Gender-Based Heat Map Images of Campus Walking Settings: A Reflection of Lived Experience.

Fear of crime can influence our view of and experience with the world around us. This can be problematic for individuals seeking physical activity, including from walk commuting. Prior work shows fear is especially evident among women, who report fear of rape and sexual abuse by men as a primary concern. We present the results of a cross-sectional survey (n = 571) where participants were shown images from college campus (n = 4 campuses) depicting different lighting (daytime, nighttime), and entrapment levels (high, low; i.e., able to easily escape if needed, with high entrapment being difficult and low being easy), and using the Qualtrics heat map tool, selected features that stood out to them most. Data were segregated by gender and analyzed to determine similarity of heat maps for the same base image. Heat map images were analyzed using canonical correlation (Rc) to determine the relationship between the two groups; dispersion testing to decipher spatial uniformity within the images; the Structural Similarity Index (SSIM) to characterize the nature of image patterns differences; and, the Breslow-Day Test to specify pattern locations within images. Several heat map images are also presented in the results. Overall, female and male participants appear to "see" different things when imagining walk-commuting (as seen by poor Rc values) and the nature of what they were looking at were different (as seen by poor SSIM values). Female participants tended to focus on areas outside the walking path, such as bushes and dark areas, whereas men's focus was on the path ahead [χ2(1) = 4.29, p = 0.04]. Furthermore, women were more likely to select areas outside the walking path during high entrapment settings [χ2(1) = 15.49, p < 0.001] and at nighttime [χ2(1) = 4.98, p = 0.02]. Our study demonstrates point-of-view differences in female-male walking space assessments. Viewing walking safety through the lens of lived experience could be productive for holistic community walking safety.

Do healthcare providers consider the social determinants of health? Results from a nationwide cross-sectional study in the United States.

BACKGROUND: While the social determinants of health (SDOH) have a greater impact on individual health outcomes than the healthcare services a person receives, healthcare providers face barriers to addressing these factors in clinical settings. Previous studies have shown that providers often lack the necessary knowledge and resources to adequately screen for and otherwise assist patients with unmet social needs. This study explores the perceptions and behaviors related to SDOH among healthcare providers in the United States (US). METHODS: This cross-sectional study analyzed data from a 22-item online survey using Reaction Data's research platform of healthcare professionals in the US. Survey items included demographic questions as well as Likert scale questions about healthcare providers' perceptions and behaviors related to SDOH. Descriptive statistics were calculated, and further analyses were conducted using t-tests and analysis of variance. RESULTS: A total of 563 respondents completed the survey, with the majority being male (72.6%), White (81%), and located in urban areas (82.2%). In terms of perceptions, most providers agreed or strongly agreed that SDOH affect the health outcomes of all patients (68.5%), while only 24.1% agreed or strongly agreed that their healthcare setting was set up to address SDOH. In terms of behavior, fewer than half currently screened for SDOH (48.6%) or addressed (42.7%) SDOH in other ways. Most providers (55.7%) wanted additional resources to focus on SDOH. Statistical analyses showed significant differences by gender, with females being more likely than males to prioritize SDOH, and by specialty, with psychiatrists, pediatricians, and family/general medicine practitioners being more likely to prioritize SDOH. CONCLUSION: Most healthcare providers understand the connection between unmet social needs and their patients' health, but they also feel limited in their ability to address these issues. Ongoing efforts to improve medical education and shift the healthcare system to allow for payment and delivery of more holistic care that considers SDOH will likely provide new opportunities for healthcare providers. In addition to what they can do at the institutional and patient levels, providers have the potential to advocate for policy and system changes at the societal level that can better address the root causes of social issues.

Considering the Potential Health Impacts of Electric Scooters: An Analysis of User Reported Behaviors in Provo, Utah.

Electric scooters (e-scooters) are an increasingly popular form of transportation in urban areas. While research on this topic has focused primarily on injuries, there are multiple mechanisms by which e-scooter share programs may impact health. The aim of this study is to explore the health-related behaviors of e-scooter users and to discuss their implications for public health. Data were collected using an online survey emailed to registered e-scooter users. A total of 1070 users completed the survey. Descriptive variable statistics and chi-squared analysis were performed to determine variable dependent relationships and equality of proportions. The most common destinations reported were "just riding around for fun", home, and dining/shopping. The two most common modes of transportation that would have been used if e-scooters were not available were walking (43.5%) and using a personal vehicle (28.5%). Riding behavior was equally mixed between on the street, on the sidewalk, and equal amounts of both. e-Scooters in Provo are likely having both positive (e.g., air pollution) and negative impacts on health (e.g., injuries, physical inactivity). Future research should further explore patterns of e-scooter use and explicitly examine the linkages between e-scooters and areas of health beyond just injuries.

Pedal-Assist Mountain Bikes: A Pilot Study Comparison of the Exercise Response, Perceptions, and Beliefs of Experienced Mountain Bikers.

BACKGROUND: Mountain biking is an aerobic physical activity that has experienced rapid growth. The emergence of the electric pedal-assist mountain bike (eMTB), while not without its critics, presents the potential for an even larger segment of the population to enjoy the health benefits of mountain biking. Although the research focused on the use of e-bikes generally is growing, there is limited research specifically targeting eMTB use. Research is needed exploring the potential exercise response of riding an eMTB, together with the beliefs and perceptions of mountain bikers who have and have not experienced eMTB riding. OBJECTIVE: This study aimed to compare conventional mountain bike and eMTB use. This was done by investigating 2 questions: (1) What proportion of exercise response is retained for an experienced mountain biker while using an eMTB when compared with a conventional mountain bike? and (2) What are the perceptions and beliefs of experienced mountain bikers toward eMTBs both before and after riding an eMTB? METHODS: A convergent mixed methods data collection approach was used in the study. Participants completed both a pre- and postride questionnaire, and data regarding heart rate were collected. Heart rates from each ride were compared against each other. RESULTS: The average heart rate during eMTB use was 94% (31/33) of the average heart rate during conventional mountain bike use. Therefore, eMTB use in this study achieved a majority of the exercise response and exceeded established biometric thresholds for cardiovascular fitness. Paired t test statistics were calculated to compare beliefs of conventional mountain bikes and eMTBs and to compare mean heart rate and speed between conventional mountain bike and eMTB use on the study loop. Participants overwhelmingly perceived the potential impact of eMTB use to be positive on both pre- and post-eMTB ride questionnaires. CONCLUSIONS: Despite the measured benefit, participants' perceived exertion while riding the eMTB was low.

Intra-urban patterns of neighborhood-level social capital: a pilot study.

Background: Social capital is a construct of interaction and social trust in one's fellow community members. These interactions can provide a safety net for individuals in terms of information, social support, and adherence to social norms. While a number of studies have previously examined the relationship between social capital and health outcomes, few have examined the theparallel relationship of social capital and geographic "place" with respect to health outcomes. Methods: Considering social capital as facilitated by specific structures, we evaluate the relationship between neighborhood-level social capital and disability rates in a major Southern US city. Disability rates were collected through neighborhood-level data via the AmericanCommunity Survey (ACS) and compared to a geocoded map of neighborhood-level social capital measures during spring, 2016. Results: Higher social capital within a neighborhood coincided with lower disability rates in that neighborhood (r=-0.14, P=0.016) when compared to random assortment models. Conclusion: Findings from this research add evidence to the value of the built environment, not only providing resources and shaping choices, but for facilitating important social relationships.

Access to Soft-Surface, Green Exercise Trails in Mountainous, Urban Municipalities.

Soft-surface exercise infrastructure (ie off-road, mountain, and dirt trails) has been a particularly valuable community asset in mountainous, urban municipalities. This off-road, trail infrastructure can encourage individuals to engage in green exercise (ie physical activity done outside while in nature, for example, mountainous trails and near waterways). Green exercise can be helpful for encouraging individuals to participate in exercise who otherwise may not; it is especially helpful for promoting mental well-being and a sense of being connected to the environment. This study characterizes trail access and predictors among urban, mountainous municipalities in the Utah Wasatch Front region. Access was determined using two-standard deviation ellipses (2SDE) activity space analysis, and predictors were identified using multiple linear regression. About 42% municipalities had no trailhead access (ie no trailhead within its corresponding activity space). Trail density and trailheads were significantly correlated (r = 0.49, P = .004). There was a significant trail density cluster in the southern area of the study region, centered all over the city of Alpine. Reduced-model regression yielded trailheads and home income as being significant predictors of trail density, and trail density and elevation as being significant predictors for trailheads. Results demonstrate patterns of access to green exercise trails that align with socioeconomic and municipal elevation. The results of this research should be insightful for those who work in exercise promotion and urban planners.

Personal exposure to fine particulate air pollution while commuting: An examination of six transport modes on an urban arterial roadway.

Traffic-related air pollution in urban areas contributes significantly to commuters' daily PM2.5 exposures, but varies widely depending on mode of commuting. To date, studies show conflicting results for PM2.5 exposures based on mode of commuting, and few studies compare multiple modes of transportation simultaneously along a common route, making inter-modal comparisons difficult. In this study, we examined breathing zone PM2.5 exposures for six different modes of commuting (bicycle, walking, driving with windows open and closed, bus, and light-rail train) simultaneously on a single 2.7 km (1.68 mile) arterial urban route in Salt Lake City, Utah (USA) during peak "rush hour" times. Using previously published minute ventilation rates, we estimated the inhaled dose and exposure rate for each mode of commuting. Mean PM2.5 concentrations ranged from 5.20 µg/m3 for driving with windows closed to 15.21 µg/m3 for driving with windows open. The estimated inhaled doses over the 2.7 km route were 6.83 µg for walking, 2.78 µg for cycling, 1.28 µg for light-rail train, 1.24 µg for driving with windows open, 1.23 µg for bus, and 0.32 µg for driving with windows closed. Similarly, the exposure rates were highest for cycling (18.0 µg/hr) and walking (16.8 µg/hr), and lowest for driving with windows closed (3.7 µg/hr). Our findings support previous studies showing that active commuters receive a greater PM2.5 dose and have higher rates of exposure than commuters using automobiles or public transportation. Our findings also support previous studies showing that driving with windows closed is protective against traffic-related PM2.5 exposure.

Spatial Analysis Methods for Health Promotion and Education.

This article provides a review of spatial analysis methods for use in health promotion and education research and practice. Spatial analysis seeks to describe or make inference about variables with respect to the places they occur. This includes geographic differences, proximity issues, and access to resources. This is important for understanding how health outcomes differ from place to place; and in terms of understanding some of the environmental underpinnings of health outcomes data by placing it in context of geographic location. This article seeks to promote spatial analysis as a viable tool for health promotion and education research and practice. Four more commonly used spatial analysis techniques are described in-text. An illustrative example of motor vehicle collisions in a large metropolitan city is presented using these techniques. The techniques discussed are as follows: descriptive mapping, global spatial autocorrelation, cluster detection, and identification and spatial regression analysis. This article provides useful information for health promotion and education researchers and practitioners seeking to examine research questions from a spatial perspective.

Characterizing bicycle collisions by neighborhood in a large Midwestern city.

INTRODUCTION: Local environmental factors provide important contributions to bicycle safety. The purpose of this study was to characterize bicycle collisions by neighborhood in Cincinnati, Ohio. BACKGROUND: The majority of prior bicycle safety research has focused on helmet use, especially among youth. Studies that have considered the neighborhood have centered on the built environment and its facilitation of bicycling (e.g., connectivity of roads and road conditions). Other broad conditions may be associated with injury beyond the use of protective equipment and the physical environment. METHOD: This study sought to determine spatial clustering, local patterning, temporal differences (time of day and season of year), and significant neighborhood-level predictors of bicycle collisions. Bicycle collision data were obtained from the Cincinnati, Ohio Police Department. CONCLUSIONS: This study showed that collisions occur at higher rates in the south-central and southwest neighborhoods of Cincinnati, Ohio. There were seasonal and time-of-day differences with respect to collision rates with summer and afternoon being the most common collision times. Neighborhood ethnicity, population density and presence of public transportation were all significant predictors of bicycle collisions. These findings will be disseminated to local city authorities and bicycle advocacy groups.

Characterizing active transportation behavior among college students using the theory of planned behavior.

Physical inactivity poses concern for health risks among all groups in the United States. Active transportation (AT) (e.g., bicycling) is one way of being physically active and may be helpful in promoting physical activity. This study characterized active transportation behavior among college students using the Theory of Planned Behavior. This study sought to describe predictors, including Theory of Planned Behavior (TPB) constructs, of AT behavior among college students at a large Midwest university. Students were recruited through the university registrar's office and e-mailed an electronic survey. Differences among AT users were determined using t-tests, and predictors of AT were identified using regression analysis. Significant differences between AT users for all TPB constructs were observed. Regression analysis using only TPB constructs accounted for 11.58% explained variation in AT use. Other variables added to the model resulted in 44.44% explained variation in AT use. The final model included subjective norms, age, perceived behavioral control, and transportation type and destination. The results of this research are insightful in explaining AT behavior. Perceived norms and the level of control students had regarding their method of transportation were important contributions to AT use. These results may be applied to promoting physical activity in community health.