Responses to COVID-19 altered environmental exposures and health behaviours associated with non-communicable diseases. We aimed to (1) quantify changes in nitrogen dioxide (NO₂), noise, physical activity, and greenspace visits associated with COVID-19 policies in the spring of 2020 in Barcelona (Spain), Vienna (Austria), and Stockholm (Sweden), and (2) estimated the number of additional and prevented diagnoses of myocardial infarction (MI), stroke, depression, and anxiety based on these changes. We calculated differences in NO₂, noise, physical activity, and greenspace visits between pre-pandemic (baseline) and pandemic (counterfactual) levels. With two counterfactual scenarios, we distinguished between Acute Period (March 15th – April 26th, 2020) and Deconfinement Period (May 2nd – June 30th, 2020) assuming counterfactual scenarios were extended for 12 months. Relative risks for each exposure difference were estimated with exposure-risk functions. In the Acute Period, reductions in NO₂ (range of change from −16.9 μg/m³ to −1.1 μg/m³), noise (from −5 dB(A) to −2 dB(A)), physical activity (from −659 MET*min/wk to −183 MET*min/wk) and greenspace visits (from −20.2 h/m to 1.1 h/m) were largest in Barcelona and smallest in Stockholm. In the Deconfinement Period, NO₂ (from −13.9 μg/m³ to −3.1 μg/m³), noise (from −3 dB(A) to −1 dB(A)), and physical activity levels (from −524 MET*min/wk to −83 MET*min/wk) remained below pre-pandemic levels in all cities. Greatest impacts were caused by physical activity reductions. If physical activity levels in Barcelona remained at Acute Period levels, increases in annual diagnoses for MI (mean: 572 (95% CI: 224, 943)), stroke (585 (6, 1156)), depression (7903 (5202, 10,936)), and anxiety (16,677 (926, 27,002)) would be anticipated. To decrease cardiovascular and mental health impacts, reductions in NO₂ and noise from the first COVID-19 surge should be sustained, but without reducing physical activity. Focusing on cities’ connectivity that promotes active transportation and reduces motor vehicle use assists in achieving this goal.

We aimed to update the evidence-base of long-term noise exposures from road, rail, and aircraft traffic on both non-accidental and cardiovascular mortality.A systematic review and meta-analysis were conducted following PRISMA guidelines. The literature was searched using PubMed, Scopus, Web of Science, and EMBASE for the period between January 01, 2000 and October 05, 2020. 13 studies were selected for final review. The risk of bias and overall quality of evidence was evaluated using a pre-defined list of criteria. Risk estimates from each study were converted into per 10 dB higher of Ldₑₙ for each traffic source. Inverse-Variance heterogeneity (I-Vhet) meta-analysis was used to pool these individual risk estimates, along with assessment of heterogeneity and publication bias. Sensitivity analyses include using random-effect model and leave-one-out meta-analysis. Subgroup analyses by study design and noise exposure assessment were conducted to explore potential sources of heterogeneity.For road traffic, the pooled relative risk (RR) per 10 dB higher Ldₑₙ for mortality from non-accidental causes was 1.01 (95% CI: 0.98, 1.05) (5 studies, I² = 78%), CVD was 1.01 (95% CI: 0.98, 1.05) (5 studies, I² = 41%), ischemic heart disease (IHD) was 1.03 (95% CI: 0.99, 1.08) (7 studies, I² = 46%), and stroke was 1.05 (95% CI: 0.97, 1.14) (5 studies, I² = 62%). The overall quality of evidence for most meta-analyses was rated as very low to low, except for CVD or IHD mortality, for which the quality of evidence was rated as moderate. A possible threshold of 53 dB was visually suggested for CVD-related mortality from road traffic noise in the trend analysis. For aircraft noise, pooled estimates were based on fewer studies and varied by mortality outcomes.Evidence of long-term exposure to traffic noise on mortality remains weak except the association between road traffic noise and IHD mortality. High-quality longitudinal studies are required to better characterise mortality effects of traffic noise.

The estimation of PM₂.₅-related mortality is becoming increasingly important. The accuracy of results is largely dependent on the selection of methods for PM₂.₅ exposure assessment and Concentration-Response (C-R) function. In this study, PM₂.₅ observed data from the China National Environmental Monitoring Center, satellite-derived estimation, widely collected geographic and socioeconomic information variables were applied to develop a national satellite-based Land Use Regression model and evaluate PM₂.₅ exposure concentrations within 2013–2015 with the resolution of 1 km × 1 km. Population weighted concentration declined from 72.52 μg/m³ in 2013 to 57.18 μg/m³ in 2015. C-R function is another important section of health effect assessment, but most previous studies used the Integrated Exposure Regression (IER) function which may currently underestimate the excess relative risk of exceeding the exposure range in China. A new Shape Constrained Health Impact Function (SCHIF) method, which was developed from a national cohort of 189,793 Chinese men, was adopted to estimate the PM₂.₅-related premature deaths in China. Results showed that 2.19 million (2013), 1.94 million (2014), 1.65 million (2015) premature deaths were attributed to PM₂.₅ long-term exposure, different from previous understanding around 1.1–1.7 million. The top three provinces of the highest premature deaths were Henan, Shandong, Sichuan, while the least ones were Tibet, Hainan, Qinghai. The proportions of premature deaths caused by specific diseases were 53.2% for stroke, 20.5% for ischemic heart disease, 16.8% for chronic obstructive pulmonary disease and 9.5% for lung cancer. IER function was also used to calculate PM₂.₅-related premature deaths with the same exposed level used in SCHIF method, and the comparison of results indicated that IER had made a much lower estimation with less annual amounts around 0.15–0.5 million premature deaths within 2013–2015.

While the health impacts of larger particulate matter, such as PM₁₀ and PM₂.₅, have been studied extensively, research regarding ultrafine particles (UFPs or PM₀.₁) and particle surface area concentration (PSC) is lacking. This case-crossover study assessed the associations between exposure to PSC and UFP number concentration (UFPnc) and hospital admissions for cardiovascular diseases (CVDs) in New York State (NYS), 2013–2018. We used a time-stratified case-crossover design to compare the PSC and UFPnc levels between hospitalization days and control days (similar days without admissions) for each CVD case. We utilized NYS hospital discharge data to identify all CVD cases who resided in NYS. UFP simulation data from GEOS-Chem-APM, a state-of-the-art chemical transport model, was used to define PSC and UFPnc. Using a multi-pollutant model and conditional logistic regression, we assessed excess risk (ER)% per inter-quartile change of PSC and UFPnc after controlling for meteorological factors, co-pollutants, and time-varying variables. We found immediate and lasting associations between PSC and overall CVDs (lag0–lag0-6: ERs% (95% CI%) ranges: 0.4 (0.1,0.7) - 0.9 (0.7–1.2), and delayed and prolonged ERs%: 0.1–0.3 (95% CIs: 0.1–0.5) between UFPnc and CVDs (lag0-3–lag0-6). Exposure to larger PSC was associated with immediate ER increases in stroke, hypertension, and ischemic heart diseases (1.1%, 0.7%, 0.8%, respectively, all p < 0.05). The adverse effects of PSC on CVDs were highest among children (5–17 years old), in the fall and winter, and during cold temperatures. In conclusion, we found an immediate, lasting effects of PSC on overall CVDs and a delayed, prolonged impact of UFPnc. PSC was a more sensitive indicator than UFPnc. The PSC effects were higher among certain CVD subtypes, in children, in certain seasons, and during cold days. Further studies are needed to validate our findings and evaluate the long-term effects.

Stroke and fine particulate matter (PM₂.₅) are two important public health concerns worldwide. Although numerous studies have reported the associations between PM₂.₅ and stroke, scientific evidence in China is incomplete, particularly the effect of PM₂.₅ on the acute incidence and national acute health burdens of stroke attributed to PM₂.₅ pollution. This study identified about 131,947 registered patients and 23,018 deaths due to stroke in 10 counties located in various regions from 2013 to 2017. Using a time-stratified case-crossover design, this study evaluated the associations between short-term exposure to PM₂.₅ and the risks of acute incidence and mortality for different types of stroke on the same spatiotemporal scale. With a 10 μg/m³ increase in the PM₂.₅ concentration, the acute incidence risk increased by 0.37% (0.15%, 0.60%) for stroke, 0.46% (0.21%, 0.72%) for ischemic stroke, and −0.13% (−0.73%, 0.48%) for hemorrhagic stroke. The corresponding values for the mortality risk were 0.71% (0.08%, 1.33%), 1.09% (0.05%, 2.14%), and 0.43% (−0.44%, 1.31%) for stroke, ischemic stroke and hemorrhagic stroke, respectively. Compared with the other groups, females and patients aged over 64 years presented higher incidence and mortality risks, while the group aged >75 years may exhibit a greater risk of mortality. Based on the estimated effects, we evaluated 43,300 excess deaths and 48,800 acute incidences attributed to short-term PM₂.₅ exposure across China in 2015. This study provided robust estimates of PM₂.₅-induced stroke incidence and mortality risks, and susceptible populations were identified. Excess mortality and morbidity attributed to short-term PM₂.₅ exposure indicate the necessity to implement health care and prevention strategies, as well as medical resource allocation for noncommunicable diseases in regions with high levels of air pollution.

This study aims to examine the association between short-term exposures to PM₁, PM₂.₅ and PM₁₀ (particulate matter with aerodynamic diameters ≤1 μm, ≤2.5 μm and ≤10 μm, respectively) and hospital admission for ischemic stroke in China. Daily counts of hospital admission for ischemic stroke were collected in 5 hospitals in China during November 2013 to October 2015. Daily concentrations of PM₁, PM₂.₅ and PM₁₀ were collected in 5 cities where the hospitals were located. A time-stratified case-crossover design was used to examine the hospital-specific PM-ischemic stroke association after controlling for potential confounders. Then the effect estimates were pooled using a random-effect meta-analysis. A total of 68,122 hospital admissions for ischemic stroke were identified from 5 hospitals during the study period. The pooled results showed that exposures to PM₁, PM₂.₅ and PM₁₀ were significantly associated with increased hospital admission for ischemic stroke on the current day and previous 1 day. The RRs (relative risk associated with per 10 μg/m³ increase in each pollutant) and 95%CIs (confidence intervals) for the cumulative effects of PM₁, PM₂.₅ and PM₁₀ on ischemic stroke during lag 0–1 days were 1.014 (1.005, 1.0023), 1.007 (1.000, 1.014) and 1.005 (1.001, 1.009), respectively. In total, 3.5%, 3.6% and 4.1% of hospital admissions for ischemic stroke could be attributable to PM₁, PM₂.₅ and PM₁₀, respectively. Exposures to ambient PM₁, PM₂.₅ and PM₁₀ pollution showed acute adverse effects on hospital admission for ischemic stroke. The health effects of PM₁ should be considered by policy-makers.

Knowledge of environmental risk factors for stroke and their role are limited. We performed a case-cohort study to evaluate the association between serum persistent organic pollutants (POPs) level and stroke risk.526 subcohort members and 111 stroke incidence cases were identified from the Korean Cancer Prevention Study-II. Serum levels of POPs were measured using gas chromatography/high-resolution mass spectrometry. The hazard ratios (HRs) for stroke (ischemic, hemorrhagic, and all stroke types) were estimated using the weighted Cox regression model. Age, sex, body mass index, smoking status, physical activity, family history of cardiovascular disease, and hypertension were adjusted in the weighted Cox regression model.After adjusting for potential confounding factors, increased risk for stroke was observed among participants with serum concentration of p,p'-DDE in the highest tertile compared to those in the lowest tertile (HR = 4.10, 95% CI: 1.58, 10.59). A similar association was estimated for PCB118 (HR = 2.33, 95% CI: 1.04, 5.22), PCB156 (HR = 3.42, 95% CI: 1.42, 8.23), and PCB138 (HR = 3.80, 95% CI: 1.48, 9.76). For TEQ, stroke was three times as likely to occur among subjects with TEQ in the highest tertile compared to those in the lowest tertile (HR = 3.12, 95% CI: 1.27, 7.65). PCBs were positively associated with ischemic stroke, but not with hemorrhagic stroke.Elevated serum POPs levels were associated with an increased risk of stroke, especially ischemic stroke.

While increasing evidence suggested that PM₂.₅ is the most harmful fraction of the particle pollutants, the health effects of coarse particles (PM₁₀–₂.₅) have been inconclusive, especially on cerebrovascular diseases, we thus evaluated the effects of PM₁₀, PM₂.₅, and PM₁₀–₂.₅ on stroke mortality in six Chinese subtropical cities using generalized additive models. We also conducted random-effects meta-analyses to estimate the overall effects across the six cities. We found that PM₁₀, PM₂.₅, and PM₁₀₋₂.₅ were significantly associated with stroke mortality. Each 10 μg/m³ increase of PM₁₀, PM₂.₅ and PM₁₀₋₂.₅ (lag03) was associated with an increase of 1.88% (95% CI: 1.37%, 2.39%), 3.07% (95% CI: 2.35%, 3.79%), and 5.72% (95% CI: 3.82%, 7.65%) in overall stroke mortality. Using the World Health Organization's guideline as reference concentration, we estimated that 3.21% (95% CI: 1.65%, 3.01%) of stroke mortality (corresponding to 1743 stroke mortalities, 95% CI: 896, 1633) were attributed to PM₁₀, 5.57% (95% CI: 0.50%, 1.23%) stroke mortality (3019, 95% CI: 2286, 3777) were attributed to PM₂.₅, and 2.02% (95% CI: 1.85%, 3.08%) of stroke mortality (1097, 95% CI: 1005, 1673) could be attributed to PM₁₀₋₂.₅. Our analysis indicates that both PM₂.₅ and PM₁₀₋₂.₅ are important risk factors of stroke mortality and should be considered in the prevention and control of stroke in the study area.

The effects of ambient temperature on stroke death in China have been well addressed. However, few studies are focused on the attributable burden for the incident of different types of stroke due to ambient temperature, especially in Beijing, China. We purpose to assess the influence of ambient temperature on hospital stroke admissions in Beijing, China. Data on daily temperature, air pollution, and relative humidity measurements and stroke admissions in Beijing were obtained between 2013 and 2014. Distributed lag non-linear model was employed to determine the association between daily ambient temperature and stroke admissions. Relative risk (RR) with 95% confidence interval (CI) and Attribution fraction (AF) with 95% CI were calculated based on stroke subtype, gender and age group. A total number of 147, 624 stroke admitted cases (including hemorrhagic and ischemic types of stroke) were documented. A non-linear acute effect of cold temperature on ischemic and hemorrhagic stroke hospital admissions was evaluated. Compared with the 25th percentile of temperature (1.2 °C), the cumulative RR of extreme cold temperature (first percentile of temperature, −9.6 °C) was 1.51 (95% CI: 1.08–2.10) over lag 0–14 days for ischemic type and 1.28 (95% CI: 1.03–1.59) for hemorrhagic stroke over lag 0–3 days. Overall, 1.57% (95% CI: 0.06%–2.88%) of ischemic stroke and 1.90% (95% CI: 0.40%–3.41%) of hemorrhagic stroke was attributed to the extreme cold temperature over lag 0–7 days and lag 0–3 days, respectively. The cold temperature's impact on stroke admissions was found to be more obvious in male gender and the youth compared to female gender and the elderly. Exposure to extreme cold temperature is associated with increasing both ischemic and hemorrhagic stroke admissions in Beijing, China.

Studies differentiating the cardiorespiratory morbidity effects of PM₂.₅, PM₁₀, and PM₂.₅∼₁₀ (i.e. coarse PM or PMc) are still limited and inconsistent.To estimate the acute, cumulative, and harvesting effects of exposure to the three size-specific PM on cardiorespiratory morbidity, and their concentration-response relations.A total of 6,727,439 emergency department (ED) visits were collected from 16 public teaching hospitals in Guangzhou, from January 1st 2012 to December 31st 2015, among which over 2.1 million were asthma, COPD, pneumonia, respiratory tract infection (RTI), hypertension, stroke, and coronary heart disease (CHD). Distributed lag non-linear models (DLNM) was used to estimate the associations between the three size-specific PM and ED visits for the cardiovascular diseases. Long-term trends, seasonality, influenza epidemics, meteorological factors, and other gas pollutants, including SO2, NO₂, and O₃, were adjusted. We stratified the analyses by gender and age.Elevated PM₂.₅ and PM₁₀ were significantly associated with increased ED visits for pneumonia, RTI, and CHD at both lag₀ and lag₀₋₃. A 10 μg/m³ increment of PMc (at lag₀₋₁₄) was estimated to increase ED visits for pneumonia by 6.32% (95% CI, 4.19, 8.49) and for RTI by 4.72% (95% CI, 3.81, 5.63), respectively. PMc showed stronger cumulative effects on asthma in children than elderly. We observed significant harvesting effects (i.e. morbidity displacements) of the three size-specific PM on respiratory but very little on cardiovascular ED visits. The concentration-response curves suggested non-linear relations between exposures to the three different sizes of PM and respiratory morbidity.Overall, the three size-specific PM demonstrated distinct acute and cumulative effects on the cardiorespiratory diseases. PM₂.₅ and PMc would have significant effects on pneumonia and RTI. Strategies should be considered to further reduce levels of ambient PM₂.₅ and PMc.