There is a need for state level implementation of specific programmes that target vulnerable children as this can help in reversing the existing patterns.

BackgroundMalaria during pregnancy is a major public health problem in Nigeria leading to increase in the risk of maternal mortality, low birth weight and infant mortality. This paper is aimed at highlighting key predictors of the ownership of insecticide treated nets (ITNs) and its use among pregnant women in Nigeria.MethodsA total of 2348 pregnant women were selected by a multi-stage probability sampling technique. Structured interview schedule was used to elicit information on socio-demographic characteristics, ITN ownership, use, knowledge, behaviour and practices. Logistic regression was used to detect predictors of two indicators: ITN ownership, and ITN use in pregnancy among those who owned ITNs.ResultsITN ownership was low; only 28.8% owned ITNs. Key predictors of ITN ownership included women who knew that ITNs prevent malaria (OR = 3.85; p < 0001); and registration at antenatal clinics (OR = 1.34; p = 0.003). The use of ITNs was equally low with only 7.5% of all pregnant women, and 25.7% of all pregnant women who owned ITNs sleeping under a net. The predictors of ITN use in pregnancy among women who owned ITNs (N = 677) identified by logistic regression were: urban residence (OR = 1.87; p = 0.001); knowledge that ITNs prevent malaria (OR = 2.93; p < 0001) and not holding misconceptions about malaria prevention (OR = 1.56; p = 0.036). Educational level was not significantly related to any of the two outcome variables. Although registration at ANC is significantly associated with ownership of a bednet (perhaps through free ITN distribution) this does not translate to significant use of ITNs.ConclusionsITN use lagged well behind ITN ownership. This seems to suggest that the current mass distribution of ITNs at antenatal facilities and community levels may not necessarily lead to use unless it is accompanied by behaviour change interventions that address the community level perceptions, misconceptions and positively position ITN as an effective prevention device to prevent malaria

Child mortality reflects a country's level of socio-economic development and quality of life. In developing countries, mortality rates are not only influenced by socio-economic, demographic and health variables but they also vary considerably across regions and districts. In this paper, we analysed child mortality in Nigeria with flexible geoadditive discrete-time survival models. This class of models allows us to measure small-area district-specific spatial effects simultaneously with possibly non-linear or time-varying effects of other factors. Inference is fully Bayesian and uses computationally efficient Markov chain Monte Carlo (MCMC) simulation techniques. The application is based on the 1999 Nigeria Demographic and Health Survey. Our method assesses effects at a high level of temporal and spatial resolution not available with traditional parametric models, and the results provide some evidence on how to reduce child mortality by improving socio-economic and public health conditions.

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