Analyzing Child Mortality in Nigeria with Geoadditive Survival Models

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 analyze child mortality in Nigeria with flexible geoadditive survival models. This class of models allows to measure small-area district-specific spatial effects simultaneously with possibly nonlinear or time-varying effects of other factors. Inference is fully Bayesian and uses recent Markov chain Monte Carlo (MCMC) simulation. 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

Private Wage Returns to Schooling in Nigeria: 1996-1999

In the last two decades, primary and secondary school enrollment rates have declined in Nigeria while enrollment rates in post-secondary school have increased. This paper estimates from the General Household Survey for Nigeria the private returns to schooling associated with levels of educational attainment for wage and self-employed workers. The estimates for both men and women are small at primary and secondary levels, 2 to 4 percent, but are substantial at post-secondary education level, 10-15 percent. These schooling return estimates may account for the recent trends in enrollments. Thus, increasing public investment to encourage increased attendance in basic education is not justifiable on grounds of private efficiency, unless investments to increase school quality have higher private returns. With high private returns to post-secondary schooling, students at this level should pay tuition, to recoup more of the public costs of schooling, which may be redistributed to poor families through scholarships.Schooling Investment; Private Wage Returns; Efficiency; Equity; Nigeria

Geoadditive latent variable modelling of count data on multiple sexual partnering in Nigeria

The 2005 National HIV/AIDS and Reproductive Health Survey in Nigeria provides evidence that multiple sexual partnering increases the risk of contracting HIV and other sexually transmitted diseases. Therefore, partner reduction is one of the prevention strategies to accomplish the Millenium development goal of halting and reversing the spread of HIV/AIDS. In order to explore possible association between sexual partnering and some risk factors, this paper utilizes a novel Bayesian geoadditive latent variable model for count outcomes. This allows us to simultaneously analyze linear and nonlinear effects of covariates as well as spatial variations of one or more latent variables, such as attitude towards multiple partnering, which in turn directly influences the multivariate observable outcomes or indicators. Influence of demographic factors such as age, gender, locality, state of residence, educational attainment, etc., and knowledge about HIV/AIDS on attitude towards multiple partnering is also investigated. Results can provide insights to policy makers with the aim of reducing the spread of HIV and AIDS among the Nigerian populace through partner reduction.factor loading; geographical variations; latent variable model; MCMC; Nigeria; semiparametric Poisson model

Bayesian Geoadditive Seemingly Unrelated Regression

Parametric seemingly unrelated regression (SUR) models are a common tool for multivariate regression analysis when error variables are reasonably correlated, so that separate univariate analysis may result in inefficient estimates of covariate effects. A weakness of parametric models is that they require strong assumptions on the functional form of possibly nonlinear effects of metrical covariates. In this paper, we develop a Bayesian semiparametric SUR model, where the usual linear predictors are replaced by more flexible additive predictors allowing for simultaneous nonparametric estimation of such covariate effects and of spatial effects. The approach is based on appropriate smoothness priors which allow different forms and degrees of smoothness in a general framework. Inference is fully Bayesian and uses recent Markov chain Monte Carlo techniques

Geoadditive Latent Variable Modelling of Count Data on Multiple Sexual Partnering in Nigeria

The 2005 National HIV/AIDS and Reproductive Health Survey in Nigeria provides evidence that multiple sexual partnering increases the risk of contracting HIV and other sexually transmitted diseases. Therefore, partner reduction is one of the prevention strategies to accomplish the Millenium development goal of halting and reversing the spread of HIV/AIDS. In order to explore possible association between sexual partnering and some risk factors, this paper utilizes a novel Bayesian geoadditive latent variable model for count outcomes. This allows us to simultaneously analyze linear and nonlinear effects of covariates as well as spatial variations of one or more latent variables, such as attitude towards multiple partnering, which in turn directly influences the multivariate observable outcomes or indicators. Influence of demographic factors such as age, gender, locality, state of residence, educational attainment, etc., and knowledge about HIV/AIDS on attitude towards multiple partnering is also investigated. Results can provide insights to policy makers with the aim of reducing the spread of HIV and AIDS among the Nigerian populace through partner reduction

Spatial analysis of women employment status in Nigeria

This study considered the nature of employment that women engage in as a multi-categorical response. A multinomial logistic model with geo-additive predictors was used to examine the determinants and geographical variations using data from the 2008 Nigeria Demographic and Health Survey. Diffuse priors were assumed for modelling fixed effects, Bayesian p-spline for the nonlinear smooth functions and intrinsic conditional autoregressive prior for the spatial effects. Results showed that while a north-south divide existed in the likelihood of women engaging in all-year employment against not working, an east-west divide was found in seasonal/occasional jobs. Other important factors found to be significantly associated with employment status included women's age, educational level, marital status, sex of household head, and type of place of residence. Policymakers need to develop appropriate strategies to address the observed imbalance in the spatial distributions of women employment status in the country

Gas Chromatography-Mass Spectrometry Analysis of Viburnum Opulus (L) Extract and its Toxicity Studies in Rats

Objectives: This study was aimed at establishing the antimicrobial and phytochemical profiles of Viburnum opulus (L) as well as the safety potential of the extract in albino Wistar rats. Methods: Ethanol, n-hexane, ethyl acetate, butanol, and water fractions were prepared for both phytochemical assessments using gas chromatography- mass spectrometry analysis (GC-MS). Five groups of seven rats were used for the study. Group A received distilled water (control), while Groups B to E were treated, respectively, with 250, 500, 1000, and 1500 mg/kg body weight of V. opulus extract by abdominal canalization for 28 days. Blood samples were obtained for biochemical analyses, and the liver tissues were further processed for histological studies. Results: The GC-MS spectra revealed the existence of various phytoconstituents such as neophytadiene, germaciene, and caryophyllene among others. High-density lipoprotein and albumin were significantly (p<0.05) elevated in animals administered with 500, 1000, and 1500 mg/kg bw of the leaf extract. Ethanol, butanol, and water fractions of the leaf of V. opulus showed antimicrobial action against most of the organisms used in this study. Conclusion: The result indicate