Association between socioeconomic and biological factors and infant weight gain: Brazilian Demographic and Health Survey - PNDS-2006/07

• Autor(a) principal: Silveira,Jonas Augusto C.
• Data de Publicação: 2015
• Outros Autores: Colugnati,Fernando Antônio B., Poblacion,Ana Paula, Taddei,José Augusto A.C.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Jornal de Pediatria (Online)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0021-75572015000300284
• topic: Child; Weight gain; Nutritional disorders; Surveys; Brazil

OBJECTIVE: To examine the associations between socioeconomic and biological factors and infant weight gain. METHODS: All infants (0-23 months of age) with available birth and postnatal weight data (n = 1763) were selected from the last nationally representative survey with complex probability sampling conducted in Brazil (2006/07). The outcome variable was conditional weight gain (CWG), which represents how much an individual has deviated from his/her expected weight gain, given the birth weight. Associations were estimated using simple and hierarchical multiple linear regression, considering the survey sampling design, and presented in standard deviations of CWG with their respective 95% of confidence intervals. Hierarchical models were designed considering the UNICEF Conceptual Framework for Malnutrition (basic, underlying and immediate causes). RESULTS: The poorest Brazilian regions (-0.14 [-0.25; -0.04]) and rural areas (-0.14 [-0.26;-0.02]) were inversely associated with CWG in the basic causes model. However, this association disappeared after adjusting for maternal and household characteristics. In the final hierarchical model, lower economic status (-0.09 [-0.15; -0.03]), human capital outcomes (maternal education < 4th grade (-0.14[-0.29; 0.01]), higher maternal height (0.02[0.01; 0.03])), and fever in the past 2 weeks (-0.13[-0.26; -0.01]) were associated with postnatal weight gain. CONCLUSION: The results showed that poverty and lower human capital are still key factors associated with poor postnatal weight gain. The approach used in these analyses was sensitive to characterize inequalities among different socioeconomic contexts and to identify factors associated with CWG in different levels of determination.