Southern Rural Development Center
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Box 9656
410 Bost Extension Bldg.
Mississippi State, MS 39762
Phone: (662) 325-3207
Fax: (662) 325-8915

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Some photos on this page courtesy of USDA NRCS.


 

Food Security and Feeding Strategies

Principal Investigator:

Barbara Laraia PhD, MPH, RD
Email: blaraia@email.unc.edu
Phone: 919-966-5969

Abstract of Study:
Increasing obesity rates may be heavily influenced by an environment that promotes energy imbalance, however, limited research exists on the relationship between environmental influences and weight status. While weight status is increasing among all sectors of the population, greater than ten percent of US households experience food insecurity; in which twenty percent of US children are living. Among the characteristics most associated with food insecurity are low-income status, being single, being black and having children. The paradox of hunger among plenty has been amplified by an association between household food insecurity and overweight in women, although this association has not been found among children. One hypothesis is the although children might be protected with regard to weight status, the stressful experience of being in a food insecure household might influence feeding strategies early in life that may in turn impact eating behaviors, diet and weight outcomes later in life. Psychological challenges that families face are important in understanding the pathway between household food insecurity and health outcomes. We will use data from the Infant Care Project, an NIH funded cohort study of low-income, first time African American mothers that has collected myriad data on socioeconomic, household dynamic, psychosocial factors, eating patters, and feeding strategies. Using multivariate analysis, we propose to identify modifiable risk factors associated with household food insecurity to inform intervention strategies to prevent overweight. Results from these analyses will help inform a larger grant proposal that will aim to test hypotheses generated using a nationally representative dataset.

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