Purpose

National prosperity has historically been based on fiscal outcomes, such as Gross Domestic Product (GDP), which has shaped government investment. The New Zealand Government has recently led the world in adopting a wellbeing agenda that broadens our measures of national prosperity to include four indicators of future wellbeing capital and 12 domains of current wellbeing. Our aim was to map how sport, active recreation and play contribute to these indicators of future and current wellbeing to generate an Outcomes Framework that guides future physical activity investment and research in New Zealand.

Methods

We reviewed existing international evidence and consulted global physical activity experts to explore how each of the future and current wellbeing outcomes are associated with sport, active recreation and play. To explore any nuanced differences to international findings, we also collected cross-sectional data on the perceived value of sport from a representative sample of 1516 New Zealanders. This was accompanied by focus groups conducted over an 18-month period with more than 100 stakeholders representing over 60 organisations from across the physical activity sector in New Zealand. We applied an intervention-logic approach to explore the direct and indirect “spill-over” contributions of physical activity to each of the wellbeing outcomes.   

Results/Findings

We found direct contributions of sport, active recreation and play into the following current wellbeing domains: Knowledge & Skills; Time Use; Cultural Identity. There were “spill-over” benefits into the following domains of current wellbeing: Health; Social Connections; Subjective Wellbeing; Civic Engagement & Governance; Environmental Quality. Our contribution to future wellbeing was primarily realised through Social and Human Capital with “spill-over” benefits to Natural and Produced Capital. Achieving these wellbeing outcomes was underpinned by delivering quality experiences through a variety of culturally distinctive pathways that leverage the intrapersonal, interpersonal, social, environmental and policy mediators within the physical activity system.

Conclusions

The Outcomes Framework clearly articulates the broad contribution of sport, active recreation and play to the wellbeing of New Zealanders beyond fiscal and produced capital. This demonstrates the cross-sectoral relevance and value of physical activity and provides a platform for dialogue across multiple national and local government agencies.

Purpose: Mayors play a pivotal role in advancing city health, yet little is known about mayors’ priorities and attitudes regarding public health challenges. This study aimed to assess mayors’ perceptions of top health challenges facing their cities, examine mayors’ perceptions of accountability for public health challenges, and explore predictors of perceived accountability.  

Methods: Data are from a nationally representative survey of U.S. mayors (N=110) and publicly available data repositores on city-level health metrics. Participants were asked to identify the greatest health challenge facing their city. Perceived accountability for nine public health issues (asthma, gun violence, hunger/malnourishment, mental health, lead/toxicants, obesity, opioids, other substance abuse, and traffic accidents) was assessed by asking participants to rate the extent to which they believe constituents hold them accountable for each issue. We conducted descriptive analyses and multivariable regression models to examine associations between mayoral and city-level characteristics (predictors) and level of perceived accountability (outcome) for each of the nine health issues.

Results: Mayors most frequently cited obesity/chronic diseases (25%), opioids/addiction (24%), health care access (15%), and mental health (14%) as the top health challenges facing their cities, yet identified traffic accidents, gun violence, and environmental toxins as health issues for which they believe constituents hold them most accountable (obesity ranked lowest). Democratic mayors rated higher accountability from constituents for gun violence (β=0.78 ;SD=0.26; p<0.001), hunger/malnourishment (β=0.75; SD=0.25; p<0.001), asthma (β=0.40; SD=0.18;  p=0.02), and obesity (β=0.46; SD=0.18; p=0.03) than Republican mayors. Male mayors rated lower accountability for mental health (β=-0.033; SD=0.23; p=0.03) than female mayors. Prevalence of opioid deaths was the only health outcome that was positively associated with perceived accountability (β=0.019; SD=0.010; p=0.05).

Conclusions: Findings indicate a discrepancy between mayors’ perceptions of public health challenges vs. perceived accountability to address such challenges. Findings can inform strategies to engage local policymakers in cross-sector collaborations to improve urban health.

Purpose: Climate change is a direct result of capitalistic economic systems prioritizing profit and accumulation over people and the planet. Both capitalism and climate change-related measures (e.g., ambient air pollution, natural disasters) may be associated with physical inactivity, and, in turn, human health. However, this relationship has not been investigated scientifically. This study examined associations between capitalism, climate change, physical inactivity, and mortality due to non-communicable diseases (NCD) in 124 countries globally.

Methods: This study used multiple secondary data sources. The Fraser Institute’s 2012 economic freedom summary index, World Bank’s 2014 carbon dioxide (CO2) emissions (metric tons per capita), and World Health Organization's 2016 physical inactivity and NCD-related deaths data were used. Linear regression and moderation analyses were conducted.

Results: With physical inactivity as the outcome variable, CO2 emissions positively predicted physical inactivity (b: .6550, 95% confidence interval [CI]: .3798, .9303) but economic freedom did not. Also, there was a significant interaction between the economic freedom index and CO2 emissions on physical inactivity (b: -.5025, 95% CI: -.9498, -.0552). When NCD-related mortality was added as the outcome, economic freedom (b: 9.3156, 95% CI: 5.4992, 13.1320), CO2  emissions (b: 1.5192, 95% CI: 0.9456, 2.0928) and physical inactivity (b: .3116, 95% CI: .0280, .6051), individually, positively predicted NCD-related deaths. Also, there were significant interactions between economic freedom and CO2 emissions (b: -1.5438, 95% CI: -2.4416, -.6460) and CO2 emissions and physical inactivity (b: -.0906, 95% CI: -.1277, -.0536) on NCD-related deaths.

Conclusions: This ecological, longitudinal investigation found that the capitalistic economic model combined with CO2 emissions and physical inactivity are jointly associated with NCD risks globally. This study suggests that the more a country’s economic model is capitalistic, the more deleterious CO2 emissions and physical inactivity on NCD risks among counties with low to average CO2 emissions. NCD-related mortality was high in countries that are hyper-capitalistic and highly physically inactive, regardless of CO2 emission levels. This study is the first to elucidate the potential mechanisms between capitalism, climate change, physical inactivity, and health at a global scale.

Purpose: Built environments are known to influence physical activity and other health determinants. Land-use, transport planning and urban design policies and interventions shape the form and function of built environments, and thus the environmental exposures and lifestyles of urban dwellers. This research assessed urban policies for four cities worldwide, to compare the extent to which they were health-promoting, and to inform policy recommendations for each city. 

Methods: Drawing on indicators proposed in a recent Lancet paper (Giles-Corti et al 2016), we reviewed policies to measure support for creating healthy, active cities. Indicators were developed focused on availability of policies and standards for integrated transport and urban planning, destination accessibility, housing density, car use demand management, urban design to support active transport, access to public transport and active transport infrastructure, and air pollution. Policy data were collected via an online survey for four cities: Auckland, New Zealand; Melbourne, Australia; Chennai, India; and Odense, Denmark. Two researchers undertook content analysis to assess presence/absence of key policies, and their potential to deliver healthy, active neighbourhoods. Inter-rater reliability was tested.

Results: There was significant variation in governance arrangements, policy standards and measurable targets between the four cities, with each having different strengths and limitations. For example, Odense had advanced policies related to destination accessibility and urban design to encourage walking and cycling. In Chennai, there was support for active transport, but policy gaps related to integrated transport and land-use. Melbourne aimed to support active living through creating 20-minute neighbourhoods. Auckland had clear public and active transport targets, but some limitations on land-use policy indicators. Further analysis will quantify the availability of policy into a score, enabling city policy performance to be compared. Inter-rater reliability results showed substantial agreement (90%; Cohen’s kappa=0.83).

Conclusions: All four cities had some level of explicit policy support for healthy cities, but no city performed well on all policy indicators. This study demonstrates opportunities to make policies more evidence-based, specific and measurable, to better support accountability and delivery of policy aspirations. Requirements for health impact assessment of major urban developments and policies could assist in creating healthy, active cities.

Purpose: Presumed pathways from environments to physical health largely implicate health behaviour although mental health may play a role. Few studies have simultaneously assessed mental health together with health behaviour as mediators between environmental factors and physical health. This longitudinal study assessed mental health, diet, and physical activity as mediators of the relationship between area socioeconomic status (SES) and 10-year change in cardiometabolic risk (CMR). Methods: Three waves of population-based biomedical cohort data collected over 10 years were spatially linked to census data, based on participant residential address. Area SES was expressed at baseline using an established index for education and occupation (SEIFA-IEO). Individual behavioural and mental health information collected at Wave 2 included diet (fruit and vegetable servings per day) and physical activity (meets/does not meet recommendations), and the SF36 (mental health component). CMR, expressed as HbA_1c, was measured at each wave of data collection. Relationships were estimated using latent variable growth models with a structural equation modelling approach to assess mediating pathways (path analyses). Multiple path models were estimated. Models were adjusted for age, sex, employment status, marital status, education, and smoking. Results: HbA_1c worsened over time (β 0.048% points per year [95% CI: 0.036, 0.061], p<0.001). Greater area SES was associated with greater fruit intake (0.060 [0.000, 0.120], p<0.05), meeting physical activity recommendations (β-log odds 0.244 [0.153, 0.335], p<0.001), and had a protective effect against worsening CMR directly (-0.014 [-0.018, -0.009], p<0.001) and indirectly through physical activity behaviour (β_IE x100 -0.043, [-0.082, -0.003], p<0.05). Positive mental health was associated with greater fruit (0.067 [0.019, 0.115], p<0.01) and vegetable intakes (0.086 [0.033, 0.139], p<0.01), and was indirectly protective against increasing HbA_1c through physical activity (β_IE x100 -0.058 [-0.113, -0.002], p<0.05). Conclusions: Greater SES was protective against worsening CMR. This relationship was partially mediated by physical activity but not diet, and a protective effect of mental health was also exerted through physical activity. Public health interventions should ensure individuals residing in low SES areas, and those with poorer mental health are supported in meeting physical activity recommendations to prevent the development of CMR.

Purpose: Public transport users accumulate more physical activity (PA) than motor vehicle users, but evidence of effective, cost-effective and scalable strategies for increasing public transport-related PA is sparse. Further, incentive-based strategies show promise for increasing leisure-time PA, but no studies have examined impacts on other PA domains, such as transport PA. This paper describes the trips4health randomised controlled trial (RCT), which aims to determine effectiveness of an incentive-based strategy to increase public transport use on PA.

Methods: trips4health is a single-blinded RCT with a four-month intervention phase and six-month follow-up phase. Three hundred and fifty adults (≥ 18 years) from southern Tasmania will be randomised to: an incentives-based intervention (bus trip credits for reaching bus trip targets, theoretically-driven weekly text messages to support greater bus use, written PA guidelines); or an active control (written PA guidelines). Incentives are allocated by the public transport provider. The primary outcome is change in mean accelerometer-measured daily step count at baseline, four- and ten-months. Secondary outcomes are changes in: measured and self-reported travel behaviours (e.g. public transport use), PA and sedentary behaviour; self-reported and measured health (blood pressure, waist circumference, height, weight); travel behaviour enablers/barriers; quality of life; and participant and provider transport-related costs. Linear mixed model regression will determine group differences. Extensive process, implementation and scalability evaluation is embedded throughout (e.g. participant surveys, intervention group interviews, public transport provider interviews, reach, fidelity).

Results: Since October 2019, 77 participants have provided been randomised. The intervention appears to be showing a high level of participant acceptability, with only one withdrawal to date (due to a non-trial-related injury). Data from process evaluation interviews with public transport provider staff (n=4) indicate high acceptability, with mutual benefits identified, workloads not significantly impacted and recognition of scalability potential.

Conclusions: trips4health will determine the effectiveness of an incentive-based strategy to increase PA by targeting public transport use. The findings from this novel partnership-based intervention will enable evidence-informed decisions about the worthiness of such strategies.

Purpose: This study assesses the reach of a diverse set of investments that employed innovative strategies (nutrition education, media campaigns, financial incentives, changes to physical activity environments, policy changes) aimed at reducing early childhood obesity (RECO) in low-income communities in LA County. We assess reach in terms of communities served and networks created through executing the RECO work. We also explore facilitators and barriers to reach.

Methods: This study used several innovative methods. Geospatial analyses of reach were conducted using ArcGIS with location data collected via grantee reports and interviews, and census-tract-level data on community need characteristics from Public Health Foundation Enterprises, WIC administrative data, and the American Community Survey. Network analysis conducted using UCINET examined connections between RECO-funded organizations based on grantee-reported partnerships and geographic overlap, using location data. Inductive thematic qualitative analysis of data from grantee reports, focus groups with community members, and interviews with RECO grantees assessed facilitators and barriers to reaching populations targeted by RECO, using NVivo 11.

Results: Geospatial analyses revealed that RECO activities reached a majority of LA County; 59% of census tracts received RECO activities. Even higher percentages of high-need communities were reached (e.g., 75% of census tracts in which more than 20% of WIC-participating 2 to 5-year-olds were obese were reached). Network analysis revealed connections between grantees and indicated greater network density based on geographic overlap compared to grantee-reported connections (25% vs. 15%), suggesting there was greater potential for grantee collaboration (based on serving the same geographic areas) than was actually realized (based on grantee-reported partnerships). Qualitative findings highlighted that building relationships with community members, policy-makers, and other stakeholders was key to reaching targeted populations. Lack of awareness of RECO activities due to minimal outreach and marketing was a key barrier to reach.

Conclusions: RECO reached many high-need communities in LA County; relationship-building and partnerships were key facilitators to this reach.  Many partnerships between RECO grantees were established, but realizing additional potential for collaboration among grantees serving the same geographic areas might have expanded the reach of RECO to even more communities in need of these nutrition and physical activity promotion services.