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BackgroundThere is increasing interest in using smartphones as stand-alone physical activity monitors via their built-in accelerometers, but there is presently limited data on the validity of this approach. ObjectiveThe purpose of this work was to determine the validity and reliability of 3 Android smartphones for measuring physical activity among midlife and older adults. MethodsA laboratory (study 1) and a free-living (study 2) protocol were conducted. In study 1, individuals engaged in prescribed activities including sedentary (eg, sitting), light (sweeping), moderate (eg, walking 3 mph on a treadmill), and vigorous (eg, jogging 5 mph on a treadmill) activity over a 2-hour period wearing both an ActiGraph and 3 Android smartphones (ie, HTC MyTouch, Google Nexus One, and Motorola Cliq). In the free-living study, individuals engaged in usual daily activities over 7 days while wearing an Android smartphone (Google Nexus One) and an ActiGraph. ResultsStudy 1 included 15 participants (age: mean 55.5, SD 6.6 years; women: 56%, 8/15). Correlations between the ActiGraph and the 3 phones were strong to very strong (ρ=.77-.82). Further, after excluding bicycling and standing, cut-point derived classifications of activities yielded a high percentage of activities classified correctly according to intensity level (eg, 78%-91% by phone) that were similar to the ActiGraph’s percent correctly classified (ie, 91%). Study 2 included 23 participants (age: mean 57.0, SD 6.4 years; women: 74%, 17/23). Within the free-living context, results suggested a moderate correlation (ie, ρ=.59, P

BackgroundMost U.S. states have legalized cannabis for medical and/or recreational use. In a 6-month prospective observational study, we examined changes in adult cannabis use patterns and health perceptions following broadened legalization of cannabis use from medical to recreational purposes in California.MethodsRespondents were part of Stanford University's WELL for Life registry, an online adult cohort concentrated in Northern California. Surveys were administered online in the 10 days prior to state legalization of recreational use (1/1/18) and 1-month (2/1/18-2/15/18) and 6-months (7/1/2018-7/15/18) following the change in state policy. Online surveys assessed self-reported past 30-day cannabis use, exposure to others' cannabis use, and health perceptions of cannabis use. Logistic regression models and generalized estimating equations (GEE) examined associations between participant characteristics and cannabis use pre- to 1-month and 6-months post-legalization.ResultsThe sample (N = 429, 51% female, 55% non-Hispanic White, age mean = 56 ± 14.6) voted 58% in favor of state legalization of recreational cannabis use, with 26% opposed, and 16% abstained. Cannabis use in the past 30-days significantly increased from pre-legalization (17%) to 1-month post-legalization (21%; odds ratio (OR) = 1.28, p-value (p) = .01) and stayed elevated over pre-legalization levels at 6-months post-legalization (20%; OR = 1.28, p = .01). Exposure to others' cannabis use in the past 30 days did not change significantly over time: 41% pre-legalization, 44% 1-month post-legalization (OR = 1.18, p = .11), and 42% 6-months post-legalization (OR = 1.08, p = .61). Perceptions of health benefits of cannabis use increased from pre-legalization to 6-months post-legalization (OR = 1.19, p = .02). Younger adults, those with fewer years of education, and those reporting histories of depression were more likely to report recent cannabis use pre- and post-legalization. Other mental illness was associated with cannabis use at post-legalization only. In a multivariate GEE adjusted for sociodemographic characteristics and diagnoses, favoring legalization and the interaction of time and positive health perceptions were associated with a greater likelihood of using cannabis.ConclusionsLegalized recreational cannabis use was associated with greater self-reported past 30-day use post-legalization, and with more-positive health perceptions of cannabis use. Future research is needed to examine longer-term perceptions and behavioral patterns following legalization of recreational cannabis use, especially among those with mental illness.

BackgroundPhysical inactivity across the lifespan remains a public health issue for many developed countries. Inactivity has contributed considerably to the pervasiveness of lifestyle diseases. Government, national and local agencies and organizations have been unable to systematically, and in a coordinated way, translate behavioral research into practice that makes a difference at a population level. One approach for mobilizing multi-level efforts to improve the environment for physical activity is to engage in a process of citizen science. Citizen Science here is defined as a participatory research approach involving members of the public working closely with research investigators to initiate and advance scientific research projects. However, there are no common measures or protocols to guide citizen science research at the local community setting.ObjectivesWe describe overarching categories of constructs that can be considered when designing citizen science projects expected to yield multi-level interventions, and provide an example of the citizen science approach to promoting PA. We also recommend potential measures across different levels of impact.DiscussionEncouraging some consistency in measurement across studies will potentially accelerate the efficiency with which citizen science participatory research provides new insights into and solutions to the behaviorally-based public health issues that drive most of morbidity and mortality. The measures described in this paper abide by four fundamental principles specifically selected for inclusion in citizen science projects: feasibility, accuracy, propriety, and utility. The choice of measures will take into account the potential resources available for outcome and process evaluation. Our intent is to emphasize the importance for all citizen science participatory projects to follow an evidence-based approach and ensure that they incorporate an appropriate assessment protocol.ConclusionsWe provided the rationale for and a list of contextual factors along with specific examples of measures to encourage consistency among studies that plan to use a citizen science participatory approach. The potential of this approach to promote health and wellbeing in communities is high and we hope that we have provided the tools needed to optimally promote synergistic gains in knowledge across a range of Citizen Science participatory projects.

Walking is a central form of physical activity among older adults that is associated with the physical environment at various scales. This mixed-methods study employs a concurrent nested design to explore objective and perceived environmental characteristics of older adults’ local walking routes. This was achieved by integrating quantitative Geographic Information System (GIS) data with qualitative data obtained using the Stanford Discovery Tool (DT). Fifty-nine community-dwelling middle-aged and older adults (14 men and 45 women aged 50+) were recruited in a snowball approach through community centers in the city of Haifa (Israel). Four neighborhood environment themes were identified: pedestrian infrastructure, access to destinations, aesthetics, and environmental quality. Both geometrical traits (i.e., distance, slope) and urban features (i.e., land-uses, greenery) of the route may impact the experience of walking. The findings thus highlight the importance of micro-scale environmental elements in shaping environmental perceptions, which may consequently influence the choice of being active. [ABSTRACT FROM AUTHOR]

Objective: To estimate the risk profile of coronary heart disease (CHD) among the staff members of Qassim University and assess their knowledge in a screening campaign in Qassim region, Saudi Arabia. Methods: A cross-sectional study was conducted among male and female staff at Qassim University campus. All employees of Qassim University were invited to participate in the study. Data were collected through a self-administered questionnaire. The study sample size was 233 staff and employees. The data were entered and analyzed using SPSS version 18. The data analysis focused on providing point estimates for the risk factors. Results: The study found that 30% of participants have one or more risk factors for CHD, namely obesity 20.6%, diabetes 10.3%, hypertension 12.4%, dyslipidemia 10.7%, and smokers (11.6%). About 54% of the participants have a family history of at least one chronic disease as a risk factor for CHD. Conclusion: The most common risk factor of CHD among the staff members is obesity by 20.6%. Risk factors for CHD are quite common among Qassim University staff. These findings need to increase the health education and disease promotion program as an important intervention to reduce the occurrence and severity of CHD risk factors and to improve the quality of the life of the staff members of Qassim University. [ABSTRACT FROM AUTHOR]