Epidemiological and nutrition transition in developing countries: impact on human health and development

Whereas common infectious and parasitic diseases such as malaria and the HIV/AIDS pandemic remain major unresolved health problems in many developing countries, emerging non-communicable diseases relating to diet and lifestyle have been increasing over the last two decades, thus creating a double burden of disease and impacting negatively on already over-stretched health services in these countries. Prevalence rates for type 2 diabetes mellitus and CVD in sub-Saharan Africa have seen a 10-fold increase in the last 20 years. In the Arab Gulf current prevalence rates are between 25 and 35% for the adult population, whilst evidence of the metabolic syndrome is emerging in children and adolescents. The present review focuses on the concept of the epidemiological and nutritional transition. It looks at historical trends in socio-economic status and lifestyle and trends in nutrition-related non-communicable diseases over the last two decades, particularly in developing countries with rising income levels, as well as the other extreme of poverty, chronic hunger and coping strategies and metabolic adaptations in fetal life that predispose to non-communicable disease risk in later life. The role of preventable environmental risk factors for obesity and the metabolic syndrome in developing countries is emphasized and also these challenges are related to meeting the millennium development goals. The possible implications of these changing trends for human and economic development in poorly-resourced healthcare settings and the implications for nutrition training are also discussed.

Modelling high particulate matter and ozone episodes in the Trans-Manche region

There is concern in the Cross-Channel region of Nord-Pas-de-Calais (France) and Kent (Great Britain), regarding the extent of atmospheric pollution detected in the area from emitted gaseous (VOC, NOx, S02)and particulate substances. In particular, the air quality of the Cross-Channel or "Trans-Manche" region is highly affected by the heavily industrial area of Dunkerque, in addition to transportation sources linked to cross-channel traffic in Kent and Calais, posing threats to the environment and human health. In the framework of the cross-border EU Interreg IIIA activity, the joint Anglo-French project, ATTMA, has been commissioned to study Aerosol Transport in the Trans-Manche Atmosphere. Using ground monitoring data from UK and French networks and with the assistance of satellite images the project aims to determine dispersion patterns. and identify sources responsible for the pollutants. The findings of this study will increase awareness and have a bearing on future air quality policy in the region. Public interest is evident by the presence of local authorities on both sides of the English Channel as collaborators. The research is based on pollution transport simulations using (a) Lagrangian Particle Dispersion (LPD) models, (b) an Eulerian Receptor Based model. This paper is concerned with part (a), the LPD Models. Lagrangian Particle Dispersion (LPD) models are often used to numerically simulate the dispersion of a passive tracer in the planetary boundary layer by calculating the Lagrangian trajectories of thousands of notional particles. In this contribution, the project investigated the use of two widely used particle dispersion models: the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and the model FLEXPART. In both models forward tracking and inverse (or·. receptor-based) modes are possible. Certain distinct pollution episodes have been selected from the monitor database EXPER/PF and from UK monitoring stations, and their likely trajectory predicted using prevailing weather data. Global meteorological datasets were downloaded from the ECMWF MARS archive. Part of the difficulty in identifying pollution sources arises from the fact that much of the pollution outside the monitoring area. For example heightened particulate concentrations are to originate from sand storms in the Sahara, or volcanic activity in Iceland or the Caribbean work identifies such long range influences. The output of the simulations shows that there are notable differences between the formulations of and Hysplit, although both models used the same meteorological data and source input, suggesting that the identification of the primary emissions during air pollution episodes may be rather uncertain.