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  • Author: Tamara Vehige Calise x
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Tamara Vehige Calise and Sarah Martin

Background:

Physical inactivity is one of the top 3 risk factors associated with an increased prevalence of obesity and other chronic diseases. The public health infrastructure positions state health departments to address physical inactivity. To examine preparedness, all 50 health departments were assessed, using the 5 benchmarks developed by CDC for physical activity and public health practice, on their capacity to administer physical activity programs.

Methods:

States were scored on a 5-point scale for each benchmark. The top 2 high and low scores were combined to create 2 categories. Exact Chi-square analyses were performed.

Results:

States with CDC obesity funding scored higher on 4 benchmarks than states without. States with a state physical activity plan scored higher on all benchmarks than states without. States with a physical activity coalition scored higher on 2 benchmarks than states without.

Conclusions:

At the time of the assessment, approximately 20% of state physical activity programs could have improved in the use of evidence-based strategies and planning and evaluation approaches. Furthermore, many programs seemed to have limited sustainability. The findings of this report serve as a baseline of the capacity and infrastructure of state health department physical activity programs.

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Tamara Vehige Calise, Samuel C. Dumith, William DeJong and Harold W. Kohl III

Background:

The ability to design or reconfigure communities to be more supportive of physical activity has broad public health implications. Assessing the context and locations of specific behaviors will lead to a better understanding of how neighborhood attributes influence overall physical activity.

Methods:

A cross-sectional survey was used to assess physical activity before and after residents moved to Mueller, a New Urbanist-inspired community in Austin, Texas. Context-specific physical activity and the locations where these activities took place were examined.

Results:

Overall, residents reported that they increased their physical activity by 66.4 minutes (95% CI: 32.8–100.1) per week after moving to Mueller. For recreational walking, residents reported an average of 159.8 minutes inside Mueller after moving, an increase from 91.7 minutes before their move (P < .001). Correspondingly, residents walked 18.6 fewer minutes per week outside Mueller (P < .001). For transport-related walking, the mean number of minutes spent walking outside Mueller remained constant, but the time spent walking inside the neighborhood decreased an average of 10.8 minutes per week after moving (P = .02).

Conclusions:

The most notable increase was seen in walking for recreation inside the neighborhood. Results of this natural experiment strongly suggest the environmental impact on physical activity and underscore the importance of investigating the context and locations where different types of physical activity occur.

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Tamara Vehige Calise, William DeJong, Timothy Heren, Chloe Wingerter and Harold W. Kohl III

Background: Older age groups are less likely than their younger counterparts to be regularly active and women are even less active. Ecological models suggest that multiple levels of influence with each level influencing the next level impacts physical activity behaviors. Methods: Hierarchical multiple regressions were used to determine factors within and across the ecological model that predicted both total physical activity and walking for recreation. Findings: The overall predictors of total physical activity were different than those of walking for recreation, with the exception of dog ownership and perceived barriers. Gender and age were significant predictors of walking for recreation, but these associations were not present for total physical activity. Women and older adults walked more for recreation in a mixed-use community, Mueller, (and thus engaged in more total physical activity) compared with men and younger adults. Conclusion: Behavior-specific physical activity as well as total physical activity led to a better understanding of factors that may impact behavior among an overall aging population, especially women. This level of specificity is important in understanding specific factors that are associated with physical activity among vulnerable populations and can help guide the development of tailored, cost-effective, and efficient policies and interventions.