Assessment of the Possible Association of Air Pollutants PM10, O3, NO2 With an Increase in Cardiovascular, Respiratory, and Diabetes Mortality in Panama City: A 2003 to 2013 Data Analysis

Monitoring and assessment of CO2 and NO2 in schools within the Sentinel Schools Network of Catalonia during the COVID-19 era

In response to the global impact of the COVID-19 pandemic, international and national authorities, including those in Catalonia (Spain), recognized the crucial need to ensure proper ventilation in classrooms, emphasizing the importance of safe and healthy indoor environments for face-to-face learning. The present work, conducted within the COVID-19 Sentinel Schools Network of Catalonia (CSSNC) framework, aimed to monitor carbon dioxide (CO2) and nitrogen dioxide (NO2) concentrations in 23 schools, ensuring a comprehensive sample regarding educational levels, daily scholar schedules, and classroom typologies distributed across the four provinces of Catalonia. The research spanned three study periods: March and April 2021, October 2021 to January 2022, and March to June 2022. Briefly, 28%, 25%, and 37% of classrooms surpassed the 700 parts per million (ppm) CO2 limit in each study period, respectively. Generally, CO2 averages were lower in preschool classrooms (mean ± SD = 486 ± 106 ppm), while high school classrooms displayed the highest CO2 concentrations (mean ± SD = 710 ± 253 ppm). Moreover, classrooms in towns (<30000 inhabitants) exhibited higher CO2 levels as compared to classrooms from schools located in cities. As for NO2, the highest averages were obtained in urban areas, particularly in the Barcelona metropolitan area (e.g. mean indoor levels of 24.56 μg m-3 as compared to 11.05 μg m-3 in towns). In addition, the Indoor/Outdoor ratio (I/O ratio) in towns was the lowest (0.60). These results, together with the higher concentration of CO2 indoors, could indicate poorer ventilation in town schools. The results of this study are anticipated to contribute to implementing evidence-based measures to improve indoor air quality (IAQ) in educational settings.

Pollutant-meteorological factors and cardio-respiratory mortality in Portugal: Seasonal variability and associations

Seasonal variations in cardiorespiratory diseases may be influenced by air pollution and meteorological factors. This work aims to highlight the relevance of a complete seasonal characterization of the pollutant-meteorological factors and cardio-respiratory mortality in Portugal and the relationships between health outcomes and environmental risk factors. To this end, air pollution and meteorological variables along with health outcomes were analyzed at national level and on a monthly basis for the period of 2011-2020. It was found that cardiorespiratory mortality rates during winter were 44% higher than during the summer. Furthermore, particulate matter with aerodynamic diameters of 10 and 2.5 μm (μm) or smaller (PM10 and PM2.5), carbon monoxide (CO) and nitrogen dioxide (NO2) showed a seasonal variability with the highest concentrations during winter while ozone (O3) presented higher concentrations during spring and summer. PM10, PM2.5 and NO2, showed a positive correlation between seasons, indicating similar patterns of behavior. Canonical correlation analysis (CCA) applied to pollutant-meteorological and cardiorespiratory mortality data indicates a strong linear correlation between pollutant-meteorological factors and health outcomes. The first canonical correlation was 0.889, and the second was 0.545, both statistically significant (p-value < 0.001). The CCA results suggest that there is a strong association between near-surface temperature, relative humidity, PM10, PM2.5, CO and NO2 and health outcomes. The results of this study provide important information of the seasonal variability of air pollutants and meteorological factors in Portugal and their associations with cardiorespiratory mortality.

Impact of NO2 emissions from household heating systems with wall-mounted gas stoves on indoor and ambient air quality in Chinese urban areas

Nitrogen dioxide (NO2) has been discussed as a typical indoor pollutant for decades. As an increasingly popular heating method, household heating system (HHS) with wall-mounted natural gas stoves has led to a continuous increase in the emission of NO2. The absence of legal regulations and strict limits for NO2 emissions from wall-mounted gas stoves has led to a significant exceedance of indoor NO2 concentrations beyond the permissible value. However, this issue is rarely taken into consideration. In this study, we present the first report on NO2 emissions from wall-mounted gas stoves for household heating and their impact on indoor and ambient air quality in Chinese urban areas based on in-situ measurements and numerical simulations. On heating days, the observed indoor NO2 concentration is within 80-200 μg/m3, much higher than the outdoor atmospheric concentration. With a low emission grade of the wall-mounted gas stoves, it is estimated that >10 % of residents in a typical residential building area are exposed to a high NO2 concentration of >200 μg/m3, and >50 % of residents are exposed to a concentration of >80 μg/m3. In addition, the indoor NO2 concentration shows an obvious non-uniform distribution with the floor in residential buildings. The NO2 emission from residential natural gas heating also shows an obvious impact on the microenvironment around buildings, which is primarily determined by the emission grade of the stoves. The findings highlight that HHS has become a non-negligible source of indoor NO2 pollution in China. It is urgently necessary to formulate NO2 emission limit standards for wall-mounted gas stoves in Chinese urban areas and upgrade traditional natural gas heaters with efficient emission reduction technologies.

Description of the National Mortality Register of Panama

Introduction

The National Mortality Register (NMR) of Panama is a key element in demographic analysis and in acquiring an updated picture of population health in Panama. The main objectives of this study are to characterize the NMR and to enumerate its strengths and weaknesses.

Methods

We describe the history, processes, and structure of the Vital Statistics Section of the National Institute of Statistics and Census (the curator of the NMR database). In addition, we discuss publication punctuality, underregistration of the data, the proportion of registered deaths certified by medical doctors, and the top 5 causes of death according to the 80 groups of the International Classification of Diseases, Tenth Revision. We also examine works derived from the register's data, from the first publication on its website (2002) until 2019.

Results

The NMR procedures were described. The web reports of the NMR were performed with a delay of between 1 to 2 years. The underregistration of deaths in 2002-2019 was 14.7%, and the national yearly proportion of deaths certified by medical doctors was always above 90%. Hard-to-reach areas had higher underregistration proportions and fewer deaths certified by medical doctors. Information extracted from the NMR supports several national and international reports, geographic information systems, and studies. The most common causes of death between 2002 and 2019 were noncommunicable diseases.

Conclusions

The NMR is a robust official information system. However, hard-to-reach areas require improvement in terms of the NMR. The NMR is used for publishing official reports, writing studies, and updating reports on the current health status of Panama in a timely fashion following international guidelines.

Quantification and the sources identification of total and insoluble hexavalent chromium in ambient PM: A case study of Aktobe, Kazakhstan

Hexavalent chromium (Cr(VI)), a known carcinogen, emanates from both anthropogenic and natural sources. A pilot study of the ambient Cr(VI) concentrations was conducted at the center of Aktobe which is a few kilometers away from major industrial chromium plants. Total Cr(VI) concentrations were measured in the fall and winter seasons with mean values (S.D) of 5.30 (2.16) ng/m³ and 2.26 (1.80) ng/m³, respectively. Insoluble Cr(VI) levels were 4.80 (1.96) and 2.19 (1.75) ng/m³ for the fall and winter, respectively. The total and insoluble Cr(VI) concentrations in the fall season were significantly higher than in winter, likely due to the higher rate of Cr(III) oxidation in the presence of ozone and ROS in fall compared to the rate of Cr(VI) reduction in the presence of VOCs at higher temperatures. On average, total Cr(VI) constituted 34.49% of the total Cr concentrations suggesting that the dominant valence state of Cr in the atmosphere is Cr(III). The previous reference values of exposure to Cr(VI) must be revisited by taking into account the insoluble Cr(VI) concentration since it is more prevalent in the atmosphere compared to soluble Cr(VI). The influence of the chromium plants as potential sources was not obvious in this study.

A long short-term memory-fully connected (LSTM-FC) neural network for predicting the incidence of bronchopneumonia in children

Bronchopneumonia is the most common infectious disease in children, and it seriously endangers children's health. In this paper, a deep neural network combining long short-term memory (LSTM) layers and fully connected layers was proposed to predict the prevalence of bronchopneumonia in children in Chengdu based on environmental factors and previous prevalence rates. The mean square error (MSE), mean absolute error (MAE), and Pearson correlation coefficient (R) were used to detect the performance of the deep learning model. The values of MSE, MAE, and R in the test dataset are 0.0051, 0.053, and 0.846, respectively. The results show that the proposed model can accurately predict the prevalence of bronchopneumonia in children. We also compared the proposed model with three other models, namely, a fully connected (FC) layer neural network, a random forest model, and a support vector machine. The results show that the proposed model achieves better performance than the three other models by capturing time series and mitigating the lag effect.

Ozone Exposure, Outdoor Physical Activity, and Incident Type 2 Diabetes in the SALSA Cohort of Older Mexican Americans

BACKGROUND

Type 2 diabetes is a leading contributor to the global burden of morbidity and mortality. Ozone (O3) exposure has previously been linked to diabetes.

OBJECTIVE

We studied the impact of O3 exposure on incident diabetes risk in elderly Mexican Americans and investigated whether outdoor physical activity modifies the association.

METHODS

We selected 1,090 Mexican American participants from the Sacramento Area Latino Study on Aging conducted from 1998 to 2007. Ambient O3 exposure levels were modeled with a land-use regression built with saturation monitoring data collected at 49 sites across the Sacramento metropolitan area. Using Cox proportional hazard models, we estimated the risk of developing incident diabetes based on average O3 exposure modeled for 5-y prior to incident diabetes diagnosis or last follow-up. Further, we estimated outdoor leisure-time physical activity at baseline and investigated whether higher vs. lower levels modified the association between O3 exposure and diabetes.

RESULTS

In total, 186 incident diabetes cases were identified during 10-y follow-up. Higher levels of physical activity were negatively associated with incident diabetes [hazard ratio (HR)=0.64 (95% CI: 0.43, 0.95)]. The estimated HRs for incident diabetes was 1.13 (95% CI: 1.00, 1.28) per 10-ppb increment of 5-y average O3 exposure; also, this association was stronger among those physically active outdoors [HR=1.52 (95% CI: 1.21, 1.90)], and close to null for those reporting lower levels of outdoor activity [HR=1.04 (95% CI: 0.90, 1.20), pinteraction=0.01].

CONCLUSIONS

Our findings suggest that ambient O3 exposure contributes to the development of type 2 diabetes, particularly among those with higher levels of leisure-time outdoor physical activity. Policies and strategies are needed to reduce O3 exposure to guarantee that the health benefits of physical activity are not diminished by higher levels of O3 pollution in susceptible populations such as older Hispanics. https://doi.org/10.1289/EHP8620.

Ambient exposure of O3 and NO2 and associated health risk in Kuwait

Ozone (O₃) and nitrogen dioxide (NO₂), indissoluble air pollutants in the atmosphere, have been confirmed in various parts of the world to have detrimental health effects on humans. Currently, such information is lacking in Kuwait. The objectives of this study are to investigate the spatial and temporal variations of O₃ and NO₂ concentrations in Kuwait during a 4-year period (2014-2017) and to quantify the associated short- and long-term health effects, including all-cause, respiratory, and cardiovascular mortalities and morbidities during the same study period. Exposure assessment showed that the annual levels (22.5-26.4 ppb), SOMO35, and the 8-hour 4-year mean (38 ppb) of O₃ were very low and below the World Health Organization (WHO) (50 ppb) and Kuwaiti (70 ppb) regulatory limits. The annual mean levels of NO₂ ranged from 30.3 to 43.8 ppb and were significantly higher than both WHO and Kuwait limits (21 ppb). As expected, O₃ and NO₂ levels showed opposing trends, with higher concentrations of NO₂ recorded in early morning and mid-evening, during autumn and winter, and during Saturdays (the so-called weekend effect). Health effects indicated high respiratory diseases due to short-term exposure to NO₂. Contrary to the western countries' pollution levels, Kuwait showed lower O₃ and higher NO₂ levels. There is potential for substantial health improvements in Kuwait by reducing NO₂ pollution through stringent control measures of stationary and mobile sources.

Short-Term Effects of Atmospheric Pollution on Daily Mortality and Their Modification by Increased Temperatures Associated with a Climatic Change Scenario in Northern Mexico

Short-term effects of air pollution on the health of residents in the Metropolitan Area of Monterrey, Mexico were assessed from 2012–2015 using a time-series approach. Guadalupe had the highest mean concentrations for SO₂, CO and O₃; whereas Santa Catarina showed the highest NO₂ concentrations. Escobedo and Garcia registered the highest levels for PM₁₀. Only PM₁₀ and O₃ exceeded the maximum permissible values established in the Mexican official standards. Most of pollutants and municipalities showed a great number of associations between an increase of 10% in their current concentrations and mortality, especially for people >60 years. Different scenarios resulting from climatic change were built (increases of 5–25% in daily mean temperature), but only the increase of 25% (5 °C) showed a significant association with air pollutant concentrations and mortality. All pollutants and municipalities showed significant increases in relative risk indexes (RRI) resulting from an increase of 5 °C when people >60 years was considered. Results were comparable to those reported by other authors around the world. The RRI were low but significant, and thus are of public concern. This study demonstrated that the elderly is strongly threatened not only by atmospheric pollution but also by climatic change scenarios in warm and semiarid places.

PM2.5 Prediction Model Based on Combinational Hammerstein Recurrent Neural Networks

Airborne particulate matter 2.5 (PM2.5) can have a profound effect on the health of the population. Many researchers have been reporting highly accurate numerical predictions based on raw PM2.5 data imported directly into deep learning models; however, there is still considerable room for improvement in terms of implementation costs due to heavy computational overhead. From the perspective of environmental science, PM2.5 values in a given location can be attributed to local sources as well as external sources. Local sources tend to have a dramatic short-term impact on PM2.5 values, whereas external sources tend to have more subtle but longer-lasting effects. In the presence of PM2.5 from both sources at the same time, this combination of effects can undermine the predictive accuracy of the model. This paper presents a novel combinational Hammerstein recurrent neural network (CHRNN) to enhance predictive accuracy and overcome the heavy computational and monetary burden imposed by deep learning models. The CHRNN comprises a based-neural network tasked with learning gradual (long-term) fluctuations in conjunction with add-on neural networks to deal with dramatic (short-term) fluctuations. The CHRNN can be coupled with a random forest model to determine the degree to which short-term effects influence long-term outcomes. We also developed novel feature selection and normalization methods to enhance prediction accuracy. Using real-world measurement data of air quality and PM2.5 datasets from Taiwan, the precision of the proposed system in the numerical prediction of PM2.5 levels was comparable to that of state-of-the-art deep learning models, such as deep recurrent neural networks and long short-term memory, despite far lower implementation costs and computational overhead.

Assessment of personal exposure to particulate air pollution in different microenvironments and traveling by several modes of transportation in Bogotá, Colombia: protocol for a mixed-methods study. (Preprint)

Background

Air pollution in most countries exceeds the levels recommended by the World Health Organization, causing up to one-third of deaths due to noncommunicable diseases. Fine particulate matter (PM_2.5) and black carbon (BC) from mobile sources are the main contaminants.

Objective

The aim of this study is to assess the relationship of exposure to air pollutants (PM_2.5 and BC) in microenvironments according to respiratory health and physical activity in users traveling by different types of transportation in Bogotá, Colombia.

Methods

A mixed methods study based on a convergent parallel design will be performed with workers and students. The sample will include 350 healthy transport users traveling by different urban transportation modes in three main routes in Bogotá. The study is broken down into two components: (1) a descriptive qualitative component focused on assessing the individual perception of air pollution using semistructured interviews; and (2) a cross-sectional study measuring the individual exposure to PM_2.5 and BC using portable instruments (DustTrak and microAeth, respectively), pulmonary function by spirometry, and physical activity with accelerometry. The analysis will include concurrent triangulation and logistic regression.

Results

The findings will be useful for the conception, design, and decision-making process in the sectors of health and mobility from public, academy, and private perspectives. This study includes personal measurements of PM_2.5 and BC during typical trips in the city to assess the exposure to these contaminants in the major roadways in real time. The study further compares the performance of two different lung tests to identify possible short-term respiratory effects. As a limitation, the protocol will include participants from different institutions in the city, which are not necessarily representative of all healthy populations in Bogotá. In this sense, it is not possible to draw causation conclusions. Moreover, a convergent parallel design could be especially problematic concerning integration because such a design often lacks a clear plan for making a connection between the two sets of results, which may not be well connected. Nevertheless, this study adopts a procedure for how to integrate qualitative and quantitative data in the interpretation of the results and a multilevel regression. The time that participants must live in the city will be considered; this will be controlled in the stratified analysis. Another limitation is the wide age range and working status of the participants. Regional pollution levels and episodes (PM_2.5) will be handled as confounding variables. The study is currently in the enrollment phase of the participants. Measurements have been made on 300 participants. Pandemic conditions affected the study schedule; however, the results are likely to be obtained by late 2022.

Conclusions

This study investigates the exposure to air pollutants in microenvironments in Bogotá, Colombia. To our knowledge, this is the first mixed methods study focusing on PM_2.5, BC, and respiratory health effects in a city over 2 meters above sea level. This study will provide an integration of air pollution exposure variables and respiratory health effects in different microenvironments.

International Registered Report Identifier (IRRID)

PRR1-10.2196/25690

Increased Risk of Sensorineural Hearing Loss as a Result of Exposure to Air Pollution

Whether exposure to air pollution is associated with developing sensorineural hearing loss (SHL) remains controversial. Using data from the National Health Insurance Research Database, we recruited a total of 75,767 subjects aged older than 20 years with no history of SHL from 1998 to 2010, and they were followed up until SHL was observed, they withdrew from the National Health Insurance program, or the study ended. The subjects were evenly exposed to low-level, mid-level, and high-level carbon monoxide (CO) and nitrogen dioxide (NO₂). The incidence rate ratio of SHL for patients exposed to high-level CO was 1.24 (95% confidence interval (CI) = 1.14–1.36). The NO₂ pollutants increased the incidence rate ratios of SHL in mid-level NO₂ and high-level NO₂ exposures by 1.10 (95% CI = 1.10–1.32) and 1.36 (95% CI = 1.24–1.49) times, respectively. The adjusted hazard ratio (adj. HR) of SHL in patients exposed to high-level CO was 1.45 (95% CI = 1.31–1.59), relative to that of patients exposed to low-level CO. Compared to patients exposed to low-level NO₂, patients exposed to mid-level NO₂ (adj. HR = 1.40, 95% CI = 1.27–1.54) and high-level NO₂ (adj. HR = 1.63, 95% CI = 1.48–1.81) had a higher risk of developing SHL. The increased risk of SHL following the increased concentrations of air pollutants (CO and NO₂) was statistically significant in this study. In conclusion, the subjects’ exposure to air pollution exhibited a significantly higher risk of developing SHL in Taiwan.

Ambient air pollution and diabetes: A systematic review and meta-analysis

BACKGROUND

Air pollutants are suggested to be related to type 2 diabetes (T2D). Since several high quality papers on air pollutants and T2D have been published beyond the last reviews, an extended systematic review is highly warranted. We review epidemiological studies to quantify the association between air pollutants and T2D, and to answer if diabetes patients are more vulnerable to air pollutants.

METHODS

We systematically reviewed the databases of PubMed and Web of Science based on the guidelines of the Preferred Reporting Items for Systematic review and Meta-analysis (PRISMA). We calculated odds ratios (OR) or hazard ratios (HR) and their 95% confidence intervals (CI) to assess the strength of the associations between air pollutants [e.g., particulate matter with diameter ≤ 2.5 μm (PM_2.5), particulate matter with diameter ≤ 10 μm (PM₁₀), and nitrogen dioxide (NO₂)] and T2D. We evaluated the quality and risk of bias of the included studies and graded the credibility of the pooled evidence using several recommended tools. We also performed sensitivity analysis, meta-regression analysis, and publication bias test.

RESULTS

Out of 716 articles identified, 86 were used for this review and meta-analysis. Meta-analyses showed significant associations of PM_2.5 with T2D incidence (11 studies; HR = 1.10, 95% CI = 1.04-1.17 per 10 μg/m³ increment; I² = 74.4%) and prevalence (11 studies; OR = 1.08; 95% CI = 1.04-1.12 per 10 μg/m³ increment; I² = 84.3%), of PM₁₀ with T2D prevalence (6 studies; OR = 1.10; 95% CI = 1.03-1.17 per 10 μg/m³ increment; I² = 89.5%) and incidence (6 studies; HR = 1.11; 95% CI = 1.00-1.22 per μg/m³ increment; I² = 70.6%), and of NO₂ with T2D prevalence (11 studies; OR = 1.07; 95% CI = 1.04-1.11 per 10 μg/m³ increment; I² = 91.1%). The majority of studies on glucose-homoeostasis markers also showed increased risks with higher air pollutants levels, but the studies were too heterogeneous for meta-analysis. Overall, patients with diabetes might be more vulnerable to PM.

CONCLUSIONS

Recent publications strengthened the evidence for adverse effects of ambient air pollutants exposure (especially for PM) on T2D and that diabetic patients might be more vulnerable to air pollutants exposure.

A kriging-calibrated machine learning method for estimating daily ground-level NO2 in mainland China

It is unclear how to develop a model based on the combined satellite data and ground monitoring data to accurately estimate daily NO₂ levels. Furthermore, the conventional cross-validation (CV) results represent average levels but the model performance may vary greatly from grid to grid. It is an essential issue to evaluate model's prediction ability in different grids and determine the factors affecting model extrapolating ability, which have never been well examined to date. The aim of this study was to compare the ability of three different methods to estimate the daily NO₂ across mainland China during 2014-2016; and to develop a novel two-stage meta-analysis method for exploring the influence of the number and the distribution of nearby sites on grid-level prediction accuracy. For better estimating the daily NO₂ level, we developed and compared three methods, including universal kriging model, satellite-based method (Non-linear exposure-lag-response model & Extreme gradient boosting combined technique) and the kriging-calibrated satellite method. For exploring influencing factors, the two-stage meta-analysis method was purposed. The kriging-calibrated satellite method had an overall CV R-square and root mean square error (RMSE) of 0.85 and 7.87μg/m³, better than the Universal Kriging model and the satellite-based method (CV R² = 0.57 and 0.81). The two-stage meta-analysis method revealed that the model performance did decrease with the sparser distribution of nearby sites. And adding 5 sites within 50 km in the random mode can bring 17.51% improvement in model extrapolating ability. The kriging-calibration can help satellite-based machine learning to provide more accurate NO₂ prediction. Our novel evaluation method can provide the suggestion of adding new sites effectively within a limit budget.

Estimation of health benefits from air quality improvement using the MODIS AOD dataset in Seoul, Korea

BACKGROUND

Exposure to fine particles in the atmosphere can adversely affect health and even lead to premature death. Recently, South Korea has attracted attention because of its rapid increase in the concentration of Particulate Matter (PM).

OBJECTIVES

We estimated the economic benefits of reducing PM₁₀ in Seoul, South Korea, based on MODerate-resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD). Based on the retrieved PM₁₀ data, we estimated its effects on overall health in each district of Seoul, Korea between 2014 and 2015.

METHODS

The relationships between MODIS AOD and ground-based PM₁₀ data were identified in different seasons in South Korea between 2012 and 2013 using the linear regression model. The health benefits were estimated by the Benefits Mapping and Analysis Program (Benmap) using the scenarios from the World Health Organization (WHO).

RESULTS

The correlation between MODIS AOD and PM₁₀ concentration differed with the season. There was a higher correlation between MODIS AOD and PM₁₀ concentration in winter (R = 0.57) than there was in other seasons. Based on the MODIS AOD, the average annual PM₁₀ concentration in Seoul was higher in 2014 than it was in 2015, at values of 45.7 μg/m³, and 41.6 μg/m³, respectively. The greatest economic benefit of reducing PM₁₀ concentration (WHO annual standard of 20 μg/m³) was in 2014. This benefit was estimated to be 7022 (95% CI: 599, 20496), 2617 (95% CI: 216, 7750), and 1328 (95% CI: -159, 4679) billion KRW for all-cause, cardiovascular, and respiratory mortalities in 2014 and 2015, respectively.

CONCLUSIONS

These results demonstrate that, despite considerable improvements in air quality in recent decades, there is still a need for countermeasures to prevent economic loss due to air pollution in Seoul.

Extreme levels of ambient air pollution adversely impact cardiac and central aortic hemodynamics: the AIRCMD-China study

Ambient air pollution is an independent risk factor for cardiovascular diseases. However, the underlying mechanisms have yet to be fully elucidated. We performed a panel study on 65 nonsmoking patients with metabolic syndrome, with four repeated clinical visits between 2012 and 2013 in Beijing, China. Cardiac and central aortic hemodynamic parameters were measured by pulse wave analyses as subendocardial viability ratio, ejection duration, and central aortic pressure. We also calculated rate-pressure product parameter and collected peripheral blood for analyses. High levels of ambient particulate matter with diameter ≤10 and 2.5 μm (PM₁₀ and PM_2.5), black carbon, sulfur dioxide, and nitrogen dioxide were 121.3, 99.5, 6.5, 24.5, and 59.2 μg/m³, respectively. Short- to medium-term exposures to high levels of ambient air pollution adversely impacted central hemodynamics-derived surrogates of myocardial perfusion and oxygen demand. Each 10 μg/m³ increase in PM_2.5 was associated with significant decreases of 0.67% (95% confidence interval: -2.84, -0.22) in subendocardial viability ratio at moving average 35 days (MA35) and an increase of 0.31 in rate-pressure product (95% confidence interval: 0.03, 0.59) at MA5. In conclusion, our results suggest that impaired myocardial perfusion and increased myocardial oxygen demand may play importantly mechanistic roles in air pollution-attributed cardiovascular diseases.

Association between environmental factors and hospitalisations for bronchiectasis in Badalona, Barcelona, Spain (2007-2015)

INTRODUCTION

The relationship between environmental factors and the exacerbation of respiratory diseases has been widely studied. However, there are no studies examining the relationship between these factors and bronchiectasis exacerbations. Our objective was to analyse the association between various environmental factors and hospitalisation for bronchiectasis.

MATERIAL AND METHODS

This was a retrospective observational study conducted at two hospitals in Badalona (Barcelona). The number of hospital admissions for exacerbation of bronchiectasis between 2007 and 2015 was obtained. Through multiple regression we analysed the relationship between the number of exacerbations and mean monthly values of temperature, SO₂, NO, NO₂, O₃ and CO.

RESULTS

Temperature, SO₂, NO, NO₂, O₃ and CO were significantly associated with an increase in admissions due to exacerbation of bronchiectasis. By controlling the effect of temperature on the pollution variables, only SO₂ maintained statistical significance (P=.008).

CONCLUSION

We have detected an increase in hospital admissions for exacerbation of bronchiectasis with increases in the atmospheric concentration of SO₂ and the decrease in temperature. Prospective studies with different geographical locations to confirm these results are needed.

Environmental Exposures and Cardiovascular Disease: A Challenge for Health and Development in Low- and Middle-Income Countries

Environmental exposures in low- and middle-income countries lie at the intersection of increased economic development and the rising public health burden of cardiovascular disease. Increasing evidence suggests an association of exposure to ambient air pollution, household air pollution from biomass fuel, lead, arsenic, and cadmium with multiple cardiovascular disease outcomes, including hypertension, coronary heart disease, stroke, and cardiovascular mortality. Although populations in low- and middle-income countries are disproportionately exposed to environmental pollution, evidence linking these exposures to cardiovascular disease is derived from populations in high-income countries. More research is needed to further characterize the extent of environmental exposures.

The Cold Dusty Harmattan: A Season of Anguish for Cardiologists and Patients

Human health and disease often demonstrate seasonal patterns. Knowledge of these aspects aids anticipation and planning. Numerous studies have shown that hypertension and cardiovascular diseases demonstrate a seasonal pattern. The Harmattan, the cold dusty season in Sub-Saharan Africa, is the season of greatest concern in this regard. In this commentary, the author draws on his and other researchers' studies to explain the grounds for onset and worsening of existing cardiovascular diseases. As implied in the title, it is a season that puts great strain on the cardiologist and the health system, as well as greater disease burden on the patient. This should be taken into consideration in planning and pooling of resources for effective patient management and mitigation of impact of disease.