determine exactly how it is that the built environment changes our behaviours and our bodies. A new term has emerged to characterize the relationship between “obesity” 1 and the environments that are thought to enable it: the “obesogenic environment.” Swinburn, Egger and Raza ( 1999 ) describe the
Laureen H. Smith, Devin Laurent, Erica Baumker and Rick L. Petosa
guidelines. 5 , 9 – 11 Personal health behaviors that contribute to obesity are often referred to as obesogenic. Obesogenic behaviors have been found to be related to weight status in nationally representative adolescent samples 5 and have been explored in smaller regional samples focusing on younger
Jill A. Nolan, Christa L. Lilly, Janie M. Leary, Wesley Meeteer, Hugh D. Campbell, Geri A. Dino and Leslie Cotrell
Parent support for child physical activity is a consistent predictor of increased childhood activity. Little is known about factors that prevent or facilitate support. The purpose of this research was to identify barriers to parent support for child physical activity in Appalachian parents.
A cross-sectional study assessed parents whose children participated in Coronary Artery Risk Detection in Appalachian Communities (CARDIAC) screenings in a rural Appalachian state. Barriers to parental support for physical activity, demographics, geographic location, and parental support for activity were measured.
A total of 475 parents completed surveys. The majority were mothers (86.7%), parents of kindergarteners (49.5%), white (89.3%), and living in a nonrural area (70.5%). Community-level factors were most frequently cited as barriers, particularly those related to the built environment. Rural and low-income parents reported significantly higher barriers. Community, interpersonal, and intrapersonal barriers were negatively correlated with parent support for child physical activity. Parents of girls reported a higher percentage of barriers related to safety.
Reported barriers in this sample differed from those reported elsewhere (Davison, 2009). Specific groups such as low-income and rural parents should be targeted in intervention efforts. Future research should explore gender differences in reported barriers to determine the influence of cultural stereotypes.
Susan B. Sisson and Stephanie T. Broyles
The primary and secondary purposes were to examine social-ecological correlates of excessive TV viewing (>2hr/day) in American children 1) between race/ethnic groups and 2) between boys and girls.
Children (n = 48,505) aged 6 to 18 years from the 2007 National Survey of Children’s Health were included. Social-ecological correlates included individual-, family-, and community-level variables. Logistic regression analyses were used for race/ethnicity [Non-Hispanic White (NHW), Non-Hispanic Black (NHB), Hispanic, other] and sex groups (boys, girls), to determine associated correlates.
By race/ethnicity, 16.6%, 37.8%, and 24.5% of NHW, NHB, and Hispanic exceeded recommendations. For boys and girls, 23.7% and 18.2% viewed excessive TV. Having a TV in the bedroom and higher poverty level were associated with excessive TV in all groups. Differences by race/ethnicity were age, sex, TV in the bedroom, extracurricular activities, physical activity, adequate sleep, family structure, family meals, knowing child’s friends, parent/ child communication, and neighborhood characteristics. Differences by sex were family structure, parent/ child communication, family meals, and neighborhood elements.
Social-ecological correlates and associated prevalence of excessive TV viewing differed across subgroups. These specific correlates can be targeted in tailored interventions.
Monika Uys, Susan Bassett, Catherine E. Draper, Lisa Micklesfield, Andries Monyeki, Anniza de Villiers, Estelle V. Lambert and the HAKSA 2016 Writing Group
We present results of the 2016 Healthy Active Kids South Africa (HAKSA) Report Card on the current status of physical activity (PA) and nutrition in South African youth. The context in which we interpret the findings is that participation in PA is a fundamental human right, along with the right to “attainment of the highest standard of health.”
The HAKSA 2016 Writing Group was comprised of 33 authorities in physical education, exercise science, nutrition, public health, and journalism. The search strategy was based on peer-reviewed manuscripts, dissertations, and ‘gray’ literature. The core PA indicators are Overall Physical Activity Level; Organized Sport Participation; Active and Outdoor Play; Active Transportation; Sedentary Behaviors; Family and Peer Influences; School; Community and the Built Environment; and National Government Policy, Strategies, and Investment. In addition, we reported on Physical Fitness and Motor Proficiency separately. We also reported on nutrition indicators including Overweight and Under-nutrition along with certain key behaviors such as Fruit and Vegetable Intake, and policies and programs including School Nutrition Programs and Tuck Shops. Data were extracted and grades assigned after consensus was reached. Grades were assigned to each indicator ranging from an A, succeeding with a large majority of children and youth (81% to 100%); B, succeeding with well over half of children and youth (61% to 80%); C, succeeding with about half of children and youth (41% to 60%); D, succeeding with less than half but some children and youth (21% to 40%); and F, succeeding with very few children and youth (0% to 20%); INC is inconclusive.
Overall PA levels received a C grade, as we are succeeding with more than 50% of children meeting recommendations. Organized Sports Participation also received a C, and Government Policies remain promising, receiving a B. Screen time and sedentary behavior were a major concern. Under- and over-weight were highlighted and, as overweight is on the rise, received a D grade.
In particular, issues of food security, obesogenic environments, and access to activity-supportive environments should guide social mobilization downstream and policy upstream. There is an urgent need for practice-based evidence based on evaluation of existing, scaled up interventions.
Mohanraj Krishnan, Andrew N. Shelling, Clare R. Wall, Edwin A. Mitchell, Rinki Murphy, Lesley M.E. McCowan and John M.D. Thompson
Global shifts surrounding dietary and exercise practices are considered the primary attributable factors in the widespread increase of obesity ( 21 ). The transition to an “obesogenic” environment has encouraged an increased intake of high-caloric food and sedentary behaviors by decreasing
Chia-Yuan Yu, Ayoung Woo, Christopher Hawkins and Sara Iman
-quality schools and public services, and high rates of unemployment. 4 , 5 Moreover, these communities often provide limited access to exercise amenities and feature “obesogenic” food environments. 6 , 7 As a result, residents living in such environments are likely to be isolated and sheltered from outdoor
Shannon S. Block, Trevor R. Tooley, Matthew R. Nagy, Molly P. O’Sullivan, Leah E. Robinson, Natalie Colabianchi and Rebecca E. Hasson
hour spent playing electronic games daily. Hence, the obesogenic risks associated with computer and video game play may outweigh the potential cognitive benefits associated with this activity. Acute bouts of exercise have also been associated with improvements in cognition ( 15 ). In a cohort of 120
Chelsea L. Kracht, Susan B. Sisson, Emily Hill Guseman, Laura Hubbs-Tait, Sandra H. Arnold, Jennifer Graef and Allen Knehans
by race/ethnicity have been reported ( 27 ). We also acknowledge there are no cut points on the FNPA tool for a “healthy” or “unhealthy” household; thus, we cannot specifically classify family behaviors into such categories, only that they exhibit a behavior more often that is related to obesogenic
Christina M. Patch, Caterina G. Roman, Terry L. Conway, Ralph B. Taylor, Kavita A. Gavand, Brian E. Saelens, Marc A. Adams, Kelli L. Cain, Jessa K. Engelberg, Lauren Mayes, Scott C. Roesch and James F. Sallis
of obesogenic environments in youth: geographic information system methods and spatial findings from the neighborhood impact on kids study . Am J Prev Med . 2012 ; 42 ( 5 ): e47 – e55 . PubMed ID: 22516503 doi:10.1016/j.amepre.2012.02.006 22516503 10.1016/j.amepre.2012.02.006 63. Saelens BE