Hourly land-use regression modeling for NO2 and PM2.5 in the Netherlands.

Annual average land-use regression (LUR) models have been widely used to assess spatial patterns of air pollution exposures. However, they fail to capture diurnal variability in air pollution and consequently might result in biased dynamic exposure assessments. In this study we aimed to model average hourly concentrations for two major pollutants, NO2 and PM2.5, for the Netherlands using the LUR algorithm. We modelled the spatial variation of average hourly concentrations for the years 2016-2019 combined, for two seasons, and for two weekday types. Two modelling approaches were used, supervised linear regression (SLR) and random forest (RF). The potential predictors included population, road, land use, satellite retrievals, and chemical transport model pollution estimates variables with different buffer sizes. We also temporally adjusted hourly concentrations from a 2019 annual model using the hourly monitoring data, to compare its performance with the hourly modelling approach. The results showed that hourly NO2 models performed overall well (5-fold cross validation R2 = 0.50-0.78), while the PM2.5 performed moderately (5-fold cross validation R2 = 0.24-0.62). Both for NO2 and PM2.5 the warm season models performed worse than the cold season ones, and the weekends' worse than weekdays'. The performance of the RF and SLR models was similar for both pollutants. For both SLR and RF, variables with larger buffer sizes representing variation in background concentrations, were selected more often in the weekend models compared to the weekdays, and in the warm season compared to the cold one. Temporal adjustment of annual average models performed overall worse than both modelling approaches (NO2 hourly R2 = 0.35-0.70; PM2.5 hourly R2 = 0.01-0.15). The difference in model performance and selection of variables across hours, seasons, and weekday types documents the benefit to develop independent hourly models when matching it to hourly time activity data.

Long-term exposure to transportation noise and diabetes mellitus mortality: a national cohort study and updated meta-analysis.

BACKGROUND: Long-term exposure to transportation noise is related to cardio-metabolic diseases, with more recent evidence also showing associations with diabetes mellitus (DM) incidence. This study aimed to evaluate the association between transportation noise and DM mortality within the Swiss National Cohort. METHODS: During 15 years of follow-up (2001-2015; 4.14 million adults), over 72,000 DM deaths were accrued. Source-specific noise was calculated at residential locations, considering moving history. Multi-exposure, time-varying Cox regression was used to derive hazard ratios (HR, and 95%-confidence intervals). Models included road traffic, railway and aircraft noise, air pollution, and individual and area-level covariates including socio-economic position. Analyses included exposure-response modelling, effect modification, and a subset analysis around airports. The main findings were integrated into meta-analyses with published studies on mortality and incidence (separately and combined). RESULTS: HRs were 1.06 (1.05, 1.07), 1.02 (1.01, 1.03) and 1.01 (0.99, 1.02) per 10 dB day evening-night level (Lden) road traffic, railway and aircraft noise, respectively (adjusted model, including NO2). Splines suggested a threshold for road traffic noise (~ 46 dB Lden, well below the 53 dB Lden WHO guideline level), but not railway noise. Substituting for PM2.5, or including deaths with type 1 DM hardly changed the associations. HRs were higher for males compared to females, and in younger compared to older adults. Focusing only on type 1 DM showed an independent association with road traffic noise. Meta-analysis was only possible for road traffic noise in relation to mortality (1.08 [0.99, 1.18] per 10 dB, n = 4), with the point estimate broadly similar to that for incidence (1.07 [1.05, 1.09] per 10 dB, n = 10). Combining incidence and mortality studies indicated positive associations for each source, strongest for road traffic noise (1.07 [1.05, 1.08], 1.02 [1.01, 1.03], and 1.02 [1.00, 1.03] per 10 dB road traffic [n = 14], railway [n = 5] and aircraft noise [n = 5], respectively). CONCLUSIONS: This study provides new evidence that transportation noise is associated with diabetes mortality. With the growing evidence and large disease burden, DM should be viewed as an important outcome in the noise and health discussion.

Socio-environmental modifiers of heat-related mortality in eight Swiss cities: A case time series analysis.

In the light of growing urbanization and projected temperature increases due to climate change, heat-related mortality in urban areas is a pressing public health concern. Heat exposure and vulnerability to heat may vary within cities depending on structural features and socioeconomic factors. This study examined the effect modification of the temperature-mortality association of three socio-environmental factors in eight Swiss cities and population subgroups (<75 and ≥ 75 years, males, females): urban heat islands (UHI) based on within-city temperature contrasts, residential greenness measured as normalized difference vegetation index (NDVI) and neighborhood socioeconomic position (SEP). We used individual death records from the Swiss National Cohort occurring during the warm season (May to September) in the years 2003-2016. We performed a case time series analysis using conditional quasi-Poisson and distributed lag non-linear models with a lag of 0-3 days. As exposure variables, we used daily maximum temperatures (Tmax) and a binary indicator for warm nights (Tmin ≥20 °C). In total, 53,593 deaths occurred during the study period. Overall across the eight cities, the mortality risk increased by 31% (1.31 relative risk (95% confidence interval: 1.20-1.42)) between 22.5 °C (the minimum mortality temperature) and 35 °C (the 99th percentile) for warm-season Tmax. Stratified analysis suggested that the heat-related risk at 35 °C is 26% (95%CI: -4%, 67%) higher in UHI compared to non-UHI areas. Indications of smaller risk differences were observed between the low vs. high greenness strata (Relative risk difference = 13% (95%CI: -11%; 44%)). Living in low SEP neighborhoods was associated with an increased heat related risk in the non-elderly population (<75 years). Our results indicate that UHI are associated with increased heat-related mortality risk within Swiss cities, and that features beyond greenness are responsible for such spatial risk differences.

The association between real-life markers of phone use and cognitive performance, health-related quality of life and sleep.

INTRODUCTION: The real-life short-term implications of electromagnetic fields (RF-EMF) on cognitive performance and health-related quality of life have not been well studied. The SPUTNIC study (Study Panel on Upcoming Technologies to study Non-Ionizing radiation and Cognition) aimed to investigate possible correlations between mobile phone radiation and human health, including cognition, health-related quality of life and sleep. METHODS: Adult participants tracked various daily markers of RF-EMF exposures (cordless calls, mobile calls, and mobile screen time 4 h prior to each assessment) as well as three health outcomes over ten study days: 1) cognitive performance, 2) health-related quality of life (HRQoL), and 3) sleep duration and quality. Cognitive performance was measured through six "game-like" tests, assessing verbal and visuo-spatial performance repeatedly. HRQoL was assessed as fatigue, mood and stress on a Likert-scale (1-10). Sleep duration and efficiency was measured using activity trackers. We fitted mixed models with random intercepts per participant on cognitive, HRQoL and sleep scores. Possible time-varying confounders were assessed at daily intervals by questionnaire and used for model adjustment. RESULTS: A total of 121 participants ultimately took part in the SPUTNIC study, including 63 from Besancon and 58 from Basel. Self-reported wireless phone use and screen time were sporadically associated with visuo-spatial and verbal cognitive performance, compatible with chance findings. We found a small but robust significant increase in stress 0.03 (0.00-0.06; on a 1-10 Likert-scale) in relation to a 10-min increase in mobile phone screen time. Sleep duration and quality were not associated with either cordless or mobile phone calls, or with screen time. DISCUSSION: The study did not find associations between short-term RF-EMF markers and cognitive performance, HRQoL, or sleep duration and quality. The most consistent finding was increased stress in relation to more screen time, but no association with cordless or mobile phone call time.

Association between exposure to multiple air pollutants, transportation noise and cause-specific mortality in adults in Switzerland.

BACKGROUND: Long-term exposure to air pollution and noise is detrimental to health; but studies that evaluated both remain limited. This study explores associations with natural and cause-specific mortality for a range of air pollutants and transportation noise. METHODS: Over 4 million adults in Switzerland were followed from 2000 to 2014. Exposure to PM2.5, PM2.5 components (Cu, Fe, S and Zn), NO2, black carbon (BC) and ozone (O3) from European models, and transportation noise from source-specific Swiss models, were assigned at baseline home addresses. Cox proportional hazards models, adjusted for individual and area-level covariates, were used to evaluate associations with each exposure and death from natural, cardiovascular (CVD) or non-malignant respiratory disease. Analyses included single and two exposure models, and subset analysis to study lower exposure ranges. RESULTS: During follow-up, 661,534 individuals died of natural causes (36.6% CVD, 6.6% respiratory). All exposures including the PM2.5 components were associated with natural mortality, with hazard ratios (95% confidence intervals) of 1.026 (1.015, 1.038) per 5 µg/m3 PM2.5, 1.050 (1.041, 1.059) per 10 µg/m3 NO2, 1.057 (1.048, 1.067) per 0.5 × 10-5/m BC and 1.045 (1.040, 1.049) per 10 dB Lden total transportation noise. NO2, BC, Cu, Fe and noise were consistently associated with CVD and respiratory mortality, whereas PM2.5 was only associated with CVD mortality. Natural mortality associations persisted < 20 µg/m3 for PM2.5 and NO2, < 1.5 10-5/m BC and < 53 dB Lden total transportation noise. The O3 association was inverse for all outcomes. Including noise attenuated all outcome associations, though many remained significant. Across outcomes, noise was robust to adjustment to air pollutants (e.g. natural mortality 1.037 (1.033, 1.042) per 10 dB Lden total transportation noise, after including BC). CONCLUSION: Long-term exposure to air pollution and transportation noise in Switzerland contribute to premature mortality. Considering co-exposures revealed the importance of local traffic-related pollutants such as NO2, BC and transportation noise.

Explorative Assessment of the Temperature-Mortality Association to Support Health-Based Heat-Warning Thresholds: A National Case-Crossover Study in Switzerland.

Defining health-based thresholds for effective heat warnings is crucial for climate change adaptation strategies. Translating the non-linear function between heat and health effects into an effective threshold for heat warnings to protect the population is a challenge. We present a systematic analysis of heat indicators in relation to mortality. We applied distributed lag non-linear models in an individual-level case-crossover design to assess the effects of heat on mortality in Switzerland during the warm season from 2003 to 2016 for three temperature metrics (daily mean, maximum, and minimum temperature), and various threshold temperatures and heatwave definitions. Individual death records with information on residential address from the Swiss National Cohort were linked to high-resolution temperature estimates from 100 m resolution maps. Moderate (90th percentile) to extreme thresholds (99.5th percentile) of the three temperature metrics implied a significant increase in mortality (5 to 38%) in respect of the median warm-season temperature. Effects of the threshold temperatures on mortality were similar across the seven major regions in Switzerland. Heatwave duration did not modify the effect when considering delayed effects up to 7 days. This nationally representative study, accounting for small-scale exposure variability, suggests that the national heat-warning system should focus on heatwave intensity rather than duration. While a different heat-warning indicator may be appropriate in other countries, our evaluation framework is transferable to any country.

Assessing the association between air pollution and child development in São Paulo, Brazil.

BACKGROUND: Outdoor air pollution is increasingly recognised as a key threat to population health globally, with particularly high risks for urban residents. In this study, we assessed the association between residential nitrogen dioxide (NO2) exposure and children's cognitive and behavioural development using data from São Paulo Brazil, one of the largest urban agglomerations in the world. METHODS: We used data from the São Paulo Western Region Birth Cohort, a longitudinal cohort study aiming to examine determinants as well as long-term implications of early childhood development. Cross-sectional data from the 72-month follow-up was analysed. Data on NO2 concentration in the study area was collected at 80 locations in 2019, and land use regression modelling was used to estimate annual NO2 concentration at children's homes. Associations between predicted NO2 exposure and children's cognitive development as well as children's behavioural problems were estimated using linear regression models adjusted for an extensive set of confounders. All results were expressed per 10 µg/m3 increase in NO2. RESULTS: 1143 children were included in the analysis. We found no association between NO2 and children's cognitive development (beta -0.05, 95% CI [-0.20; 0.10]) or behavioural problems (beta 0.02, 95% CI [-0.80; 0.12]). CONCLUSION: No association between child cognition or child behaviour and NO2 was found in this cross-sectional analysis. Further research will be necessary to understand the extent to which these null results reflect a true absence of association or other statistical, biological or adaptive factors not addressed in this paper.

Transportation noise exposure and cardiovascular mortality: 15-years of follow-up in a nationwide prospective cohort in Switzerland.

BACKGROUND: Death from cardiovascular diseases (CVD) has been associated with transportation noise. This nationwide cohort, with state-of-the-art exposure assessment, evaluates these associations by noise source. METHODS: Road traffic, railway and aircraft noise for 2001 and 2011 were linked to 4.1 million adults in the Swiss National Cohort, accounting for address history. Mean noise exposure in 5-year periods was calculated. Time-varying Cox regression models, with age as timescale, were applied to all and cause-specific cardiovascular causes of death. Models included all three noise sources plus PM2.5, adjusted for individual and spatial covariates. Nighttime noise events for all sources combined (expressed as intermittency ratio or number of events) were considered in sensitivity analyses. Absolute excess risk was calculated by multiplying deaths/100,000 person-years by the excess risk (hazard ratio-1) within each age/sex group. RESULTS: During a 15-year follow-up, there were 277,506 CVD and 34,200 myocardial infarction (MI) deaths. Associations (hazard ratio; 95%-CIs) for road traffic, railway and aircraft noise and CVD mortality were 1.029 (1.024-1.034), 1.013 (1.010-1.017), and 1.003 (0.996-1.010) per 10 dB Lden, respectively. Associations for MI mortality were a respective 1.043 (1.029-1.058), 1.020 (1.010-1.030) and 1.040 (1.020-1.060) per 10 dB Lden. Blood pressure-related, ischemic heart disease, and all stroke mortality were significantly associated with road traffic and railway noise, while ischemic stroke mortality was associated with aircraft noise. Associations were mostly linear, often starting below 40 dB Lden for road traffic and railway noise. Higher levels of noise intermittency were also independently associated with each outcome. While the absolute number of deaths attributed to noise increased with age, the hazard ratios declined with age. Relative and absolute risk was higher in males compared to females. CONCLUSION: Independent of air pollution, transportation noise exposure is associated with all and cause-specific CVD mortality, with effects starting below current guideline limits.

Association between community noise and children's cognitive and behavioral development: A prospective cohort study.

BACKGROUND: Noise exposure has been associated with adverse cognitive and behavioral outcomes in children, but evidence on longitudinal associations between community noise and child development in low- and middle-income countries is rare. We investigated associations between community noise and behavioral and cognitive development in preschool children in São Paulo. METHODS: We linked child development data from the São Paulo Western Region Birth Cohort with average (Lden) and night-time (Lnight) community noise exposure at children's home, estimated by means of a land use regression model using various predictors (roads, schools, greenness, residential and informal settlements). Outcomes were the Strengths and Difficulties Questionnaire (SDQ) and Regional Project on Child Development Indicators (PRIDI) at 3 years of age and the Child Behavior Checklist (CBCL) and International Development and Early Learning Assessment (IDELA) at 6 years of age. We investigated the relationship between noise exposure and development using cross-sectional and longitudinal regression models. RESULTS: Data from 3385 children at 3 years of age and 1546 children at 6 years of age were analysed. Mean Lden and Lnight levels were 70.3 dB and 61.2 dB, respectively. In cross-sectional analyses a 10 dB increase of Lden above 70 dB was associated with a 32% increase in the odds of borderline or abnormal SDQ total difficulties score (OR = 1.32, 95% CI: 1.04; 1.68) and 0.72 standard deviation (SD) increase in the CBCL total problems z-score (95% CI: 0.55; 0.88). No cross-sectional association was found for cognitive development. In longitudinal analyses, each 10 dB increase was associated with a 0.52 SD increase in behavioral problems (95% CI: 0.28; 0.77) and a 0.27 SD decrease in cognition (95%-CI: 0.55; 0.00). Results for Lnight above 60 dB were similar. DISCUSSION: Our findings suggest that community noise exposure above Lden of 70 dB and Lnight of 60 dB may impair behavioral and cognitive development of preschool children.

User-Centred Design of a Final Results Report for Participants in Multi-Sensor Personal Air Pollution Exposure Monitoring Campaigns.

Using low-cost portable air quality (AQ) monitoring devices is a growing trend in personal exposure studies, enabling a higher spatio-temporal resolution and identifying acute exposure to high concentrations. Comprehension of the results by participants is not guaranteed in exposure studies. However, information on personal exposure is multiplex, which calls for participant involvement in information design to maximise communication output and comprehension. This study describes and proposes a model of a user-centred design (UCD) approach for preparing a final report for participants involved in a multi-sensor personal exposure monitoring study performed in seven cities within the EU Horizon 2020 ICARUS project. Using a combination of human-centred design (HCD), human-information interaction (HII) and design thinking approaches, we iteratively included participants in the framing and design of the final report. User needs were mapped using a survey (n = 82), and feedback on the draft report was obtained from a focus group (n = 5). User requirements were assessed and validated using a post-campaign survey (n = 31). The UCD research was conducted amongst participants in Ljubljana, Slovenia, and the results report was distributed among the participating cities across Europe. The feedback made it clear that the final report was well-received and helped participants better understand the influence of individual behaviours on personal exposure to air pollution.

Harmonization and Visualization of Data from a Transnational Multi-Sensor Personal Exposure Campaign.

Use of a multi-sensor approach can provide citizens with holistic insights into the air quality of their immediate surroundings and their personal exposure to urban stressors. Our work, as part of the ICARUS H2020 project, which included over 600 participants from seven European cities, discusses the data fusion and harmonization of a diverse set of multi-sensor data streams to provide a comprehensive and understandable report for participants. Harmonizing the data streams identified issues with the sensor devices and protocols, such as non-uniform timestamps, data gaps, difficult data retrieval from commercial devices, and coarse activity data logging. Our process of data fusion and harmonization allowed us to automate visualizations and reports, and consequently provide each participant with a detailed individualized report. Results showed that a key solution was to streamline the code and speed up the process, which necessitated certain compromises in visualizing the data. A thought-out process of data fusion and harmonization of a diverse set of multi-sensor data streams considerably improved the quality and quantity of distilled data that a research participant received. Though automation considerably accelerated the production of the reports, manual and structured double checks are strongly recommended.

Land use regression modelling of NO2 in São Paulo, Brazil.

BACKGROUND: Air pollution is a major global public health problem. The situation is most severe in low- and middle-income countries, where pollution control measures and monitoring systems are largely lacking. Data to quantify the exposure to air pollution in low-income settings are scarce. METHODS: In this study, land use regression models (LUR) were developed to predict the outdoor nitrogen dioxide (NO2) concentration in the study area of the Western Region Birth Cohort in São Paulo. NO2 measurements were performed for one week in winter and summer at eighty locations. Additionally, weekly measurements at one regional background location were performed over a full one-year period to create an annual prediction. RESULTS: Three LUR models were developed (annual, summer, winter) by using a supervised stepwise linear regression method. The winter, summer and annual models explained 52 %, 75 % and 66 % of the variance (R2) respectively. Cross-holdout validation tests suggest robust models. NO2 levels ranged from 43.2 µg/m3 to 93.4 µg/m3 in the winter and between 28.1 µg/m3 and 72.8 µg/m3 in summer. Based on our annual prediction, about 67 % of the population living in the study area is exposed to NO2 values over the WHO suggested annual guideline of 40 µg/m3 annual average. CONCLUSION: In this study we were able to develop robust models to predict NO2 residential exposure. We could show that average measures, and therefore the predictions of NO2, in such a complex urban area are substantially high and that a major variability within the area and especially within the season is present. These findings also suggest that in general a high proportion of the population is exposed to high NO2 levels.

Land use regression modelling of community noise in São Paulo, Brazil.

Noise pollution has negative health consequences, which becomes increasingly relevant with rapid urbanization. In low- and middle-income countries research on health effects of noise is hampered by scarce exposure data and noise maps. In this study, we developed land use regression (LUR) models to assess spatial variability of community noise in the Western Region of São Paulo, Brazil.We measured outdoor noise levels continuously at 42 homes once or twice for one week in the summer and the winter season. These measurements were integrated with various geographic information system variables to develop LUR models for predicting average A-weighted (dB(A)) day-evening-night equivalent sound levels (Lden) and night sound levels (Lnight). A supervised mixed linear regression analysis was conducted to test potential noise predictors for various buffer sizes and distances between home and noise source. Noise exposure levels in the study area were high with a site average Lden of 69.3 dB(A) ranging from 60.3 to 82.3 dB(A), and a site average Lnight of 59.9 dB(A) ranging from 50.7 to 76.6 dB(A). LUR models had a good fit with a R2 of 0.56 for Lden and 0.63 for Lnight in a leave-one-site-out cross validation. Main predictors of noise were the inverse distance to medium roads, count of educational facilities within a 400 m buffer, mean Normalized Difference Vegetation Index (NDVI) within a 100 m buffer, residential areas within a 50 m (Lden) or 25 m (Lnight) buffer and slum areas within a 400 m buffer. Our study suggests that LUR modelling with geographic predictor data is a promising and efficient approach for noise exposure assessment in low- and middle-income countries, where noise maps are not available.

Residential radon - Comparative analysis of exposure models in Switzerland.

Residential radon exposure is a major public health issue in Switzerland due to the known association between inhaled radon progeny and lung cancer. To confirm recent findings of an association with skin cancer mortality, an updated national radon model is needed. The aim of this study was to derive the best possible residential radon prediction model for subsequent epidemiological analyses. Two different radon prediction models were developed (linear regression model vs. random forest) using ca. 80,000 measurements in the Swiss Radon Database (1994-2017). A range of geographic predictors and building specific predictors were considered in the 3-D models (x,y, floor of dwelling). A five-fold modelling strategy was used to evaluate the robustness of each approach, with models developed (80% measurement locations) and validated (20%) using standard diagnostics. Random forest consistently outperformed the linear regression model, with higher Spearman's rank correlation (51% vs. 36%), validation coefficient of determination (R2 31% vs. 15%), lower root mean square error (RMSE) and lower fractional bias. Applied to the population of 5.4 million adults in 2000, the random forest resulted in an arithmetic mean (standard deviation) of 75.5 (31.7) Bq/m3, and indicated a respective 16.1% and 0.1% adults with predicted radon concentrations exceeding the World Health Organization (100 Bq/m3) and Swiss (300 Bq/m3) reference values.

Estimating the health benefits associated with a speed limit reduction to thirty kilometres per hour: A health impact assessment of noise and road traffic crashes for the Swiss city of Lausanne.

Reductions of speed limits for road traffic are effective in reducing casualties, and are also increasingly promoted as an effective way to reduce noise exposure. The aim of this study was to estimate the health benefits of the implementation of 30 km/h speed limits in the city of Lausanne (136'077 inhabitants) under different scenarios addressing exposure to noise and road crashes. The study followed a standard methodology for quantitative health impact assessments to derive the number of attributable cases in relation to relevant outcomes. We compared a reference scenario (without any 30 km/h speed limits) to the current situation with partial speed limits and additional scenarios with further implementation of 30 km/h speed limits, including a whole city scenario. Compared to the reference scenario, noise reduction due to the current speed limit situation was estimated to annually prevent 1 cardiovascular death, 72 hospital admissions from cardiovascular disease, 17 incident diabetes cases, 1'127 individuals being highly annoyed and 918 individuals reporting sleep disturbances from noise. Health benefits from a reduction in road traffic crashes were less pronounced (1 severe injury and 4 minor injuries). The whole city speed reduction scenario more than doubled the annual benefits, and was the only scenario that contributed to a reduction in mortality from road traffic crashes (one death per two years). Implementing 30 km/h speed limits in a city yields health benefits due to reduction in road traffic crashes and noise exposure. We found that the benefit from noise reduction was more relevant than safety benefits.

Concurrently Measured Concentrations of Atmospheric Mercury in Indoor (household) and Outdoor Air of Basel, Switzerland.

Indoor air pollution can be a major health risk because urban populations spend up to 90% of their time in closed rooms. Gaseous elemental mercury (GEM) has not been measured as routinely as other indoor air pollutants due to the high costs and limited mobility of active Hg analyzers. However, household GEM concentrations may exceed Hg air quality guidelines as a result of potential indoor GEM sources like broken Hg thermometers. Here we deploy novel low-cost mercury passive air samplers (MerPAS) in 27 households (7 days) and at 14 outdoor locations (29-31 days) in Basel, Switzerland. Average Hg concentrations ranged from 2.0 to 10.8 ng m-3 indoors and from 1.8 to 2.5 ng m-3 outdoors. These results reveal that households are a net source of Hg to the urban atmosphere and exceed outdoor Hg levels by a factor of 2 on average. We estimated an average weekly intake rate of 0.01 µg of Hg/kg of body weight for adult residents in Basel, which is usually lower than Hg exposure of people with dental amalgam fillings. Our campaign demonstrates that air monitoring programs can easily be complemented by straightforward Hg measurements using MerPAS.

Associations of Various Nighttime Noise Exposure Indicators with Objective Sleep Efficiency and Self-Reported Sleep Quality: A Field Study.

It is unclear which noise exposure time window and noise characteristics during nighttime are most detrimental for sleep quality in real-life settings. We conducted a field study with 105 volunteers wearing a wrist actimeter to record their sleep during seven days, together with concurrent outdoor noise measurements at their bedroom window. Actimetry-recorded sleep latency increased by 5.6 min (95% confidence interval (CI): 1.6 to 9.6 min) per 10 dB(A) increase in noise exposure during the first hour after bedtime. Actimetry-assessed sleep efficiency was significantly reduced by 2%-3% per 10 dB(A) increase in measured outdoor noise (Leq, 1h) for the last three hours of sleep. For self-reported sleepiness, noise exposure during the last hour prior to wake-up was most crucial, with an increase in the sleepiness score of 0.31 units (95% CI: 0.08 to 0.54) per 10 dB(A) Leq,1h. Associations for estimated indoor noise were not more pronounced than for outdoor noise. Taking noise events into consideration in addition to equivalent sound pressure levels (Leq) only marginally improved the statistical models. Our study provides evidence that matching the nighttime noise exposure time window to the individual's diurnal sleep-wake pattern results in a better estimate of detrimental nighttime noise effects on sleep. We found that noise exposure at the beginning and the end of the sleep is most crucial for sleep quality.

Reasons for Prehospital Delay in Acute Ischemic Stroke.

Background Prehospital delay reduces the proportion of patients with stroke treated with recanalization therapies. We aimed to identify novel and modifiable risk factors for prehospital delay. Methods and Results We included patients with an ischemic stroke confirmed by diffusion-weighted magnetic resonance imaging, symptom onset within 24 hours and hospitalized in the Stroke Center of the University Hospital Basel, Switzerland. Trained study nurses interviewed patients and proxies along a standardized questionnaire. Prehospital delay was defined as >4.5 hours between stroke onset-or time point of wake-up-and admission. Overall, 336 patients were enrolled. Prehospital delay was observed in 140 patients (42%). The first healthcare professionals to be alarmed were family doctors for 29% of patients (97/336), and a quarter of these patients had a baseline National Institute of Health Stroke Scale score of 4 or higher. The main modifiable risk factor for prehospital delay was a face-to-face visit to the family doctor (adjusted odds ratio, 4.19; 95% CI, 1.85-9.46). Despite transport by emergency medical services being associated with less prehospital delay (adjusted odds ratio, 0.41; 95% CI, 0.24-0.71), a minority of patients (39%) who first called their family doctor were transported by emergency medical services to the hospital. The second risk factor was lack of awareness of stroke symptoms (adjusted odds ratio, 4.14; 95% CI, 2.36-7.24). Conclusions Almost 1 in 3 patients with a diffusion-weighted magnetic resonance imaging-confirmed ischemic stroke first called the family doctor practice. Face-to-face visits to the family doctor quadrupled the odds of prehospital delay. Efforts to reduce prehospital delay should address family doctors and their staffs as important partners in the prehospital pathway. Clinical Trial Registration URL: http://www.clinicaltrials.gov. Unique identifier: NCT02798770.

Impact of the warm 2015 on emergency hospital admissions in Switzerland.

BACKGROUND: Only a few studies have examined the impact of a particular heat event on morbidity. The aim of this study was to evaluate the impact of the warm summer 2015 on emergency hospital admissions (EHA) in Switzerland. The summer 2015 ranks as the second hottest after 2003 in the history of temperature observation in Switzerland. METHODS: Daily counts of EHA for various disease categories during summer 2015 were analyzed in relation to previous summers in Switzerland. Excess EHA for non-external causes during summer 2015 (June-August) were estimated by age group, gender, geographic region and disease category by comparing observed and expected cases. The latter were predicted from strata-specific quasi-Poisson regression models fitted to the daily counts of EHA for years 2012-2014. RESULTS: Over the three summer months in 2015, an estimated 2.4% (95% confidence interval [CI] 1.6-3.2%) increase in EHA (non-external causes) occurred corresponding to 2,768 excess cases. Highest excess EHA estimates were found in the warmest regions (Ticino [8.4%, 95% CI 5.1-11.7%] and the Lake Geneva region [4.8%, 95% CI 3.0-6.7%]) and among the elderly population aged ≥75 years (5.1%, 95% CI 3.7-6.5%). Increased EHA during days with most extreme temperatures were observed for influenza and pneumonia, certain infectious diseases and diseases of the genitourinary system. CONCLUSIONS: Summer 2015 had a considerable impact on EHA in Switzerland. The daily number of EHA mainly increased due to diseases not commonly linked to heat-related mortality. No excess morbidity was found for cardiovascular and most respiratory diseases. This suggests that current public health interventions should be reevaluated to prevent both heat-related illness and deaths.

Modelling the vertical gradient of nitrogen dioxide in an urban area.

INTRODUCTION: Land use regression models environmental predictors to estimate ground-floor air pollution concentration surfaces of a study area. While many cities are expanding vertically, such models typically ignore the vertical dimension. METHODS: We took integrated measurements of NO2 at up to three different floors on the facades of 25 buildings in the mid-sized European city of Basel, Switzerland. We quantified the decrease in NO2 concentration with increasing height at each facade over two 14-day periods in different seasons. Using predictors of traffic load, population density and street configuration, we built conventional land use regression (LUR) models which predicted ground floor concentrations. We further evaluated which predictors best explained the vertical decay rate. Ultimately, we combined ground floor and decay models to explain the measured concentrations at all heights. RESULTS: We found a clear decrease in mean nitrogen dioxide concentrations between measurements at ground level and those at higher floors for both seasons. The median concentration decrease was 8.1% at 10 m above street level in winter and 10.4% in summer. The decrease with height was sharper at buildings where high concentrations were measured on the ground and in canyon-like street configurations. While the conventional ground floor model was able to explain ground floor concentrations with a model R2 of 0.84 (RMSE 4.1 µg/m3), it predicted measured concentrations at all heights with an R2 of 0.79 (RMSE 4.5 µg/m3), systematically overpredicting concentrations at higher floors. The LUR model considering vertical decay was able to predict ground floor and higher floor concentrations with a model R2 of 0.84 (RMSE 3.8 µg/m3) and without systematic bias. DISCUSSION: Height above the ground is a relevant determinant of outdoor residential exposure, even in medium-sized European cities without much high-rise. It is likely that conventional LUR models overestimate exposure for residences at higher floors near major roads. This overestimation can be minimized by considering decay with height.