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BACKGROUND: There is a long tradition in environmental health of using frameworks for evidence synthesis, such as those of the U.S. Environmental Protection Agency for its Integrated Science Assessments and the International Agency for Research on Cancer Monographs. The framework, Grading of Recommendations Assessment, Development, and Evaluation (GRADE), was developed for evidence synthesis in clinical medicine. The U.S. Office of Health Assessment and Translation (OHAT) elaborated an approach for evidence synthesis in environmental health building on GRADE. METHODS: We applied a modified OHAT approach and a broader narrative assessment to assess the level of confidence in a large systematic review on traffic-related air pollution and health outcomes. DISCUSSION: We discuss several challenges with the OHAT approach and its implementation and suggest improvements for synthesizing evidence from observational studies in environmental health. We consider the determination of confidence using a formal rating scheme of up- and downgrading of certain factors, the treatment of every factor as equally important, and the lower initial confidence rating of observational studies to be fundamental issues in the OHAT approach. We argue that some observational studies can offer high-confidence evidence in environmental health. We note that heterogeneity in magnitude of effect estimates should generally not weaken the confidence in the evidence, and consistency of associations across study designs, populations, and exposure assessment methods may strengthen confidence in the evidence. We mention that publication bias should be explored beyond statistical methods and is likely limited when large and collaborative studies comprise most of the evidence and when accrued over several decades. We propose to identify possible key biases, their most likely direction, and their potential impacts on the results. We think that the OHAT approach and other GRADE-type frameworks require substantial modification to align better with features of environmental health questions and the studies that address them. We emphasize that a broader, narrative evidence assessment based on the systematic review may complement a formal GRADE-type evaluation. https://doi.org/10.1289/EHP11532.

Air pollution is a major health hazard, and while air quality overall has been improving in industrialized nations, pollution is still a major economic and public health issue, with some species, such as ozone (O3), still exceeding the standards set by governing agencies. Chemical transport models (CTMs) are valuable tools that aid in our understanding of the risks of air pollution both at local and regional scales. In this study, the Polair3D v1.11 CTM of the Polyphemus air quality modeling platform was set up over Quebec, Canada, to assess the model's capability in predicting key air pollutant species over the region, at seasonal temporal scales and at regional spatial scales. The simulation by the model included three nested domains, at horizontal resolutions of 9 km by 9 km and 3 km by 3 km, as well as two 1 km by 1 km domains covering the cities of Montréal and Québec. We find that the model captures the spatial variability and seasonal effects and, to a lesser extent, the hour-by-hour or day-to-day temporal variability for a fixed location. The model at both the 3 km and the 1 km resolution struggled to capture high-frequency temporal variability and showed large variabilities in correlation and bias from site to site. When comparing the biases and correlation at a site-wide scale, the 3 km domain showed slightly higher correlation for carbon monoxide (CO), nitrogen dioxide (NO2), and nitric oxide (NO), while ozone (O3), sulfur dioxide (SO2), and PM2.5 showed slight increases in correlation at the 1 km domain. The performance of the Polair3D model was in line with other models over Canada and comparable to Polair3D's performance over Europe.

Objectives: We report results of a systematic review on the health effects of long-term traffic-related air pollution (TRAP) and diabetes in the adult population. Methods: An expert Panel appointed by the Health Effects Institute conducted this systematic review. We searched the PubMed and LUDOK databases for epidemiological studies from 1980 to July 2019. TRAP was defined based on a comprehensive protocol. Random-effects meta-analyses were performed. Confidence assessments were based on a modified Office for Health Assessment and Translation (OHAT) approach, complemented with a broader narrative synthesis. We extended our interpretation to include evidence published up to May 2022. Results: We considered 21 studies on diabetes. All meta-analytic estimates indicated higher diabetes risks with higher exposure. Exposure to NO2 was associated with higher diabetes prevalence (RR 1.09; 95% CI: 1.02; 1.17 per 10 μg/m3), but less pronounced for diabetes incidence (RR 1.04; 95% CI: 0.96; 1.13 per 10 μg/m3). The overall confidence in the evidence was rated moderate, strengthened by the addition of 5 recently published studies. Conclusion: There was moderate evidence for an association of long-term TRAP exposure with diabetes.

Abstract Many studies have projected malaria risks with climate change scenarios by modelling one or two environmental variables and without the consideration of malaria control interventions. We aimed to predict the risk of malaria with climate change considering the influence of rainfall, humidity, temperatures, vegetation, and vector control interventions (indoor residual spraying (IRS) and long-lasting insecticidal nets (LLIN)). We used negative binomial models based on weekly malaria data from six facility-based surveillance sites in Uganda from 2010–2018, to estimate associations between malaria, environmental variables and interventions, accounting for the non-linearity of environmental variables. Associations were applied to future climate scenarios to predict malaria distribution using an ensemble of Regional Climate Models under two Representative Concentration Pathways (RCP4.5 and RCP8.5). Predictions including interaction effects between environmental variables and interventions were also explored. The results showed upward trends in the annual malaria cases by 25% to 30% by 2050s in the absence of intervention but there was great variability in the predictions (historical vs RCP 4.5 medians [Min–Max]: 16,785 [9,902–74,382] vs 21,289 [11,796–70,606]). The combination of IRS and LLIN, IRS alone, and LLIN alone would contribute to reducing the malaria burden by 76%, 63% and 35% respectively. Similar conclusions were drawn from the predictions of the models with and without interactions between environmental factors and interventions, suggesting that the interactions have no added value for the predictions. The results highlight the need for maintaining vector control interventions for malaria prevention and control in the context of climate change given the potential public health and economic implications of increasing malaria in Uganda.

We appreciate the emphasis on the flexibility of the OHAT approach, including a narrative assessment. We respectfully disagree that we incorrectly portrayed the OHAT approach, and we clarify below with [...]

Objective: Exposure to fine particulate matter (PM 2.5 ) has been linked to many diseases. However, it remains unclear which PM 2.5 chemical components for these diseases, including rheumatoid arthritis (RA), are more harmful. This study aimed to assess potential associations between PM 2.5 components and RA and quantify the individual effects of each chemical component on RA risk., Methods: An open cohort of 11,696,930 Canadian adults was assembled using Ontario administrative health data from January 2007 onward. Individuals were followed until RA onset, death, emigration from Ontario, or the end of the study (December 2019). Incident RA cases were defined by physician billing and hospitalization discharge diagnostic codes. The average levels of PM 2.5 components (ammonium, black carbon, mineral dust, nitrate, organic matter, sea salt, and sulfate) for 5 years before cohort entry were assigned to participants based on residential postal codes. A quantile g-computation and Cox proportional hazard models for time to RA onset were developed for the mixture of PM 2.5 components and environmental overall PM 2.5 , respectively., Results: We identified 67,676 new RA cases across 130,934,256 person-years. The adjusted hazard ratios for the time to RA onset were 1.027 and 1.023 (95% confidence intervals 1.021-1.033 and 1.017-1.029) per every decile increase in exposures to all seven components and per 1 μg/m 3 increase in the overall PM 2.5 , respectively. Ammonium contributed the most to RA onset in the seven components., Conclusion: Exposure to PM 2.5 components was modestly associated with RA risk. Public health efforts focusing on specific components (eg, ammonium) may be a more efficient way to reduce RA burden., (© 2024 The Author(s). Arthritis Care & Research published by Wiley Periodicals LLC on behalf of American College of Rheumatology.)

Abstract Studies have estimated the impact of the environment on malaria incidence although few have explored the differential impact due to malaria control interventions. Therefore, the objective of the study was to evaluate the effect of indoor residual spraying (IRS) on the relationship between malaria and environment (i.e. rainfall, temperatures, humidity, and vegetation) using data from a dynamic cohort of children from three sub-counties in Uganda. Environmental variables were extracted from remote sensing sources and averaged over different time periods. General linear mixed models were constructed for each sub-counties based on a log-binomial distribution. The influence of IRS was analysed by comparing marginal effects of environment in models adjusted and unadjusted for IRS. Great regional variability in the shape (linear and non-linear), direction, and magnitude of environmental associations with malaria risk were observed between sub-counties. IRS was significantly associated with malaria risk reduction (risk ratios vary from RR = 0.03, CI 95% [0.03–0.08] to RR = 0.35, CI95% [0.28–0.42]). Model adjustment for this intervention changed the magnitude and/or direction of environment-malaria associations, suggesting an interaction effect. This study evaluated the potential influence of IRS in the malaria-environment association and highlighted the necessity to control for interventions when they are performed to properly estimate the environmental influence on malaria. Local models are more informative to guide intervention program compared to national models.

Pleural effusion is the most common manifestation of pleural disease, and chest ultrasound is crucial for diagnostic workup and post-treatment monitoring. Ultrasound helps distinguish the various types of pleural effusion and enables the detection of typical manifestations of empyema, which presents as a complicated, septated effusion. This may benefit from drainage and the use of intrapleural enzyme therapy or may require more invasive approaches, such as medical or surgical thoracoscopy. The mechanism of action of intrapleural enzymatic therapy (IPET) is the activation of plasminogen to plasmin, which breaks down fibrin clots that form septa or the loculation of effusions and promotes their removal. In addition, IPET has anti-inflammatory properties and can modulate the immune response in the pleural space, resulting in reduced pleural inflammation and improved fluid reabsorption. In this article, we briefly review the literature on the efficacy of IPET and describe a case series in which most practical applications of IPET are demonstrated, i.e., as a curative treatment but also as an alternative, propaedeutic, or subsequent treatment to surgery. [ABSTRACT FROM AUTHOR]

ABSTRACT The L‐enantiomer of β‐aminoisobutyric acid (BAIBA) is secreted by contracted muscle in mice, and exercise increases serum levels in humans. In mice, L‐BAIBA reduces bone loss with unloading, but whether it can have a positive effect with loading is unknown. Since synergism can be more easily observed with sub‐optimal amounts of factors/stimulation, we sought to determine whether L‐BAIBA could potentiate the effects of sub‐optimal loading to enhance bone formation. L‐BAIBA was provided in drinking water to C57Bl/6 male mice subjected to either 7 N or 8.25 N of sub‐optimal unilateral tibial loading for 2 weeks. The combination of 8.25 N and L‐BAIBA significantly increased the periosteal mineral apposition rate and bone formation rate compared to loading alone or BAIBA alone. Though L‐BAIBA alone had no effect on bone formation, grip strength was increased, suggesting a positive effect on muscle function. Gene expression analysis of the osteocyte‐enriched bone showed that the combination of L‐BAIBA and 8.25 N induced the expression of loading‐responsive genes such as Wnt1, Wnt10b, and the TGFb and BMP signaling pathways. One dramatic change was the downregulation of histone genes in response to sub‐optimal loading and/or L‐BAIBA. To determine early gene expression, the osteocyte fraction was harvested within 24 hours of loading. A dramatic effect was observed with L‐BAIBA and 8.25 N loading as genes were enriched for pathways regulating the extracellular matrix (Chad, Acan, Col9a2), ion channel activity (Scn4b, Scn7a, Cacna1i), and lipid metabolism (Plin1, Plin4, Cidec). Few changes in gene expression were observed with sub‐optimal loading or L‐BAIBA alone after 24 hours. These results suggest that these signaling pathways are responsible for the synergistic effects between L‐BAIBA and sub‐optimal loading. Showing that a small muscle factor can enhance the effects of sub‐optimal loading of bone may be of relevance for individuals unable to benefit from optimal exercise. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Background: The health effects of traffic-related air pollution (TRAP) continue to be of important public health interest across the globe. Following its 2010 review, the Health Effects Institute appointed a new expert Panel to systematically evaluate the epidemiological evidence regarding the associations between long-term exposure to TRAP and selected health outcomes. This paper describes the main findings of the systematic review on non-accidental mortality. Methods: The Panel used a systematic approach to conduct the review. An extensive search was conducted of literature published between 1980 and 2019. A new exposure framework was developed to determine whether a study was sufficiently specific to TRAP, which included studies beyond the near-roadway environment. We performed random-effects meta-analysis when at least three estimates were available of an association between a specific exposure and outcome. We evaluated confidence in the evidence using a modified Office of Health Assessment and Translation (OHAT) approach, supplemented with a broader narrative synthesis. Results: Thirty-six cohort studies were included. Virtually all studies adjusted for a large number of individual and area-level covariates—including smoking, body mass index, and individual and area-level socioeconomic status—and were judged at a low or moderate risk for bias. Most studies were conducted in North America and Europe, and a few were based in Asia and Australia. The meta-analytic summary estimates for nitrogen dioxide, elemental carbon and fine particulate matter—pollutants with more than 10 studies—were 1.04 (95% CI 1.01, 1.06), 1.02 (1.00, 1.04) and 1.03 (1.01, 1.05) per 10, 1 and 5 µg/m3, respectively. Effect estimates are interpreted as the relative risk of mortality when the exposure differs with the selected increment. The confidence in the evidence for these pollutants was judged as high, because of upgrades for monotonic exposure–response and consistency across populations. The consistent findings across geographical regions, exposure assessment methods and confounder adjustment resulted in a high confidence rating using a narrative approach as well. Conclusions: The overall confidence in the evidence for a positive association between long-term exposure to TRAP and non-accidental mortality was high.

Objectives: We report results of a systematic review on the health effects of long-term traffic-related air pollution (TRAP) and diabetes in the adult population.Methods: An expert Panel appointed by the Health Effects Institute conducted this systematic review. We searched the PubMed and LUDOK databases for epidemiological studies from 1980 to July 2019. TRAP was defined based on a comprehensive protocol. Random-effects meta-analyses were performed. Confidence assessments were based on a modified Office for Health Assessment and Translation (OHAT) approach, complemented with a broader narrative synthesis. We extended our interpretation to include evidence published up to May 2022.Results: We considered 21 studies on diabetes. All meta-analytic estimates indicated higher diabetes risks with higher exposure. Exposure to NO2 was associated with higher diabetes prevalence (RR 1.09; 95% CI: 1.02; 1.17 per 10 μg/m3), but less pronounced for diabetes incidence (RR 1.04; 95% CI: 0.96; 1.13 per 10 μg/m3). The overall confidence in the evidence was rated moderate, strengthened by the addition of 5 recently published studies.Conclusion: There was moderate evidence for an association of long-term TRAP exposure with diabetes.

Background: Past investigations of air pollution and systemic autoimmune rheumatic diseases (SARDs) typically focused on individual (not mixed) and overall environmental emissions. We assessed mixtures of industrial emissions of fine particulate matter (PM2.5), nitrogen dioxide (NO2), and sulfur dioxide (SO2) and SARDs onset in Ontario, Canada. Methods: We assembled an open cohort of over 12 million adults (without SARD diagnoses at cohort entry) based on provincial health data for 2007–2020 and followed them until SARD onset, death, emigration, or end of study (December 2020). SARDs were identified using physician billing and hospitalization diagnostic codes for systemic lupus, scleroderma, myositis, undifferentiated connective tissue disease, and Sjogren’s. Rheumatoid arthritis and vasculitis were not included. Average PM2.5, NO2, and SO2 industrial emissions from 2002 to one year before SARDs onset or end of study were assigned using residential postal codes. A quantile g-computation model for time to SARD onset was developed for the industrial emission mixture, adjusting for sex, age, income, rurality index, chronic obstructive pulmonary disease (as a proxy for smoking), background (environmental overall) PM2.5, and calendar year. We conducted stratified analyses across age, sex, and rurality. Results: We identified 43,931 new SARD diagnoses across 143,799,564 person-years. The adjusted hazard ratio for SARD onset for an increase in all emissions by one decile was 1.018 (95% confidence interval 1.013–1.022). Similar positive associations between SARDs and the mixed emissions were observed in most stratified analyses. Industrial PM2.5 contributed most to SARD risk. Conclusions: Industrial air pollution emissions were associated with SARDs risk.

Over the last 20 years, scientific literature and interest on chest/lung ultrasound (LUS) have exponentially increased. Interpreting mixed-anatomical and artifactual-pictures determined the need of a proposal of a new nomenclature of artifacts and signs to simplify learning, spread, and implementation of this technique. The aim of this review is to collect and analyze different signs and artifacts reported in the history of chest ultrasound regarding normal lung, pleural pathologies, and lung consolidations. By reviewing the possible physical and anatomical interpretation of these artifacts and signs reported in the literature, this work aims to present the AdET (Accademia di Ecografia Toracica) proposal of nomenclature and to bring order between published studies., (© 2024 American Institute of Ultrasound in Medicine.)

Abstract Objectives To estimate associations between fine particulate matter (PM2.5) and ozone and the onset of systemic autoimmune rheumatic diseases (SARDs). Methods An open cohort of over 6 million adults was constructed from provincial physician billing and hospitalization records between 2000 and 2013. We defined incident SARD cases (SLE, Sjogren’s syndrome, scleroderma, polymyositis, dermatomyositis, polyarteritis nodosa and related conditions, polymyalgia rheumatic, other necrotizing vasculopathies, and undifferentiated connective tissue disease) based on at least two relevant billing diagnostic codes (within 2 years, with at least 1 billing from a rheumatologist), or at least one relevant hospitalization diagnostic code. Estimated PM2.5 and ozone concentrations (derived from remote sensing and/or chemical transport models) were assigned to subjects based on residential postal codes, updated throughout follow-up. Cox proportional hazards models with annual exposure levels were used to calculate hazard ratios (HRs) for SARDs incidence, adjusting for sex, age, urban-versus-rural residence, and socioeconomic status. Results The adjusted HR for SARDS related to one interquartile range increase in PM2.5 (3.97 µg/m3) was 1.12 (95% confidence interval 1.08–1.15), but there was no clear association with ozone. Indirectly controlling for smoking did not alter the findings. Conclusions We found associations between SARDs incidence and PM2.5, but no relationships with ozone. Additional studies are needed to better understand interplays between the many constituents of air pollution and rheumatic diseases.

Background: Noise has been related to several cardiovascular diseases (CVDs) such as coronary heart disease and to their risk factors such as hypertension, but associations with stroke remain under-researched, even if CVD likely share similar pathophysiologic mechanisms. Aim: The objective of the study was to examine the association between long-term residential exposure to total environmental noise and stroke incidence in Montreal, Canada. Materials and Methods: We created an open cohort of adults aged ≥45years, free of stroke before entering the cohort for the years 2000 to 2014 with health administrative data. Residential total environmental noise levels were estimated with land use regression (LUR) models. Incident stroke was based on hospital admissions. Cox hazard models with age as the time axis and time-varying exposures were used to estimate associations, which were adjusted for material deprivation, year, nitrogen dioxide, stratified for sex, and indirectly adjusted for smoking. Results: There were 9,072,492 person-years of follow-up with 47% men; 26,741 developed stroke (21,402 ischemic; 4947 hemorrhagic; 392 had both). LUR total noise level acoustic equivalent for 24 hours (LAeq24h) ranged 44 to 79 dBA. The adjusted hazard ratio (HR) for stroke (all types), for a 10-dBA increase in LAeq24h, was 1.06 [95% confidence interval (CI): 1.03–1.09]. The LAeq24h was associated with ischemic (HR per 10 dBA: 1.08; 95% CI: 1.04–1.12) but not hemorrhagic stroke (HR per 10 dBA: 0.97; 95% CI: 0.90–1.04). Conclusion: The results suggest that total environmental noise is associated with incident stroke, which is consistent with studies on transportation noise and other CVD.

Large-scale analysis of the fossil record requires aggregation of palaeontological data from individual fossil localities. Prior to computers, these synoptic datasets were compiled by hand, a laborious undertaking that took years of effort and forced palaeontologists to make difficult choices about what types of data to tabulate. The advent of desktop computers ushered in palaeontology's first digital revolution-online literature-based databases, such as the Paleobiology Database (PBDB). However, the published literature represents only a small proportion of the palaeontological data housed in museum collections. Although this issue has long been appreciated, the magnitude, and thus potential significance, of these so-called 'dark data' has been difficult to determine. Here, in the early phases of a second digital revolution in palaeontology--the digitization of museum collections-we provide an estimate of the magnitude of palaeontology's dark data. Digitization of our nine institutions' holdings of Cenozoic marine invertebrate collections from California, Oregon and Washington in the USA reveals that they represent 23 times the number of unique localities than are currently available in the PBDB. These data, and the vast quantity of similarly untapped dark data in other museum collections, will, when digitally mobilized, enhance palaeontologists' ability to make inferences about the patterns and processes of past evolutionary and ecological changes.

ObjectivesSince 2004, the Montreal heat response plan (MHRP) has been developed and implemented on the Island of Montreal to reduce heat-related health effects in the general population. In this paper, we aimed to assess the barriers and facilitators to implementation of the MHRP and evaluate the awareness of key elements of the plan by healthcare professionals and individuals from vulnerable populations.MethodsData were gathered from monitoring reports and a questionnaire administered to managers of healthcare institutions and healthcare workers in Montreal-area health and social services institutions. Individual interviews and focus groups with healthcare workers and with individuals with schizophrenia or suffering from drug or alcohol dependencies were performed. Data were categorized according to predefined subthemes. Coding matrices were then used to determine the most frequently occurring elements in the subthemes.ResultsOur results indicate that actions are progressively implemented each year in the healthcare network. Intensification of surveillance for signs of heat-related illness is the most frequently reported measure. Identification and prioritization of clientele and homecare patients are identified as a challenge, as is ensuring the availability of sufficient personnel during a heat wave. Analysis of practice and awareness in healthcare professionals reveals that preventive measures are known and applied by the personnel. Individuals from vulnerable population groups were not uniformly aware of preventive measures, and consequently, variability was observed in their application.ConclusionThe framework proposed in this study revealed valuable information that can be useful to improve plans aimed at reducing heat-related health effects in the population.