Silveira Jonas Augusto C, Colugnati Fernando Antônio B, Poblacion Ana Paula, Taddei José Augusto A C
Department of Pediatrics, Universidade Federal de São Paulo (UNIFESP), São Paulo, SP, Brazil.
Núcleo Interdisciplinar de Estudos e Pesquisas em Nefrologia (NIEPEN), Nephrology Division, Universidade Federal de Juiz de Fora (UFJF), Juiz de Fora, MG, Brazil.
J Pediatr (Rio J). 2015 May-Jun;91(3):284-91. doi: 10.1016/j.jped.2014.08.013. Epub 2015 Feb 13.
To examine the associations between socioeconomic and biological factors and infant weight gain.
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).
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.
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.
研究社会经济因素与生物学因素和婴儿体重增加之间的关联。
从巴西最近一次具有复杂概率抽样的全国代表性调查(2006/07年)中选取所有有出生和产后体重数据的婴儿(0至23个月龄,n = 1763)。结果变量是条件体重增加(CWG),它表示个体相对于其出生体重预期体重增加的偏离程度。考虑到调查抽样设计,使用简单和分层多元线性回归估计关联,并以CWG的标准差及其各自95%的置信区间呈现。分层模型是根据联合国儿童基金会营养不良概念框架(基本、根本和直接原因)设计的。
在基本原因模型中,巴西最贫困地区(-0.14[-0.25;-0.04])和农村地区(-0.14[-0.26;-0.02])与CWG呈负相关。然而,在调整了母亲和家庭特征后,这种关联消失了。在最终的分层模型中,较低的经济地位(-0.09[-0.15;-0.03])、人力资本结果(母亲教育程度低于四年级(-