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dc.contributor.authorWang, Monica L.
dc.contributor.authorGoins, Karin V.
dc.contributor.authorAnatchkova, Milena D.
dc.contributor.authorBrownson, Ross
dc.contributor.authorEvenson, Kelly R.
dc.contributor.authorMaddock, Jay
dc.contributor.authorClausen, Kristian E.
dc.contributor.authorLemon, Stephenie C.
dc.date2022-08-11T08:08:34.000
dc.date.accessioned2022-08-23T15:59:34Z
dc.date.available2022-08-23T15:59:34Z
dc.date.issued2016-05-01
dc.date.submitted2016-05-09
dc.identifier.citation<p>J Public Health Manag Pract. 2016 May-Jun;22(3):221-30. doi: 10.1097/PHH.0000000000000289. <a href="http://dx.doi.org/10.1097/PHH.0000000000000289">Link to article on publisher's site</a></p>
dc.identifier.issn1078-4659 (Linking)
dc.identifier.doi10.1097/PHH.0000000000000289
dc.identifier.pmid26079657
dc.identifier.urihttp://hdl.handle.net/20.500.14038/30699
dc.description.abstractOBJECTIVE: 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.
dc.language.isoen_US
dc.relation<p><a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&list_uids=26079657&dopt=Abstract">Link to Article in PubMed</a></p>
dc.relation.urlhttp://dx.doi.org/10.1097/PHH.0000000000000289
dc.subjectHealth Policy
dc.subjectPublic Health
dc.titlePriorities of Municipal Policy Makers in Relation to Physical Activity and the Built Environment: A Latent Class Analysis
dc.typeJournal Article
dc.source.journaltitleJournal of public health management and practice : JPHMP
dc.source.volume22
dc.source.issue3
dc.identifier.legacycoverpagehttps://escholarship.umassmed.edu/faculty_pubs/978
dc.identifier.contextkey8575202
html.description.abstract<p>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.</p> <p>DESIGN: Cross-sectional survey data from municipal officials in 94 cities and towns across 6 US states were analyzed.</p> <p>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.</p> <p>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.</p> <p>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.</p> <p>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.</p>
dc.identifier.submissionpathfaculty_pubs/978
dc.contributor.departmentPrevention Research Center
dc.contributor.departmentDepartment of Medicine, Division of Preventive and Behavioral Medicine
dc.contributor.departmentDepartment of Quantitative Health Sciences
dc.source.pages221-30


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