Factors associated with gestational weight gain: a cross-sectional survey

BMC Pregnancy Childbirth. 2018 Dec 3;18(1):465. doi: 10.1186/s12884-018-2112-7.

Abstract

Background: The aim of this study was to describe the dietary patterns in pregnant women and determine the association between diet factors, pre-pregnancy body mass index, socio-demographic characteristics and gestational weight gain.

Methods: The analysis was conducted on a group of 458 women. Cut-off values of gestational weight gain adequacy were based on recommendations published by the US Institute of Medicine and were body mass index-specific. Logistic regression analysis was used to assess the risk of the occurrence of inadequate or excessive gestational weight gain. Dietary patterns were identified by factor analysis.

Results: Three dietary patterns characteristic of pregnant women in Poland were identified: 'unhealthy', 'varied' and 'prudent'. The factor associated with increased risk of inadequate gestational weight gain was being underweight pre-pregnancy (OR = 2.61; p = 0.018). The factor associated with increased risk of excessive weight gain were being overweight or obese pre-pregnancy (OR = 7.00; p = 0.031) and quitting smoking (OR = 7.32; p = 0.019). The risk of excessive weight gain was decreased by being underweight pre-pregnancy (OR = 0.20; p = 0.041), being in the third or subsequent pregnancy compared to being in the first (OR = 0.37; p = 0.018), and having a high adherence to a prudent dietary pattern (OR = 0.47; p = 0.033).

Conclusions: Women who were overweight or obese pre-pregnancy and those who quit smoking at the beginning of pregnancy should be provided with dietary guidance to prevent excessive gestational weight gain.

Keywords: Body mass index; Dietary patterns; Excessive weight gain.

MeSH terms

  • Adolescent
  • Adult
  • Body Mass Index
  • Cross-Sectional Studies
  • Diet / statistics & numerical data*
  • Diet, Healthy
  • Factor Analysis, Statistical
  • Female
  • Gestational Weight Gain*
  • Gravidity
  • Humans
  • Logistic Models
  • Obesity / epidemiology*
  • Odds Ratio
  • Overweight / epidemiology
  • Poland / epidemiology
  • Pregnancy
  • Risk Factors
  • Smoking Cessation / statistics & numerical data*
  • Surveys and Questionnaires
  • Thinness / epidemiology*
  • Young Adult