Estimating the burden of disease attributable to four selected environmental risk factors in South Africa

The first South African National Burden of Disease study quantified the underlying causes of premature mortality and morbidity experienced in South Africa in the year 2000. This was followed by a Comparative Risk Assessment to estimate the contributions of 17 selected risk factors to burden of disease in South Africa. This paper describes the health impact of exposure to four selected environmental risk factors: unsafe water, sanitation and hygiene; indoor air pollution from household use of solid fuels; urban outdoor air pollution and lead exposure.The study followed World Health Organization comparative risk assessment methodology. Population-attributable fractions were calculated and applied to revised burden of disease estimates (deaths and disability adjusted life years, [DALYs]) from the South African Burden of Disease study to obtain the attributable burden for each selected risk factor. The burden attributable to the joint effect of the four environmental risk factors was also estimated taking into account competing risks and common pathways. Monte Carlo simulation-modeling techniques were used to quantify sampling, uncertainty.Almost 24 000 deaths were attributable to the joint effect of these four environmental risk factors, accounting for 4.6% (95% uncertainty interval 3.8-5.3%) of all deaths in South Africa in 2000. Overall the burden due to these environmental risks was equivalent to 3.7% (95% uncertainty interval 3.4-4.0%) of the total disease burden for South Africa, with unsafe water sanitation and hygiene the main contributor to joint burden. The joint attributable burden was especially high in children under 5 years of age, accounting for 10.8% of total deaths in this age group and 9.7% of burden of disease.This study highlights the public health impact of exposure to environmental risks and the significant burden of preventable disease attributable to exposure to these four major environmental risk factors in South Africa. Evidence-based policies and programs must be developed and implemented to address these risk factors at individual, household, and community levels

Evaluation des caractéristiques physico-chimiques et sensorielles de la purée de tomate locale produite à petite échelle au Bénin

Physico-chemical and Sensorial Evaluation of Local Tomato Past Produced at Small Scale in Benin. L'article fait le point sur les avancements notés dans l'éradication de la peste bovine en Afrique sub-saharienne, avec à l'horizon 2010, l'éradication mondiale de la peste, telle que prévu par le Global Rinderpest Eradication Programme (GREP). Le programme Pan-Africain de Contrôle des Epizooties (PACE), un programme exécuté depuis 1999 sous l'égide de l'Union Africaine (UA) avec le concours financier du Fonds Européen pour le Développement (UE), exécute actuellement la dernière phase de ce programme d'éradication. Les auteurs passent en revue l'historique, le diagnostic et les outils de contrôle de cette maladie, tant chez le bétail que chez la faune. A l'heure actuelle, il ne reste qu'une partie de l'Afrique de l'est où sévit la maladie. Cependant aucun foyer n'y a été signalé depuis 2001. La seule lignée encore rencontrée (lignée 2 africaine) se cantonne à l'écosystème somalien, qui regroupe la Somalie, l'est du Kenya et la 5ième région de l'Ethiopie. Réapparue en 1994, 1998, et 2001 dans la faune sauvage, cette lignée représente donc la cible des derniers efforts d'éradication. En dehors de cette zone, la peste bovine semblerait être absente de l'Afrique de l'est. En Afrique de l'ouest et du centre où la maladie est absente depuis des décennies, les activités sont axées sur la certification internationale (par l'Organisation Mondiale de la Santé Animale, OIE) de l'absence de la maladie et de l'infection. Sur les 30 pays que couvre le PACE, 12 pays ont obtenu à ce jour le statut 'indemne de l'infection': Bénin, Burkina Faso, Burundi, Congo, Erythrée, Guinée, Guinée Bissau, Mali, RDC, Rwanda, Sénégal et Togo. Onze pays enfin, la Côte d'Ivoire, l'Ethiopie, le Ghana, le Kenya, la Mauritanie, le Niger, le Nigeria, l'Ouganda, le Soudan, la Tanzanie et le Tchad ont été déclarés 'indemnes de maladie' (en ce qui concerne le Kenya et l'Ethiopie, sur base zonale). En supposant que les procédures n'encourront pas de retards supplémentaires (p.e. pour cause de dépistage de cas), les derniers pays de la zone PACE seront déclarés indemnes de l'infection en 2009. Avec les perspectives d'éradication de la peste bovine du continent africain, plusieurs pays commencent à étudier sérieusement les opportunités d'exportation régionale et internationale de bétail et de produits d'animaux

Child disability, parental self-rated health and food security:a multivariate cross-sectional analysis

The literature on child disability reports differentials in health and socio-economic outcomes between families with child disability and families without child disability. Often based on bivariate or descriptive multivariate analysis of survey data the relationship between child disability, health and poverty is extended to other social and health outcomes such as stress, mental health. In this paper, these relationships are re-examined within a statistical modelling framework. In other words, in examining the relationship between health outcomes and child disability the modelling process allows control for other variables. In particular, three models are fitted to a large secondary data set for the three outcomes, health, poverty, and child disability. This approach can be very instructive in an exploratory study in identifying spurious relationships. The results suggest that after controlling for multicollinearity far fewer variables appear to be associated with health, child disability and food security outcomes; child disability appears to be related to health or food security but health or food security do not appear to be related to child disability i.e. none of the child disability variables appeared significant in model of health or poverty. Furthermore, the analysis highlights complex inter-relationships in data possibly due to the dynamic nature of these processes and the definition and measurement of these outcomes