Five Community-wide Approaches to Physical Activity Promotion: A Cluster Analysis of These Activities in Local Health Jurisdictions in 6 States

More People, More Active, More Often for Heart Health - Taking Action on Physical Activity

Physical inactivity is a leading contributor to increased cardiovascular morbidity and mortality. Almost 500 million new cases of preventable noncommunicable diseases (NCDs) will occur globally between 2020 and 2030 due to physical inactivity, costing just over US$300 billion, or around US$ 27 billion annually (WHO 2022). Active adults can achieve a reduction of up to 35% in risk of death from cardiovascular disease. Physical activity also helps in moderating cardiovascular disease risk factors such as high blood pressure, unhealthy weight and type 2 diabetes. For people with cardiovascular disease, hypertension, type 2 diabetes and many cancers, physical activity is an established and evidence-based part of treatment and management. For children and young people, physical activity affords important health benefits. Physical activity can also achieve important cross-sector goals. Increased walking and cycling can reduce journeys by vehicles, air pollution, and traffic congestion and contribute to increased safety and liveability in cities.

Generation Pep - study protocol for an intersectoral community-wide physical activity and healthy eating habits initiative for children and young people in Sweden

Background

There is overwhelming evidence for the preventive effects of regular physical activity and healthy eating habits on the risk for developing a non-communicable disease (NCD). Increasing attention has been paid to community-wide approaches in the battle against NCDs. Communities can create supportive policies, modify physical environments, and foster local stakeholder engagement through intersectoral collaboration to encourage communities to support healthy lifestyles. The Pep initiative is based on intersectoral community-wide collaboration among Sweden's municipalities. Primary targets are municipality professionals who work with children and young people as well as parents of children <18 years. The goal is to spread knowledge and create commitment to children's and young people's health with a special focus on physical activity and healthy eating habits to facilitate and support a healthy lifestyle. The overarching aim of the research project described in this study protocol is to investigate factors that influence the implementation of the Pep initiative in Sweden, to inform tailored implementation strategies addressing the needs and local prerequisites of the different municipalities.

Methods

The project includes a qualitative and a quantitative study and is framed by a theoretical model involving four complementary forms of knowledge, explicitly recognized in the Pep initiative: knowledge about the issue; knowledge about interventions; knowledge about the context; and knowledge about implementation. Study 1 is a focus group study exploring barriers and facilitators for implementing the Pep initiative. The study will be carried out in six municipalities, selected purposively to provide wide variation in municipality characteristics, including population size and geographical location. Data will be analyzed using thematic analysis. Study 2 is a cross-sectional web-based survey investigating the implementability of the Pep initiative in Sweden's 290 municipalities. Conditions for implementing different areas of the Pep initiative will be examined in terms of the acceptability, appropriateness, and feasibility, three predictors of implementation success. Data will be analyzed using non-parametric statistics.

Discussion

The findings of the two studies will increase understanding of the prerequisites for implementing the Pep initiative in Swedish municipalities, which will provide valuable input into how implementation of the Pep initiative can best be facilitated in the different municipality settings.

Cultivating an Active Living Plan Through a Social-Ecological Evaluation

Physical activity (PA) social-ecological model (SEM) posits the importance of several levels of influence critical for PA promotion within communities. The purpose of this study was to examine an SEM evaluation informing a county-wide active living plan in McLennan County, Texas in the United States. Mixed-methods evaluation occurred in 4 stages: (1) county policies (n = 15) were evaluated for PA promoting strategies; (2) PA resource assessments (PARAs) were conducted via Google Maps (n = 171); (3) surveys (n = 244) included the International Physical Activity Questionnaire and interpersonal and intrapersonal factors related to PA; and (4) focus groups (n = 5) were conducted with residents (n = 30), discussing barriers and facilitators to being active. Logistic regression determined significant associations between SEM factors and meeting PA recommendations. Policy scans and PARAs identified strengths and areas of improvement (eg, equitable project selection and disparities in resource quality). Residents reporting fewer barriers (OR = 0.89, P =.01), more perceived behavioral control (odds ratio [OR] = 1.38, P = .01), more social co-participation in PA (OR = 1.20, P = .03), and living in zip codes with higher mean PARA score (OR = 1.22, P = .04) were significantly more likely to meet PA recommendations (Nagelkerke R2 = 0.32). Focus groups also discussed safety and disparities in access and quality. This study suggests the utility of the SEM when evaluating and promoting community PA.

Who Are the Local Policy Innovators? Cluster Analysis of Municipal Tobacco Control Policies in Massachusetts

CONTEXT

Tobacco use is a leading cause of preventable death, yet it is challenging to establish public policy to reduce tobacco use. Massachusetts has been a national leader in tobacco control, and its policy-making patterns can be informative to the country.

OBJECTIVE

To identify factors associated with the adoption of tobacco policy within 351 Massachusetts municipalities.

DESIGN

We obtained the 2019 Massachusetts municipality-level tobacco control policy information from Massachusetts' Tobacco Automated Fact Sheet Information system and compiled it with data from American Community Survey, Massachusetts Municipal Association, and Massachusetts state government's Web sites. We used k -means clustering method to identify statistical clustering patterns and hotspot analysis (Getis-Ord Gi*) and Local Indicators of Spatial Association to identify geographic clustering patterns. We then performed multinomial logistic regression to identify factors associated with policy clusters.

SETTING

Massachusetts.

PARTICIPANTS

Three hundred fifty-one municipalities in Massachusetts.

MAIN OUTCOME MEASURE

Policy clusters-groups of municipalities with similar tobacco control policy behaviors.

RESULTS

Based on the k -means analyses, we identified 3 clusters in Massachusetts municipal tobacco control policy behaviors: 54% (N = 191) of municipalities were "Policy Leaders" with a high adoption rate of the 6 tobacco control policies; 18% (N = 63) were "Peer-Influenced Actors" focused on tobacco purchase restrictions for individuals younger than 21 years; and 28% (N = 97) were "Policy Non-Actors," with no tobacco control policies in place. Policy Leaders were geographically clustered in larger cities and the MetroWest region. Policy Non-Actors were clustered in rural areas of Western and Central Massachusetts. Larger municipal population size, higher municipal tax income, and higher percentages of residents voting Democratic were associated with higher policy adoption activities.

CONCLUSIONS

Local variation in the adoption of tobacco policies may exacerbate inequities in tobacco use and population health. Opportunities remain to implement additional tobacco control regulations at the local level to promote public health.

The DASH model: Data for addressing social determinants of health in local health departments

Recent frameworks, models, and reports highlight the critical need to address social determinants of health for achieving health equity in the United States and around the globe. In the United States, data play an important role in better understanding community-level and population-level disparities particularly for local health departments. However, data-driven decision-making-the use of data for public health activities such as program implementation, policy development, and resource allocation-is often presented theoretically or through case studies in the literature. We sought to develop a preliminary model that identifies the factors that contribute to data-driven decision-making in US local health departments and describe relationships between them. Guided by implementation science literature, we examined organizational-level capacity and individual-level factors contributing to using data for decision-making related to social determinants of health and the reduction of county-level disparities. This model has the potential to improve implementation of public health interventions and programs aimed at upstream structural factors, by elucidating the factors critical to incorporating data in decision-making.

Principles and strategies of inclusive physical activity: a European Delphi study

Aim/Purpose

The article seeks to articulate a consensus of the opinions of a group of subject experts about the principles and strategies of inclusive physical activity.

Methods

A 3-stage Delphi study involving a group of 34 Europe-based subject specialists was used to articulate shared expert opinions on the main research question: What are the key principles (general theories, values, or framework) that should guide practice of inclusive approaches to physical activity? What are the key strategies (practical approaches that can promote inclusive physical activity) of inclusive approaches to physical activity?

Results

Four core principles and four core strategies (and six less-supported principles/strategies for each) were identified through this process. The core principles were: focus on participants' needs; include disabled people in planning; focus on ability, not disability; and promote equal opportunities. The four core strategies were: adapt the rules and aims of the programme to the abilities of participants; apply adaptability of teaching/coaching methods; be accessible and available to participants; and establish models to make sure participants' voices are heard.

Conclusions

The article concludes by offering ten concepts - drawn from the empirical findings - that might act as a starting-point for the development of the concept for an inclusive physical activity programme.

Involvement of Local Health Departments in Obesity Prevention: A Scoping Review

INTRODUCTION

Local health department (LHD) obesity prevention (OP) efforts, particularly by rural LHDs, are seemingly uncommon, in part, due to limited infrastructure, workforce capacity, accessible data, and available population-level interventions aimed at social determinants of health (SDOH).

METHODS

We conducted a scoping review to determine LHD roles in OP efforts and interventions. Inclusion criteria were articles including evidence-based OP and LHD leaders or staff. Articles were coded by type of LHD involvement, data use, intervention characteristics, use of an SDOH lens, and urban or rural setting.

RESULTS

We found 154 articles on LHD OP-52 articles met inclusion criteria. Typically, LHDs engaged in only surveillance, initial intervention development, or evaluation and were not LHD led. Data and SDOH lens use were infrequent, and interventions typically took place in urban settings.

CONCLUSION

LHDs could likely play a greater role in OP and population-level interventions and use data in intervention decision making. However, literature is limited. Future research should focus on LHD capacity building, including academic-public health partnerships. Studies should include rural populations, data, and SDOH frameworks addressing "upstream" factors.

Patterns of Cross-Sector Collaboration in Local Health Departments: A Cluster Analysis

Local health departments (LHDs) are positioned to act as the community health strategist for their catchment area, which requires cross-sector collaboration. However, little research exists to understand how much and what types of cross-sector collaboration occur and its impact on LHD practice. Data from 490 LHDs who participated in the 2016 National Profile of Local Health Departments survey were analyzed to identify patterns of cross-sector collaboration among LHDs. In the survey, LHDs reported the presence of collaborative activities for each of 22 categories of organizations. Factor analysis was used to identify patterns in the types of organizations with which LHDs collaborate. Then, cluster analysis was conducted to identify patterns in the types of cross-sector collaboration, and cross-sectional analyses examined which LHD characteristics were associated with cluster assignment. LHDs collaborated most with traditional health care-oriented organizations, but less often with organizations focused on upstream determinants of health such as housing. Three distinct clusters represented collaboration patterns in LHDs: coordinators, networkers, and low-collaborators. LHDs who were low-collaborators were more likely to serve smaller populations, be unaccredited, have a smaller workforce, have a White top executive, and have a top executive without a graduate degree. These findings imply that public health practitioners should prioritize building bridges to a variety of organizations and engage in collaboration beyond information sharing. Furthermore, LHDs should prioritize accreditation and workforce development activities for supporting cross-sector collaboration. With these investments, the public health system can better address the social and structural determinants of health and promote health equity.

Challenges and lessons learned in promoting adoption of standardized local public health service delivery data through the application of the Public Health Activities and Services Tracking model

Population-level prevention activities are often publicly invisible and excluded in planning and policymaking. This creates an incomplete picture of prevention service-related inputs, particularly at the local level. We describe the process and lessons learned by the Public Health Activities and Services Tracking team in promoting adoption of standardized service delivery measures developed to assess public health inputs and guide system transformations. The 3 factors depicted in our Public Health Activities and Services Tracking model-data need and use, data access, and standardized measures-must be realized to promote collection of standard public health system data. Bureaucratic, resource, system, and policy challenges hampered our efforts toward adoption of the standardized measures we promoted. Substantial investments of time, resources, and coordination appear necessary for systems to adopt changes needed for collecting comparable service delivery data. Lessons from our process of promoting adoption of standardized measures provide recommendations to support future efforts to measure public health system contributions to the public's health.

Effectiveness of Policies and Programs to Combat Adult Obesity: a Systematic Review

BACKGROUND

This systematic review identifies programs, policies, and built-environment changes targeting prevention and control of adult obesity and evaluates their effectiveness.

METHODS

We searched PubMed, CINAHL, PsycINFO, and EconLit from January 2000 to March 2018. We included natural experiment studies evaluating a program, policy, or built-environment change targeting adult obesity and reporting weight/body mass index (BMI). Studies were categorized by primary intervention target: physical activity/built environment, food/beverage, messaging, or multiple. Two reviewers independently assessed the risk of bias for each study using the Effective Public Health Practice Project tool.

RESULTS

Of 158 natural experiments targeting obesity, 17 reported adult weight/BMI outcomes. Four of 9 studies reporting on physical activity/built environment demonstrated reduced weight/BMI, although effect sizes were small with low strength of evidence and high risk of bias. None of the 5 studies targeting the food/beverage environment decreased weight/BMI; strength of evidence was low, and 2 studies were rated high risk of bias.

DISCUSSION

We identified few natural experiments reporting on the effectiveness of programs, policies, and built-environment changes on adult obesity. Overall, we found no evidence that policies intending to promote physical activity and healthy eating had beneficial effects on weight/BMI and most studies had a high risk of bias. Limitations include few studies met our inclusion criteria; excluded studies in children and those not reporting on weight/BMI outcomes; weight/BMI reporting was very heterogeneous. More high-quality research, including natural experiments studies, is critical for informing the population-level effectiveness of obesity prevention and control initiatives in adults.