Gebrenegus Ghilagaber

Inequalities in child mortality in Mozambique : differentials by parental socio-economic position

This study investigates the relation between socio-economic parental position (education and occupation) and child death in Mozambique using data from the Mozambican Demographic and Health Survey carried out between March and July 1997. The analysis included 9142 children born within 10 years before the survey. In spite of the Western system of classification used in the study, the results partly showed a parental socio-economic gradient of infant and child mortality in Mozambique. Fathers education seemed to reflect the familys social standing in the Mozambique context, showing a strong statistical association with postneonatal and child mortality. However, maternal education as a measure of socio-economic position was not statistically significantly associated with child mortality. This finding may partly be explained by the extreme hardships experienced by the country (civil war and natural disasters) and the implementation of the Economic Structural Adjustment Programme that have also affected the health of women and their children during the years covered by this study. Other measures of socio-economic position applicable to the rural African setting should be investigated.

Trends in infant and child mortality in Mozambique during and after a period of conflict

This study describes urban and rural trends of infant, child and under-five mortality in Mozambique (1973-1997) by mothers place of residence. A direct method of estimation was applied to the 1997 Mozambican Demographic and Health Survey data. The levels of infant, child and under-five mortality were considerably higher in rural than in urban areas. The difference in mortality between urban and rural areas increased over time until 1988-1992 and thereafter diminished. Possible causes of the different trends (e.g. the impact of civil war, drought, migration, adjustment programme and HIV/AIDS) are discussed. The increase in mortality in urban areas during the last few years before the survey may have been related to the immigration to urban areas of mothers whose children had high levels of mortality. Higher levels of infant, child and under-five mortality still prevail, particularly in rural areas. Further studies are needed to investigate the differentials of infant and child mortality by mothers place of residence.

Employment status and inequalities in self-reported health

Background: The aim of this study was to investigate the impact of employment status on self-reported health in Gavleborg County. Methods: The study used data from the 2010 Health in Equal terms survey, a cross-sectional survey carried out in Gavleborg County in Sweden. A total of 4,245 individuals, aged 16–65 years were included in the analysis. Descriptive and logistic regression analyses were used to assess the relationship between employment status and self-reported health Results: People who were outside the labour market had odds of poor health of 2.64 (Cl 2.28–3.05) compared to their employed counterparts. Controlling for other covariates reduced the risk slightly to 2.10 (1.69-2.60) but remained statistically significant. In addition, other variables were associated with self-reported poor health Conclusion: This study found a statistically significant association between being outside the labour market and poor self-reported health. The relation was explained partially by socio-economic and demographic variables. Further studies are needed to further investigate the observed relationships. Longitudinal studies are needed to further investigate the observed relationship. Policy-makers within the Gavleborg County need to pay attention to the health status of those out of work, especially during times of combined economic and labour market fluctuations. Results of the study suggest the need to pay attention to the health status of those outside the labour market especially during times of economic hardship. Keywords : Employment status, self-reported health, health inequalities

Disentangling Selection and Causality in Assessing the Effects of Health Inputs on Child Survival: Evidence from East Africa

Many demographic data have a hierarchical or clustered structure. For example, the analysis of childhood mortality involves a natural hierarchy where children are grouped within mothers or families, and the latter, in turn, are grouped into communities. Children from the same parents tend to be more alike in their characteristics than children chosen at random from the population at large. To ignore this grouping risks overlooking the importance of group effects, and may render invalid many of the traditional statistical analysis techniques used for studying data relationships.

A Family of Flexible Parametric Duration Functions and Their Applications to Modeling Child-Spacing in Sub-Saharan Africa

Examining the dynamics of child spacing is of interest for several reasons. First, several inferences are consistent with the view that in much of the developing world, women with large families ha ...

Advanced techniques for modelling maternal and child health in Africa

More than ten million women die or experience adverse consequences during pregnancy and childbirth each year (WHO 2005). Furthermore, nearly nine million children under the ages of 5 years die each year, largely from preventable and treatable diseases (UNICEF 2010). The hardest hit countries in poor maternal health (defined as the health of mothers during pregnancy, childbirth, and in the postpartum period) and child health (defined as the health of children from birth through adolescence) are in the developing world. For example, the global estimates of maternal and child mortality rates in 2008 were at 260 per 100,000 and 60 per 1,000 live births, respectively. The rates ranged from 21 to 620 and 13 to 127 respectively, with the African region at the top of both ranges (WHO 2011)

Modeling Spatial Effects on Childhood Mortality Via Geo-additive Bayesian Discrete-Time Survival Model: A Case Study from Nigeria

Childhood mortality is an important indicator of overall health and development in a country. It is the result of a complex interplay of determinants at many levels, and as such several studies have recognized that, for instance, maternal (Caldwell 1979; Cleland and van Ginneken 1988), socio-economic (Castro-Leal et al. 1999; Wagstaff 2001), and environmental (Wolfe and Behrman 1982; Lee et al. 1997) factors are important determinants of childhood mortality. However, only a few studies have incorporated environmental factors that are spatial in nature and derived from geographic databases, such as distances from households or communities (Watson et al. 1997).

On the Effects of Malaria Treatment on Parasite Drug Resistance – Probability Modelling of Genotyped Malaria Infections

Abstract We compare the frequency of resistant genes of malaria parasites before treatment and at first malaria incidence after treatment. The data come from a clinical trial at two health facilities in Tanzania and concerns single nucleotide polymorphisms (SNPs) at three positions believed to be related to resistance to malaria treatment. A problem is that mixed infections are common, which both obscures the underlying frequency of alleles at each locus as well as the associations between loci in samples where alleles are mixed. We use combinatorics and quite involved probability methods to handle multiple infections and multiple haplotypes. The infection with the different haplotypes seemed to be independent of each other. We showed that at two of the three studied SNPs, the proportion of resistant genes had increased after treatment with sulfadoxine–pyrimethamine alone but when treated in combination with artesunate, no effect was noticed. First recurrences of malaria associated more with sulfadoxine–pyrimethamine alone as treatment than when in combination with artesunate. We also found that the recruited children had two different ongoing malaria infections where the parasites had different gene types.

Bayesian Adjustment of Anticipatory Covariates in Analyzing Retrospective Data

In retrospective surveys, records on important variables such as the respondents educational level and social class refer to what is achieved by the date of the survey. Such variables are then used as covariates in investigations of behavior such as marriage and divorce in life segments that have occurred before the survey. To what extent can any change in the behavior be attributed to the misclassification of respondents across the various levels of the anticipatory variable? To what extent do they reflect real differences in the behavior across the levels? The connection is obtained by a Bayesian adjustment, by specifying a continuous-time Markov model for the incompletely observed time-varying anticipatory covariates, and by implementing standard Bayesian data augmentation techniques. The issues are illustrated by estimating effects of educational level on risks of divorce in a multiplicative piecewise-constant hazard model. Results show that ignoring the time-inconsistency of anticipatory variables may seriously plague the analyses because the relative risks across the anticipatory educational level are overestimated.

An application of diagonal reference models and time-varying covariates in social mobility research on mortality and fertility

In social mobility research, the diagonal reference model (DRM) is argued to best isolate the effect of social mobility from origin and destination status effects. In demographic research, standard analyses of the duration until an event occurs rely heavily on the appropriate use of covariates that change over time. We apply these best-practice methods to the study of social mobility and demographic outcomes in Sweden using register data that covers the years 1996-2012. The mortality analysis includes 1,024,142 women and 747,532 men and the fertility analysis includes 191,142 women and 164,368 men. We identify the challenges inherent in this combination and present strategies with an application to how social mobility is related to both fertility and mortality. Our application is successful at incorporating all requirements related to these methods. Our findings suggest, however, that certain data characteristics, such as a relatively high share of missing data, can be problematic. We also find that controlling for origin and destination status generally provides acceptable estimates of the mobility association in the specific case of Sweden and the relationship between social mobility and both fertility and mortality.