Multifactorial airborne exposures and respiratory hospital admissions--the example of Santiago de Chile

Association of ambient carbon monoxide exposure with hospitalization risk for respiratory diseases: A time series study in Ganzhou, China

Background

Ambient carbon monoxide (CO) exposure is associated with increased mortality and hospitalization risk for total respiratory diseases. However, evidence on the risk of hospitalization for specific respiratory diseases from ambient CO exposure is limited.

Methods

Data on daily hospitalizations for respiratory diseases, air pollutants, and meteorological factors from January 2016 to December 2020 were collected in Ganzhou, China. A generalized additive model with the quasi-Poisson link and lag structures was used to estimate the associations between ambient CO concentration and hospitalizations of total respiratory diseases, asthma, chronic obstructive pulmonary disease (COPD), upper respiratory tract infection (URTI), lower respiratory tract infection (LRTI), and influenza-pneumonia. Possible confounding co-pollutants and effect modification by gender, age, and season were considered.

Results

A total of 72,430 hospitalized cases of respiratory diseases were recorded. Significant positive exposure-response relationships were observed between ambient CO exposure and hospitalization risk from respiratory diseases. For each 1 mg/m³ increase in CO concentration (lag0-2), hospitalizations for total respiratory diseases, asthma, COPD, LRTI, and influenza-pneumonia increased by 13.56 (95% CI: 6.76%, 20.79%), 17.74 (95% CI: 1.34%, 36.8%), 12.45 (95% CI: 2.91%, 22.87%), 41.25 (95% CI: 18.19%, 68.81%), and 13.5% (95% CI: 3.41%, 24.56%), respectively. In addition, the associations of ambient CO with hospitalizations for total respiratory diseases and influenza-pneumonia were stronger during the warm season, while women were more susceptible to ambient CO exposure-associated hospitalizations for asthma and LRTI (all P < 0.05).

Conclusion

In brief, significant positive exposure-response relationships were found between ambient CO exposure and hospitalization risk for total respiratory diseases, asthma, COPD, LRTI, and influenza-pneumonia. Effect modification by season and gender was found in ambient CO exposure-associated respiratory hospitalizations.

Horse Racing as a Model to Study the Relationship between Air Pollutants and Physical Performance

Simple Summary

Ambient air contains a mixture of pollutants, the effects of which on animal and human health have been widely described. In contrast, the effects on physical performance are poorly understood, largely due to the difficulty of implementing an experimental model to study this problem. Thoroughbred horse racing involves many animal athletes, of similar genetics, environmental exposure, training, and diet, who participate by breathing varying mixtures of ambient air. This paper presents an analysis strategy based on the homogeneity of the races, the distance, and the design of the track. This paper presents a preliminary analysis in which we observe that the level of performance is decreased by concentrations of PM₁₀, PM_2.5, NO₂, NO, and CO in the air. Thus, we note that this natural experiment may constitute a model of interest to advance the understanding of the problem.

Abstract

This study proposes the theoretical principles for the selection of a sample of horse races to study the relationship between air pollutants and performance. These criteria were then applied to an original dataset comparing the correlations between these variables obtained in “Handicap” versus “Conditional” type races. Methods: The mean concentration of pollutants during the six hours prior to the race and the speed of the test were determined in 441 official races at a racecourse in Santiago, Chile, during the summer and winter months of 2012. Using layout, track condition and distance (1000, 1100 and 1200 m) as criteria, a homogeneous group of races (“Handicap”; n = 214) versus a heterogeneous group (“Conditional”; n = 95) were compared using simple correlations (Spearman’s test). Results: Race speed was related to greater levels of PM₁₀, PM_2.5, NO₂, NO and SO₂ and it was positively related to O₃, a trend that was observed in the 1000, 1100 m races and in the total “Handicap” group. Similar results were observed only in 1000 m for the “Conditional” group with lower Rho, except for PM₁₀ and PM_2.5. The total races of the conditional group showed lower Rho values and significant associations of the same trend for CO, NO₂, NO and SO₂. Conclusions: Horse races between 1000 and 1200 m of the “Handicap” type appear to be an interesting group to study the relationship between air pollutants and the performance of racehorses. In the future, our observations should be expanded to other distances and other types of races.

Short-term exposure to air pollution and hospital admission for pneumonia: a systematic review and meta-analysis

BACKGROUND

Air pollution is a major issue that poses a health threat worldwide. Although several studies investigated the adverse effects of air pollution on various diseases, few have directly demonstrated the effects on pneumonia. Therefore, we performed a systematic review and meta-analysis on the associations between short-term exposure of air pollutants and hospital admission or emergency room (ER) visit for pneumonia.

METHODS

A literature search was performed using PubMed, Embase, and Web of Science up to April 10, 2020. Pooled estimates were calculated as % increase with 95% confidence intervals using a random-effects model. A sensitivity analysis using the leave-one-out method and subgroup analysis by region were performed.

RESULTS

A total of 21 studies were included in the analysis. Every 10 μg/m3 increment in PM2.5 and PM10 resulted in a 1.0% (95% CI: 0.5-1.5) and 0.4% (95% CI: 0.2-0.6) increase in hospital admission or ER visit for pneumonia, respectively. Every 1 ppm increase of CO and 10 ppb increase of NO2, SO2, and O3 was associated with 4.2% (95% CI: 0.6-7.9), 3.2% (95% CI: 1.3-5.1), 2.4% (95% CI: - 2.0-7.1), and 0.4% (95% CI: 0-0.8) increase in pneumonia-specific hospital admission or ER visit, respectively. Except for CO, the sensitivity analyses yielded similar results, demonstrating the robustness of the results. In a subgroup analysis by region, PM2.5 increased hospital admission or ER visit for pneumonia in East Asia but not in North America.

CONCLUSION

By combining the inconsistent findings of several studies, this study revealed the associations between short-term exposure of air pollutants and pneumonia-specific hospital admission or ER visit, especially for PM and NO2. Based on the results, stricter intervention policies regarding air pollution and programs for protecting human respiratory health should be implemented.

Forecasting emergency admissions due to respiratory diseases in high variability scenarios using time series: A case study in Chile

Respiratory diseases are ranked in the top ten group of the most frequent illness in the globe. Emergency admissions are proof of this issue, especially in the winter season. For this study, the city of Santiago de Chile was chosen because of the high variability of the time series for admissions, the quality of data collected in the governmental repository DEIS (selected period: 2014-2018), and the poor ventilation conditions of the city, which in winter contributes to increase the pollution level, and therefore, respiratory emergency admissions. Different forecasting models were reviewed using the Akaike Information Criteria (AIC) with other error estimators, such as the Root Mean Square Error (RMSE), for selecting the best approach. At the end, Seasonal Autoregressive Integrated Moving Average (SARIMA) model, with parameters (p,d,q)(P,D,Q)_s=(2,1,3)(3,0,2)₇, was selected. The Mean Average Percentage Error (MAPE) for this model was 7.81%. After selection, an investigation of its performance was made using a cross-validation through a rolling window analysis, forecasting up to 30 days ahead (testing period of one year). The results showed that error do not exceed a MAPE of 20%. This allows taking better resource managing decisions in real scenarios: reactive staff hiring is avoided given the reduction of uncertainty for the medium term forecast, which translates into lower costs. Finally, a methodology for the selection of forecasting models is proposed, which includes other constraints from resource management, as well as the different impacts for social well-being.

Sulfur or Pollen? Chemical, Biological, and Toxicological Basis for the Correct Risk Communication of Urban Yellow Dust Deposition

Urban yellow dust deposition is a common phenomenon in many parts of the world, which is sometimes called "sulfur shower," "sulfur rain," or "pollen storm." Most people, especially those living in the vicinity of industrial facilities, wrongly perceive the yellow dust as sulfur when in fact it is pollen. The misunderstanding increases risk perception as people believe the "yellow powder" is a serious threat to their health. Based on simple observations, it is virtually impossible to differentiate sulfur from pollen, so risk communication should consider the chemical, biological, and toxicological aspects of these agents. In this review, we clarify that industrial emissions of sulfur are under the form of sulfides, oxides, and other volatile compounds which are gaseous and noncolored, and we explain that it is chemically impossible for gaseous sulfur to become solid yellow sulfur under normal environmental conditions. We also describe pollen and its release from trees, shrubs, and herbs a process influenced by atmospheric conditions. We suggest take-home messages that risk communicators may use when explaining the phenomenon to their communities.

A Methodology for Data-Driven Decision-Making in the Monitoring of Particulate Matter Environmental Contamination in Santiago of Chile

Atmospheric pollution derives mainly from anthropogenic activities that use combustion and may lead to adverse effects in exposed populations. It is generally accepted that air contamination causes cardiovascular and pulmonary morbidity in addition to increased mortality after exposure, but other epidemiological associations have also been described, including cancer as well as reproductive and immunological toxicity. Thus the concentration of chemicals in the air must be controlled. We propose that monitoring of air quality may be achieved by employing data analytics to generate information within the context of data-driven decision making to prevent and/or adequately alert the population about possible critical episodes of air contamination. In this paper, we propose a methodology for monitoring particulate matter pollution in Santiago of Chile which is based on bivariate control charts with heavy-tailed asymmetric distributions. This methodology is useful for monitoring environmental risk when the particulate matter concentrations follow bivariate Birnbaum-Saunders or Birnbaum-Saunders-t-Student distributions. A case study with real particulate matter pollution from Santiago is provided, which shows that the methodology is suitable to alert early episodes of extreme air pollution. The results are in agreement with the critical episodes reported with the current model used by the Chilean health authority.

Quantifying personal exposure to air pollution from smartphone-based location data

Personal exposure assessment is a challenging task that requires both measurements of the state of the environment as well as the individual's movements. In this paper, we show how location data collected by smartphone applications can be exploited to quantify the personal exposure of a large group of people to air pollution. A Bayesian approach that blends air quality monitoring data with individual location data is proposed to assess the individual exposure over time, under uncertainty of both the pollutant level and the individual location. A comparison with personal exposure obtained assuming fixed locations for the individuals is also provided. Location data collected by the Earthquake Network research project are employed to quantify the dynamic personal exposure to fine particulate matter of around 2500 people living in Santiago (Chile) over a 4-month period. For around 30% of individuals, the personal exposure based on people movements emerges significantly different over the static exposure. On the basis of this result and thanks to a simulation study, we claim that even when the individual location is known with nonnegligible error, this helps to better assess personal exposure to air pollution. The approach is flexible and can be adopted to quantify the personal exposure based on any location-aware smartphone application.

Carbon monoxide and risk of outpatient visits due to cause-specific diseases: a time-series study in Yichang, China

BACKGROUND

Previous studies showed inconsistent results on risk of increased outpatient visits for cause-specific diseases associated with ambient carbon monoxide (CO).

METHODS

Daily data for CO exposure and outpatient visits for all-causes and five specific diseases in Yichang, China from 1st January 2016 to 31st December 2017 were collected. Generalised additive models with different lag structures were used to examine the short-term effects of ambient CO on outpatient visits. Potential effect modifications by age, sex and season were examined.

RESULTS

A total of 5,408,021 outpatient visits were recorded. We found positive and statistically significant associations between CO and outpatient visits for multiple outcomes and all the estimated risks increased with longer moving average lags. An increase of 1 mg/m³ of CO at lag06 (a moving average of lag0 to lag6), was associated with 24.67% (95%CI: 14.48, 34.85%), 21.79% (95%CI: 12.24, 31.35%), 39.30% (95%CI: 25.67, 52.92%), 25.83% (95%CI: 13.91, 37.74%) and 19.04% (95%CI: 8.39, 29.68%) increase in daily outpatient visits for all-cause, respiratory, cardiovascular, genitourinary and gastrointestinal diseases respectively. The associations for all disease categories except for genitourinary diseases were statistically significant and stronger in warm seasons than cool seasons.

CONCLUSION

Our analyses provide evidences that the CO increased the total and cause-specific outpatient visits and strengthen the rationale for further reduction of CO pollution levels in Yichang. Ambient CO exerted adverse effect on respiratory, cardiovascular, genitourinary, gastrointestinal and neuropsychiatric diseases especially in the warm seasons.

The relationship between fine particulate matter (PM2.5) and schizophrenia severity

PURPOSE

Although particulate matter (PM) is reported to affect the rate of emergency admissions for schizophrenia, no study has examined the relationship between particulate matter less than 2.5 μm in diameter (PM_2.5) and the severity of schizophrenia.

METHODS

We obtained data on patients with schizophrenia at a psychiatric hospital, and on air pollution in Sakai, Japan between Feb 1, 2013 and April 30, 2016. Multivariate logistic regression analyses were used to estimate the relationship between PM_2.5 concentrations and scores on the Brief Psychiatric Rating Scale (BPRS) of schizophrenia patients at admission, with a lag of up to 7 days.

RESULTS

During the study period, there were 1193 schizophrenia cases. The odds ratio (OR) for a BPRS score ≥ 50 at admission was 1.05 [95% confidence interval 1.00-1.10] and the effect of PM_2.5 concentration was significant for lag period of 2 days. The ORs associated with PM_2.5 concentration increased substantially for patients over 65 years of age.

CONCLUSIONS

Ambient PM_2.5 concentration was associated with exacerbation of schizophrenia. Our results suggest that protection for several days should be considered for controlling PM_2.5-related schizophrenia, especially among elderly patients.

A review of the experimental evidence on the toxicokinetics of carbon monoxide: the potential role of pathophysiology among susceptible groups

BACKGROUND

Acute high level carbon monoxide (CO) exposure can cause immediate cardio-respiratory arrest in anyone, but the effects of lower level exposures in susceptible persons are less well known. The percentage of CO-bound hemoglobin in blood (carboxyhemoglobin; COHb) is a marker of exposure and potential health outcomes. Indoor air quality guidelines developed by the World Health Organization and Health Canada, among others, are set so that CO exposure does not lead to COHb levels above 2.0%, a target based on experimental evidence on toxicodynamic relationships between COHb and cardiac performance among persons with cardiovascular disease (CVD). The guidelines do not consider the role of pathophysiological influences on toxicokinetic relationships. Physiological deficits that contribute to increased CO uptake, decreased CO elimination, and increased COHb formation can alter relationships between CO exposures and resulting COHb levels, and consequently, the severity of outcomes. Following three fatalities attributed to CO in a long-term care facility (LTCF), we queried whether pathologies other than CVD could alter CO-COHb relationships. Our primary objective was to inform susceptibility-specific modeling that accounts for physiological deficits that may alter CO-COHb relationships, ultimately to better inform CO management in LTCFs.

METHODS

We reviewed experimental studies investigating relationships between CO, COHb, and outcomes related to health or physiological outcomes among healthy persons, persons with CVD, and six additional physiologically susceptible groups considered relevant to LTCF residents: persons with chronic obstructive pulmonary disease (COPD), anemia, cerebrovascular disease (CBD), heart failure, multiple co-morbidities, and persons of older age (≥ 60 years).

RESULTS

We identified 54 studies published since 1946. Six studies investigated toxicokinetics among healthy persons, and the remaining investigated toxicodynamics, mainly among healthy persons and persons with CVD. We identified one study each of CO dynamics in persons with COPD, anemia and persons of older age, and no studies of persons with CBD, heart failure, or multiple co-morbidities. Considerable heterogeneity existed for exposure scenarios and outcomes investigated.

CONCLUSIONS

Limited experimental human evidence on the effects of physiological deficits relevant to CO kinetics exists to support indoor air CO guidelines. Both experimentation and modeling are needed to assess how physiological deficits influence the CO-COHb relationship, particularly at sub-acute exposures relevant to indoor environments. Such evidence would better inform indoor air quality guidelines and CO management in indoor settings where susceptible groups are housed.

Air pollution, PM2.5 composition, source factors, and respiratory symptoms in asthmatic and nonasthmatic children in Santiago, Chile

The objective of this study was to determine the association of respiratory symptoms and medication use and exposure to various air pollutants, PM_2.5 components, and source factors in a panel of asthmatic and nonasthmatic children in Santiago, Chile. To this end, 174 children (90 asthmatics and 84 nonasthmatics) were followed throughout the winter months of 2010 and 2011. During the study period, children filled out daily diaries to record respiratory symptoms and medication use. Air pollution data were obtained from government central site measurements and a PM_2.5 characterization campaign. PM_2.5 source factors were obtained using positive matrix factorization (PMF). Associations of symptoms and exposure to pollutants and source-factor daily scores were modeled separately for asthmatic and nonasthmatic children using mixed logistic regression models with random intercepts, controlling for weather, day of the week, year, and viral outbreaks. Overall, high concentrations of air pollutants and PM_2.5 components were observed. Six source factors were identified by PMF (motor vehicles, marine aerosol, copper smelter, secondary sulfates, wood burning, and soil dust). Overall, single pollutant models showed significant and strong associations between 7-day exposures for several criteria pollutants (PM_2.5, NO₂, O₃), PM_2.5 components (OC, K, S, Se, V), and source factors (secondary sulfate) and coughing, wheezing and three other respiratory symptoms in both in asthmatic and nonasthmatic children. No associations were found for use of rescue inhalers in asthmatics. Two-pollutant models showed that several associations remained significant after including PM_2.5, and other criteria pollutants, in the models, particularly components and source factors associated with industrial sources. In conclusion, exposure to air pollutants, especially PM_2.5, NO₂, and O₃, were found to exacerbate respiratory symptoms in both asthmatic and nonasthmatic children. Some of the results suggest that PM_2.5 components associated with a secondary sulfate source may have a greater impact on some symptoms than PM_2.5. In general, the results of this study show important associations at concentrations close or below current air quality standards.

The association between particulate air pollution and respiratory admissions among young children in Hanoi, Vietnam

While the effects of ambient air pollution on health have been studied extensively in many developed countries, few studies have been conducted in Vietnam, where the population is exposed to high levels of airborne particulate matter. The aim of our study was to examine the short-term effects of PM₁₀, PM_2.5, and PM₁ on respiratory admissions among young children in Hanoi. Data on daily admissions from the Vietnam National Hospital of Paediatrics and daily records of PM₁₀, PM_2.5, PM₁ and other confounding factors as NO₂, SO₂, CO, O₃ and temperature were collected from September 2010 to September 2011. A time-stratified case-crossover design with individual lag model was applied to evaluate the associations between particulate air pollution and respiratory admissions. Significant effects on daily hospital admissions for respiratory disease were found for PM₁₀, PM_2.5 and PM₁. An increase in 10μg/m³ of PM₁₀, PM_2.5 or PM₁ was associated with an increase in risk of admission of 1.4%, 2.2% or 2.5% on the same day of exposure, respectively. No significant difference between the effects on males and females was found in the study. The study demonstrated that infants and young children in Hanoi are at increased risk of respiratory admissions due to the high level of airborne particles in the city's ambient air.