Do objective and subjective traffic-related pollution, physical activity and nature exposure affect mental wellbeing? Evidence from Shenzhen, China

Objective and subjective accounts of urban exposures for epidemiological research on mental health. Measurement and analysis

The interest in the impact of urban environmental exposures (UrbEEs) on mental health has greatly increased in the last two decades. Researchers have tended to measure said exposures either via objective measurement procedures (eg, air pollution campaigns and geographic information systems computations) or by self-reported techniques such as the use of scales and questionnaires. It has been suggested that studying both the objective features of the environments and people's perceptions are key to understand environmental determinants of health and might be needed to tailor effective interventions. However, there is little guidance on how to approach this matter, the comparability between objective and subjective accounts of UrbEEs and, more importantly, suitable statistical procedures to deal with the practicalities of this kind of data. In this essay, we aim to build the case for the joint use of both sets of variables in epidemiological studies and propose socioecological models as a valid theoretical framework to accommodate these. In the methodological sphere, we will also review current literature to select examples of (un)appropriate subjective accounts of urban exposures and propose a series of statistical procedures to estimate the total, direct and indirect effects of UrbEEs on mental health and the potential associations between objective and subjective UrbEEs accounts.

Association between outdoor jogging behavior and PM2.5 exposure: Evidence from massive GPS trajectory data in Beijing

Outdoor jogging is one of the most popular practised exercises worldwide, providing various benefits for health and wellbeing. However, PM2.5 exposure risks of jogging behaviors were rarely explored. This study aims to investigate the association between jogging behavior and PM2.5 exposure with big data. PM2.5 exposure concentration and dose inhalation of individuals were calculated by integrating hourly PM2.5 concentration data and jogging GPS trajectory recorded by a sports app during 2015 in Beijing, after which relationships between jogging behaviors and PM2.5 exposure were unpacked using statistics analysis and structural equation modelling. Experimental results on massive jogging trajectories show that: (1) the average jogging PM2.5 exposure concentration is 60.43 μg/m3, and female joggers inhaled significantly less air pollution dose (19.70 μg) than men (24.91 μg). (2) There exist significant spatiotemporal disparities in jogging exposure to PM2.5. Joggings in the city center, in the morning, on weekdays and in autumn and winter seasons were exposed to higher pollution concentrations. (3) Jogging behavior characteristics, especially distance, activity space size, duration and rotation, were systematically associated with PM2.5 exposure across space and time. (4) The role of gender directly shaped joggers' dose inhalation of PM2.5 pollution and indirectly via duration, timing choice and distance. (5) The effects of weather conditions on joggers' exposure to PM2.5 are mainly via direct effects, whereas the direct impacts of precipitation and wind speed are mitigated by indirect effects stemming from jogging behavior patterns. Our findings provide insights for personal guidance and policy intervention for the sake of promoting physical activity and reducing PM2.5 exposure.

Association between green space and multiple ambient air pollutants with depressive and anxiety symptoms among Chinese adolescents: The role of physical activity

OBJECTIVE

To explore the association between green space, multiple ambient air pollutants and depressive/anxiety symptoms and the mediating role of physical activity (PA) in Chinese adolescents.

METHOD

A school-based health survey was conducted in eight provinces in China in 2021. 22,868 students aged 14.64 (±1.77) years completed standard questionnaires to record details of depressive, anxiety symptoms and PA. We calculated the average normalized difference vegetation index (NDVI) in circular buffers of 200 m, 500 m and 1000 m and estimated the concentrations of PM10, PM2.5, CO, NO2, O3, SO2 around the adolescents' school addresses.

RESULTS

The exposure-response curves showed that the lower the NDVI value, the higher the risk of depressive and anxiety symptoms. CO, PM2.5 and SO2 and air pollution score were associated with increased risk of depressive and anxiety symptoms. NDVI in all circular buffers decreased the risk of depressive and anxiety symptoms at low levels of PA, but the associations were not significant at high levels of PA. In the subgroup analysis, PM10, PM2.5, CO, NO2, SO2, AQI and air pollution score increased the risk of depressive and anxiety symptoms at low PA levels, but the associations were not significant at high levels of PA. Mediation analysis indicated that the mediating effect of PA on the association between NDVI, NDVI-200 m NDVI-500 m, CO, PM10, PM2.5, SO2, AQI and depressive/anxiety symptoms was statistically significant（p < 0.05）.

CONCLUSION

Middle-high level PA could reduce the strength of association between air pollution and depressive and anxiety symptoms. Meanwhile, the association between green space/air pollution and depressive/anxiety symptoms was partly mediated by PA.

Exploring the effect of different typical plant community on human stress reduction: a field experiment

Research has demonstrated the positive effect of natural environment on human restoration and well-being. Time spent in nature can often alleviate both physiological and psychological stress. However, few studies have discussed the environmental health effects of the nature's components and characteristics. Sixty volunteers were recruited and one manufactured environment and five different natural environments were randomly assigned to them, including coniferous forests (pure coniferous forest-PC and mixed coniferous forest-MC), broad-leaved forests (pure broad-leaved forest-PB and mixed broad-leaved forest-MB), and mixed forest (mixed coniferous and broad-leaved forest-MCB). Each volunteer sat in a built or natural environment and looked around the environment for 15 min. Physiological (HR, HRV, BP, pulse rate and salivary cortisol) and psychological indicators (POMS and STAI) were used to evaluate the changes in their stress level. Results indicated a strong difference in HR, HRV, POMS and STAI between the built and natural environment, which showed that natural environment can lower the stress level. MC had the best effect on relieving physiological stress, whereas MCB is most successful in improving emotional state and reducing anxiety. Broad-leaved forest and mixed forest significantly affected the DBP and vigor level of the subjects, respectively. While coniferous forest did significantly increase the concentration of salivary cortisol in subjects. The study confirmed that compared to the built environment, the natural environment can relieve the human body's physical and psychological stress and negative emotions, while significantly increasing vitality. And different plant communities also have different effects on the physiological and psychological indicators of the subjects. These results will provide scientific basis for the construction and improvement of urban green space environment.

Traffic noise distribution characteristics of high-rise buildings along ultra-wide cross section highway with multiple noise reduction measures

Nowadays, ultra-wide cross section highway is a hotspot in construction and brings some unique noise distribution characteristics. In this work, we further investigate noise distribution characteristics of diverse building layouts along ultra-wide cross section highway in Guangdong Province with multiple noise mitigation measures. By the aid of vehicle noise emission model and noise mapping, the influence of high-rise building layouts and shielding in the urban planning on noise mitigation is also considered. Some key findings are summarized as follows: (1) Under the same distance, the noise level of non-frontage building facades is higher than frontage building facades. After taking noise reduction measures, the noise reduction effect of non-street-facing building facades, buildings facing the road, and buildings at a long distance to the road is greater than street-facing building facades, buildings sideways to the road, and buildings at a short distance; (2) the distribution trend of insertion loss (IL) of non-frontage buildings is influenced by the height of the frontage buildings. Specifically, the trend of insertion loss first increases and then decreases as the floor rises when the height of non-frontage buildings is higher than frontage buildings. Comparatively, the trend of insertion loss decreases as the floor rises when the height of non-frontage buildings is equal to frontage buildings; (3) when double noise reduction measures are implemented, the noise distribution trend in buildings is similar to that observed with individual noise reduction measure, where the difference between both is only 0.6 dB(A). Thanks to the high representativeness of the case area, this work can provide some design guidance for the urban planning and the selection of noise reduction measures along the ultra-wide cross section highway.

Exploring the non-linear relationship and synergistic effect between urban built environment and public sentiment integrating macro- and micro-level perspective: a case study in San Francisco

Public sentiment can effectively evaluate the public's feelings of well-being in the urban environment and reflect the quality of the spatial environment to a certain extent. Previous studies on the relationship between public sentiment and urban built environmental factors have yielded meaningful results. However, few studies have focused on the effect of micro-built environment on public sentiment at the street level, which directly shapes people's perceptions. In addition, the nonlinear relationship and synergistic effect among urban built environmental factors have been commonly disregarded in previous studies, resulting in an incomplete understanding of the impact of urban built environment on public emotions. Therefore, this paper takes San Francisco as a study case to explore the complex relationship between urban built environmental factors and public emotions. Specifically, this paper measures the polarity of public emotions through sentiment analysis on Twitter data, establishes a comprehensive built environment index system from both macro- and micro- perspectives, and subsequently explores the complex relationship between the urban built environment and public sentiment through the OLS model and Shapley Additive Explanation algorithm. Results show that: (1) micro-built environmental factors have a significant influence on public emotion, although they have been frequently ignored. (2) Public sentiment tends to be more positive in areas with recreation facilities, mixed land use, rich street view visual environment, suitable thermal and acoustic environment, balanced income, and a suitable degree of high population density. (3) A nonlinear relationship and threshold effect exist between the built environmental variables and the semantic orientations of public emotion. Environment improvement strategies based on the synergic effect between variables can effectively promote the generation of positive emotions. Our empirical findings can offer valuable insights to promote feelings of well-being and foster an urban development approach through strategic interventions within the urban built environment.

Parenthood, spatial temporal environmental exposure, and leisure-time physical activity participation: Evidence from a micro-timescale retrospective longitudinal study

Parents with dependent children are at a high risk of physical inactivity. While previous studies have mostly focused on how parents' time constraints and changing social network may inhibit leisure time physical activity (LTPA) over the long-term, less is known about the integrated effects of parenting and spatial-temporal environmental exposure on the execution of LTPA during certain episodes of a day. By adopting an integrated social-spatiotemporal-environmental model (ST-ISEM) based on micro-timescale retrospective longitudinal analysis, we examine the association between LTPA participation and spatial-temporal environmental exposure at a micro-timescale, i.e., at the episode-level in working adults' workday, and specifically how parenting integrated with spatial-temporal environmental exposure can jointly influence episode-level LTPA participation. Using data from the day reconstruction method from 701 individuals in Shenzhen, China, we find that parenting may affect the participation of LTPA on workdays not only by shaping temporal environmental factors (time constraint path and social network path), but also by interacting with built environmental exposures (spatial path), both at the episode-level. This study contributes to the theorizing of an integrated social-environmental model for health and wellbeing by extending the ISEM from the life span to the micro-timescale and also by highlighting the importance of temporality in environmental exposure and health studies. It also contributes to the spatial temporal behavioral perspective of time geography literature by clarifying multiple pathways through which social and spatiotemporal environmental factors could interact and jointly affect health behaviors at a micro-timescale. This study contributes to the literature on parenting and LTPA decline by enriching and deepening the understanding of the time constraint and social network pathways through which parenting leads to LTPA change at the micro-timescale. While time constraints may decrease parents' LTPA at long-term, increasing physical activities related to childcare after work may strongly obstruct moderate-to-vigorous LTPA at a micro-timescale. This study also identifies a spatial pathway by which parenting hinders LTPA due to changing understanding and usage of urban spaces. This pathway warrants attention from social epidemiologists, health geographers, and urban planners since existing interventions promoting physical activity in urban spaces may be ineffective for parents.

Using geospatial trajectories to explore how the COVID-19 pandemic affects the associations between environmental attributes and runnability of park trails

The worldwide coronavirus disease 2019 (COVID-19) pandemic and the associated social distancing measures have produced alterations in park visits of individuals, as well as their park-based physical activity (e.g. running exercise). Although studies on the influence of the COVID-19 pandemic on changes in running activity patterns are becoming an emerging focus, less is known about how these changes are related to the environmental attributes of parks before and after the pandemic, the knowledge of which is essential to planning green infrastructure that better supports physical activities. Therefore, we employed a volunteered geographic information approach to investigate the runnability of park trails in Shenzhen, utilizing self-tracking routes from Strava, in order to uncover the associations between trail characteristics and park features with the running intensity before and after the pandemic. Multilevel regression model analyses revealed that trail network connectivity was the only environmental attribute indicating consistent and positive associations with running intensity. Blue space density was positively correlated with running intensity in urban parks but indicated no significant association in forest parks before the pandemic. In the pre-pandemic era, population density was positively related to running intensity in urban and forest parks. However, after the pandemic, the associations between running behaviours and population density remained positive in forest parks but turned insignificant in urban parks. The outbreak of the pandemic also altered the influence of other park features (e.g. park shape and trail density) on running intensity. The evidence-based knowledge provides planners with significant insights into pandemic-resilient park planning for the post-COVID era.

Are the epidemic prevention facilities effective? How cities should choose epidemic prevention facilities: Taking Wuhan as an example

The COVID-19 pandemic highlighted the limitations of urban public health emergency response capabilities. Taking Wuhan as an example, this study used breakpoint regression, kernel density analysis, overlay analysis, and accessibility analysis from Stata and ArcGIS, and divided epidemic prevention facilities into the basic epidemic prevention facilities (hospitals), and the emergency epidemic prevention facilities (mobile cabin hospitals) for further analysis. The results showed that over 70% of the basic epidemic prevention facilities in Wuhan were located in high density population areas. On the contrary, most of the emergency epidemic prevention facilities were located in low density population areas. The local treatment effect of the implementation of the emergency epidemic prevention facility policy is about 1, indicating that there was a significant impact of emergency epidemic prevention facilities on outbreak control, which passed the bandwidth test. What’s more, the analysis of the accessibility of residential points revealed that more than 67.3% of people from the residential points could arrive at the epidemic prevention facilities within 15 min, and only 0.1% of them took more than 20 min to arrive. Therefore, the epidemic prevention facilities can effectively curb the spread of the epidemic, and people from residential areas can quickly get there. This study summarized the spatial characteristics of epidemic prevention facilities in Wuhan and analyzed the importance of them, thus providing a new perspective for future research on upgrading the city’s comprehensive disaster prevention system.