Inadequate feeding practices and impaired growth among children from subsistence farming households in Sidama, Southern Ethiopia.

Whether current child feeding practices and behaviours among rural households in Sidama, Southern Ethiopia conform to the World Health Organization (WHO) guiding principles for complementary feeding is uncertain. We assessed socio-demographic status, anthropometry, breastfeeding, complementary feeding practices and behaviours, and motor development milestones in a convenience sample of 97 breastfed children aged 6-23 months from three rural Sidama communities. Energy and nutrient intakes from complementary foods were also calculated from 1-day in-home weighed records. Prevalence of stunting ranged from 25% for infants aged 6-8 months to 52% for children aged 12-23 months, whereas for wasting, the corresponding prevalence was 10% and 14%, respectively. Very few children were exclusively breastfed up to 6 months of age (n = 2), or received solids/semi-solids for the recommended minimum number of times containing the recommended number of food groups. Responsive feeding was not practised and no cellular animal products were consumed. Median intakes of energy, and intakes and densities of micronutrients from complementary foods (but not protein) were below WHO recommendations, assuming average breast milk intakes; greatest shortfalls were for retinol, vitamin C and calcium densities. Mothers of stunted children were shorter and lighter, and from households of lower socio-economic status than non-stunted children (P < 0.05). Acquisition of some motor development milestones was delayed in stunted infants compared with their non-stunted counter-parts. In conclusion, interventions that address the WHO guiding principles for complementary feeding practices and behaviours, as well as prenatal influences on growth, are urgently required in this setting.

Risk map for cutaneous leishmaniasis in Ethiopia based on environmental factors as revealed by geographical information systems and statistics.

Cutaneous leishmaniasis (CL) is a neglected tropical disease strongly associated with poverty. Treatment is problematic and no vaccine is available. Ethiopia has seen new outbreaks in areas previously not known to be endemic, often with co-infection by the human immunodeficiency virus (HIV) with rates reaching 5.6% of the cases. The present study concerns the development of a risk model based on environmental factors using geographical information systems (GIS), statistical analysis and modelling. Odds ratio (OR) of bivariate and multivariate logistic regression was used to evaluate the relative importance of environmental factors, accepting P ≤ 0.056 as the inclusion level for the model's environmental variables. When estimating risk from the viewpoint of geographical surface, slope, elevation and annual rainfall were found to be good predictors of CL presence based on both probabilistic and weighted overlay approaches. However, when considering Ethiopia as whole, a minor difference was observed between the two methods with the probabilistic technique giving a 22.5% estimate, while that of weighted overlay approach was 19.5%. Calculating the population according to the land surface estimated by the latter method, the total Ethiopian population at risk for CL was estimated at 28,955,035, mainly including people in the highlands of the regional states of Amhara, Oromia, Tigray and the Southern Nations, Nationalities and Peoples' Region, one of the nine ethnic divisions in Ethiopia. Our environmental risk model provided an overall prediction accuracy of 90.4%. The approach proposed here can be replicated for other diseases to facilitate implementation of evidence-based, integrated disease control activities.

Identification of environmental parameters and risk mapping of visceral leishmaniasis in Ethiopia by using geographical information systems and a statistical approach.

Visceral leishmaniasis (VL), a vector-borne disease strongly influenced by environmental factors, has (re)-emerged in Ethiopia during the last two decades and is currently of increasing public health concern. Based on VL incidence in each locality (kebele) documented from federal or regional health bureaus and/or hospital records in the country, geographical information systems (GIS), coupled with binary and multivariate logistic regression methods, were employed to develop a risk map for Ethiopia with respect to VL based on soil type, altitude, rainfall, slope and temperature. The risk model was subsequently validated in selected sites. This environmental VL risk model provided an overall prediction accuracy of 86% with mean land surface temperature and soil type found to be the best predictors of VL. The total population at risk was estimated at 3.2 million according to the national population census in 2007. The approach presented here should facilitate the identification of priority areas for intervention and the monitoring of trends as well as providing input for further epidemiological and applied research with regard to this disease in Ethiopia.