Monica L Wang1, Karin Valentine Goins, Milena Anatchkova, Ross C Brownson, Kelly Evenson, Jay Maddock, Kristian E Clausen, Stephenie C Lemon. 1. Department of Community Health Sciences, Boston University School of Public Health, Boston, Massachusetts (Dr Wang and Ms Clausen); Department of Quantitative Health Sciences (Dr Anatchkova), Division of Preventive and Behavioral Medicine, University of Massachusetts Medical School, Worcester (Ms Goins and Dr Lemon); Division of Public Health Sciences and Siteman Cancer Center, School of Medicine, Washington University in St Louis (Dr Brownson); Department of Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill (Dr Evenson); and Office of the Dean, Texas A&M School of Public Health (Dr Maddock).
Abstract
OBJECTIVE: To examine policy makers' public policy priorities related to physical activity and the built environment, identify classes of policy makers based on priorities using latent class analysis, and assess factors associated with class membership. DESIGN: Cross-sectional survey data from municipal officials in 94 cities and towns across 6 US states were analyzed. PARTICIPANTS: Participants (N = 423) were elected or appointed municipal officials spanning public health, planning, transportation/public works, community and economic development, parks and recreation, and city management. MAIN OUTCOME MEASURES: Participants rated the importance of 11 policy areas (public health, physical activity, obesity, economic development, livability, climate change, air quality, natural resource conservation, traffic congestion, traffic safety, and needs of vulnerable populations) in their daily job responsibilities. Latent class analysis was used to determine response patterns and identify distinct classes based on officials' priorities. Logistic regression models assessed participant characteristics associated with class membership. RESULTS: Four classes of officials based on policy priorities emerged: (1) economic development and livability; (2) economic development and traffic concerns; (3) public health; and (4) general (all policy areas rated as highly important). Compared with class 4, officials in classes 1 and 3 were more likely to have a graduate degree, officials in class 2 were less likely to be in a public health job/department, and officials in class 3 were more likely to be in a public health job/department. CONCLUSIONS: Findings can guide public health professionals in framing discussions with policy makers to maximize physical activity potential of public policy initiatives, particularly economic development.
OBJECTIVE: To examine policy makers' public policy priorities related to physical activity and the built environment, identify classes of policy makers based on priorities using latent class analysis, and assess factors associated with class membership. DESIGN: Cross-sectional survey data from municipal officials in 94 cities and towns across 6 US states were analyzed. PARTICIPANTS: Participants (N = 423) were elected or appointed municipal officials spanning public health, planning, transportation/public works, community and economic development, parks and recreation, and city management. MAIN OUTCOME MEASURES: Participants rated the importance of 11 policy areas (public health, physical activity, obesity, economic development, livability, climate change, air quality, natural resource conservation, traffic congestion, traffic safety, and needs of vulnerable populations) in their daily job responsibilities. Latent class analysis was used to determine response patterns and identify distinct classes based on officials' priorities. Logistic regression models assessed participant characteristics associated with class membership. RESULTS: Four classes of officials based on policy priorities emerged: (1) economic development and livability; (2) economic development and traffic concerns; (3) public health; and (4) general (all policy areas rated as highly important). Compared with class 4, officials in classes 1 and 3 were more likely to have a graduate degree, officials in class 2 were less likely to be in a public health job/department, and officials in class 3 were more likely to be in a public health job/department. CONCLUSIONS: Findings can guide public health professionals in framing discussions with policy makers to maximize physical activity potential of public policy initiatives, particularly economic development.
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