Cycling and Diabetes Prevention: Practice-Based Evidence for Public Health Action

Personal determinants of change agents' decision-making behavior in community health promotion: a qualitative study

BACKGROUND

Implementing environmental changes to promote healthier communities requires initial positive decisions by change agents from local politics and government. However, there is little research on what influences the change agents' decisions. This explorative, qualitative study aims to identify the personal determinants of the decision-making behavior of local change agents.

METHODS

We conducted semi-structured interviews to assess the personal determinants of decision-making behavior among 22 change agents from local politics and government. Relevant determinants were identified through a structured content analysis of the interview transcripts using the software MAXQDA 2020.

RESULTS

We found the following seven essential clusters of personal determinants of the decision-making behavior of change agents from local politics and government: Imprinting, socialization, and biography; experiences and involvement; attitudes and outcome expectations towards important issues and aspects; knowledge; emotions; personal benefits; and the perceived influences of others.

CONCLUSIONS

The identified personal determinants might serve as a source of understanding the decision-making behavior of change agents in community decision-making processes. Our findings can contribute to the effective planning and implementation of evidence-based multilevel interventions related to changing environmental conditions in communities and provide important information on which personal determinants should be considered when derive strategies for community health promotion within a systematic approach of developing an intervention program theory.

Forschungsprojekt EUBeKo

Hintergrund

Bewegung ist über eine Reihe sozialökologischer Bedingungsfaktoren zu verstehen, an welchen eine erfolgreiche Bewegungsförderung ansetzen muss. Kommunen nehmen dabei eine bedeutende Rolle ein, da sie gesundheitsförderliche Verhältnisse ermöglichen können. Häufig wird die Konzipierung, Umsetzung und Evaluierung sozialökologischer Ansätze jedoch nicht systematisch und theoriegeleitet abgeleitet. Veränderungen in den Verhältnissen werden durch das Verhalten und die Entscheidungen sog. „change agents“ bzw. kommunaler Entscheidungstragender, wie z. B. Bürgermeister:innen, beeinflusst. Daher ist es wichtig, Einflussfaktoren auf Entscheidungsprozesse zu kennen, um Überzeugungsarbeit für Bewegungsförderung in der Kommune zu leisten. Zudem braucht es Multiplikator:innen (z. B. Mitarbeitende in Gesundheitsämtern), die Kompetenzen besitzen, verhältnisorientierte Interventionen in Kommunen systematisch umzusetzen.

Zielstellung und Projektverlauf

Das Forschungsprojekt „Entscheidungs- und Umsetzungsprozesse verhältnisorientierter Bewegungsförderung in der Kommune für mehr Chancengerechtigkeit systematisch planen und implementieren“ (EUBeKo) wurde im Rahmen des Förderschwerpunkts „Bewegung und Bewegungsförderung“ des Bundesministeriums für Gesundheit gefördert. In diesem Beitrag werden das Projekt EUBeKo mit seinen zwei Forschungsfragen zum einen nach der Rolle und den Kompetenzen von Multiplikator:innen und zum anderen nach den Einflussfaktoren auf kommunale Entscheidungsprozesse sowie die Planung und Umsetzung verhältnisorientierter Bewegungsförderung in zwei Modellkommunen als auch die Strategien der Dissemination (z. B. Projekt-Webseite) beschrieben.

Diskussion und Schlussfolgerungen

Zu den Stärken des Projekts zählt die systematische und theoriegeleitete Aufbereitung und Durchführung eines Prozesses verhältnisorientierter Bewegungsförderung in der Kommune mit besonderem Fokus auf Planungs- und Entscheidungsprozesse sowie auf die Zielgruppen der kommunalen Multiplikator:innen und Entscheidungstragenden. Herausforderungen finden sich im Theorie-Praxis-Transfer und in den Auswirkungen der COVID-19-Pandemie („coronavirus disease 2019“) auf die Projektumsetzung.

An overview of cycling as active transportation and as benefit for health

Active transportation is defined as travelling on foot, by bicycle or other non-motorized means, sometimes in combination with other forms of public transportation, in contrast with the use of motor vehicles. The prevalence of sedentary lifestyle and physical inactivity is a growing epidemic in most developed countries that spread over the last three decades; active transportation may be a promising approach to increase physical activity and reduce the risk of non-communicable diseases improving cardiorespiratory fitness and cardiometabolic health. The health benefits of physical activity in reducing mortality and morbidity have been proved by several publications. Cardiorespiratory fitness can be improved by regular physical activity with an amelioration of insulin sensitivity, blood lipid profile, body composition, inflammation, and blood pressure. Active transportation as a daily physical activity is less expensive compared to motor vehicle use. The advantages are remarkable in terms of contrasting obesity and sedentary lifestyle, decrease motor traffic congestion and mitigate climate change. Massive investments in policies and interventions aimed to increase active transportation are not generally promoted and there are differences in the prevalence of active transportation in the daily routine among different areas. As in the literature several studies as randomized trials or observational studies have been published, with different end-points, in order to investigate if active commuting may be the right answer to improve cardiorespiratory fitness and cardiometabolic health, we aimed to review the available evidences of cycling as an active transportation and to consider its benefits on health.

Is cycle network expansion cost-effective? A health economic evaluation of cycling in Oslo

BACKGROUND

Expansion of designated cycling networks increases cycling for transport that, in turn, increases physical activity, contributing to improvement in public health. This paper aims to determine whether cycle-network construction in a large city is cost-effective when compared to the status-quo. We developed a cycle-network investment model (CIM) for Oslo and explored its impact on overall health and wellbeing resulting from the increased physical activity.

METHODS

First, we applied a regression technique on cycling data from 123 major European cities to model the effect of additional cycle-networks on the share of cyclists. Second, we used a Markov model to capture health benefits from increased cycling for people starting to ride cycle at the age of 30 over the next 25 years. All health gains were measured in quality-adjusted life years (QALYs). Costs were estimated in US dollars. Other data to populate the model were derived from a comprehensive literature search of epidemiological and economic evaluation studies. Uncertainty was assessed using deterministic and probabilistic sensitivity analyses.

RESULTS

Our regression analysis reveals that a 100 km new cycle network construction in Oslo city would increase cycling share by 3%. Under the base-case assumptions, where the benefits of the cycle-network investment relating to increased physical activity are sustained over 25 years, the predicted average increases in costs and QALYs per person are $416 and 0.019, respectively. Thus, the incremental costs are $22,350 per QALY gained. This is considered highly cost-effective in a Norwegian setting.

CONCLUSIONS

The results support the use of CIM as part of a public health program to improve physical activity and consequently avert morbidity and mortality. CIM is affordable and has a long-term effect on physical activity that in turn has a positive impact on health improvement.

Association between trail use and self-rated wellness and health

Background

Incorporating trail use into daily activity routines could be an important venue to increase a population’s physical activity. This study presents important health impacts of trail use.

Methods

A cross-sectional study was conducted on 8 trails throughout the State of Indiana. A mix of urban, suburban, and rural trails were selected. Recruitment sessions were completed during four 1-week periods throughout the study in various locations and at various times of day on each trail between April and October 2017. Data were collected through online and paper surveys. For each type of physical activity, a generalized additive model for self-rated wellness and health was built adjusting for demographics, socioeconomic status, amounts of physical activity on trails, mood status, sleep pattern, diet and smoking habit. The plots of estimated smoothing spline function with 95% confidence band were pictured. All statistical analyses were conducted using R.

Results

The final sample size included 1299 trail users; 92% were White, 79% aged 18–65 years, 71% were married and 56% were male. Biking, walking and running were the main activities with 52, 29 and 19%, respectively. Female to male ratio was 3:2 in walkers vs. 2:3 in runners and bikers. Runners were significantly younger than the other two groups. Runners also had the highest percentage of college graduates and above, the highest rate of employment, the highest income, and the lowest percentage of being retired among the three groups. They more commonly used the trails alone than the walkers and bikers. Bikers had the highest rate of job satisfaction. They also showed a better mean score of mood than that the walkers and runners. There was a linear association between walking and self-rated wellness and health, and a curved association between running/biking and self-rated wellness and health. Running < 6.5 miles/week and biking > 14 miles/week were associated with steeper rise in self-rated wellness and health.

Conclusions

Employed educated married middle-aged people had the highest prevalence of walking, running or biking. The higher the walking, the higher self-rated wellness and health. A similar association was observed for running up to 6.5 miles/week or biking > 14 miles/week.

Title: Can changing the physical environment promote walking and cycling? A systematic review of what works and how

Environmental changes aimed at encouraging walking or cycling may promote activity and improve health, but evidence suggests small or inconsistent effects in practice. Understanding how an intervention works might help explain the effects observed and provide guidance about generalisability. We therefore aimed to review the literature on the effects of this type of intervention and to understand how and why these may or may not be effective. We searched eight electronic databases for existing systematic reviews and mined these for evaluative studies of physical environmental changes and assessed changes in walking, cycling or physical activity. We then searched for related sources including quantitative or qualitative studies, policy documents or reports. We extracted information on the evidence for effects ('estimation'), contexts and mechanisms ('explanation') and assessed credibility, and synthesised material narratively. We identified 13 evaluations of interventions specifically targeting walking and cycling and used 46 related sources. 70% (n = 9 evaluations) scored 3 or less on the credibility criteria for effectiveness. 6 reported significant positive effects, but higher quality evaluations were more likely to report positive effects. Only two studies provided rich evidence of mechanisms. We identified three common resources that interventions provide to promote walking and cycling: (i) improving accessibility and connectivity; (ii) improving traffic and personal safety; and (iii) improving the experience of walking and cycling. The most effective interventions appeared to target accessibility and safety in both supportive and unsupportive contexts. Although the evidence base was relatively limited, we were able to understand the role of context in the success of interventions. Researchers and policy makers should consider the context and mechanisms which might operate before evaluating and implementing interventions.