Heterogeneous effect of gestational weight gain on birth weight

Quantile regression analysis from a population-based screening

Adam Hulmán, Daniel R. Witte, Z. Kerényi, Eszter Madarász, Tímea Tänczer, Zsolt Bosnyák, Eszter Szabó, Viktória Ferencz, Andrea Péterfalvi, A. Tabák, T. Nyári

Research output: Article

2 Citations (Scopus)

Abstract

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 20kg/m2, a 1-kg difference in GWG was associated with a 14.2g (95% confidence interval, 10.0-20.9) higher birth weight at the fifth percentile of the birth weight distribution and a 29.0g (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 30kg/m2. 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.

Original languageEnglish
Pages (from-to)133-137
Number of pages5
JournalAnnals of Epidemiology
Volume25
Issue number2
DOIs
Publication statusPublished - febr. 1 2015

Fingerprint

Birth Weight
Weight Gain
Regression Analysis
Population
Body Mass Index
Gestational Diabetes
Hungary
Low Birth Weight Infant
Teaching Hospitals
Linear Models
Confidence Intervals

ASJC Scopus subject areas

  • Epidemiology
  • Medicine(all)

Cite this

Heterogeneous effect of gestational weight gain on birth weight : Quantile regression analysis from a population-based screening. / Hulmán, Adam; Witte, Daniel R.; Kerényi, Z.; Madarász, Eszter; Tänczer, Tímea; Bosnyák, Zsolt; Szabó, Eszter; Ferencz, Viktória; Péterfalvi, Andrea; Tabák, A.; Nyári, T.

In: Annals of Epidemiology, Vol. 25, No. 2, 01.02.2015, p. 133-137.

Research output: Article

Hulmán, Adam ; Witte, Daniel R. ; Kerényi, Z. ; Madarász, Eszter ; Tänczer, Tímea ; Bosnyák, Zsolt ; Szabó, Eszter ; Ferencz, Viktória ; Péterfalvi, Andrea ; Tabák, A. ; Nyári, T. / Heterogeneous effect of gestational weight gain on birth weight : Quantile regression analysis from a population-based screening. In: Annals of Epidemiology. 2015 ; Vol. 25, No. 2. pp. 133-137.
@article{a53b1e6253ce485091e4491f76a7d046,
title = "Heterogeneous effect of gestational weight gain on birth weight: Quantile regression analysis from a population-based screening",
abstract = "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 20kg/m2, a 1-kg difference in GWG was associated with a 14.2g (95{\%} confidence interval, 10.0-20.9) higher birth weight at the fifth percentile of the birth weight distribution and a 29.0g (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 30kg/m2. 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.",
keywords = "Birth weight, Body mass index, Prevention, Quantile regression, Weight gain",
author = "Adam Hulm{\'a}n and Witte, {Daniel R.} and Z. Ker{\'e}nyi and Eszter Madar{\'a}sz and T{\'i}mea T{\"a}nczer and Zsolt Bosny{\'a}k and Eszter Szab{\'o} and Vikt{\'o}ria Ferencz and Andrea P{\'e}terfalvi and A. Tab{\'a}k and T. Ny{\'a}ri",
year = "2015",
month = "2",
day = "1",
doi = "10.1016/j.annepidem.2014.11.001",
language = "English",
volume = "25",
pages = "133--137",
journal = "Annals of Epidemiology",
issn = "1047-2797",
publisher = "Elsevier Inc.",
number = "2",

}

TY - JOUR

T1 - Heterogeneous effect of gestational weight gain on birth weight

T2 - Quantile regression analysis from a population-based screening

AU - Hulmán, Adam

AU - Witte, Daniel R.

AU - Kerényi, Z.

AU - Madarász, Eszter

AU - Tänczer, Tímea

AU - Bosnyák, Zsolt

AU - Szabó, Eszter

AU - Ferencz, Viktória

AU - Péterfalvi, Andrea

AU - Tabák, A.

AU - Nyári, T.

PY - 2015/2/1

Y1 - 2015/2/1

N2 - 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 20kg/m2, a 1-kg difference in GWG was associated with a 14.2g (95% confidence interval, 10.0-20.9) higher birth weight at the fifth percentile of the birth weight distribution and a 29.0g (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 30kg/m2. 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.

AB - 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 20kg/m2, a 1-kg difference in GWG was associated with a 14.2g (95% confidence interval, 10.0-20.9) higher birth weight at the fifth percentile of the birth weight distribution and a 29.0g (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 30kg/m2. 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.

KW - Birth weight

KW - Body mass index

KW - Prevention

KW - Quantile regression

KW - Weight gain

UR - http://www.scopus.com/inward/record.url?scp=84924540226&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84924540226&partnerID=8YFLogxK

U2 - 10.1016/j.annepidem.2014.11.001

DO - 10.1016/j.annepidem.2014.11.001

M3 - Article

VL - 25

SP - 133

EP - 137

JO - Annals of Epidemiology

JF - Annals of Epidemiology

SN - 1047-2797

IS - 2

ER -