17 research outputs found
Child mortality inequalities across Rwanda districts: a geoadditive continuous-time survival analysis
No full textChild survival programmes are efficient when they target the most significant and area-specific factors. This study aimed to assess the key determinants and spatial variation of child mortality at the district level in Rwanda. Data from the 2010 Rwanda Demographic and Health Survey were analysed for 8817 live births that occurred during five years preceding the survey. Out of the children born, 433 had died before survey interviews were carried out. A full Bayesian geo-additive continuous-time hazard model enabled us to maximise data utilisation and hence improve the accuracy of our estimates. The results showed substantial district- level spatial variation in childhood mortality in Rwanda. District-specific spatial characteristics were particularly associated with higher death hazards in two districts: Musanze and Nyabihu. The model estimates showed that there were lower death rates among children from households of medium and high economic status compared to those from low-economic status households. Factors, such as four antenatal care visits, delivery at a health facility, prolonged breastfeeding and mothers younger than 31 years were associated with lower child death rates. Long preceding birth intervals were also associated with fewer hazards. For these reasons, programmes aimed at reducing child mortality gaps between districts in Rwanda should target maternal factors and take into consideration district-specific spatial characteristics. Further, child survival gains require strengthening or scaling-up of existing programmes pertaining to access to, and utilisation of maternal and child health care services as well as reduction of the household gap in the economic status
Bayesian mapping of HIV infection among women of reproductive age in Rwanda.
No full textHIV prevalence is rising and has been consistently higher among women in Rwanda whereas a decreasing national HIV prevalence rate in the adult population has stabilised since 2005. Factors explaining the increased vulnerability of women to HIV infection are not currently well understood. A statistical mapping at smaller geographic units and the identification of key HIV risk factors are crucial for pragmatic and more efficient interventions. The data used in this study were extracted from the 2010 Rwanda Demographic and Health Survey data for 6952 women. A full Bayesian geo-additive logistic regression model was fitted to data in order to assess the effect of key risk factors and map district-level spatial effects on the risk of HIV infection. The results showed that women who had STIs, concurrent sexual partners in the 12 months prior to the survey, a sex debut at earlier age than 19 years, were living in a woman-headed or high-economic status household were significantly associated with a higher risk of HIV infection. There was a protective effect of high HIV knowledge and perception. Women occupied in agriculture, and those residing in rural areas were also associated with lower risk of being infected. This study provides district-level maps of the variation of HIV infection among women of child-bearing age in Rwanda. The maps highlight areas where women are at a higher risk of infection; the aspect that proximate and distal factors alone could not uncover. There are distinctive geographic patterns, although statistically insignificant, of the risk of HIV infection suggesting potential effectiveness of district specific interventions. The results also suggest that changes in sexual behaviour can yield significant results in controlling HIV infection in Rwanda
Distribution of Budget Shares for Food: An Application of Quantile Regression to Food Security 1
No full textThis study examines, using quantile regression, the linkage between food security and efforts to enhance smallholder coffee producer incomes in Rwanda. Even though in Rwanda smallholder coffee producer incomes have increased, inhabitants these areas still experience stunting and wasting. This study examines whether the distribution of the income elasticity for food is the same for coffee and noncoffee growing provinces. We find that that the share of expenditures on food is statistically different in coffee growing and noncoffee growing provinces. Thus, the increase in expenditure on food is smaller for coffee growing provinces than noncoffee growing provinces
Models comparison based on the DIC statistic.
No full text<p>Models comparison based on the DIC statistic.</p
Posterior odds ratio (POR) estimates for fixed effects with 95% credible intervals based on Model 5.
No full text<p>*Statistically significant different PORs</p><p>Posterior odds ratio (POR) estimates for fixed effects with 95% credible intervals based on Model 5.</p
District codes and levels of HIV prevalence among women (15–49 years) in Rwanda.
No full text<p>District codes and levels of HIV prevalence among women (15–49 years) in Rwanda.</p
Posterior mean of the adjusted structured (A) and unstructured (B) spatial effects.
No full text<p>Posterior mean of the adjusted structured (A) and unstructured (B) spatial effects.</p
Sensitivity analysis: DIC, posterior mean variance, its standard error (within brackets), and 95% CI based on Model 5.
No full text<p>Sensitivity analysis: DIC, posterior mean variance, its standard error (within brackets), and 95% CI based on Model 5.</p
Districts of Rwanda and their geographic codes used during the 2010 RDHS.
No full text<p>Districts of Rwanda and their geographic codes used during the 2010 RDHS.</p
