Traffic-related air pollution in urban areas contributes significantly to commuters’ daily PM_2.5 exposures, but varies widely depending on mode of commuting. To date, studies show conflicting results for PM_2.5 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 PM_2.5 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 PM_2.5 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 PM_2.5 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 PM_2.5 exposure.

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.

Air pollution causes more damage to health and economy than previously understood, contributing to approximately one in six deaths globally. However, pollution reduction policies remain controversial even when proven effective and cost negative, partially because of misunderstanding and growing mistrust in science. We used an expert assessment to bridge these research–policy divides in the State of Utah, USA, combining quantitative estimates from 23 local researchers and specialists on the human health and economic costs of air pollution. Experts estimated that air pollution in Utah causes 2480 to 8000 premature deaths annually (90% confidence interval) and decreases the median life expectancy by 1.1 to 3.6 years. Economic costs of air pollution in Utah totaled $0.75 to $3.3 billion annually, up to 1.7% of the state’s gross domestic product. Though these results were generally in line with available estimates from downscaled national studies, they were met with surprise in the state legislature, where there had been an almost complete absence of quantitative health and economic cost estimates. We discuss the legislative and personal responses of Utah policy makers to these results and present a framework for increasing the assimilation of data into decision making via regional expert assessment. In conclusion, combining quantitative assessments from local experts is a responsive and cost-effective tool to increase trust and information uptake during time-sensitive policy windows.

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.

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 [ χ ² (1) = 4.29, p = 0.04]. Furthermore, women were more likely to select areas outside the walking path during high entrapment settings [ χ ² (1) = 15.49, p < 0.001] and at nighttime [ χ ² (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.