Traffic Exposure Research Articles

Road Traffic Noise, Obesity, and the Risk of Incident Type 2 Diabetes: A Cohort Study in UK Biobank.

Objectives: To assess the association of road traffic noise exposure with Type 2 Diabetes (T2D) risk, and to explore the potential moderation effect of obesity. Methods: A total of 305,969 participants from the UK Biobank Cohort - an open access cohort of 500,000 participants recruited in the United Kingdom (UK) between 2006 and 2010 - were included in the study. A Cox proportional hazard model was fitted to assess the association between road traffic noise exposure and T2D. Results: A total of 19,303 participants were diagnosed with T2D during the 11.9-year median follow-up period. For every 10 dB increase in road traffic noise, there was a 4% increase in T2D risk (HR = 1.04, 95%CI: 1.01, 1.07). Besides, a significant positive interaction was observed between obesity and road traffic noise (P interaction <0.001) for the risk of T2D. The association of road traffic noise with T2D was stronger in overweight and obese participants (HR = 1.04, 95% CI: 1.01–1.08), but not significant among lean ones (HR = 0.96, 95% CI: 0.86–1.07). Conclusion: Our study observed a longitudinal association of road traffic noise exposure with T2D risk, which was stronger among overweight and obese individuals than the lean ones.

Effect of wearing helmet on traffic noise-induced health issues of motorcycle riders

IntroductionTransportation noise is a major source of concern in urban areas. Motorcycle riders, on the other hand, are the most exposed to traffic noise while riding. This study was carried out on 363 respondents (no-helmet: 121 respondents, half-face helmet: 121 respondents, and full-face helmet: 121 respondents) who were exposed to traffic noise while riding their motorcycles on the same noisy route, having the same exposure hours. The purpose of this study was to determine whether wearing a helmet protects against various traffic noise-induced psychophysiological health issues. It also tried to determine whether the riders were more affected than the pillion riders as a result of traffic noise exposure. MethodThe psychophysiological factors of the respondents, such as annoyance, tiredness, depression, headache, and sleeping problem, were obtained using a standard questionnaire in accordance with ISO 15666, Beck et al. (1961), and Eriksen et al. (1999), respectively. The effect of wearing a helmet on traffic noise-induced psychophysiological reactions was investigated using structural equation modelling. ResultsSEM route analysis revealed these significant relationships: (i) helmet use and gender (p-value: 0.017), (ii)) helmet use and marital status (p-value: 0.043), (iii) riders/pillion-riders and annoyance (p-value: < 0.001), (iv) riders/pillion-riders and gender (p-value: < 0.001). It was also observed that motorcyclists suffer from higher traffic noise-related health issues than pillion riders. SEM analysis further revealed that use of helmet can negatively affect the traffic noise induced annoyance, tiredness, depression, headache, and sleeping problem. Paired test data shows that there are significant differences in traffic noise induced annoyance level, tiredness, headache, depression, sleeping problems, and equivalent noise level. ConclusionThe use of a full-face helmet protects motorcyclists against a variety of traffic noise-related health problems. Practical implicationsThis study presents a thorough overview of the benefits of wearing a helmet against traffic noise pollution.

Association of sound pressure levels and frequency components of road traffic noise with prevalent depression in Taichung, Taiwan

The World Health Organization has reported that the prevalence of mental illness is 4% in the global population. Epidemiological studies have reported a relationship between road traffic noise exposure and depression, but the association between noise frequency components and depression remains unclear. This cross-sectional study investigated the associations between road traffic noise exposure and its frequency components with prevalent depression. A total of 3,200 residents living in Taichung who participated in the Taiwan Biobank between 2010 and 2017, were included as study participants. We used land-use regression models to evaluate individual annual average values of A-weighted equivalent sound level over 24 h (Leq,24h) and particulate matter with an aerodynamic diameter less than 2.5 &amp;#x3bc;m (PM2.5) using the geographic information system. Multiple logistic regression was applied to estimate the odds ratios (ORs) for depression after adjusting for potential risk factors and PM2.5. An interquartile range increase in Leq,24h at full frequency (4.7 dBA), 1000 Hz (5.2 dB), and 2000 Hz (4.8 dB) was significantly associated with an elevated risk for depression with ORs of 1.62 (95% confidence interval [CI]: 1.03, 2.55), 1.58 (95% CI: 1.05, 2.37), and 1.58 (95% CI:1.03, 2.43), respectively, by controlling for PM2.5. The high-exposure group (&amp;#x2265; the median of noise levels) at full frequency, 500 Hz, and 2000 Hz had an increased risk for depression with ORs of 1.87 (95% CI: 1.03, 3.39), 1.94 (95% CI: 1.03, 3.65), and 1.86 (95% CI: 1.03, 3.37), respectively, compared with the low-exposure group (&amp;#x3c; the median of noise levels) after adjustment for PM2.5. Road traffic noise exposure may be associated with an increased prevalence of depression, particularly at 500 to 2000 Hz.

Changes in socioeconomic and demographic disparities for traffic-related air pollution exposure during pregnancy over a 20-year period in Texas

Background and Aim: Environmental justice issues surround population exposure to ambient air pollution; however, few studies have specifically examined traffic air pollution (a pollutant with localized concentration patterns) and pregnancy exposures (maternal-infant dyads may be particularly susceptible to air pollution effects). How socioeconomic and demographic disparities may change over time is also unclear but could have important policy implications. Methods: We identified ~ 6.9 million pregnant mothers in Texas from 1996 to 2016 using individual-level vital statistics records. We estimated traffic air pollution exposures using full residential addresses and calculated the total vehicle miles travelled (VMT) within 300 m, assigned nitrogen dioxide (NO2) concentrations from a spatial-temporal land use regression model (an indicator of vehicle tailpipe emissions), and linked the National Air Toxic Agency cancer risk index from vehicles emissions to maternal addresses. From census tract data, we examined median household income. We quantified annual absolute and relative mean percent differences in traffic air pollution across socio-demographic indicators of maternal race and ethnicity, educational attainment, and maternal birthplace. Results: We observed marked differences in traffic air pollution exposures by all socio-demographic variables examined. Overall, the strongest disparities were seen among non-White and foreign-born pregnancies. While the absolute level of disparity shrank from 1996 to 2016 (e.g., in 1996 Black individuals were exposed to NO2 levels 1.8 ppb higher than white individuals, while in 2016 NO2 levels were 1.5 ppb higher among Black compared to white individuals), the relative level of disparity continued to increase. Within census tracts (i.e., neighborhoods), we also observed sizeable disparities among socioeconomic and demographic groups. Conclusion: Despite considerable reductions in traffic-related air pollution, the magnitude of disparity has increased when we compared groups with lower socioeconomic positioning to their higher socioeconomic positioned counterparts. Keywords: traffic-related air pollution, pregnancy, environmental justice

Road traffic noise and incidence of primary hypertension: a prospective analysis in UK Biobank

BACKGROUND AND AIM The quality of evidence regarding the associations between road traffic noise and hypertension is low due to the limitations of cross-sectional study design, with the role of air pollution remains to be further clarified. To evaluate associations of long-term road traffic noise and air pollution exposure with incident primary hypertension, we conducted a prospective population-based analysis in UK Biobank. METHODS Road traffic noise was estimated at baseline residential address using the Common Noise Assessment Method model. Incident primary hypertension (ICD 10: I10) was ascertained through linkage with medical records for ~250 000 participants. Cox proportional hazard models were used to estimate hazard ratios (HRs) for association between road traffic noise and incident primary hypertension, adjusting for covariates determined via directed acyclic graph. RESULTS During a median of 8.1 years follow up, 21 185 incident primary hypertension cases were ascertained. The HR for a 10 dB[A] increase in mean weighted average 24-h road traffic noise level (Lden) exposure was 1.08 [95% confidence interval (CI) 1.02, 1.14]. A dose-response relationship was found, with HRs of 1.14 (95% CI: 1.04, 1.26) for Lden &amp;#x3e; 65dB[A] vs. &amp;#x2264; 55dB[A] (P trend &amp;#x3c;0.05), and HRs of 1.15 (95% CI: 1.04, 1.26) for night-time road traffic noise (Lnight)&amp;#x3e;55 dB[A] vs. &amp;#x2264; 45dB[A] (P trend &amp;#x3c;0.05). The associations were all robust to adjustment for fine particulate matter (PM2.5) and nitrogen dioxide (NO2). Furthermore, the highest incident hypertension risk was seen in the group who were exposed to the highest level of both road traffic noise and air pollution. CONCLUSIONS Long-term exposure to road traffic noise was associated with increased incidence of primary hypertension, and the effect estimates were greater in those with higher air pollution exposure. KEYWORDS road traffic noise; air pollution; primary hypertension; prospective analysis

Association between traffic density exposure during pregnancy and low birthweight in Spain, 2000-2017

Association between traffic density exposure during pregnancy and low birthweight in Spain, 2000-2017

Suicide and transportation noise: a prospective cohort study from Switzerland

Background: Evidence for effects of transportation noise on mental health remains scarce, mainly due to a lack of high quality studies. Meanwhile, psychiatric diseases are among the most prevalent non-communicable diseases worldwide, and suicide as a mortality outcome presents a pressing public health issue. The aim of this study is to investigate the association between transportation noise and suicide, while adjusting for air pollution. Methods: Road traffic, railway and aircraft noise exposure as well as PM2.5 exposure were linked to 5.1 million participants 15 years or older in the Swiss National Cohort, accounting for their address history. Mean noise exposure in 5-year periods was calculated. Individuals were followed for up to 15-years (2001-2015). Time-varying Cox regression models were applied to total suicides and cause-specific suicide deaths. Models included all three noise sources, PM2.5 plus individual and spatial covariates including socio-economic status. Effect modification by sex was also explored. Results: During the follow-up, there were 11,265 suicide deaths. Road traffic and railway noise were associated with total suicides (Hazard ratio: 1.039 [95% CI: 1.015-1.064] and 1.022 [1.004-1.041] per 10dB Lden, respectively ), while no significant association was found for aircraft noise. Associations were stronger for females than males. The pattern was robust across all outcomes, with the strongest association seen in non-violent suicides (poisoning: HR 1.122 [1.042-1.209] per 10dB Lden road traffic noise). No robust association was observed for PM2.5, whether adjusted for noise or separately. Conclusion: In this longitudinal, nationwide cohort study, we report a robust association between exposure to road traffic and railway noise and an increased risk for death by suicide. These findings add to the growing body of evidence that mental health disorders may be related to transportation noise exposure. Keywords : road traffic, railway, aircraft, Lden, air pollution, mental health

Adverse childhood experiences intensify retinal microvascular and inflammatory responses to semi-controlled acute traffic related air pollution exposure

Background: Potential synergy between childhood exposure to psychosocial stressors and traffic-related air pollution exposure, two factors that commonly overlap in socially disadvantaged groups, could increase the risk of cardiovascular disease and lead to greater health disparity than what is currently attributed to these factors independently. Aim: To test whether adverse childhood experiences (ACEs) potentiate the response of retinal microvasculature caliber and circulatory pro-inflammatory cytokines following a two-hour semi-controlled exposure to traffic related air pollution. Method: In a crossover experiment, 57 participants were exposed to near-traffic ambient air and filtered ambient air, in separate occasions for two hours each time. Central retinal arteriolar/venular equivalent (CRAE/CRVE), blood pressure, pulse, and circulating interleukin (IL)-1β, IL-6, IL-8, and tumor necrosis factor-α (TNF-α) were measured pre-exposure and, again, 1 hour and 24 hours post-exposure. ACEs were documented using the ACE questionnaire. Based on ACE scores, participants were grouped into high (ACE &amp;#x2265; 4) and low (ACE &amp;#x2264; 1) ACE groups. Microvascular and inflammatory response to the exposure were analyzed across groups. Results: ACE scores significantly predicted CRAE, IL-6, IL-8, and pulse reactivity. Left eye CRAE narrowing was greater in the high- vs. low-ACE group at 1-hour and 24-hours post-exposure. 24-hours post-exposure, IL-8 and pulse were significantly higher in the high- vs. low-ACE group. IL-6 was significantly lower in the high- vs. low-ACE group at 1-hour post-exposure. Conclusion: Our results support the hypothesis that ACEs may induce susceptibility to air pollution across the lifespan. These findings may thus help explain how health disparities develop and persist across the lifespan in persons who are most vulnerable to experiencing ACEs and poor air quality, leading to continued social disadvantage.

Traffic density exposure and metabolomics in a population-based sample: The HORTEGA Study

Traffic density exposure and metabolomics in a population-based sample: The HORTEGA Study

High contribution from outdoor air to personal exposure and potential inhaled dose of PM2.5 for indoor-active university students

People spend most of their time indoors, isolated from the outdoor environment where serious air pollution usually occurs. To what extent outdoor air pollution contributes to their daily personal exposure and inhaled dose? To fill this knowledge gap, an exposure assessment study was conducted for indoor-active university students during a wintertime period of hazy and non-hazy (clear) days in Beijing. Indoor and outdoor fine particulate matter (PM2.5) samples were collected at six indoor microenvironments, and two outdoor environments representing traffic and ambient exposure in the university, respectively, to estimate the personal exposure of students. The average daily personal exposure and poteantial inhaled dose on hazy days (124.8 ± 72.3 μg m−3 and 2.74 ± 1.53 mg) were much higher than that on clear days (57.5 ± 31.9 μg m−3 and 1.26 ± 0.59 mg), indicating a significant influence from the ambient air quality. The indoor PM2.5 concentrations were significantly and positively correlated with the outdoor ones (r = 0.67–0.96) with an FINF (infiltration factor) range of 0.44–0.81 during sampling periods. The outdoor-origin air contributed 68%–95% to the total indoor PM2.5, the average of which was higher during haze events (87%) than clear periods (73%). Correspondingly, outdoor-origin PM2.5 contributed around 105.4 μg m−3 and 2.41 mg (85% and 89%) to the daily exposure and inhaled dose of college students on hazy days, respectively, compared to just 39.2 μg m−3 and 0.95 mg (68% and 75%) on clear days. Our results highlight the significant contribution of outdoor-origin PM2.5 occurred indoor to both the daily personal exposure and inhaled dose due to air pollution filtration between outdoor and indoor environments. These also suggest a continuous effort not only on ambient air quality improvements, but also on environmental friendly building for public health protection with lower exposure.

Exposure to road traffic noise and behavioral problems in Chinese schoolchildren: A cross-sectional study.

Transportation noise is second only to air pollution as an environmental contributor to adverse health outcomes in Western countries. However, no studies investigated the association between road traffic noise and behavioral problems among schoolchildren in China. To investigate the association between exposure to road traffic noise at home and behavioral problems in Chinese schoolchildren. From January to June 2017, we screened 3236 children aged 7-13 years in Guangzhou (Guangdong, China) from the first investigation of an ongoing school-based cohort study with complete information on behavioral problems and residential geolocation. Residential road traffic noise exposure levels were assessed using a validated modeling method in different periods of the day, including daytime (Lday), nighttime (Lnight), and weighted 24-hr (Ldn). The annual mean concentration of nitrogen dioxide was also modeled in our study. Behavioral problems were assessed by the parent-rated Strengths and Difficulties Questionnaire (SDQ). Generalized linear mixed models were utilized to estimate the associations between road traffic noise and behavioral problems. In the main adjusted model, a 10-dB increase in Ldn was associated with 0.33 (95% CI: 0.08, 0.59), 0.08 (95% CI: -0.01, 0.17), and 0.09 (95% CI: 0.01, 0.16) increases in three subscales score for total difficulties score, emotional problems, and conduct problems, respectively. The same increase in Ldn was also associated with the abnormal total difficulties score (OR = 1.25, 95%CI: 1.01, 1.55), emotional problems (OR = 1.19, 95%CI: 0.98, 1.44), and conduct problems (OR = 1.28, 95%CI:1.02, 1.63). Externalising behavior appears more susceptible to traffic noise than internalising behavior. NO2 had a small impact on the associations between Ldn and behavioral problems. Our estimates were generally robust in several sensitivity analyses. Residential road traffic noise exposure might be related to increased behavioral problems in Chinese schoolchildren, such as emotional symptoms and conduct problems.

Urban design of inner courtyards and road traffic noise: Influence of façade characteristics and building orientation on perceived noise annoyance

Residents of densely populated urban areas are often exposed to high road traffic noise. While noise control measures help mitigating road traffic noise exposure in residential areas (e.g., inner courtyards), their psychoacoustic impacts on residents have not been well explored. In this study, effects of façade surface material (sound reflecting, absorbing or diffusing) and building rotation (parallel vs. nonparallel walls) on perceived noise annoyance were investigated in laboratory experiments. To that aim, a virtual acoustic environment within a residential area was designed. Moving passenger cars were artificially generated by convolving synthesised car emission sound signals with position-specific impulse responses and simulating sound propagation for static receiver locations along different vehicle trajectories. A method to interpolate the impulse responses was developed to generate receiver audio signals of a continuously passing vehicle. The resulting stimuli were spatially reproduced using loudspeakers. The laboratory experiments revealed that absorbing façades were associated with lower noise annoyance than reflecting or diffusing façades due to reduced sound pressure level. However, at the same level, the absorbing façades were perceived as more annoying than the reflecting or diffusing façades, indicating somewhat unfavourable acoustical quality. Building rotation (resulting in nonparallel walls) was associated with lower noise annoyance compared to the original parallel-wall building orientation. While this was due to reduced sound level as well, the positive effect also tended to remain when the level was the same for rotated and parallel buildings. Our experiments show that façade characteristics and building orientation may be important architectural features to optimize the sound environment of inner courtyards.

Effect of preconceptional, prenatal and postnatal exposure to home environmental factors on childhood pneumonia: A key role in early life exposure

BackgroundIncreasing evidence have associated pneumonia with early exposure to ambient air pollution. However, the role of indoor environmental factors exposure in early life on childhood pneumonia remains unclear. ObjectiveTo examine the association between indoor environmental factors exposure during different timing windows and childhood pneumonia, and to identify the key indoor factor(s) in different critical window(s). MethodsA retrospective cohort study of 8689 pre-schoolers was performed in Changsha, China during 2019–2020. Our questionnaire survey was designed to collect information on pre-schooler's outcome and residential environmental exposure containing indoor pollution and allergens during 1 year before pregnancy, pregnancy, first year, and past year. The associations were further estimated stratified by personal exposure level of outdoor NO2, CO, temperature (T) and different covariates. Associations were assessed by multiple logistic regression model in terms of odds ratio (OR) of 95% confidence interval (CI). ResultsPre-schooler's pneumonia was significantly related with exposure of new furniture, redecoration, mold/damp stains, and mold or damp clothing or bedding exposure during the four periods, with the strongest associations observed during 1 year before pregnancy based on multi-window model, with ORs (95% CI) of 1.27 (1.12–1.44), 1.26 (1.09–1.46), 1.34 (1.14–1.57), and 1.28 (1.05–1.56) respectively. Environmental tobacco smoke (ETS) including both parental and grandparental smoking were significantly related with increased risk of pre-schooler's pneumonia, and ETS played a more important role in early life, with ORs (95% CI) of 1.17 (1.01–1.36) and 1.19 (1.02–1.39) in pregnancy and first year. Indoor plants particularly nonflowering plants significantly elevated pneumonia risk but only in past year, with ORs (95% CI) of 1.17 (1.05–1.30) and 1.14 (1.03–1.26). Higher pneumonia risk was observed for renovation exposure in pre-birth compared to post-birth, while mold/dampness exerted an accumulative effect with the highest risk for exposure during both pre- and post-birth. Living near traffic road and exposure to high level of traffic-related air pollution and high temperature significantly increased pneumonia risk. Sensitivity analysis found that some sub-groups were more susceptible to pneumonia risk of home environment exposure. ConclusionEarly life exposure to indoor environmental factors plays an important role in pneumonia development, supporting the hypothesis of “Preconceptional and Fetal Origin of Childhood Pneumonia” and “Developmental Origins of Health and Pneumonia”.

Risk Associations between Vehicular Traffic Noise Exposure and Cardiovascular Diseases: A Residential Retrospective Cohort Study.

Environmental noise can induce detrimental health effects such as cardiovascular disease (CVD). The relationship between vehicular traffic noise pollution and CVD was investigated through a retrospective residential cohort study in the city of Pisa. Four exposure classes were defined for noise pollution, using noise propagation maps. The association between noise exposures and cause-specific mortality or hospitalization of the subjects of the cohort was calculated using the hazard ratio (HR) for night and day through a multiple time-dependent and sex-specific Cox regression adjusting for age, the socio-economic deprivation index, and traffic air pollution. Mortality excess for CVD and risk trends for a 1 decibel noise increment were observed among the most exposed women (mortality: HRnightclass4 1.15 (1.03–1.28); Trendnight 1.007 (1.002–1.012); HRdayclass4 1.14 (1.02–1.27); Trendday 1.008 (1.003–1.013)), particularly for ischaemic disease (mortality: Trendnight 1.008 (0.999–1.017); Trendday 1.009 (0.999–1.018)) and cerebrovascular disease (mortality: HRnightclass3 1.23 (1.02–1.48), HRdayclass3 1.24 (1.03–1.49)). Hospitalization analyses confirm mortality results. A decreased risk for hospitalization was also observed among the most exposed men (HRdayclass4 0.94 (0.88–1.01), particularly for ischaemic disease (HRnightclass4 0.90 (0.80–1.02); HRdayclass4 0.86 (0.77–0.97)) and cerebrovascular disease (HRnightclass4 0.89 (0.78–1.01)). Authors recommend the adoption of prevention measures aimed at mitigating noise and the activation of a monitoring of the risk profile in the Pisa population updating both the residential cohort and health data.

Exposure to surrounding greenness and natural-cause and cause-specific mortality in the ELAPSE pooled cohort.

The majority of studies have shown higher greenness exposure associated with reduced mortality risks, but few controlled for spatially correlated air pollution and traffic noise exposures. We aim to address this research gap in the ELAPSE pooled cohort. Mean Normalized Difference Vegetation Index (NDVI) in a 300-m grid cell and 1-km radius were assigned to participants' baseline home addresses as a measure of surrounding greenness exposure. We used Cox proportional hazards models to estimate the association of NDVI exposure with natural-cause and cause-specific mortality, adjusting for a number of potential confounders including socioeconomic status and lifestyle factors at individual and area-levels. We further assessed the associations between greenness exposure and mortality after adjusting for fine particulate matter (PM2.5), nitrogen dioxide (NO2) and road traffic noise. The pooled study population comprised 327,388 individuals who experienced 47,179 natural-cause deaths during 6,374,370 person-years of follow-up. The mean NDVI in the pooled cohort was 0.33 (SD 0.1) and 0.34 (SD 0.1) in the 300-m grid and 1-km buffer. In the main fully adjusted model, 0.1 unit increment of NDVI inside 300-m grid was associated with 5% lower risk of natural-cause mortality (Hazard Ratio (HR) 0.95 (95% CI: 0.94, 0.96)). The associations attenuated after adjustment for air pollution [HR (95% CI): 0.97 (0.96, 0.98) adjusted for PM2.5; 0.98 (0.96, 0.99) adjusted for NO2]. Additional adjustment for traffic noise hardly affected the associations. Consistent results were observed for NDVI within 1-km buffer. After adjustment for air pollution, NDVI was inversely associated with diabetes, respiratory and lung cancer mortality, yet with wider 95% confidence intervals. No association with cardiovascular mortality was found. We found a significant inverse association between surrounding greenness and natural-cause mortality, which remained after adjusting for spatially correlated air pollution and traffic noise.

Prediction of traffic noise induced annoyance of vendors through noise indices using structural equation modeling: Artificial neural network model

AbstractUrbanization and population growth, as well as the movement of diverse vehicles on urban roadways, all contribute to excessive noise in the urban acoustic environment. Annoyance, cardiovascular disease, dementia, hypertension, stress, sleeping problem, irritation, hair‐fall, headache, are the most common reported problems due to traffic noise exposure. The “Structural Equation Modeling–Artificial Neural Network Model” was used in the current study to predict traffic noise induced annoyance among 100 vendors whose shops are located from Khandagiri to Baramunda along the National Highway 16 of the smart city Bhubaneswar Odisha. Due to the movement of large number of heavy vehicles as well as medium and light weight vehicles, these roadways remain noisy throughout the day. Moreover, the annoyance questionnaire was developed in compliance with ISO/TS 15666 criteria for assessing annoyance level. The combination of SEM and ANN is rarely seen in acoustics, especially in noise studies. However, in this study, both SEM and ANN are used to predict annoyance using various noise indices. Moreover, the SEM model revealed a significant association between “Equivalent Noise Level” (Leq) and annoyance (p‐value = 0.031), “Minimum Noise Level” (LMin) and annoyance (p‐value = 0.049), “Background Noise Level” (L90) and annoyance (p‐value = 0.047), “Noise Pollution Level” (NPL) and annoyance (p‐value = 0.038). These associations indicate that Leq, LMin, L90 and NPL have a significant effect on annoyance. Furthermore, the PLS algorithm output from the measurement model verified a 47 percent variance in annoyance level. The ANN model confirmed that NPL is the most significant predictor of noise annoyance, followed by LMin, Leq, and L90. Moreover, the ANN model can predict annoyance with an accuracy of 68.5 percent.

Road traffic density and recurrent asthma emergency department visits among Medicaid enrollees in New York State 2005–2015

BackgroundEnvironmental exposures such as traffic may contribute to asthma morbidity including recurrent emergency department (ED) visits. However, these associations are often confounded by socioeconomic status and health care access.ObjectiveThis study aims to assess the association between traffic density and recurrence of asthma ED visits in the primarily low income Medicaid population in New York State (NYS) between 2005 and 2015.MethodsThe primary outcome of interest was a recurrent asthma ED visit within 1-year of index visit. Traffic densities (weighted for truck traffic) were spatially linked based on home addresses. Bivariate and multivariate logistic regression analyses were conducted to identify factors predicting recurrent asthma ED visits.ResultsIn a multivariate model, Medicaid recipients living within 300-m of a high traffic density area were at a statistically significant risk of a recurrent asthma ED visit compared to those in a low traffic density area (OR = 1.31; 95% CI:1.24,1.38). Additionally, we evaluated effect measure modification for risk of recurrent asthma visits associated with traffic exposure by socio-demographic factors. The highest risk was found for those exposed to high traffic and being male (OR = 1.87; 95% CI:1.46,2.39), receiving cash assistance (OR = 2.11; 95% CI:1.65,2.72), receiving supplemental security income (OR = 2.21; 95% CI:1.66,2.96) and being in the 18.44 age group (OR = 1.59;95% CI 1.48,1.70) was associated with the highest risk of recurrent asthma ED visit. Black non-Hispanics (OR = 2.35; 95% CI:1.70,3.24), Hispanics (OR = 2.13; 95% CI:1.49,3.04) and those with race listed as “Other” (OR = 1.89 95% CI:1.13,3.16) in high traffic areas had higher risk of recurrent asthma ED visits as compared to White non-Hispanics in low traffic areas.ConclusionWe observed significant persistent disparities in asthma morbidity related to traffic exposure and race/ethnicity in a low-income population. Our findings suggest that even within a primarily low-income study population, socioeconomic differences persist. These differences in susceptibility in the extremely low-income group may not be apparent in health studies that use Medicaid enrollment as a proxy for low SES.

Association between traffic related air pollution exposure and direct health care costs in Northern California

BackgroundTraffic related air pollution (TRAP) is associated with a complex and diverse array of health effects. It is unknown whether these effects may be reflected by higher health care costs. ObjectivesEvaluate the association between TRAP exposure and direct health care costs in an elderly population. MethodsThis multi-ethnic population-based cohort of 25,684 elderly subjects, served by Kaiser Permanente Northern California (KPNC), were followed between 2013 and 2017. Hyperlocal long-term pollutant concentrations for nitrogen dioxide [NO2], nitric oxide [NO], and black carbon [BC] were measured at a resolution of 30 m using repeated street-level mobile measurements and linked to residential addresses. Health care utilization and costs were derived from KPNC databases and were used to calculate individual annual total health care, inpatient, outpatient, and emergency room (ER) and pharmacy costs. The associations between TRAP exposures and health care costs were evaluated using generalized estimating equation models adjusted for age, sex, race, BMI, smoking, SES and comorbidities. Subgroup analyses and interaction models were used to assess differences among specific susceptible population subgroups. ResultsAn IQR difference (10.1 ppb vs 4.2 ppb) in NO2 concentration was associated with a 3% (95% CI: -1%, 6%), 22% (95% CI:11%, 35%), and 5% (95% CI:1%, 8%) increase in annual total health care, ER and outpatient costs in the baseline model. Associations with black carbon showed similar patterns but were smaller in magnitude. Among those with cardiovascular diseases, an IQR increase in NO2 was associated with a 7% (95% CI: 1%, 13%) increase in total annual health care cost and 23% (95% CI: 17%, 29%) increase in ER costs. DiscussionHigher long-term TRAP exposure was associated with higher direct annual health care cost in this elderly cohort. Those with existing cardiovascular disease had particularly strong associations between TRAP exposure and direct annual health care costs.

The effect of traffic noise on cognitive performance with regard to personality traits: A laboratory experiment study.

Exposure to traffic noise could play an important part in inducing psychological disorders which in turn can affect individuals' cognitive and mental performance. The aim of this study was to determine the effect of traffic noise exposure on the cognitive performance with regard to subjects' personality traits. Sixty students with normal hearing and vision took part in this experimental study. In order to simulate the traffic noise condition of Tehran, the noise from several busy streets was first carefully recorded. Later on, the subjects were exposed to this recorded noise in an anechoic chamber. Also, the NEO-five factor inventory questionnaire and the continuous performance test were used to assess personality traits and cognitive performance of participants respectively. The results showed that the cognitive features of the study, such as reaction time and the number of commission/omission errors in continuous performance testing increased significantly after exposure to the traffic noise (p < 0.05), and among the personality traits, only the neuroticism has a significant correlation with response time in the continuous performance tests (p < 0.05). Apart from the effect of traffic noise on cognitive function, the findings of this study confirmed that Neuroticism (one of the personality traits) also significantly affect the cognitive performance of individuals when they are exposed to traffic noise in laboratory conditions.

Short Duration Crash Prediction for Rural Two-Lane Roadways: Applying Explainable Artificial Intelligence

Conventional traffic crash analysis methods often use highly aggregated data, making it difficult to understand the effects of time-varying factors on crash occurrence. In this study, the combined effect of roadway geometry, speed distribution, and weather conditions on crash occurrence and severity was investigated on short duration daily level crash data. This study collected data from four different sources on rural two-lane roadways in Texas. A machine learning method, XGBoost (eXtreme Gradient Boosting), was applied to train the data. To mitigate imbalanced data problems, a synthetic minority oversampling technique (SMOTE) was applied. The XGBoost model was trained separately on all crash occurrences and severe crash occurrences. Finally, an explainable artificial intelligence (AI) technique, SHAP (SHapley Additive exPlanation), was applied to investigate the contribution of all variables to the model’s output. The results show that annual average daily traffic has a significant impact on all crash occurrences and severe crash (fatal and incapacitating injury) occurrences on rural two-lane roadways. Moreover, weather condition factors including daily precipitation, average visibility, and the standard deviation of visibility show association with high crash occurrences. The short duration crash prediction models of this study can provide more insights into the relationships between crash, geometric variables, traffic exposure, weather, and operating speed.