2015
DOI: 10.1371/journal.pone.0122534
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Does Breastfeeding Help to Reduce the Risk of Childhood Overweight and Obesity? A Propensity Score Analysis of Data from the KiGGS Study

Abstract: BackgroundCurrent studies suggest that the beneficial effect of breastfeeding on overweight and obesity may have been largely overestimated. We examined the relationship between >4 months of full breastfeeding and overweight/obesity in children living in Germany.MethodsWe analyzed retrospectively collected data on breastfeeding from children aged 3–17 years who participated in the German Health Interview and Examination Survey for Children and Adolescents (KiGGS baseline study) between 2003 and 2006 (n = 13163… Show more

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Cited by 31 publications
(28 citation statements)
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“…With only cross-sectional data available, propensity score matching (PSM) methods were used to model the impact of improved dairy cow adoption on child nutrition outcomes and on hypothesized intermediary pathways. A few recent studies have used PSM to draw causal effects to child nutrition and health outcomes [ 25 , 30 , 31 ]. For this study, it was posited that despite initial investment costs for dairy cow systems, households that adopt improved dairy cows may increase milk yields, which in turn ensures increased on-farm per capita milk availability and intakes.…”
Section: Methodsmentioning
confidence: 99%
“…With only cross-sectional data available, propensity score matching (PSM) methods were used to model the impact of improved dairy cow adoption on child nutrition outcomes and on hypothesized intermediary pathways. A few recent studies have used PSM to draw causal effects to child nutrition and health outcomes [ 25 , 30 , 31 ]. For this study, it was posited that despite initial investment costs for dairy cow systems, households that adopt improved dairy cows may increase milk yields, which in turn ensures increased on-farm per capita milk availability and intakes.…”
Section: Methodsmentioning
confidence: 99%
“…For this study, the combined use of PSM and multivariable logistic regression have the following advantages over ordinary logistic regression. Firstly, PSM minimizes the potential effect of selection bias due to self-selection of mothers who may have breastfed their babies [52,53]. Secondly, PSM helps to account for the systematic differences in background characteristics between infants and young children who were appropriately fed and those who were inappropriately fed [43,54].…”
Section: Analytical Strategymentioning
confidence: 99%
“…It deals with selection on observable characteristics, does not extrapolate to unobservable parts of the data and avoids imposing a functional form on the relationship between breastfeeding and BMI. Other studies have previously used propensity score (PS) approaches, 11 , 30 , 31 including a generalized PS approach 11 and inverse probability of treatment weights, 30 but both of these approaches impose a functional form which is not required when using PSM. Grube et al .…”
Section: Introductionmentioning
confidence: 99%