Login / Signup

General methodological aspects in the Brazilian National Survey on Child Nutrition (ENANI-2019): a population-based household survey.

Nadya Helena Alves-SantosInês Rugani Ribeiro de CastroLuiz Antonio Dos AnjosElisa Maria de Aquino LacerdaPaula NormandoMaiara Brusco de FreitasDayana Rodrigues FariasElisa Maria de Aquino LacerdaMaurício Teixeira Leite de VasconcellosPedro Luis do Nascimento SilvaGilberto Kac
Published in: Cadernos de saude publica (2021)
This article aims to present general methodological aspects of the Brazilian National Survey on Child Nutrition (ENANI-2019), from the conception of the study design to details of the data collection. This is a household-based population survey with a sample calculated at 15,000 households to identify children under five years of age, conducted in 123 municipalities in Brazil's 26 states and the Federal District. ENANI-2019 includes data on breastfeeding and dietary intake; anthropometric nutritional status of all children and their biological mothers; and nutritional status concerning the following micronutrients: iron (hemoglobin and ferritin), zinc, selenium, and vitamins A, B1, B6, B12, D, E, and folic acid of children from 6 to 59 months of age. A total of 193,212 households were visited, of which 19,951 were eligible, and 12,524 were included in the study. A total of 14,558 children were studied, of whom 13,990 (96.1%) and 13,921 (95.6%) had their body mass and length/stature measured, respectively, and 14,541 (99.9%) underwent 24-hour dietary recalls (24HR). Of the 12,598 children eligible for blood sample collection, 8,739 (69.3%) had at least one laboratory parameter measured. Data were collected from February 2019 to March 2020, when the survey was interrupted due to the COVID-19 pandemic. The evidence produced by the ENANI-2019 survey can back the formulation, follow-up, and/or reorientation of food and nutrition policies such as the promotion of breastfeeding and healthy eating and the prevention and control of different forms of malnutrition.
Keyphrases
  • young adults
  • physical activity
  • cross sectional
  • electronic health record
  • mental health
  • preterm infants
  • big data
  • public health
  • blood pressure
  • risk assessment
  • machine learning
  • south africa
  • deep learning