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- Title
An Exploration of the Determinants of Gestational Weight Gain in African American Women: Genetic Factors and Energy Expenditure.
- Authors
Meng, Ying; Groth, Susan W.; Stewart, Patricia; Smith, Joyce A.
- Abstract
Background: Excessive gestational weight gain (GWG) has a long-term impact on women’s body weight and contributes to the development of obesity in the mother and her child. Many risk factors for GWG have been identified, but to date, only 6–33.8% of the variance in GWG has been explained. The purpose of this study was to evaluate the overall variance of GWG that can be explained by including weight-adjusted resting metabolic rate (aRMR) and a genetic risk score constructed on obesity-related genes in addition to sociodemographic and lifestyle factors. Methods: In this observational study involving 55 African American women, data collected/measured during pregnancy included sociodemographic factors, medical information, lifestyle factors, aRMR, and seven obesity-related genes. Multivariable linear regression was performed to evaluate the variance in GWG explained by the potential risk factors listed above. Results: The mean GWG was 15 kg (±7.5 kg), and 63.6% of women gained more than the Institute of Medicine’s GWG recommendations. The final regression model explained 53.3% of the variance in GWG. Higher genetic risk score, lower aRMR, and higher dietary intake of total energy and percentage of fat were significantly associated with increased GWG (p < .05). These factors explained 18% additional variance in GWG over that explained by significant sociodemographic and lifestyle factors in the analysis (i.e., maternal age, prepregnancy body mass index, parity, illegal drug use, and education). Conclusion: Overall, our results indicate that the genetic risk score, aRMR, and dietary intake have a substantial impact on GWG in African American women.
- Subjects
BLACK people; DIET; ENERGY metabolism; GENES; GENETICS; LONGITUDINAL method; SCIENTIFIC observation; REGRESSION analysis; RESEARCH; RESEARCH funding; STATISTICS; T-test (Statistics); WEIGHT gain; DATA analysis; BODY mass index; LIFESTYLES; PHYSICAL activity; DATA analysis software; PREGNANCY
- Publication
Biological Research for Nursing, 2018, Vol 20, Issue 2, p118
- ISSN
1099-8004
- Publication type
Article
- DOI
10.1177/1099800417743326