Predictors of the double burden of malnutrition at the household level in the Brazilian Amazon: a latent class analysis

• Grant number: 23/17875-1
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Effective date (Start): May 15, 2024
• Effective date (End): December 14, 2024
• Field of knowledge: Health Sciences - Nutrition - Nutritional Analysis of Population
• Principal Investigator: Bárbara Hatzlhoffer Lourenço
• Grantee: Caroline Zani Rodrigues
• Supervisor: Hugo Cogo Moreira
• Host Institution: Faculdade de Saúde Pública (FSP). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Research place: Ostfold University College, Norway
• Associated to the scholarship: 22/13550-8 - Intergenerational burden of malnutrition in the Western Brazilian Amazon: trajectories until preschool age and alternative measurement approaches, BP.DR

Abstract

The double burden of malnutrition (DBM) is described as the coexistence of under and overnutrition at the population level; at the household level, considering the mother-child dyad in an intergenerational perspective; or at the individual level. Mainly occurring in low- and medium-income countries, DBM during childhood can lead to health issues throughout life. However, there is a lack of longitudinal evidence that considers empirically derived combinations of anthropometric and biochemical indicators of malnutrition. This project aims to identify latent classes of DBM at the household level up to 2 years of age and investigate its predictors in Cruzeiro do Sul, Acre. This analysis is part of the MINA-Brazil Study, the first birth cohort in the western Amazonian region. At baseline, all admissions for delivery were screened between July 2015 and June 2016 at the only maternity of Cruzeiro do Sul. During the 1 and 2-year follow-ups, participants answered a structured questionnaire about sociodemographic characteristics and about health history and lifestyle, anthropometric data of the children and their mothers were collected, and venous blood samples from children were drawn to analyze anemia, iron deficiency, and vitamins A and D. Maternal anthropometry will be characterized according to BMI, and children's anthropometric indices will be classified according to the WHO growth standards. Latent class analysis will be carried out to identify groups with similar patterns of malnutrition at the household level up to 2 years of age, according to the grouping of maternal and child anthropometric and biochemical variables. Structural equation modeling will be used to identify predictors of the most likely patterns of DBM at the household level. Findings from this project shall support health strategies and interventions to combat different forms of malnutrition during childhood.