PURPOSE: Classical regression models might give an incomplete picture of the associations between predictors and outcomes. We investigated associations between gestational @entity1017 (GWG) and birth weight along the entire birth weight distribution with quantile regression and estimated effects of hypothetical prevention strategies. METHODS: The GWG-birth weight association was analyzed using quantile and classical regression models on data from a population-based gestational @entity6 screening (n  =  4760) at the Szent Imre Teaching Hospital in Budapest, Hungary (2002-2005). Birth weight distributions were modeled based on hypothetical GWG changes. RESULTS: At a body mass index of 20  kg/m(2), a 1-kg difference in GWG was associated with a 14.2  g (95% confidence interval, 10.0-20.9) higher birth weight at the fifth percentile of the birth weight distribution and a 29.0  g (21.3-35.6) higher birth weight at the 95th percentile. The coefficient from linear regression was 20.7 (17.5-24.0). Estimates differed modestly between the two regressions at a body mass index of 30  kg/m(2). A population-wide 2-kg decrease in GWG would rather affect the risk of @entity8455 (-1.8%) than that of low birth weight (+0.4%). In contrast, a 3-kg decrease in GWG among overweight and @entity28 @entity1 would lower @entity8455 more modestly (-0.8%). CONCLUSIONS: A population-wide lowering of GWG would lead to greater improvements in the right tail of the birth weight distribution.

Heterogeneous effect of gestational XXXX on birth weight: quantile regression analysis from a population-based screening.

@entity1 :: ('9606', 'Species') :: ['women'] @entity28 :: ('MESH:D009765', 'Disease') :: ['obese'] @entity6 :: ('MESH:D003920', 'Disease') :: ['diabetes'] @entity1017 :: ('MESH:D015430', 'Disease') :: ['weight gain'] @entity8455 :: ('MESH:D005320', 'Disease') :: ['macrosomia']
@entity1017 :: (MESH:D015430,Disease) :: ['weight gain']
