BACKGROUND: Obesity has been identified as the most common health problem facing America's youth today. Results gathered from two National Health and Nutrition Examination Surveys (NHANES), (1976- 1980 and 2003-2004) show that the prevalence of overweight is increasing. For children 2-5 years of age, prevalence has increased from 5.0% to 13.9%. For children ages 6-11 the prevalence has increased from 6.5% to 18.8%, and for those ages 12-19 prevalence increased from 5.0% to 17.4%. The Center for Disease Control (CDC) reports that on an individual level, childhood overweight/obesity is the result of an imbalance between the calories a child consumes and the calories a child uses to support normal growth and development, metabolism and physical activity. The imbalance between calories consumed and calories used can have many variables and factors including genetic, behavioral and environmental influences. Childhood obesity is believed to be a combination or interaction of these factors rather than any single factor. The purpose of this study is to determine if a family's demographics and/or a child's lifestyle choice's have an impact on body weight which may subsequently affect their health. HYPOTHESIS: The researchers predict the incidence of obese youths will appear in both children and adolescents, and in all age, race and gender groups. The researchers hypothesize that a family which participates in more sporting activities, has fewer hours of exposure to screen time and consumes more meals at home together each week, will have a statistically significantly lower BMI than those families/children who do not. We believe that the lifestyle choices and demographic information of family members and their children will influence a child's BMI as shown by statistically significant results. We believe that our study will prove consistent with what is reported in the media and other research, including higher BMI's correlated with more screen time, a TV in a child's room, more meals consumed away from home and less exercise. We believe conversely that children with lower BMI will have more activity, less screen time and other more healthy behaviors. STUDY DESIGN: This comparison study was carried out using single page photo copied surveys handed to families by office staff at one of five pediatric clinics in Utah, Oregon and Washington to patients arriving for sick or well child checks. Surveys were handed out regardless of child stature, race, disability or age. Only surveys completed for children 2-18 and with a completed height/ weight category were used in the research study. METHODS: Anonymous surveys were created and handed out at 5 participating clinics. Height, weight and date of birth were filled in by the medical staff. The number of returned surveys was evaluated for survey response and BMI data. BMI, as defined by the CDC, for 119 children was calculated by the researchers using a standard BMI calculator provided by the CDC. The "risk of overweight" and "overweight" youth survey variables were then compared with "normal weight" survey variables. Survey data was entered using standard BMI measures as well as a numerical coding system and then analyzed using Microsoft Excel. A statistical analysis of comparison was performed on the data to observe significance of the population's medical history. The variables surveyed included basic demographic questions for gender, age, household size and familial income. Survey questions addressed household smoking exposure, child illness frequency, protective helmet use, hours of physical activity, seasons of sport participation, perception of child's body size by parent, number of electronic entertainment devices in the home, the presence of a television or video game in child's room, hours of video exposure, meals consumed in front of a TV or computer, number of breakfasts eaten per week and number of fast food meals per week. The final question concluded with parent listing top concerns about their child's health. Results: Of our 131 participants, 124 subjects were used for data analysis. Seven children were considered "under weight", 82 were defined as "normal weight", 19 were defined as "at risk for overweight" and 16 were defined as "overweight". (See Figure 4) When BMI coded data was analyzed there were no statistically significant findings. However when raw BMI numbers were then compared against survey variables, there were significant findings associated with screen time, helmet use, exercise, breakfast consumption and video entertainment. Conclusion: Our research showed a statistically significant correlation between BMI and several lifestyle choices. Our data showed that the more often a child wears a helmet while riding a bike, daily eats breakfast and exercises throughout the week, the lower their BMI as compared to their same age counterparts who make the opposite lifestyle choices. Conversely we found that the more meals consumed in front of the TV and the more time using video entertainment correlates to a higher BMI when compared to their same age counterparts who are doing those activities less frequently.
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