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Dwellers of urban informal settlements in developing countries are consistently reported to be victims of high diarrhoea prevalence. Studies have frequently reported the association between high diarrhoea prevalence and other factors, such as poor living conditions, inadequate hygiene, and sanitation in these settings. However, little is known about the dynamics of diarrhoea prevalence in mountainous urban informal settlements similar to the Rwandan context. This study was conducted in the Matyazo cell of Huye town to review the prevalence and correlates of diarrhoea. A survey of 214 households and transect walks in the neighbourhoods were conducted during the rainy and dry seasons. Logistic regression was used to analyse the survey data while the thematic analysis technique was used to analyse qualitative data. Results indicated a substantial reduction of diarrhoea prevalence from the rainy to the dry season. It was also found that the prevalence was unequally distributed in the neighbourhoods according to household location. After controlling for other household characteristics and sanitation conditions of around homes, the study indicated that households established at 1800 metres or more above sea level were protected against diarrhoea during both rainy seasons (Adjusted Odds Ratio_ AOR: .42, 95% Confidence Interval_ CI: .13-.81) and dry seasons (AOR: .58, CI: .12-.90) while households found further from the road were likely to suffer from diarrhoea during rainy seasons (AOR: 3.32, CI: 1.47-7.48) as well as in dry seasons (AOR: 1.60, CI: 1.26-4.10). Poor sanitation within and around homes was also found to be associated with the increase of diarrhoea in either season. However, the evidence was not sufficient enough to confirm a significant association between diarrhoea prevalence and other household characteristics. We believe this is due to the strength of environmental factors in mountainous settings.Electronic supplementary materialThe online version of this article (doi:10.1186/2193-1801-3-745) contains supplementary material, which is available to authorized users.

The main objective of the study was to map poverty at sub-village and village levels in Kilindi District in Tanga region, Tanzania. Disaggregated poverty maps like these are very useful in showing the spatial distribution of poverty at micro level which can lead to effective poverty reduction intervention measures. A sample of 391 households was collected from five villages located along the road and off-road of Handeni-Songe road. The poverty mapping results indicated that the study villages had better food security because of adopting new varieties of crops especially beans followed by asset and income poverty indicators. Medium poverty was observed in energy and transport. However, the villages had very high poverty in health and sanitation and so require more intervention measures from the Government and Civil Society Organizations. The overall poverty mapping indicators showed that Mafisa Village was better off when compared to other villages in terms of poverty. The level of poverty was very high in Kibirashi and Balang’a villages which had a high proportion of Maasai pastoralists.

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Recently, the Mbeya Rural district has experienced land fragmentation and scarcity due to population increase. However, it is paradoxical to see that farmers have been converting productive croplands into woodlots instead of practicing agricultural intensification on their already scarce croplands. This paper contributes to the understanding of changes that are experienced by farmers in Uporoto Highlands by analysing factors that influence them to convert productive croplands into woodlots. The selection of the research area was based on the rate of conversion of croplands into woodlots, and easy accessibility from main roads. A simple random sampling technique was used in selecting 366 farmers for household interviews, while purposive sampling was used to select the research area, key informants, and participant of focus group discussions (FGDs). Field observation and documentary review were also used to complement the collection of data. The paper employed a mixed method approach to capture both quantitative and qualitative data. Quantitative data were analysed with the aid of the IBM SPSS Statistics software, version 21, to allow the generation of descriptive statistics, cross-tabulation functions, and multinomial regression analysis results. Qualitative data were analysed using content analysis. The results suggest that the conversion of productive croplands into woodlots is influenced by market conditions, social/peer influence, institutional factors, nature and characteristics of trees, holding land for future use, farmers’ characteristics and urban to peri-urban expansion. The study recommends that agricultural institutions in the country should create enabling conditions that help farmers convert their productive croplands in a manner that does not threaten food security.