Your search found 5 Results
Eastern Africa Social Science Research Review. 2005 Jun; 21(2):1-17.The objective of this study is to understand determinants of mortality rates of children under the age of five years in developing countries. The study uses secondary data to investigate the relationship between under-five mortality rates and such socioeconomic variables as fertility, literacy, immunization, access to clean drinking water, HIV/AIDS prevalence, and human and material resources using linear regression analysis. Results show that while most of these variables have a significant relationship with under-five mortality rate, the proportion of doctors for every 100,000 population, and health expenditure per capita have an insignificant predictive value. Conclusion: Reducing child mortality rates requires multiple intervention strategies, such as access to safe drinking water, improvement in education opportunities, family planning, and tackling HIV/AIDS. (author's)
International Journal of Epidemiology. 2004; 33(6):1260-1270.Child malnutrition is an important indicator for monitoring progress towards the Millennium Development Goals (MDG). This paper describes the methodology developed by the World Health Organization (WHO) to derive global and regional trends of child stunting and underweight, and reports trends in prevalence and numbers affected for 1990–2005. National prevalence data from 139 countries were extracted from the WHO Global Database on Child Growth and Malnutrition. A total of 419 and 388 survey data points were available for underweight and stunting, respectively. To estimate trends we used linear mixed-effect models allowing for random effects at country level and for heterogeneous covariance structures. One model was fitted for each United Nation’s region using the logit transform of the prevalence and results back-transformed to the original scale. Best models were selected based on explicit statistical and graphical criteria. During 1990–2000 global stunting and underweight prevalences declined from 34% to 27% and 27% to 22%, respectively. Large declines were achieved in Eastern and South-eastern Asia, while South-central Asia continued to suffer very high levels of malnutrition. Substantial improvements were also made in Latin America and the Caribbean, whereas in Africa numbers of stunted and underweight children increased from 40 to 45, and 25 to 31 million, respectively. Linear mixed-effect models made best use of all available information. Trends are uneven across regions, with some showing a need for more concerted and efficient interventions to meet the MDG of reducing levels of child malnutrition by half between 1990 and 2015. (author's)
Prediction of community prevalence of human onchocerciasis in the Amazonian onchocerciasis focus: Bayesian approach. [Prévisions portant sur la prévalence communautaire de l'onchocercose humaine au niveau du foyer amazonien de l'onchocercose : approche bayésienne]
Bulletin of the World Health Organization. 2003 Jul; 81(7):482-490.Objective: To develop a Bayesian hierarchical model for human onchocerciasis with which to explore the factors that influence prevalence of microfilariae in the Amazonian focus of onchocerciasis and predict the probability of any community being at least mesoendemic (>20% prevalence of microfilariae), and thus in need of priority ivermectin treatment. Methods: Models were developed with data from 732 individuals aged515 years who lived in 29 Yanomami communities along four rivers of the south Venezuelan Orinoco basin. The models’ abilities to predict prevalences of microfilariae in communities were compared. The deviance information criterion, Bayesian P-values, and residual values were used to select the best model with an approximate cross-validation procedure. Findings: A three-level model that acknowledged clustering of infection within communities performed best, with host age and sex included at the individual level, a river-dependent altitude effect at the community level, and additional clustering of communities along rivers. This model correctly classified 25/29 (86%) villages with respect to their need for priority ivermectin treatment. Conclusion: Bayesian methods are a flexible and useful approach for public health research and control planning. Our model acknowledges the clustering of infection within communities, allows investigation of links between individual- or community-specific characteristics and infection, incorporates additional uncertainty due to missing covariate data, and informs policy decisions by predicting the probability that a new community is at least mesoendemic. (author's)
Lancet. 2003 Jul 19; 362(9379):198-204.Background: Antibiotics are an important part of WHO’s strategy to eliminate trachoma as a blinding disease by 2020. At present, who needs to be treated is unclear. We aimed to establish the burden of ocular Chlamydia trachomatis in three trachomaendemic communities in Tanzania and The Gambia with real-time quantitative PCR. Methods: Conjunctival swabs were obtained at examination from 3146 individuals. Swabs were first tested by the qualitative Amplicor PCR, which is known to be highly sensitive. In positive samples, the number of copies of omp1 (a single-copy C trachomatis gene) was measured by quantitative PCR. Findings: Children had the highest ocular loads of C trachomatis, although the amount of pooling in young age groups was less striking at the site with the lowest trachoma frequency. Individuals with intense inflammatory trachoma had higher loads than did those with other conjunctival signs. At the site with the highest prevalence of trachoma, 48 of 93 (52%) individuals with conjunctival scarring but no sign of active disease were positive for ocular chlamydiae. Interpretation: Children younger than 10 years old, and those with intense inflammatory trachoma, probably represent the major source of ocular C trachomatis infection in endemic communities. Success of antibiotic distribution programmes could depend on these groups receiving effective treatment. (author's)
In: International Population Conference / Congres International de la Population, Montreal 1993, 24 August - 1st September. Volume 3, [compiled by] International Union for the Scientific Study of Population [IUSSP]. Liege, Belgium, IUSSP, 1993. 269-78.Modeling life table functions by statistical methods, begun at the Population Branch of the UN in the early 1950s, resulted in the publication of a set of model life tables. From 158 life tables for various countries and periods, the UN analysts noted that the probability of dying in a certain age interval provides excellent approximation when the parameters defining the polynomial are obtained by the method of least squares. Factor analysis of probabilities of dying from a set of 154 abridged life tables was found to produce 5 factors in an earlier study by Ledermann and Breas. In this study of 120 life tables each for males and females, a principal component analysis produced only 2 factors with eigenvalues greater than 1. Together these 2 factors explained 97 and 98%, respectively, of the male and the female variance. The 1st factor loadings were found to be inversely related to age, while the opposite was the case with the 2nd set. They could reproduce life expectancy with a high degree of accuracy, the squared multiple correlations being .98 for male and .97 for female life tables. In conjunction with suitable pairs of factor scores, model life tables can be constructed. The method is also suitable for the determination of factor scores of any life table which are indicators of the states of mortality at younger and older ages. Combinations of these factor scores can also generate sets of life tables with identical life expectancies. In replicating the analysis of Ledermann and Breas with these data, 4 factors with a 5th bordering on significance together explained only 91% of the variance compared with the 97% and 98% found by the current study. The 2 dimensions of life tables represented by the 2 factors provide an interesting comparison with their counterparts, namely region and life expectancy. A comparison of this model with the Brass relational logit model revealed it was similar to a special case of this model derived by retaining only the 1st factor. The 2-factor model should produce better results.