Perceptions of air quality and concern for health in relation to long-term air pollution exposure, bushfires, and COVID-19 lockdown: A before-and-after study.

Background: Air pollution is a major health burden and the leading environmental risk factor for non-communicable diseases worldwide. People's perceptions and concerns about air pollution are important as they may predict protective behaviour or support for climate change mitigation policies. Methods: This repeat cross-sectional study uses survey data collected from participants in Sydney, Australia in September-November 2019 (n = 1,647) and October-December 2020 (n = 1,458), before and after the devastating 2019/2020 bushfires and first COVID-19 lockdown restrictions in Sydney in 2020. Participants' perceptions of air quality and concerns for health in relation to air quality were modeled against estimates of annual average NO2 and PM2.5 concentrations in their neighbourhood. Results: Participants in suburbs with higher estimated air pollution concentrations generally perceived poorer air quality and were more concerned for health in relation to air quality. A 5 µg/m3 increase in NO2 was associated with perceived poorer air quality (OR 1.32, 95%CI 1.18-1.47). A 1 µg/m3 increase in estimated PM2.5 was associated with perceived poorer air quality (OR 1.37, 95%CI 1.24-1.52) and greater concern for health (OR 1.18, 95%CI 1.05-1.32). Air quality was perceived as better in 2020 than in 2019 in both NO2 and PM2.5 models (p<0.001). Air quality concern increased in 2020 in both models. Discussion: This study provides the first Australian data on the association between estimated air quality exposure and air quality perceptions and concerns, contributing new evidence to inform public health approaches that increase awareness for air pollution and reduce the health burden.

Speeding in urban environments: Are the time savings worth the risk?

Perceived time savings by travelling faster is often cited as a motivation for drivers' speeding behaviour. These time savings, however, come at a cost of significant road injuries and fatalities. While it is known that drivers tend to overestimate the time savings attributable to speeding there is little empirical evidence on how much time drivers genuinely save during day-to-day urban driving and how this relates to speeding-related crashes. The current paper reports on a study to address the lack of empirical evidence on this issue using naturalistic driving data collected from 106 drivers over a period of five weeks. The results show that the average driver saves 26s/day or 2min/week by speeding. More importantly, the cost of these time savings is one fatality for every 24,450h saved by the population on 100km/h roads in dry conditions and one injury for every 2458h saved on the same roads. Full speed compliance - and consequently a dramatic reduction in the road toll - could be achieved through almost imperceptible increases in travel time by each driver.

Time-series analysis of continuously monitored blood glucose: the impacts of geographic and daily lifestyle factors.

Type 2 diabetes is known to be associated with environmental, behavioral, and lifestyle factors. However, the actual impacts of these factors on blood glucose (BG) variation throughout the day have remained relatively unexplored. Continuous blood glucose monitors combined with human activity tracking technologies afford new opportunities for exploration in a naturalistic setting. Data from a study of 40 patients with diabetes is utilized in this paper, including continuously monitored BG, food/medicine intake, and patient activity/location tracked using global positioning systems over a 4-day period. Standard linear regression and more disaggregated time-series analysis using autoregressive integrated moving average (ARIMA) are used to explore patient BG variation throughout the day and over space. The ARIMA models revealed a wide variety of BG correlating factors related to specific activity types, locations (especially those far from home), and travel modes, although the impacts were highly personal. Traditional variables related to food intake and medications were less often significant. Overall, the time-series analysis revealed considerable patient-by-patient variation in the effects of geographic and daily lifestyle factors. We would suggest that maps of BG spatial variation or an interactive messaging system could provide new tools to engage patients and highlight potential risk factors.

Driver behaviour profiles for road safety analysis.

Driver behaviour is a contributing factor in over 90 percent of road crashes. As a consequence, there is significant benefit in identifying drivers who engage in unsafe driving practices. Driver behaviour profiles (DBPs) are introduced here as an approach for evaluating driver behaviour as a function of the risk of a casualty crash. They employ data collected using global positioning system (GPS) devices, supplemented with spatiotemporal information. These profiles are comprised of common risk scores that can be used to compare drivers between each other and across time and space. The paper details the development of these DBPs and demonstrates their use as an input into modelling the factors that influence driver behaviour. The results show that even having controlled for the influence of the road environment, these factors remain the strongest predictors of driver behaviour suggesting different spatiotemporal environments elicit a variety of psychological responses in drivers. The approach and outcomes will be of interest to insurance companies in enhancing the risk-profiling of drivers with on-road driving and government through assessing the impacts of behaviour-change interventions.

Evaluating changes in driver behaviour: a risk profiling approach.

New road safety strategies continue to be devised by researchers and policy makers with pay-as-you-drive (PAYD) schemes gaining increasing attention. However, empirically measuring the effectiveness of these strategies is challenging due to the influence of the road environment and other factors external to the driver. The analysis presented here applies Temporal and Spatial Identifiers to control for the road environment and Driver Behaviour Profiles to provide a common measure of driving behaviour based on the risk of a casualty crash for assessing the effectiveness of a PAYD scheme on reducing driving risks. The results show that in many cases personalised feedback alone is sufficient to induce significant changes, but the largest reductions in risk are observed when drivers are also awarded a financial incentive to change behaviour. Importantly, the more frequent the exposure to the speeding information, the greater the magnitude of the change. However, the changes are disproportionately associated with those that were already safer drivers in the baseline period suggesting that some drivers may be predisposed to changing their behaviour. These results suggest that it would be beneficial to provide real-time or daily feedback on speeding behaviour in conjunction with a financial reward scheme, potentially as a component of insurance premiums.

Personality, risk aversion and speeding: an empirical investigation.

Evidence suggests that in addition to demographics, there are strong relationships between facets of drivers' personality (e.g., aggression, thrill-seeking, altruism), aversion to risk and driving behaviour, particularly speeding. However, evidence is muted by the reliance on self-reported driving behaviour, which is thought to not accurately reflect actual driving behaviour. This paper reports on a study of 133 drivers in Sydney, who were asked to complete a short survey to develop their personality and risk aversion profiles and self-reported speeding behaviour. A Global Positioning System (GPS) device was then installed in their vehicle for several weeks as part of a major investigation of driving behaviour from which empirical measures of speeding are derived. Among the most pertinent findings are: (1) the tendency for drivers to both under and over-estimate their propensity to speed, (2) significant heterogeneity in speeding with a small, but notable number of drivers exceeding the limit for more than 20 percent of the distance driven, (3) weak relationships between the personality/risk-aversion measures and actual speeding, and (4) the suggestion that different personality traits appear to influence behaviour in different situations both from self-reported and actual speeding behaviour.