OBJECTIVE: To analyze the nutritional situation of children under five years old from both urban and rural areas of Colombia. METHOD: Analytical study, based on cross-sectional data, collected from ENSIN-2015. The sample consisted of 12,256 children aged between 0 and 4 years old. We calculated the prevalence ratios (PR) with their respective 95% confidence interval (95%CI). PR were assessed by binomial regression models with malnutrition or overweight as the dependent variable and geographic area as the explanatory variable. We used context variables to adjust the estimated PR and control the confounder within. RESULTS: Acute malnutrition (weight-for-height) had a prevalence of 1.6%, while overweight had a 5.6% rate. No differences per geographic zone in the weight-for-height indicator were found. Stunted growth – chronic malnutrition – was higher in the rural area (PR = 1.2; 95%CI 1–1.53; p = 0.050). Prevalences adjusted by variables related to structural, social and economic developement showed that both the household chief’s educational level and the food insecurity of the area account for malnutrition. CONCLUSION: The height-for-age indicator works better to establish development level. Measures against coverage, relevance and quality of education and access to food can harm the nutritional status of the children.
An explicit representation of phase-type distributions as an infinite mixture of Erlang distributions is introduced. The representation unveils a novel and useful connection between a class of Bayesian nonparametric mixture models and phase-type distributions. In particular, this sheds some light on two hot topics, estimation techniques for phase-type distributions, and the availability of closed-form expressions for some functionals related to Dirichlet process mixture models. The power of this connection is illustrated via a posterior inference algorithm to estimate phase-type distributions, avoiding some difficulties with the simulation of latent Markov jump processes, commonly encountered in phase-type Bayesian inference. On the other hand, closed-form expressions for functionals of Dirichlet process mixture models are illustrated with density and renewal function estimation, related to the optimal salmon weight distribution of an aquaculture study.
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