Semiparametric Analysis of the Socio-Demographic and Spatial Determinants of Undernutrition in Two African Countries

We estimate semiparametric regression models of chronic undernutrition (stunting) using the 1992 Demographic and Health Surveys (DHS) from Tanzania and Zambia. We focus particularly on the influence of the child's age, the mother's body mass index, and spatial influences on chronic undernutrition. Conventional parametric regression models are not flexible enough to cope with possibly nonlinear effects of the continuous covariates and cannot flexibly model spatial influences. We present a Bayesian semiparametric analysis of the effects of these two covariates on chronic undernutrition. Moreover, we investigate spatial determinants of undernutrition in these two countries. Compared to previous work with a simple fixed effects approach for the influence of provinces, we model small scale district specific effects using flexible spatial priors. Inference is fully Bayesian and uses recent Markov chain Monte Carlo techniques

Socio-demographic determinants of anaemia and nutritional status in the Democratic Republic of Congo, Uganda and Malawi

Anaemia is a worldwide public health concern. Anaemia is multifactorial and its related factors are classified according to their position in the pathophysiological process. Socioeconomic and demographic factors such as poor education, cultural norms such as food taboos can predispose children and women to anaemia through immediate causes such as physiological, biological, diet and infections. However, socioeconomic and demographic factors associated with anaemia are not widely reported and it is difficult to find published literature on this subject, which could be due to the lack of data. The objective of this research is to provide an understanding of socioeconomic and demographic factors related with anaemia among children and women and the links between anaemia during childhood and child nutritional status which can be used as a basis for policy formulation, planning and implementation.Almost three quarters of children and half of women in DRC (2007), Uganda (2006) and Malawi (2004) are anaemic. Multilevel ordinal regression models were fitted for anaemia among children and multilevel logistic regression models for anaemia among women. The models showed variations in anaemia prevalence within the countries at the community level. However, country level interactions indicate that there are no significant differences in the risk of anaemia in children and women between these countries. Endogenous switching regression models were fitted to the data to explore the link between anaemia and child’s health outcomes. Anaemia is endogenous to children’s nutritional status (weight-for-age z-scores) which should be accounted for. The prevalence of anaemia is high in DRC (71%), Uganda (74%) and Malawi (73%) and anaemia is a severe public health problem in the three countries. Although it will take considerable time for the three countries to control anaemia, it is not an impossible task. By improving nutrition and iron status, and treating helminth and malaria infections, the prevalence of anaemia can decrease as observed in Malawi in 2010. More effort is needed to identify the pathways through which anaemia within each country may be addressed

Giant Anisotropic Magnetoresistance in a Quantum Anomalous Hall Insulator

When a three-dimensional (3D) ferromagnetic topological insulator thin film is magnetized out-of-plane, conduction ideally occurs through dissipationless, one-dimensional (1D) chiral states that are characterized by a quantized, zero-field Hall conductance. The recent realization of this phenomenon - the quantum anomalous Hall effect - provides a conceptually new platform for studies of edge-state transport, distinct from the more extensively studied integer and fractional quantum Hall effects that arise from Landau level formation. An important question arises in this context: how do these 1D edge states evolve as the magnetization is changed from out-of-plane to in-plane? We examine this question by studying the field-tilt driven crossover from predominantly edge state transport to diffusive transport in Cr-doped (Bi,Sb)2Te3 thin films, as the system transitions from a quantum anomalous Hall insulator to a gapless, ferromagnetic topological insulator. The crossover manifests itself in a giant, electrically tunable anisotropic magnetoresistance that we explain using the Landauer-Buttiker formalism. Our methodology provides a powerful means of quantifying edge state contributions to transport in temperature and chemical potential regimes far from perfect quantization

Geo-additive models of Childhood Undernutrition in three Sub-Saharan African Countries

We investigate the geographical and socioeconomic determinants of childhood undernutrition in Malawi, Tanzania and Zambia, three neighboring countries in Southern Africa using the 1992 Demographic and Health Surveys. We estimate models of undernutrition jointly for the three countries to explore regional patterns of undernutrition that transcend boundaries, while allowing for country-specific interactions. We use semiparametric models to flexibly model the effects of selected so-cioeconomic covariates and spatial effects. Our spatial analysis is based on a flexible geo-additive model using the district as the geographic unit of anal-ysis, which allows to separate smooth structured spatial effects from random effect. Inference is fully Bayesian and uses recent Markov chain Monte Carlo techniques. While the socioeconomic determinants generally confirm what is known in the literature, we find distinct residual spatial patterns that are not explained by the socioeconomic determinants. In particular, there appears to be a belt run-ning from Southern Tanzania to Northeastern Zambia which exhibits much worse undernutrition, even after controlling for socioeconomic effects. These effects do transcend borders between the countries, but to a varying degree. These findings have important implications for targeting policy as well as the search for left-out variables that might account for these residual spatial patterns

Identification of Wheat Varieties with a Parallel-Plate Capacitance Sensor Using Fisher’s Linear Discriminant Analysis

Fisher’s linear discriminant (FLD) models for wheat variety classification were developed and validated. The inputs to the FLD models were the capacitance (C), impedance (Z), and phase angle (θ), measured at two frequencies. Classification of wheat varieties was obtained as output of the FLD models. Z and θ of a parallel-plate capacitance system, holding the wheat samples, were measured using an impedance meter, and the C value was computed. The best model developed classified the wheat varieties, with accuracy of 95.4%, over the six wheat varieties tested. This method is simple, rapid, and nondestructive and would be useful for the breeders and the peanut industry