Further Analysis of the 2014 Cambodia Demographic and Health Survey | DHS Further Analysis Reports No. 105
Further Analysis of the 2000, 2005, and 2011 Demographic and Health Surveys. DHS Further Analysis Reports No. 83
DHS Working Papers No. 83.
Further Analysis of the 2011 Ethiopia Demographic and Health
Survey. DHS Further Analysis Reports No. 82
Further Analysis of the 2000, 2005, and 2011 Demographic and Health Surveys. DHS Further Analysis Reports No. 80
Further Analysis of the 2000, 2005, and 2011 Demographic Health Surveys. DHS Further Analysis Reports No. 72
DHS Working Papers No. 90.
DHS Working Papers No. 98.
DHS Working Papers No. 110 | Zimbabwe Working Papers No. 11
DHS Working Papers No. 111 | Zimbabwe Working Papers No. 12
DHS WORKING PAPERS 2016 No. 126 | DEMOGRAPHIC AND HEALTH SURVEYS
DHS Analytical Studies No. 40
DHS Analytical Studies No. 39
This report summarizes the findings of the 2010 Rwanda Demographic and Health Survey (RDHS). The 2010 Rwanda Demographic and Health Survey (RDHS) was designed to provide data for monitoring the population and health situation in Rwanda. The 2010 RDHS is the fifth Demographic and Health Survey to be ...conducted in Rwanda (DHS in 1992, 2000, and 2005 and Interim DHS in 2007-08). The objective of the survey was to provide up-to-date information on fertility, family planning, childhood mortality, nutrition including anemia testing, maternal and child health, domestic violence, malaria including malaria testing, maternal mortality, awareness and behavior regarding HIV/AIDS and other sexually transmitted infections, and HIV prevalence.
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DHS Further Analysis Reports No. 109 - This report documents trends in key child nutrition indicators in Rwanda. Data from the Demographic and Health Surveys (DHS) in 2005, 2010, and 2014-15 were analyzed, disaggregated by selected equity-related variables, and tested for trends. Over the survey per...iod, Rwanda had high rates of exclusive breastfeeding, with regional variation. Rates of continued breastfeeding were also high but generally decreased as mother’s education and household wealth increased in all survey years. Complementary feeding practices varied by region, mother’s education, household wealth, urban-rural residence, and sex of the child.
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DHS Further Analysis Reports No. 107 - This report, based largely on the 2014-15 national survey in Rwanda, focuses on changes and trends in reproductive behavior since 2010. In the 4-5 years after the 2010 survey, fertility continued its decline to 4.2 births per woman as contraceptive prevalence i...ncreased slightly. However, the earlier downward trend in number of children desired appears stalled. This is clearly evident from an increase in the proportions of married women and men who say they want more children. Child mortality has significantly declined and remains strongly related to fertility; while age at marriage has continued to increase. The demographic goals specified in the 1998-99 plan for development, Rwanda Vision 2020, appear on track, but the annual rate of population growth remains high, currently 2.5%, because fertility is high. Furthermore, large numbers of young people are now entering their child-bearing years. Although most trends seem encouraging, especially compared with other countries in sub-Saharan Africa, significant population growth is expected in Rwanda, from 12 to 16 million people by 2030, and to 22 million people by mid-century, even with assumed reductions of fertility.
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DHS Working Papers No. 105 - Rwanda has developed and implemented many strategies at the national level to reduce the incidence of HIV in the general population. One of the main objectives of such interventions is to improve the general level of knowledge of HIV, with the hypothesis that increasing... HIV knowledge will reduce risky sexual behavior. However, there has been a concern that HIV knowledge may not necessarily reduce risky sexual behavior. Only a limited number of population-based studies describe the results of these interventions in terms of how HIV knowledge affects risky sexual behavior. Therefore, the aim of this paper is to fill in this gap, by exploring HIV knowledge and its effect on risky sexual behavior among men in Rwanda.
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DHS Further Analysis Reports No. 111
This study is a theory-driven analysis of the socio-demographic determinants of maternal care seeking in Kenya. Specifically, it examines predisposing, enabling, and need factors potentially associated with use of antenatal care (ANC), health facility delive...ry, and timely postnatal care (PNC).
This study uses data from the 2014 Kenya Demographic and Health Survey (KDHS) conducted among women age 15-49 with a live birth in the five years preceding the survey. It includes data from all 47 counties of Kenya, grouped contiguously into 12 regions. We apply Andersen’s Behavioral Model of Health Services Use to examine socio-demographic predictors of health service use. We estimate logistic regression models for adequate use of ANC (defined as attending at least four ANC visits, starting in the first three months of pregnancy), delivery in a health facility, and PNC within 48 hours of delivery.
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DHS Further Analysis Reports No. 108 - This report examines levels, trends, and inequalities in maternal health in Rwanda from 2010 to 2014-15 among women age 15-49 with a recent birth. The analysis uses Demographic and Health Survey (DHS) data for 15 key indicators of maternal health: 6 for antenat...al care, 3 for delivery, 1 for postnatal care, and 5 for barriers to accessing medical care. Levels and trends in these indicators were analyzed overall and by three background characteristics: women’s education, household wealth quintile, and region.
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DHS Methodological Report No. 20
This study used Service Provision Assessment (SPA) and Demographic and Health Survey (DHS) data from Haiti, Malawi, and Tanzania to compare traditionally used additive methods with a data reduction method—principal component analysis (PCA).
We scored ...the quality of health facilities with three approaches (simple additive, weighted additive, and PCA) for two constructs: quality of services, with only facilities-level data, and quality of care, which incorporates observation and client data. We ranked facilities as high, medium, or low quality based on their scores. Our results indicated that the rankings change with the scoring methodology. There was more consistency in the rankings of facilities by the simple additive and PCA methods than the weighted additive and PCA-based rankings. This may be due to the low factor loadings and little variance explained by the first component in the PCA. We aggregated facility scores to their respective DHS clusters (Haiti, Malawi) or regions (Tanzania) and geographically linked them to women interviewed in DHS surveys to test associations between the use of family planning services and the quality environment, as measured with each index.
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