Socioeconomic context of the community and chronic child malnutrition in Colombia.

Rev Saude Publica

Pontificia Universidad Javeriana Seccional Cali. Departamento de Economia. Cali, Colombia.

Published: July 2018

Objective: To analyze the influence of the socioeconomic context of the community on chronic child malnutrition in Colombia.

Methods: We estimated multilevel logistic models using data from the National Demographic and Health Survey in Colombia in 2010. The final sample included 11,448 children under the age of five gathered in 3,528 communities. In addition, we used the Principal Component Analysis with polychoric correlations for the construction of composed indicators of wealth, autonomy of the woman, and the use and access to the health system.

Results: The average level of community wealth was significantly and independently associated with chronic malnutrition in early childhood, more than the socioeconomic status of the household itself. At the individual and household level, the probability of chronic malnutrition was higher for children from mothers with low levels of autonomy and use and access to the health system, mothers who had their first child in adolescence, and mothers who live in homes in the lowest wealth quintiles. In contrast, children from mothers with a body mass index > 25 and with at least secondary education (versus no education) were less likely to suffer from chronic malnutrition.

Conclusions: Research, programs, and interventions need to take into account the physical, economic, and social context of communities to contribute with the improvement of the nutritional status of early childhood in Colombia.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6063712PMC
http://dx.doi.org/10.11606/S1518-8787.2018052000394DOI Listing

Publication Analysis

Top Keywords

socioeconomic context
8
context community
8
community chronic
8
chronic child
8
child malnutrition
8
access health
8
chronic malnutrition
8
early childhood
8
children mothers
8
chronic
5

Similar Publications

Factors influencing livestock ownership and herd intensity among smallholder farmers in the Eastern Cape, South Africa.

Heliyon

January 2025

Risk and Vulnerability Science Centre, Faculty of Science and Agriculture, University of Fort Hare, P. Bag X1314, 1 King William's Town Road, Alice, 5700, South Africa.

This study explores the factors influencing smallholder farmers' decisions on livestock ownership and herd size in the context of climate change. A cross-sectional approach was employed, using a multi-stage sampling method to survey 600 smallholder farmers, 495 of whom were engaged in livestock production. Data were collected through a semi-structured questionnaire and analysed using a double hurdle model.

View Article and Find Full Text PDF

To explore the consumption patterns and demand for famous wines exported in Late Antiquity, such as Gaza wine and Cilician wine, several case studies were analyzed: studies involving excavation results from sites where Late Roman amphorae, such as the LRA 1 and LRA 4 types, were found. Several themes emerged from the analysis. First, Gaza jars used for the transportation of Gaza wine seem to be less frequent than LRA 1 amphorae used to transport Cilician wine.

View Article and Find Full Text PDF

Exclusionary bargaining behavior in 14 countries: Prevalence and predictors.

PNAS Nexus

January 2025

Department of Political Science, Aarhus University, Bartholins Allé 7, Aarhus 8000, Central Denmark Region, Denmark.

Primates are known to engage in exclusionary behavior, forming alliances to block a minority from accessing scarce resources. Humans are no exception, and examples of exclusionary behavior abound in political, business, and social settings. However, despite its socio-economic relevance, little is known about the prevalence and determinants of such behavior worldwide.

View Article and Find Full Text PDF

A Bayesian Network model to integrate blue-green and gray infrastructure systems for different urban conditions.

J Environ Manage

January 2025

College of Interdisciplinary Studies, Zayed University, Dubai, United Arab Emirates.

In facing growing challenges in cities and the environment, cities need to make informed decisions on where and how to allocate resources for infrastructure investments. Nature-based Solutions present a promising approach to urban environmental and socioeconomic challenges, but their successful integration into urban planning requires a nuanced understanding of both their benefits and limitations. This paper presents a preliminary Bayesian Network model designed to model the optimal integration of specific blue-green and gray Infrastructure solutions in hybrid systems for specific local contexts.

View Article and Find Full Text PDF

Background: In data-sparse areas such as health care, computer scientists aim to leverage as much available information as possible to increase the accuracy of their machine learning models' outputs. As a standard, categorical data, such as patients' gender, socioeconomic status, or skin color, are used to train models in fusion with other data types, such as medical images and text-based medical information. However, the effects of including categorical data features for model training in such data-scarce areas are underexamined, particularly regarding models intended to serve individuals equitably in a diverse population.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!