Co-Produce, Co-Design, Co-Create, or Co-Construct-Who Does It and How Is It Done in Chronic Disease Prevention? A Scoping Review.

Co-production in health literature has increased in recent years. Despite mounting interest, numerous terms are used to describe co-production. There is confusion regarding its use in health promotion and little evidence and guidance for using co-produced chronic disease prevention interventions in the general population. We conducted a scoping review to examine the research literature using co-production to develop and evaluate chronic disease prevention programs. We searched four electronic databases for articles using co-production for health behaviour change in smoking, physical activity, diet, and/or weight management. In 71 articles that reported using co-production, co-design, co-create, co-develop, and co-construct, these terms were used interchangeably to refer to a participatory process involving researchers, stakeholders, and end users of interventions. Overall, studies used co-production as a formative research process, including focus groups and interviews. Co-produced health promotion interventions were generally not well described or robustly evaluated, and the literature did not show whether co-produced interventions achieved better outcomes than those that were not. Uniform agreement on the meanings of these words would avoid confusion about their use, facilitating the development of a co-production framework for health promotion interventions. Doing so would allow practitioners and researchers to develop a shared understanding of the co-production process and how best to evaluate co-produced interventions.

Ecological study of playground space and physical activity among primary school children.

OBJECTIVES: To examine the relationship between school playground size and total physical activity (PA), fitness and fundamental movement skills (FMS) of primary school students. DESIGN: Cross-sectional ecological analysis. SETTING: 43 primary schools in New South Wales, Australia. PARTICIPANTS: Data were from 5238 students, aged 5 to 12 years, participating in the Schools Physical Activity and Nutrition Survey. OUTCOME MEASURES: Self (for age ≥11 years) and parent (for age <11 years) report of PA (meeting PA recommendations and number of days meeting recommendations), objectively measured FMS and cardiorespiratory and muscular fitness. RESULTS: Associations between playground space and measures of PA and fitness were mostly non-linear and moderated by loose equipment. Students in schools with no loose equipment showed a weak association between space and meeting PA recommendations (self-report). In schools with equipment, students' predicted probability of meeting PA recommendations increased sharply between 15 m2 and 25 m2 per student from 0.04 (95% CI: 0.01 to 0.08) to 0.30 (95% CI: 0.14 to 0.46), but at 30 m2 returned to levels comparable to students in schools with no equipment (0.18, 95% CI: 0.07 to 0.28). For cardiorespiratory fitness, in schools with no loose equipment, probabilities for being in the healthy cardiovascular fitness zone varied between 0.66 and 0.77, showing no consistent trend. Students in schools with loose equipment had a predicted probability of being in the healthy fitness zone of 0.56 (95% CI: 0.41 to 0.71) at 15 m2 per student, which rose to 0.75 (95% CI: 0.63 to 0.86) at 20 m2 per student. There was no relationship between space and FMS. CONCLUSIONS: School space guidelines need to incorporate sufficient playground space for students. Our study provides evidence supporting better PA outcomes with increasing space up to 25 m2 per student, and access to loose equipment, however further research is required to determine precise thresholds for minimum space. Intersectoral planning and cooperation is required to meet the needs of growing school populations.

Multiple lifestyle behaviours and mortality, findings from a large population-based Norwegian cohort study - The HUNT Study.

BACKGROUND: Lifestyle risk behaviours are responsible for a large proportion of disease burden and premature mortality worldwide. Risk behaviours tend to cluster in populations. We developed a new lifestyle risk index by including emerging risk factors (sleep, sitting time, and social participation) and examine unique risk combinations and their associations with all-cause and cardio-metabolic mortality. METHODS: Data are from a large population-based cohort study in a Norway, the Nord-Trøndelag Health Study (HUNT), with an average follow-up time of 14.1 years. Baseline data from 1995-97 were linked to the Norwegian Causes of Death Registry. The analytic sample comprised 36 911 adults aged 20-69 years. Cox regression models were first fitted for seven risk factors (poor diet, excessive alcohol consumption, current smoking, physical inactivity, excessive sitting, too much/too little sleep, and poor social participation) separately and then adjusted for socio-demographic covariates. Based on these results, a lifestyle risk index was developed. Finally, we explored common combinations of the risk factors in relation to all-cause and cardio-metabolic mortality outcomes. RESULTS: All single risk factors, except for diet, were significantly associated with both mortality outcomes, and were therefore selected to form a lifestyle risk index. Risk of mortality increased as the index score increased. The hazard ratio for all-cause mortality increased from 1.37 (1.15-1.62) to 6.15 (3.56-10.63) as the number of index risk factors increased from one to six respectively. Among the most common risk factor combinations the association with mortality was particularly strong when smoking and/or social participation were included. CONCLUSIONS: This study adds to previous research on multiple risk behaviours by incorporating emerging risk factors. Findings regarding social participation and prolonged sitting suggest new components of healthy lifestyles and potential new directions for population health interventions.

Retirement-A Transition to a Healthier Lifestyle?: Evidence From a Large Australian Study.

INTRODUCTION: Population aging is associated with a rising burden of non-communicable disease, profoundly impacting health policy and practice. Adopting and adhering to healthy lifestyles in middle or older age can protect against morbidity and mortality. Retirement brings opportunities to reconfigure habitual lifestyles and establish new routines. This study examines the longitudinal association between retirement and a range of lifestyle risk behaviors among a large population-based sample of Australian adults. METHODS: Study sample included working adults aged ≥45 years at baseline (2006-2009, N=23,478-26,895). Lifestyle behaviors, including smoking, alcohol use, physical activity, diet, sedentary behavior, and sleep, were measured at both baseline and follow-up (2010). Logistic regression models estimated the odds of having each risk factor at follow-up and multiple linear regression models calculated the change in the total number of risk factors, adjusted for baseline risk and other covariates. Sociodemographic characteristics and reasons for retirement were tested as potential effect modifiers. RESULTS: During the 3.3-year follow-up, about 11% of respondents retired. Retirement was associated significantly with reduced odds of smoking (AOR=0.74); physical inactivity (AOR=0.73); excessive sitting (AOR=0.34); and at-risk sleep patterns (AOR=0.82). There was no significant association between retirement and alcohol use or fruit and vegetable consumption. Change in the total number of lifestyle risk factors differed significantly by reason for retirement. CONCLUSIONS: In a large population-based Australian cohort, retirement was associated with positive lifestyle changes. Health professionals and policymakers should consider developing special programs for retirees to capitalize on the healthy transitions through retirement.

Out of Sight and Out of Mind? Evaluating the Impact of Point-of-Sale Tobacco Display Bans on Smoking-Related Beliefs and Behaviors in a Sample of Australian Adolescents and Young Adults.

INTRODUCTION: The Australian states of New South Wales (NSW) and Queensland implemented bans on tobacco pack displays at point-of-sale (PoS) in July 2010 and November 2011, respectively. This study evaluated the medium-term impact of the bans on youth. METHODS: Data were drawn from the Tobacco Promotion Impact Study, a repeated cross-sectional survey of youth (12-24 years) in NSW and Queensland conducted yearly 2010-2012 (n = 6,014). Regression analyses examined differences in youth's recall of PoS tobacco displays, smoking-related beliefs, and smoking behaviors in relation to the timing of the PoS display bans. RESULTS: Recall of PoS tobacco displays was significantly less likely for youth interviewed after the bans versus before (OR = 0.45, 95% CI = 0.39, 0.52, p < .01). They were also less likely to report tobacco brand awareness (OR = 0.76, 95% CI = 0.62, 0.92, p < .01), to over-estimate peer smoking (OR = 0.84, 95% CI = 0.74, 0.96, p < .01), or be current smokers (OR = 0.73, 95% CI = 0.55, 0.96, p < .05). Stratified analyses showed that these differences were primarily apparent in the group of youth most likely to be affected by tobacco PoS displays: those who visit tobacco retailers most frequently. After the bans, smokers were less likely to report that they think about smoking as a result of seeing PoS tobacco displays (OR = 0.60, 95% CI = 0.37, 0.97, p < .039). CONCLUSIONS: Our findings suggest an immediate impact of display bans on youth's exposure to tobacco pack displays, and likely impacts on smoking-related outcomes. These results suggest that removing tobacco displays from retail environments can positively contribute to the denormalization of smoking among youth.

A profile of callers to the New South Wales Quitline, Australia, 2008-2011.

INTRODUCTION: One population-level solution to smoking cessation are quitlines, telephone-based services to aid quitting. Monitoring the profile of quitline callers in a changing tobacco policy environment is important for informing future policy strategies and identifying target groups to improve the reach and impact of quitline services. METHODS: De-identified data from 43,618 new callers to the New South Wales Quitline, Australia between January 2008 and October 2011 (inclusive) were extracted from the Quitline database. Regression analyses explored the effect of year of first call on the distribution of demographic and smoking-related variables. RESULTS: Men calling the Quitline increased proportionately (prevalence ratio [PR] = 1.05, 95% CI = 1.03-1.08), but callers from non-major city areas fell (PR = 0.90, 95% CI = 0.87-0.93) in 2011 versus 2008. The proportion of callers not working demonstrated a significant increasing linear trend (PR = 1.08, p < .001), although area-level socioeconomic status did not change. The proportions of new Quitline callers who had stopped smoking (relative to still smoking) (relative risk ratio [RRR] = 1.29, 95% CI = 1.14-1.46) and who were classified as low nicotine dependent (vs. high nicotine dependent, RRR = 1.60, 95% CI = 1.39-1.83) were higher in 2011 versus 2008. Proportionately, more callers nominated "money" as a motivation to quit in 2010 (PR = 1.58, 95% CI = 1.49-1.66) and 2011 (PR = 1.70, 95% CI = 1.62-1.79) compared with 2008. CONCLUSIONS: Quitline callers showed decreasing tobacco consumption and dependence 2008 to 2011, but remained more addicted than the average NSW smoker. Clear effects of tobacco policy were shown, as money as a motivator increased dramatically in conjunction with increased tobacco taxation, highlighting the importance of promoting cessation services concurrent with policy change to capitalize on increased motivation to quit.

Tobacco promotion 'below-the-line': exposure among adolescents and young adults in NSW, Australia.

BACKGROUND: Exposure to tobacco advertising and promotion increases the likelihood of smoking amongst young people. While there is a universal ban on traditional or 'above-the-line' advertising in Australia, the types and extent of exposure of young people to 'below-the-line' tobacco advertising and promotion is largely unknown. In this study we aim to identify levels of exposure of New South Wales (NSW) adolescents and young adults to tobacco promotion at the point-of-sale (PoS), on the internet, in entertainment media and at venues such as events or festivals and pubs, clubs, nightclubs, or bars; and to identify those most at risk of exposure. METHODS: A telephone survey of 1000 NSW adolescents and young adults aged 12 to 24 years was conducted. Self-reported exposure to tobacco promotions or advertising in the last month were measured in four areas: (1) promotions or advertising at (a) events or festivals and (b) pubs, clubs, nightclubs or bars, (2) on the internet, (3) people smoking cigarettes in (a) movies, (b) TV shows, (c) video games and (d) on the internet, and (4) displays of cigarette packs for sale at (a) large supermarkets, (b) grocery stores or small supermarkets, (c) convenience stores, and (d) service or petrol stations. Smoking status and susceptibility to smoking was also assessed. RESULTS: A substantial proportion of the young people surveyed reported seeing tobacco promotion sometimes or often in the last month over most of the channels studied.The highest levels of exposure were at the PoS (approx. two-thirds) and to people smoking cigarettes in movies(77%). Lower levels of exposure to tobacco promotions and imagery were reported on the internet (20%); at events or festivals (22.5%); in pubs, clubs, nightclubs or bars (31%); and in video games (23%). However, the odds of exposure through video games increased by 8% for every additional hour spent on the internet per day. CONCLUSIONS: This study shows that adolescents and young adults in NSW are exposed to tobacco advertising or promotion at the PoS, on the internet, in entertainment media and at venues such as events or festivals and pubs, clubs, nightclubs or bars, despite the restrictions on the marketing of tobacco in Australia.

Australian athletes' health behaviours and perceptions of role modelling and marketing of unhealthy products.

ISSUE ADDRESSED: This study examined Australian athletes' support for athletes' role in promoting physical activity and obesity prevention, the acceptability of unhealthy products promotion in sport, and their own health behaviours. METHODS: Surveys were conducted with (n = 1990) elite and sub-elite athletes recruited from 22 sports across Australia. Athletes' perceptions and behaviours were analysed across demographic and sport-related factors (e.g. individual vs team sport) and correlations calculated between perceptions and health behaviours. RESULTS: Most respondents supported a role for athletes in promoting physical activity and obesity prevention, and disagreed that athletes should promote unhealthy foods and alcohol (73.9%). Athletes reported low smoking rates, but high rates of binge drinking. Female, younger, individual and amateur athletes had more health-positive perceptions and healthier behaviours than older, male, team and professional athletes. More sympathy towards junk food and alcohol advertising in sport and less support for athletes as role models were associated with more unhealthy behaviours. CONCLUSIONS: Elite athletes are receptive to supporting health promotion through sport and many are not in agreement with the promotion of unhealthy products in sport or by sports people. Improving elite athletes' health behaviours would benefit not only the individual but also health promotion within elite sport.