Estimating double burden of malnutrition among rural and urban children in Amazonia using Bayesian latent models.

ABSTRACT:

Background

The double burden of malnutrition (DBM) in the same individual is a neglected public health concern, especially in low- and middle-income countries (LMICs). The DBM is associated with increased risks of non-communicable diseases, childbirth complications, and healthcare costs related to obesity in adulthood. However, evaluating low prevalence outcomes in relatively small populations is challenging using conventional frequentist statistics. Our study used Bayesian latent models to estimate DBM prevalence at the individual-level in small populations located in remote towns and rural communities in the Brazilian Amazon.

Methods

We employed a cross-sectional survey of urban and rural children aged 6-59 months, considering DBM as the coexistence of stunting and overwei

SUBMITTER: Orellana JDY 

PROVIDER: S-EPMC11937108 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature