covariate layers, age-structure maps of unprecedented detail can be produced to guide the targeting of interventions in resource-poor settings