Heterogeneous effect of gestational weight gain on birth weight quantile regression analysis from a population-based screening /

PURPOSE: Classical regression models might give an incomplete picture of the associations between predictors and outcomes. We investigated associations between gestational weight gain (GWG) and birth weight along the entire birth weight distribution with quantile regression and estimated effects of...

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Main Authors: Hulmán Ádám
Witte Daniel R.
Kerényi Zsuzsa
Madarász Eszter
Tänczer Tímea
Bosnyák Zsolt
Szabó Eszter
Ferencz Viktória
Péterfalvi Andrea
Tabák Ádám
Nyári Tibor András
Format: Article
Published: 2015
Series:ANNALS OF EPIDEMIOLOGY 25 No. 2
doi:10.1016/j.annepidem.2014.11.001

mtmt:2945296
Online Access:http://publicatio.bibl.u-szeged.hu/9828
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100 1 |a Hulmán Ádám 
245 1 0 |a Heterogeneous effect of gestational weight gain on birth weight  |h [elektronikus dokumentum] :  |b quantile regression analysis from a population-based screening /  |c  Hulmán Ádám 
260 |c 2015 
300 |a 133-137 
490 0 |a ANNALS OF EPIDEMIOLOGY  |v 25 No. 2 
520 3 |a PURPOSE: Classical regression models might give an incomplete picture of the associations between predictors and outcomes. We investigated associations between gestational weight gain (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 diabetes 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 macrosomia (-1.8%) than that of low birth weight (+0.4%). In contrast, a 3-kg decrease in GWG among overweight and obese women would lower macrosomia 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. 
700 0 1 |a Witte Daniel R.  |e aut 
700 0 1 |a Kerényi Zsuzsa  |e aut 
700 0 1 |a Madarász Eszter  |e aut 
700 0 1 |a Tänczer Tímea  |e aut 
700 0 1 |a Bosnyák Zsolt  |e aut 
700 0 1 |a Szabó Eszter  |e aut 
700 0 1 |a Ferencz Viktória  |e aut 
700 0 1 |a Péterfalvi Andrea  |e aut 
700 0 1 |a Tabák Ádám  |e aut 
700 0 1 |a Nyári Tibor András  |e aut 
856 4 0 |u http://publicatio.bibl.u-szeged.hu/9828/1/005_HA_1_s2.0_S1047279714004797_main_u.pdf  |z Dokumentum-elérés