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Background The mechanism for spread of SARS-CoV-2 has been attributed to large particles produced by coughing and sneezing. There is controversy whether smaller airborne particles may transport SARS-CoV-2. Smaller particles, particularly fine particulate matter (≤ 2.5 µm in diameter), can remain airborne for longer periods than larger particles and after inhalation will penetrate deeply into the lungs. Little is known about the size distribution and location of airborne SARS-CoV-2 RNA. Methods As a measure of hospital-related exposure, air samples of three particle sizes (> 10.0 µm, 10.0–2.5 µm, and ≤ 2.5 µm) were collected in a Boston, Massachusetts (USA) hospital from April to May 2020 ( N  = 90 size-fractionated samples). Locations included outside negative-pressure COVID-19 wards, a hospital ward not directly involved in COVID-19 patient care, and the emergency department. Results SARS-CoV-2 RNA was present in 9% of samples and in all size fractions at concentrations of 5 to 51 copies m −3 . Locations outside COVID-19 wards had the fewest positive samples. A non-COVID-19 ward had the highest number of positive samples, likely reflecting staff congregation. The probability of a positive sample was positively associated ( r  = 0.95, p  < 0.01) with the number of COVID-19 patients in the hospital. The number of COVID-19 patients in the hospital was positively associated ( r  = 0.99, p  < 0.01) with the number of new daily cases in Massachusetts. Conclusions More frequent detection of positive samples in non-COVID-19 than COVID-19 hospital areas indicates effectiveness of COVID-ward hospital controls in controlling air concentrations and suggests the potential for disease spread in areas without the strictest precautions. The positive associations regarding the probability of a positive sample, COVID-19 cases in the hospital, and cases in Massachusetts suggests that hospital air sample positivity was related to community burden. SARS-CoV-2 RNA with fine particulate matter supports the possibility of airborne transmission over distances greater than six feet. The findings support guidelines that limit exposure to airborne particles including fine particles capable of longer distance transport and greater lung penetration.

It is uncertain what climate change could bring to populations and countries in the hot desert environment of the Arabian Peninsula. Not only because they are already hot, countries in this region also have unique demographic profiles, with migrant populations potentially more vulnerable and constituting a large share of the population. In Kuwait, two-thirds of the population are migrant workers and record-high temperatures are already common. We quantified the temperature-related mortality burdens in Kuwait in the mid- (2050–2059) and end-century (2090–2099) decades under moderate (SSP2-4.5) and extreme (SSP5-8.5) climate change scenarios. We fitted time series distributed lag non-linear models to estimate the baseline temperature–mortality relationship which was then applied to future daily mean temperatures from the latest available climate models to estimate decadal temperature-mortality burdens under the two scenarios. By mid-century, the average temperature in Kuwait is predicted to increase by 1.80 °C (SSP2-4.5) to 2.57 °C (SSP5-8.5), compared to a 2000–2009 baseline. By the end of the century, we could see an increase of up to 5.54 °C. In a moderate scenario, climate change would increase heat-related mortality by 5.1% (95% empirical confidence intervals: 0.8, 9.3) by end-century, whereas an extreme scenario increases heat-related mortality by 11.7% (2.7, 19.0). Heat-related mortality for non-Kuwaiti migrant workers could increase by 15.1% (4.6, 22.8). For every 100 deaths in Kuwait, 13.6 (−3.6, 25.8) could be attributed to heat driven by climate change by the end of the century. Climate change induced warming, even under more optimistic mitigation scenarios, may markedly increase heat-related mortality in Kuwait. Those who are already vulnerable, like migrant workers, could borne a larger impact from climate change.

This study investigated the associations between solar and geomagnetic activity and circulating biomarkers of systemic inflammation and endothelial activation in the Normative Aging Study (NAS) cohort. Mixed effects models with moving day averages from day 0 to day 28 were used to study the associations between solar activity (sunspot number (SSN), interplanetary magnetic field (IMF)), geomagnetic activity (planetary K index (K p index), and various inflammatory and endothelial markers. Biomarkers included intracellular adhesion molecule-1 (sICAM-1), vascular cell adhesion molecule-1 (sVCAM-1), C-reactive protein (CRP), and fibrinogen. After adjusting for demographic and meteorological variables, we observed significant positive associations between sICAM-1 and sVCAM-1 concentrations and solar and geomagnetic activity parameters: IMF, SSN, and K p . Additionally, a negative association was observed between fibrinogen and K p index and a positive association was observed for CRP and SSN. These results demonstrate that solar and geomagnetic activity might be upregulating endothelial activation and inflammation.

COPD is characterized by variability in exercise capacity and physical activity (PA), and acute exacerbations (AEs). Little is known about the relationship between daily step count, a direct measure of PA, and the risk of AEs, including hospitalizations. In an observational cohort study of 169 persons with COPD, we directly assessed PA with the StepWatch Activity Monitor, an ankle-worn accelerometer that measures daily step count. We also assessed exercise capacity with the 6-minute walk test (6MWT) and patient-reported PA with the St. George's Respiratory Questionnaire Activity Score (SGRQ-AS). AEs and COPD-related hospitalizations were assessed and validated prospectively over a median of 16 months. Mean daily step count was 5804±3141 steps. Over 209 person-years of observation, there were 263 AEs (incidence rate 1.3±1.6 per person-year) and 116 COPD-related hospitalizations (incidence rate 0.56±1.09 per person-year). Adjusting for FEV1 % predicted and prednisone use for AE in previous year, for each 1000 fewer steps per day walked at baseline, there was an increased rate of AEs (rate ratio 1.07; 95%CI = 1.003-1.15) and COPD-related hospitalizations (rate ratio 1.24; 95%CI = 1.08-1.42). There was a significant linear trend of decreasing daily step count by quartiles and increasing rate ratios for AEs (P = 0.008) and COPD-related hospitalizations (P = 0.003). Each 30-meter decrease in 6MWT distance was associated with an increased rate ratio of 1.07 (95%CI = 1.01-1.14) for AEs and 1.18 (95%CI = 1.07-1.30) for COPD-related hospitalizations. Worsening of SGRQ-AS by 4 points was associated with an increased rate ratio of 1.05 (95%CI = 1.01-1.09) for AEs and 1.10 (95%CI = 1.02-1.17) for COPD-related hospitalizations. Lower daily step count, lower 6MWT distance, and worse SGRQ-AS predict future AEs and COPD-related hospitalizations, independent of pulmonary function and previous AE history. These results support the importance of assessing PA in patients with COPD, and provide the rationale to promote PA as part of exacerbation-prevention strategies.

The effects of indoor air pollution on human health have drawn increasing attention among the scientific community as individuals spend most of their time indoors. However, indoor air sampling is labor-intensive and costly, which limits the ability to study the adverse health effects related to indoor air pollutants. To overcome this challenge, many researchers have attempted to predict indoor exposures based on outdoor pollutant concentrations, home characteristics, and weather parameters. Typically, these models require knowledge of the infiltration factor, which indicates the fraction of ambient particles that penetrates indoors. For estimating indoor fine particulate matter (PM2.5 ) exposure, a common approach is to use the indoor-to-outdoor sulfur ratio (Sindoor /Soutdoor ) as a proxy of the infiltration factor. The objective of this study was to develop a robust model that estimates Sindoor /Soutdoor for individual households that can be incorporated into models to predict indoor PM2.5 and black carbon (BC) concentrations. Overall, our model adequately estimated Sindoor /Soutdoor with an out-of-sample by home-season R2 of 0.89. Estimated Sindoor /Soutdoor reflected behaviors that influence particle infiltration, including window opening, use of forced air heating, and air purifier. Sulfur ratio-adjusted models predicted indoor PM2.5 and BC with high precision, with out-of-sample R2 values of 0.79 and 0.76, respectively.

Understanding the potential health implications of living near nuclear power plants is important given the renewed interest in nuclear energy as a low-carbon power source. Here we show that U.S. counties located closer to operational nuclear power plants have higher cancer mortality rates than those farther away. Using nationwide mortality data from 2000-2018, we assess long-term spatial patterns of cancer mortality in relation to proximity to nuclear facilities while accounting for socioeconomic, demographic, behavioral, environmental, and healthcare factors. Cancer mortality is higher across multiple age groups in both males and females, with the strongest associations among older adults, males aged 65–74 and females aged 55–64. While our findings cannot establish causality, they highlight the need for further research into potential exposure pathways, latency effects, and cancer-specific risks, emphasizing the importance of addressing these potentially substantial but overlooked risks to public health. ‘Populations residing near nuclear power plants may experience low-level chronic exposure to ionizing radiation through environmental release pathways. In here the authors find higher cancer mortality rates in U.S. counties closer to operational nuclear power plants, with the strongest relative risks observed in older adults.’

Background Little is known about the link between solar activity and variations in melatonin. In this study, we investigated if melatonin's major urinary metabolite, urinary 6-sulfatoxymelatonin (aMT6s), is lowest under periods of intense solar activity. Methods We investigated associations between high-energy solar particle events [Coronal Mass Ejection (CME) mass, speed and energy] on creatinine-adjusted aMT6s (aMT6sr) concentrations in 140 patients with chronic obstructive pulmonary disease (COPD) using up to four seasonal urine samples (n = 440). Mixed effect models with a random intercept for each subject were used to estimate associations, including effect modification attributable to diabetes, obesity, and reduced pulmonary function. Results Higher values of CME were associated with reduced aMT6sr concentrations, with stronger associations in patients with diabetes. An interquartile range (IQR) increase in natural log CME speed averaged through two days before urine collection was associated with a reduction of 9.3% aMT6sr (95%CI: − 17.1%, − 0.8%) in aMT6sr. There was a greater reduction in aMT6sr in patients with diabetes (− 24.5%; 95%CI: − 35.9%, − 11.6%). In patients without diabetes there was no meaningful association (− 2.2%; 95%CI: − 12%, 8.4%). There were similar associations with CME energy and CME mass . There was no effect modification attributable to reduced pulmonary function or obesity. Conclusions This is the first study in patients with COPD to demonstrate strong detrimental impact of high-energy solar particle events on aMT6sr, with greater associations in patients with diabetes. Since melatonin is an anti-oxidant, it is possible that adverse effects of intense solar activity may be attributable to a reduction in circulating melatonin and that patients with both COPD and diabetes may be more susceptible.

Background Incidental findings (IFs) are common on low dose CT obtained during lung cancer screening (LCS). The identification and management of clinically significant IFs is a challenging aspect of LCS programs and there is no standardized method of reporting IFs to primary care providers or patients. We explored the prevalence of incidental findings and radiologist use of the “S” modifier to identify clinically significant findings compared to what the LCS team identified as a clinically significant finding. We also presented a standardized reporting approach that provides suggested actions for providers and patients. Methods We conducted a review of a sample of low-dose CT scans of the chest reported between August 17, 2023 and April 29, 2024 completed at VA Boston Healthcare System, omitting scans with findings concerning for lung cancer. We assessed the reporting of incidental findings by the radiologist, compared this to identification of clinically significant incidental findings by the lung cancer screening team, and evaluated factors associated with number and occurrence of incidental findings (via complete case regression). Results Among 495 patients (Mean Age: 69.0 (6.6), 94.4% Male, 53.2% Current Smoker), 444 scans were retained for analysis. Scans had a median of seven incidental findings. The most common incidental finding was multiple pulmonary nodules (77.9%). There were 165 low-dose CT with findings the lung cancer screening team considered clinically important, however, radiologists only assigned the “S” modifier to 35 scans. Conclusions All scans reviewed had incidental findings and nearly 40% had a finding that was clinically significant to the lung cancer screening team. There was inconsistent reporting between the radiologists and lung cancer screening team on clinical significance. Radiologists identified fewer clinically important findings than the lung cancer screening team and applied the “S” modifier inconsistently. There is no standardized method for reporting clinically significant low-dose CT results to primary care providers or patients. Our approach provides a structured approach, acknowledges multiple clinical opinions, and provides a framework for communication.

Exposure to radioactivity inside homes potentially poses severe health risks which can be exacerbated by the interaction between radioactive particles and fine indoor particles; in particular, the presence of α particles are a key risk factor. Hence, in this study, particle radioactivity was concurrently measured in the family rooms and basements of 26 homes to assess its concentrations and identify its sources, both indoors and outdoors, across two seasons. The levels of radon, air ions, and particle radioactivity, which included short- and long-lived α-activity (SLA and LLA, respectively), varied greatly but were substantially higher in the basements. Also, particle radioactivity—as well as PM 2 5 and sulfur concentrations—were lower during the heating season. SLA was associated with radon, which was consistently of indoor origin, whereas LLA was more strongly related to the sulfur measured in indoor PM 2 5 , which is a proxy of outdoor infiltration. A regression model adjusted for sulfur and SLA also indicated a predominance of outdoor sources, likely due to the short residence time of indoor particles. Our results suggest that radiation in homes originates from both the decay of indoor radon and the infiltration of outdoor radioactivity.

Background: Diesel exhaust has been considered to be a probable lung carcinogen based on studies of occupationally exposed workers. Efforts to define lung cancer risk in these studies have been limited in part by lack of quantitative exposure estimates. Objective: We conducted a retrospective cohort study to assess lung cancer mortality risk among U.S. trucking industry workers. Elemental carbon (EC) was used as a surrogate of exposure to engine exhaust from diesel vehicles, traffic, and loading dock operations. Methods: Work records were available for 31,135 male workers employed in the unionized U.S. trucking industry in 1985. A statistical model based on a national exposure assessment was used to estimate historical work-related exposures to EC. Lung cancer mortality was ascertained through the year 2000, and associations with cumulative and average EC were estimated using proportional hazards models. Results: Duration of employment was inversely associated with lung cancer risk consistent with a healthy worker survivor effect and a cohort composed of prevalent hires. After adjusting for employment duration, we noted a suggestion of a linear exposure-response relationship. For each 1,000-μg/m³ months of cumulative EC, based on a 5-year exposure lag, the hazard ratio (HR) was 1.07 [95% confidence interval (CI): 0.99, 1.15] with a similar association for a 10-year exposure lag [HR = 1.09 (95% CI: 0.99, 1.20)]. Average exposure was not associated with relative risk. Conclusions: Lung cancer mortality in trucking industry workers increased in association with cumulative exposure to EC after adjusting for negative confounding by employment duration.