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Maternal and Child Health in Nepal: The Effects of Caste, Ethnicity, and Regional Identity
Pandey, J. P., M.R. Dhakal, S. Karki, P. Poudel, and M.S. Pradhan
Nepal Ministry of Health and Population, New ERA, and ICF International
(2013)
C2
Further analysis of the 2011 Nepal Demographic and Health Survey
DHS Further Analysis Reports No. 101
DHS Analytical Studies No. 55.
DHS Working Papers No. 88
education, wealth, mobility, employment, and media exposure
DHS Working Papers No. 85
A community-based approach.
These guidelines focus on manmade rather than natural disasters, but our experiences in India, El Salvador and Pakistan (earthquake interventions), and following the 2004 tsunami, cyclone Nargis in 2008 and the Haiti earthquake in 2010, showed that the principles describ
...
ed also work well in contexts of natural disasters.
more
Formation en Premiers Secours Psychologiques aux enfants : 2 jours
Gestion du stress du personnel : 1 journée
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.
more
This report investigates the impact of potential misclassification of samples on HIV prevalence estimates for 23 surveys conducted from 2010-2014. In addition to visual inspection of laboratory results, we examined how accounting for potential misclassification of HIV status through Bayesian latent
...
class models affected the prevalence estimates. Two types of Bayesian models were specified: a model that only uses the individual dichotomous test results and a continuous model that uses the quantitative information of the EIA (i.e., the signal-to-cutoff values). Overall, we found that adjusted prevalence estimates matched the surveys’ original results, with overlapping uncertainty intervals. This suggested that misclassification of HIV status should not affect the prevalence estimates in most surveys. However, our analyses suggested that two surveys may be problematic. The prevalence could have been overestimated in the Uganda AIDS Indicator Survey 2011 and the Zambia Demographic and Health Survey 2013-14, although the magnitude of overestimation remains difficult to ascertain. Interpreting results from the Uganda survey is difficult because of the lack of internal quality control and potential violation of the multivariate normality assumption of the continuous Bayesian latent class model. In conclusion, despite the limitations of our latent class models, our analyses suggest that prevalence estimates from most of the surveys reviewed are not affected by sample misclassification.
more
The National Institute of statistics of Rwanda (NISR) in collaboration with the worldwide Demographic and Health Surveys Program implemented the 2014-15 Rwanda Demographic and Health Survey (RDHS) to collect data for monitoring progress on health programs and policies in Rwanda. This publication ill
...
ustrates the profile of Kigali City
more
The National Institute of statistics of Rwanda (NISR) in collaboration with the worldwide Demographic and Health Surveys Program implemented the 2014-15 Rwanda Demographic and Health Survey (RDHS) to collect data for monitoring progress on health programs and policies in Rwanda. This publication ill
...
ustrates the profile of Eastern Province.
more
he National Institute of statistics of Rwanda (NISR) in collaboration with the worldwide Demographic and Health Surveys Program implemented the 2014-15 Rwanda Demographic and Health Survey (RDHS) to collect data for monitoring progress on health programs and policies in Rwanda. This publication illu
...
strates the profile of Northern Province.
more
The National Institute of statistics of Rwanda (NISR) in collaboration with the worldwide Demographic and Health Surveys Program implemented the 2014-15 Rwanda Demographic and Health Survey (RDHS) to collect data for monitoring progress on health programs and policies in Rwanda. This publication ill
...
ustrates the profile of Southern province
more
This report provides an update on the level of poverty based on 2013/14 Integrated Household Living Conditions Survey (EICV4) focusing on poverty as measured in consumption terms. The report also highlights other trend dimensions of living conditions captured in other surveys that complement and pro
...
vide a holistic understanding of poverty and living conditions.
Rwanda’s economy has been growing steadily at about 8% since 2001 with GDP per capita more than tripling from US$ 211 in 2001 to US$ 718 in 2014. Food crop production growth was more than twice that of population growth between 2007 and 2014.
more
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. more
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. more
