Understanding childhood obesity in a diverse population of low income children li

Tufts University Boston, Boston MA

Investigators

Linked publications & trials

Abstract

[unreadable] DESCRIPTION (provided by applicant): US Children living in impoverished rural communities have limited opportunities for physical activity and accessibility to healthy foods. Research in this area is limited as much of the work has been done in urban and suburban areas. Given the increasing obesity rates it is necessary to identify the factors that are driving this epidemic in rural areas. [unreadable] [unreadable] Specific Aims and Hypotheses: 1. To describe the feeding and parenting styles of low income, rural parents living in four distinct areas of the US (Appalachia, Central Valley, Mississippi River Delta, and the Southeast) and to examine the agreement among feeding style instruments (CFSQ/CFQ) and between feeding style and parenting style instruments (CFSQ/PDI-S). Hypothesis 1a: There are associations between the feeding style dimensions of demandingness and responsiveness (CFSQ) and the feeding style dimensions (CFQ) of pressure to eat, restriction, and level of monitoring. Hypothesis 1b: There are associations between the feeding style dimensions of demandingness and responsiveness (CFSQ) and the parenting style subscales (PDI-S) of nurturance, inconsistency, follow thru, organization, letting go, punishment, reasoning, reminding, and control. [unreadable] [unreadable] 2. To determine the relationship between parent feeding styles and child's dietary quality, energy intake, and weight status in a low income, rural population. Hypothesis 2a: There are associations between child diet quality and parent level of demandingness (+) and responsiveness (+) toward feeding, as measured by the CFSQ, and pressure to eat (+), restriction (-), and level of monitoring (+), as measured by the CFQ. Hypothesis 2b: There are associations between child energy intake and parent level of demandingness (-) and responsiveness (-) toward feeding as measured by the CFSQ and pressure to eat (-), restriction (+), and level of monitoring (-) as measured by the CFQ. Hypothesis 2c: The pressure to eat score reported by parents, as measured by the CFQ, will be different between children who have a high vs. average BMI z-score. [unreadable] [unreadable] 3. To determine the relationship between physical activity-related parenting practices and parenting styles of low income rural parents and their child's physical activity level. Hypothesis 3a: There is a positive association between a child's PA level and their parents activity-related practices score. Hypothesis 3b: Levels of physical activity will be different in children with an authoritative parent, as measured by the PDI-S, compared to children with a nonauthoritative parent. [unreadable] [unreadable] Methods: a. Study/evaluation design: Quantitative, cross-sectional assessment of parenting style, feeding styles, body composition, and physical activity and dietary habits among 99 parent-child dyads. b. Setting and population: The target population is rural American elementary school children between the ages of 6-11 years living in poor areas within the Central Valley (CA), Mississippi Delta (MS, AR), Appalachia (KY), and Southeast (GA, SC) regions of the US. We will randomly select 1 school from each region (N=4 schools). c. Measures: Parents will complete the Caregiver's Feeding Styles Questionnaire, Child Feeding Questionnaire, Parenting Dimensions Inventory as measures of feeding style and global parenting style. Parents will also report their family demographics, seasonal activities, and questions about their own habits, attitudes, and perceptions toward physical activity. Children will self-report their food and activity preferences as well as participate in a parent-assisted 24-hour recall and wear a physical activity monitor. Both parents and children will have their height and weight measured to determine BMI. d. Analysis: Descriptive, exploratory, and correlation analyses will be performed using SPSS for the quantitative data. The 24-hour recalls will be analyzed using NDS-R. Activity monitor data will be downloaded and computed using SAS. Multivariate regression models will test for the effect of feeding style and parenting style on child health outcomes. [unreadable] [unreadable] [unreadable]