Is urban–rural location associated with weight status in school children? An examination of 42 small and rural Californian counties
Citation: Strochlic R, Au LE, Ritchie L. Is urban–rural location associated with weight status in school children? An examination of 42 small and rural Californian counties. Rural and Remote Health (Internet) 2017; 17: 3966. Available: http://www.rrh.org.au/articles/subviewnew.asp?ArticleID=3966 (Accessed 29 July 2017)
Introduction: Studies have identified geographic variation in overweight and obesity rates among children, with higher rates of overweight and obesity often found among children living in rural compared to urban areas. A small number of studies have explored differences in overweight and obesity based on more nuanced gradations along the urban–rural continuum. The purpose of the present study was to identify differences in overweight and obesity based on gradations along the urban–rural continuum among children in 42 Californian counties with populations less than 500 000.Key words: body mass index, children, obesity, overweight, schools, USA.
Methods: An observational study was conducted using FITNESSGRAM data collected from 5th, 7th and 9th grade students in public schools in California during 2010–2011. The FITNESSGRAM dataset was merged with the 2011 Public Elementary/Secondary School Universe Survey Data from the National Center for Educational Statistics Common Core of Data, which includes an 'urban-centric locale' code for each school, consisting of four broad classifications – city, suburb, town, and rural – each of which is further broken down into three subcategories. Multivariate analyses using a general linear model were conducted to compare differences in body mass index (BMI) between geographic regions of schools (city, suburb, town and rural) as well as 11 urban-centric locale code subcategories; none of the schools were located in large cities. The percentage of students who were overweight and/or obese was compared by grade level, gender, and race/ethnicity across geographic regions using multivariate logistic regression models. Analyses were adjusted for student age, grade, gender, race/ethnicity (African-American, Asian, Hispanic, Indian/Alaskan, White, two or more races or unknown), eligibility for free or reduced price meals, and clustering of students by school. When a stratified analysis was done, the variable of stratification (ie grade, gender, race/ethnicity) was not included among the covariates. When significant differences in BMI or prevalence of overweight or obesity were found between geographic regions, Tukey’s method was applied to adjust for multiple comparisons at a 5% procedure-wise error rate. A p-value at or less than 0.05 was used to indicate statistical significance.
Results: Students in suburban schools had significantly lower mean BMI and lower prevalence of overweight than students in other geographic areas (p<0.0001). Among 5th and 7th grade students, prevalence of obesity (but not overweight) varied by urban–rural status (p<0.0001, p=0.01, respectively), with 7th grade students in suburbs having lower rates of obesity than those in towns. Among 9th grade students, prevalence of overweight (but not obesity) varied by urban–rural status (p=0.02). Among females, prevalence of overweight and obesity varied (p=0.006, p<0.0001, respectively), with suburbs having lower rates than cities and towns. Among males, prevalence of obesity varied (p<0.0001), with suburbs having lower rates. Among whites, there were differences in prevalence of overweight and obesity by urban–rural status (p=0.01, p <0.0001, respectively). Among Hispanics, the prevalence of obesity varied by urban–rural status (p=0.001). Large suburban areas had the lowest rates of obesity compared to all other subcategories.
Conclusions: Students attending schools in suburban, especially larger suburban, areas appear to have lower prevalence of obesity than their peers at schools in other geographic areas. Further research is needed to understand the factors associated with differences in weight status between urban, suburban, town and rural areas.
|This abstract has been viewed 1176 times since 18-Apr-2017.|