The report studied child poverty in nine dimensions – development/stunting, nutrition, health, water, sanitation, and housing. Other dimensions included education, health related knowledge, and information and participation.
An estimated 36 million of a total population of 41 million children und...er the age of 18 in Ethiopia are multi-dimensionally poor, meaning they are deprived of basic goods and services in at least three dimensions
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The document will provide information for Ministries of Health and hospital sentinel sites on why and how to determine the denominator of at-risk children <5 years of age and rate of meningitis hospitalizations for a sentinel hospital site conducting IB-VPD surveillance. Such a methodology is curren...tly unavailable and this estimation is critical to enable interpretation of surveillance data, particularly pre- and post- vaccine introduction
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Kulkarni et al. The Journal of Headache and Pain (2015) 16:67 DOI 10.1186/s10194-015-0549-x
PLoS Med 15(7): e1002615. https://doi.org/10.1371/journal. pmed.1002615
The epidemiology of wheeze in children, when assessed by questionnaires, is dependent on parents' understanding of the term “wheeze”.
In a questionnaire survey of a random population sample of 4,236 children aged 6–10 yrs, parents' definition of wheeze was assessed. Predictors of a correct ...definition were determined and the potential impact of incorrect answers on prevalence estimates from the survey was assessed.
Current wheeze was reported by 13.2% of children. Overall, 83.5% of parents correctly identified “whistling or squeaking” as the definition of wheeze; the proportion was higher for parents reporting wheezy children (90.4%). Frequent attacks of reported wheeze (adjusted odds ratio (OR) 3.0), maternal history of asthma (OR 1.5) and maternal education (OR 1.5) were significantly associated with a correct answer, while the converse was found for South Asian ethnicity (OR 0.6), first language not English (OR 0.6) and living in a deprived neighbourhood (OR 0.6).
In summary, the present study showed that misunderstanding could lead to an important bias in assessing the prevalence of wheeze, resulting in an underestimation in children from South Asian and deprived family backgrounds. Prevalence estimates for the most severe categories of wheeze might be less affected by this bias and questionnaire surveys on wheeze should incorporate measures of parents' understanding of the term wheeze.
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Most African Countries Avoid Major Economic Loss but Impact on Guinea, Liberia, Sierra Leone Remains Crippling
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.
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To help adapt cardiovascular disease risk prediction approaches to low-income and middle-income countries, WHO has convened an effort to develop, evaluate, and illustrate revised risk models. Here, we report the derivation, validation, and illustration of the revised WHO cardiovascular disease risk ...prediction charts that have been adapted to the circumstances of 21 global regions.
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Background:Tracking aid fl ows helps to hold donors accountable and to compare the allocation of resources in relation to health need. With the use of data reported by donors in 2015, we provided estimates of offi cial development assistance and grants from the Bill & Melinda Gates Foundation (coll...ectively termed ODA+) to reproductive, maternal, newborn, and child health for 2013 and complete trends in reproductive, maternal, newborn, and child health support for the period 2003–13. Methods: We coded and analysed fi nancial disbursements to reproductive, maternal, newborn, and child health to all recipient countries from all donors reporting to the creditor reporting system database for the year 2013. We also revisited disbursement records for the years 2003–08 and coded disbursements relating to reproductive and sexual health activities resulting in the Countdown dataset for 2003–13. We matched this dataset to the 2015 creditor reporting system dataset and coded any unmatched creditor reporting system records. We analysed trends in ODA+ to reproductive, maternal, newborn, and child health for the period 2003–13, trends in donor contributions, disbursements to recipient countries, and targeting to need.
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