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J Rural Health. 2013 Winter;29(1):1-11. doi: 10.1111/j.1748-0361.2012.00421.x. Epub 2012 Jul 11.

Maternal obesity and gestational weight gain in rural versus urban dwelling women in South Carolina.

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1
South Carolina Rural Health Research Center, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA. alexagallagher@yahoo.com

Abstract

PURPOSE:

An unhealthy prepregnancy weight and/or gaining an inappropriate amount of weight during pregnancy increase the risk for poor pregnancy and birth outcomes. To our knowledge, no studies to date have examined differences in prepregnancy body mass index (BMI) and gestational weight gain (GWG) patterns by rurality.

METHODS:

The 2004-2006 South Carolina birth certificate data (n = 132,795) were used. Rurality of residence was determined using Rural-Urban Commuting Area (RUCA) codes. Mothers were categorized as underweight (<18.5 kg/m(2)), normal weight (18.5-24.9), overweight (25.0-29.9), and obese (≥30.0) using their prepregnancy BMI and as having inadequate, adequate, or excessive GWG according to the Institute of Medicine's 2009 GWG guidelines. Chi-square tests and adjusted multinomial logistic regression were used in analysis.

FINDINGS:

Rural women had higher odds of being overweight and obese compared to urban women. This relationship was found to be partially explained by the higher proportion of minorities living in rural areas. The relationship between GWG and residence type varied by BMI category. Specifically, among normal weight women, rural women had increased odds of inadequate GWG. Among overweight women, rural women had decreased odds of excessive GWG. In obese women, rural women had decreased odds of both inadequate and excessive GWG.

CONCLUSIONS:

Rural women were more likely to have an unhealthy prepregnancy weight than urban women. However, rural residence was found to be protective against unhealthy GWG in overweight and obese women. Future research exploring reasons for these findings and confirmation of these results in other populations is necessary.

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