21
views
0
recommends
+1 Recommend
2 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Risk factors for low birth weight in Rio Grande do Sul State, Brazil: classical and multilevel analysis Translated title: Fatores de risco para baixo peso ao nascer no Estado do Rio Grande do Sul, Brasil: análise clássica e multinível

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The objective of this study was to identify risk factors for low birth weight in singleton live born infants in Rio Grande do Sul State, Brazil, in 2003, based on data from the Information System on Live Births. The study used both classical multivariate and multilevel logistic regression. Risk factors were evaluated at two levels: individual (live births) and contextual (micro-regions). At the individual level the two models showed a significant association between low birth weight and prematurity, number of prenatal visits, congenital anomalies, place of delivery, parity, sex, maternal age, maternal occupation, marital status, schooling, and type of delivery. In the multilevel models, the greater the urbanization of the micro-region, the higher the risk of low birth weight, while in less urbanized micro-regions, single mothers had an increased risk of low birth considering all live births. Low birth weight varied according to micro-region and was associated with individual and contextual characteristics. Although most of the variation in low birth weight occurred at the individual level, the multilevel model identified an important risk factor in the contextual level.

          Translated abstract

          O objetivo deste estudo foi identificar os fatores de risco para o baixo peso ao nascer de nascidos vivos de gestação simples no Rio Grande do Sul, Brasil, em 2003, obtidos do Sistema de Informações sobre Nascidos Vivos. Foram utilizadas regressão logística múltipla clássica e multinível. Os fatores de risco foram avaliados no nível individual (nascidos vivos) e contextual (microrregiões). No nível individual dos dois modelos foi encontrada associação significativa entre baixo peso ao nascer e prematuridade, consultas pré-natais, anomalia congênita, local do nascimento, paridade, sexo, idade materna, ocupação materna, estado civil, escolaridade e tipo de parto. Nos modelos multiníveis, quanto maior a urbanização da microrregião maior o risco de baixo peso ao nascer, e, em microrregiões menos urbanizadas, mães solteiras têm risco aumentado, para todos os nascidos vivos. O baixo peso ao nascer varia com a microrregião e está associado a características individuais e contextuais. Embora a maior parte da variação no baixo peso ao nascer se encontre no nível individual, o modelo multinível identificou um fator de risco importante no nível contextual.

          Related collections

          Most cited references 49

          • Record: found
          • Abstract: found
          • Article: not found

          Bringing context back into epidemiology: variables and fallacies in multilevel analysis.

           A Diez-Roux (1998)
          A large portion of current epidemiologic research is based on methodologic individualism: the notion that the distribution of health and disease in populations can be explained exclusively in terms of the characteristics of individuals. The present paper discusses the need to include group- or macro-level variables in epidemiologic studies, thus incorporating multiple levels of determination in the study of health outcomes. These types of analyses, which have been called contextual or multi-level analyses, challenge epidemiologists to develop theoretical models of disease causation that extend across levels and explain how group-level and individual-level variables interact in shaping health and disease. They also raise a series of methodological issues, including the need to select the appropriate contextual unit and contextual variables, to correctly specify the individual-level model, and, in some cases, to account for residual correlation between individuals within contexts. Despite its complexities, multilevel analysis holds potential for reemphasizing the role of macro-level variables in shaping health and disease in populations.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Multilevel statistical models

              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Neighborhood mechanisms and the spatial dynamics of birth weight.

              This study addresses two questions about why neighborhood contexts matter for individuals via a multilevel, spatial analysis of birthweight for 101,662 live births within 342 Chicago neighborhoods. First, what are the mechanisms through which neighborhood structural composition is related to health? The results show that mechanisms related to stress and adaptation (violent crime, reciprocal exchange and participation in local voluntary associations) are the most robust neighborhood-level predictors of birth weight. Second, are contextual influences on health limited to the immediate neighborhood or do they extend to a wider geographic context? The results show that contextual effects on birth weight extend to the social environment beyond the immediate neighborhood, even after adjusting for potentially confounding covariates. These findings suggest that the theoretical understanding and empirical estimation of 'neighborhood effects' on health are bolstered by collecting data on more causally proximate social processes and by taking into account spatial interdependencies among neighborhoods.
                Bookmark

                Author and article information

                Journal
                csp
                Cadernos de Saúde Pública
                Cad. Saúde Pública
                Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz (Rio de Janeiro, RJ, Brazil )
                0102-311X
                1678-4464
                December 2012
                : 28
                : 12
                : 2293-2305
                Affiliations
                Santa Maria Rio Grande do Sul orgnameUniversidade Federal de Santa Maria Brazil
                Porto Alegre Rio Grande do Sul orgnameUniversidade Federal do Rio Grande do Sul Brazil
                Article
                S0102-311X2012001400008 S0102-311X(12)02801208
                10.1590/S0102-311X2012001400008

                This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 32, Pages: 13
                Product
                Product Information: website
                Categories
                Article

                Comments

                Comment on this article