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The Lag Structure Between Particulate Air Pollution and Respiratory and Cardiovascular Deaths in 10 US Cities
Abstract
To assess differences in the lag structure pattern between particulate matter < 10 microns/100 microns in diameter (PM10) and cause-specific mortality, we performed a time-series analysis in 10 US cities using generalized additive Poisson regressions in each city; nonparametric smooth functions were used to control for long time trend, weather, and day of the week. The PM10 effect was estimated based on its daily mean, 2-day moving average, and the cumulative 7-day effect by means of an unconstrained distributed lag model. A 10-microgram/m3 increase in the 7-day mean of PM10 was associated with increases in deaths due to pneumonia (2.7%, 95% confidence interval [CI]: 1.5, 3.9), chronic obstructive pulmonary disease (1.7%, 95% CI: 0.1, 3.3), and all cardiovascular diseases (1.0%, 95% CI: 0.6, 1.4). A 10-microgram/m3 increase in the 2-day mean of PM10 was associated with a 0.7% (95% CI: 0.3, 1.1) increase in deaths from myocardial infarction. When the distributed lag was assessed, two different patterns could be observed: respiratory deaths were more affected by air pollution levels on the previous days, whereas cardiovascular deaths were more affected by same-day pollution. These results contribute to the overall efforts so far in understanding how exposure to air pollution promotes adverse health effects.
... A case-crossover study from Barcelona found increased PM 10 associated with the higher mortality of COPD (ER: 11%) (Sunyer and Basagaña 2001). Another time series study from 10 US cities (Braga et al. 2001) and Hong Kong (Wong et al. 2002) also found that the increased COPD mortality risk was associated with PM 10 (ER: 1.7% for the USA and 1.0% for Hong Kong). On the other side, several studies only observed significant associations in specific groups. ...
... Compared with the ER values in previous studies, we found the values in cohort and case-crossover studies were largely higher than those in a time series design, which was in part due to the bigger power of the test in cohort and case-crossover design. Meanwhile, the ER values in this time series study were consistent with the results from other time series studies (Braga et al. 2001;Wong et al. 2002). Best lags for PM 2.5 and PM 10 were lag 2 for single-day and lag 03 for multiple-day, respectively. ...
... Best lags for PM 2.5 and PM 10 were lag 2 for single-day and lag 03 for multiple-day, respectively. Those were similar to the Hong Kong study (Wong et al. 2002) and differ from the US study (Braga et al. 2001), which suggested that delay effects are varied in different regions partly owing to spatial variation of pollutants. Additionally, various effects of PMs on different regions or cities may also due to different pollution sources, distinguishing between natural (wildfires, eolian dust) and anthropogenic emissions, including fossil fuel use (Lelieveld et al. 2020). ...
The objective of this study was to investigate the association between ambient particulate matters (PMs) and chronic obstructive pulmonary disease (COPD) mortality. generalized additive mixed model was employed to investigate the effects of ambient fine and coarse PMs on COPD mortality using 13,066 deaths from 2014 to 2016 among six cities in Zhejiang Province in Southeastern China. The daily average death count due to COPD was 3, varying from 1 to 7 among six cities. The daily 24-h mean concentrations were diverse among cities, from 29.7 to 56.8 μg/m3 for PM2.5, 16.7 to 30.3 μg/m3 for PM2.5–10, and 50.3 to 87.1 μg/m3 for PM10, respectively. The analysis showed that daily exposure to PM2.5 and PM10 was associated with increased mortality due to COPD and that weak effects were observed between PM2.5–10 and COPD mortality. Our results provided solid evidence that the fine particles in air pollution have stronger functions on adverse health effects other than coarser particles in Southeastern China, which may be considered as a potential clinic target in PM-associated COPD.
... A case-crossover study from Barcelona found increased PM 10 associated with the higher mortality of COPD(ER:11%) [28]. Another time series study from 10 US cities [29] and Hong ...
... Compared with the ER values in previous studies, we found the values in cohort and case-crossover studies were largely higher than those in a time series design, which was in part due to the bigger power of the test in cohort and case-crossover design. Meanwhile, the ER values in this time series study were consistent with the results from other time series studies [29,30]. Best lags for PM 2.5 and PM 10 were lag 2 for single-day and lag 03 for multiple-day, respectively. ...
... Best lags for PM 2.5 and PM 10 were lag 2 for single-day and lag 03 for multiple-day, respectively. Those were similar to the Hong Kong study [30], and differ from the US study [29], which suggested delay effects are varied in different regions partly owing to spatial variation of pollutants. ...
Background: The objective of this study was to investigate the association between ambient particulate matters(PMs)and chronic obstructive pulmonary disease (COPD) mortality.
Methods: Generalized Additive Mixed Model was employed to investigate the effects of ambient fine and coarse PMs on COPD mortality using 13,066 deaths from 2014 to 2016 among six cities in Zhejiang Province in Southeastern China.
Results: The daily average death count due to COPD was 3, varying from 1 to 7among six cities. The daily 24-hour mean concentrations were diverse among cities, from 29.7 to 56.8 µg/m³ for PM2.5, 16.7 to 30.3 µg/m³ for PM2.5−10, and 50.3 to 87.1 µg/m³ for PM10, respectively. The analysis showed that daily exposure to PM2.5 and PM10 was associated with increased mortality due to COPD and that weak effects were observed between PM2.5−10 and COPD mortality.
Conclusions: Our results provided evidence that the fine particles in air pollution have stronger functions on adverse health effects other than coarser particles in Southeastern China, which may be considered as a potential clinic target in PM-associated COPD.
... A further issue is the length of the lag period (delay). The time between initial exposure to a pollutant and various health outcomes depends on how the pollutant interacts with a target organ, and this interaction can lead to a specific disease [13]. ...
... This approach provided a numerical comparison of the effects of PM10 on mortality in the different temperature strata, while allowing for heterogeneity of the effects of PM10 across the strata [11]. Furthermore, we examined the effects of PM10 under different lag structures, because a delayed health effect is known to exist in the association between PM10 and mortality [13]. Specifically, we explored the lag structures of PM10 in elderly people during the warm months (April to September) and the cold months (October to March) by cause of death and sex. ...
... Lag structures in the relationship between PM concentration and health outcomes have been previously assessed [13,22,26]. In our assessment of the lag effects of PM10 on cause-specific mortality, we found that the short-term effects of a rise in PM10 concentration on mortality persisted for longer periods in the case of respiratory mortality than in the case of cardiovascular mortality. ...
Climate change, air pollution, and the rapidly aging population are important public health challenges. An understanding of air pollution impacts is imperative for preventing air-pollution-related deaths and illnesses, particularly in vulnerable subgroups such as the increasing population of older adults. To assess the effects of short-term air-pollution exposure on the elderly, we conducted a time-series analysis (1996–2015) of the associations between particulate matter with an aerodynamic diameter of <10 μm (PM10) and deaths among elderly residents of Seoul, South Korea, which has a rapidly aging population. We also investigated the synergistic effects of temperature and the lag structures of the effects by sex, cause of death, and season. A 10 μg/m3 rise in the 4-day moving average concentration of PM10 was associated with 0.31% (95% confidence interval (CI): 0.18% to 0.44%), 0.32% (95% CI: 0.09% to 0.55%), and 0.22% (95% CI: –0.23% to 0.66%) increases in non-accidental, cardiovascular, and respiratory mortalities, respectively. We found a significant and strong synergistic effect of PM10 concentration and ambient temperature on mortality in elderly people. PM10 posed an increased risk of non-accidental or cardiovascular mortality with increasing temperature, whereas the associated risk of respiratory death was highest on very cold days. The shape and length of the lag structure varied with the cause of death, sex, and season. Results indicate that elderly people exposed to PM10 are at increased risk of premature death. In the near future, these risks are likely to increase in step with the temperature rise associated with climate change and the continued population aging. Stronger emission controls will be needed to minimize the increased health risks associated with air pollution, especially in regions with high populations of elderly individuals.
... Πέρα από αυτό το κατώφλι θερμοκρασιών η θνησιμότητα αυξάνει, με την μέγιστη θνησιμότητα να παρατηρείται όταν προσεγγίζονται τα ακρότατα της θερμοκρασίας. Η σχέση αυτή μεταξύ θνησιμότητας και θερμοκρασίας έχει προσδιοριστεί για πολλές γεωγραφικές περιοχές, συμπεριλαμβανομένης της Ευρώπης, των ΗΠΑ, της Κίνας κλπ (Armstrong 2006, Armstrong et al. 2011, Baccini et al. 2008, Braga et al. 2001, Curriero et al. 2002, Guo et al. 2011, Hajat & Kosatky 2010. ...
... Σημαντικές είναι επίσης οι ενδείξεις για την ύπαρξη της λεγόμενης «χρονικής υστέρησης», δηλαδή του φαινομένου κατά το οποίο οι αρνητικές επιπτώσεις του θερμικού στρες μπορεί να εμφανίζονται μετά από ορισμένες ημέρες από την έκθεση των ατόμων στις ακραίες συνθήκες. Υπ' αυτήν την έννοια, τα περιστατικά θανάτων που σημειώνονται κατά την ημέρα n μπορεί να οφείλονται στην έκθεση κατά τις ημέρες n-i, όπου ο αριθμός i εκφράζει την αλληλουχία των διαδοχικών ημερών που προηγήθηκαν της εμφάνισης του περιστατικού (Anderson & Bell 2009, Braga et al. 2001, Gasparrini et al. 2010. ...
... Οι confounders παίζουν ενεργό ρόλο, όταν μια μεταβλητή σχετίζεται ισχυρά τόσο με την έκθεση όσο και με την επίπτωση που αυτή προκαλεί, χωρίς να είναι αποτέλεσμα της έκθεσης. Χαρακτηριστικό παράδειγμα confounder αποτελούν οι μετεωρολογικές παράμετροι, όπως για παράδειγμα η σχετική υγρασία, που είναι γνωστό ότι σχετίζεται ισχυρά με τη θερμοκρασία (έκθεση) αλλά και με το αποτέλεσμα της έκθεσης, δηλαδή την θνησιμότητα (Armstrong et al. 2011, Braga et al. 2001, Curriero et al. 2002, Guo et al. 2011. ...
Η λεπτή ισορροπία ανάμεσα στην εξερχόμενη και στην εισερχόμενη ηλιακή
ακτινοβολία προσδιορίζει το παγκόσμιο κλίμα. Οποιαδήποτε μεταβολή οδηγεί σε
αλλαγή του κλίματος. Οι βασικότεροι παράγοντες είναι η ηλιακή ακτινοβολία, η
ατμοσφαιρική σύσταση, οι αλλαγές στη χρήση γης. Η συχνότητα ακραίων
φαινομένων οδήγησε τους επιστήμονες στη χρήση μοντέλων και δεικτών για την
παρατήρηση των κλιματικών μεταβολών που οφείλονται σε αυξομειώσεις
σημαντικών παραμέτρων.
Σε αυτήν την εργασία θα γίνει αρχικά αναφορά στα σημαντικότερα μαθηματικά
μοντέλα ατμοσφαιρικής ρύπανσης και διασποράς (Gauss, Euler, Αριθμητικά, Φυσικά,
Στατιστικά, Εμπειρικά) και σε δείκτες ποιότητας αέρα. Επιπλέον θα δοθεί ιδιαίτερη
σημασία στη χρησιμότητα των παγκόσμιων και τοπικών κλιματικών μοντέλων ως
εργαλεία προσομοίωσης του κλίματος στα σενάρια κλιματικής αλλαγής καθώς και
στις σημαντικότερες αλλαγές που θα προκύψουν στην Ελλάδα έως το 2100 από την
εφαρμογή των μοντέλων αυτών στη δημόσια υγεία. Ένα άλλο σημαντικό μέρος αυτής
της εργασίας αφορά στη χρήση Υπολογιστικής Νοημοσύνης για την διερεύνηση του
προβλήματος. Συγκεκριμένα, θα γίνει σύνδεση των μετεωρολογικών παραμέτρων με
φαινόμενα ατμοσφαιρικής ρύπανσης και με περιόδους έντονης ξηρασίας και
υγρασίας με τη βοήθεια Ασαφών Γνωστικών Χαρτών (Fuzzy Cognitive Maps). Με
αυτό τον τρόπο θα δημιουργηθούν σενάρια που θα υποδηλώνουν τις συσχετίσεις,
θετικές ή αρνητικές, ανάμεσα στις συνδέσεις των παραμέτρων με τα φαινόμενα
ρύπανσης και ξηρασίας.
Στο Τμήμα Δασολογίας και Διαχείρισης Περιβάλλοντος και Φυσικών Πόρων του
Δημοκρίτειου Πανεπιστημίου Θράκης έχει γίνει στο πρόσφατο παρελθόν μια
ερευνητική προσπάθεια με τη Χρήση Συστημάτων Ασαφούς Άλγεβρας-Νόησης και
Γεωγραφικών Συστημάτων Πληροφοριών, για την μοντελοποίηση του προβλήματος
της ξηρασίας στην Κύπρο τα τελευταία 30 έτη (Παπακωνσταντίνου κ.ά. 2010).
Η καινοτομία της έρευνας που παρουσιάζεται σε αυτήν την εργασία είναι η χρήση
Χαρτών Ασαφούς Νόησης (Fuzzy Cognitive Maps) προς το ευρύτερο πρόβλημα της
κλιματικής αλλαγής και των συνεπειών του.
... After the fixed interruption point (initial post-intervention phase), the linear data requirement of the CSR model makes the impacts of interventions perceived as immediate, direct, and leapfrogged at a fixed point, which may be violated in intervention evaluations [6]. However, some interventions and exposures in practice may have gradual or delayed impacts on the outcome time series, as reported in many studies [11][12][13][14]. For example, the nursing intervention carried out by the Oncology Advanced Practice Nurse in the USA had a lag effect on the quality of life of post-surgical women with gynecologic cancer, [11] and the effects of the Medicare Act on hospital admission tended to emerge gradually after its adoption [12]. ...
... For example, the nursing intervention carried out by the Oncology Advanced Practice Nurse in the USA had a lag effect on the quality of life of post-surgical women with gynecologic cancer, [11] and the effects of the Medicare Act on hospital admission tended to emerge gradually after its adoption [12]. In addition, there is substantial evidence that air pollution exposure has a lag effect on respiratory and cardiovascular disease-related mortality and morbidity [13][14][15][16]. The effect of supra-threshold heat exposure on mortality persisted for several days, and the cumulative effect remained high even after 30 days of exposure in Seoul and Incheon [17]. ...
The interrupted time series (ITS) design is widely used to examine the effects of large-scale public health interventions and has the highest level of evidence validity. However, there is a notable gap regarding methods that account for lag effects of interventions.
To address this, we introduced activation functions (ReLU and Sigmoid) to into the classic segmented regression (CSR) of the ITS design during the lag period. This led to the proposal of proposed an optimized segmented regression (OSR), namely, OSR-ReLU and OSR-Sig. To compare the performance of the models, we simulated data under multiple scenarios, including positive or negative impacts of interventions, linear or nonlinear lag patterns, different lag lengths, and different fluctuation degrees of the outcome time series. Based on the simulated data, we examined the bias, mean relative error (MRE), mean square error (MSE), mean width of the 95% confidence interval (CI), and coverage rate of the 95% CI for the long-term impact estimates of interventions among different models.
OSR-ReLU and OSR-Sig yielded approximately unbiased estimates of the long-term impacts across all scenarios, whereas CSR did not. In terms of accuracy, OSR-ReLU and OSR-Sig outperformed CSR, exhibiting lower values in MRE and MSE. With increasing lag length, the optimized models provided robust estimates of long-term impacts. Regarding precision, OSR-ReLU and OSR-Sig surpassed CSR, demonstrating narrower mean widths of 95% CI and higher coverage rates.
Our optimized models are powerful tools, as they can model the lag effects of interventions and provide more accurate and precise estimates of the long-term impact of interventions. The introduction of an activation function provides new ideas for improving of the CSR model.
... Our study shows similar results for the cardiovascular system disease admission. However, Braga et al. (2001) reported that cardiovascular deaths represented an acute response to exposure to air pollution, but respiratory deaths were more affected by exposure on the 1 or 2 previous days [17]. In our survey the cardiovascular disease admission, the highest effect of exposure to air pollution (PM2.5 and PM10 level) was observed at the first and second days of exposure. ...
... Our study shows similar results for the cardiovascular system disease admission. However, Braga et al. (2001) reported that cardiovascular deaths represented an acute response to exposure to air pollution, but respiratory deaths were more affected by exposure on the 1 or 2 previous days [17]. In our survey the cardiovascular disease admission, the highest effect of exposure to air pollution (PM2.5 and PM10 level) was observed at the first and second days of exposure. ...
... where E(Y t ) represents the expected number of deaths at day t, β represents the log-relative rate of mortality associated with a unit increase of ambient air pollutants, X i indicates the concentration of ambient air pollutants at day t, W t (week) is the dummy variable for day of the week, Z j is the predictor variables other than ambient air pollutants (i.e., time, mean daily temperature, and relative humidity), and fj is a smooth function of these variables. Single-day lag models are known to possibly underestimate the cumulative effect of air pollution on mortality; 2-day moving averages of current-day and previous-day concentrations of air pollutants (lag01) were used in our main analysis with current-day (lag 0 day) temperature and relative humidity (Bell et al. 2004;Braga et al. 2001). Sensitivity analyses were conducted to examine the impact of air pollutants on mortality with lag structures, including single-day lag (lag 0 to 4) and multi-day lag (lag 01 to 04). ...
... Exposure to ambient air pollution is known to be associated with adverse health outcomes. Several studies have reported the effect of short-term exposure to ambient air pollutants on cardiovascular mortality (Burroughs Peña and Rollins 2017; Braga et al. 2001;Fung et al. 2003). The results of our study showed that PM 2.5 , O 3 , and SO 2 in the single pollutant model were strongly associated with circulatory mortality, with risk estimates of 1.288(1.198, ...
Various studies have illustrated that exposure to ambient air pollution has negative impacts on health. However, little evidence exists on the effects of ambient air pollution on circulatory mortality in Xi’an, China. This study aims to investigate and ascertain the association between short-term exposure to ambient air pollutants and circulatory mortality in Xi’an, China. Daily average concentrations of PM2.5, SO2, and O3, meteorological data (temperature and relative humidity) and daily counts of circulatory mortality were obtained between January 2014 and June 2016. Mortality was stratified by gender and age group (≤ 64 years and ≥ 65 years). A generalized additive model (GAM) with natural splines (NS) was constructed to analyze the relationship between ambient air pollutants and daily circulatory mortality. There were 57,570 cases of circulatory mortality, with cerebrovascular and ischemic heart diseases accounting for 48.5% and 43.5%, respectively. All ambient air pollutants displayed different seasonal patterns. In the single pollutant model, 10 μg/m³ increase in 2-day moving average concentrations of PM2.5, SO2, and O3 was associated with relative risk of 1.288(1.198, 1.388), 1.360(0.877, 2.331), and 1.324(1.059, 1.705) in circulatory mortality, respectively. After adjusting for collinearity in the multi-pollutant model, the effects remained statistically significant. The ≥ 65 years and female sub-groups were associated with a higher risk of circulatory mortality. Short-term exposure to ambient air pollutants plays a pivotal role in the genesis of circulatory mortality in Xi’an. Responses to ambient air pollutants exposure in relation to circulatory mortality are different when analyzed by sub-groups.
... after one month's delay [40]. However, in another study conducted by Braga et al., in 10 US cities, results showed that cardiovascular deaths in contrary to respiratory deaths, which were affected by the level of PM 10 2 days before (time lag 2), were af fected by the level of PM 10 on the same day as well [43]. ...
... as well [41]. Investigat ing the effects of air pollution and cause-specific mortality (cardiovascular, respiratory, etc.) after delays may help dis cover the relation between pollutants and causes of death and provide more insight for finding the mechanisms of ef fects of ambient air pollutants on those deaths [43]. Some of the mechanisms for the effect of air pollutants on cardiovascular outcomes have been mentioned in stud ies. ...
Objectives:
There are few studies about the association between breathing polluted air and increased risk of cardiovascular diseases and cardiac death in the Middle East. This study aimed to investigate the relation between air pollutants and cardiovascular mortality (based on ICD-10) in Ahvaz.
Material and methods:
In this ecological study, the data about cardiovascular disease mortality and air pollutants from March 2008 until March 2015 was inquired from the Ahvaz City Authority and the Khuzestan Province Environmental Protection Agency. The quasi-Poisson, second degree polynomial constrained, distributed lag model; using single and cumulative lag structures, adjusted by trend, seasonality, temperature, relative humidity, weekdays and holidays was used for the data analysis purposes.
Results:
Findings indicated a direct significant relation between an interquartile range (IQR) increase in ozone and cardiovascular deaths among men after 3 days' lag. There was also a significant relation between an IQR increase in particulate matter below 10 μm and cardiovascular deaths for all people, over 60 years old and under 18 years old after 3 and 13 days' lags. There was a significant relation between an IQR increase in nitrogen dioxide and carbon monoxide, and cardiovascular deaths in the case of under 18-year-olds (in the lag 11) and over 60-year-olds (in the lag 9), respectively. We finally found a significant association between an IQR increase in sulfur dioxide and cardiovascular deaths in the case of men, under 18-year-olds and from 18- to 60-year-olds in the lag 9, 0, and 11, respectively (p-values < 0.05).
Conclusions:
It appears that air pollution is significantly associated with cardiovascular deaths in Ahvaz City.
... Cardiovascular disease is the leading cause of mortality all over the world. The prevalence and the incidence of cardiovascular pathologies ascent as both long-term and short-term exposures to air pollutants increase (Braga et al. 2001;Tonne et al. 2007). More specifically, higher densities of ozone (O 3 ), sulfur dioxide (SO 2 ), nitric dioxide (NO 2 ), carbon monoxide (CO), and particulate matter less than 2.5 μm (PM 2.5 ) and particulate matter less than 10 μm (PM 10 ) in the ambient air have described in pathogenesis of cardiorespiratory diseases (Schwela 2000). ...
... More specifically, higher densities of ozone (O 3 ), sulfur dioxide (SO 2 ), nitric dioxide (NO 2 ), carbon monoxide (CO), and particulate matter less than 2.5 μm (PM 2.5 ) and particulate matter less than 10 μm (PM 10 ) in the ambient air have described in pathogenesis of cardiorespiratory diseases (Schwela 2000). It has been shown that emergency room visits are higher on polluted days, which adds to the clinical and the economic burden on healthcare systems and necessitate preventive measures to handle the situation (Braga et al. 2001;Lin et al. 2003a). Diverse mechanisms have been described for the role of air pollutants in pathogenesis of cardiovascular diseases. ...
We investigated the association between the levels of air pollutants and the number of daily admissions due to ST segment elevation myocardial infarction (STEMI) in a metropolitan in the northwest of Iran. Daily concentrations of common air pollutants were obtained for the greater city of Tabriz for a period of 2 years. These reports included sulfur dioxide (SO2), nitrogen dioxide (NO2), nitric oxide (NO), nitrogen byproducts (NOx), carbon monoxide (CO), ozone (O3), and particulate matters < 10 μm (PM10). The census of admissions for STEMI was retrieved for the same period from hospital registries. The association of daily variations in air pollutant levels and the daily number of STEMI admissions were investigated in a time-series analysis. In the multi-pollutant model adjusting for long-term trend, seasonality, and temperature, a significant association was found for 1-h [NO2] and 24-h [CO]. A marginally significant association was observed for 24-h [NO2] and 8-h [CO]. The 24-h [CO] had the strongest association with the number of admissions with STEMI. Maximum 1-h concentrations of NO2 on the same day and on the prior day as well as 24-h concentrations of CO on the prior day were independently associated with increased number of STEMI admissions. However, daily concentrations of SO2, NO, O3, and PM10 were not associated with the frequency of hospital admissions for STEMI.
... In subsection 5.1, we find significant decreases in air pollution in the second and third months after a coal mine accident which is consistent with the result that an accident leads to a significant decrease in RES mortality three months later. This is consistent with the epidemiological literature that finds that the cumulative effects of air pollution on RES mortality are larger than the contemporaneous effects (Braga et al., 2001;Costa et al., 2017). We check the parallel trend assumption for RES mortality. ...
We leverage the timing of coalmine accidents to examine the effect of coal mining on air pollution. Safety regulations mandate that coal mining be suspended if a mine experiences an accident with 10 or more fatalities. We use a stacked difference-in-differences approach to compare counties with an accident to those experiencing an accident more than two years earlier or later. We provide evidence that the timing of accidents cannot be predicted. Next, we combine satellite-based air pollution data at the county-day level with the dates of accidents to show that on average, suspending coal mining reduces local air pollution by 8%. Changes in the level of coal consumption do not drive this reduction. We also find significant decreases in respiratory mortality after suspending coal mining with particularly large effects on vulnerable populations.
... We analyzed the associations between the daily maximum values of PM 10 and O 3 levels and cause-specific mortality, and we investigated this effect on the susceptible elderly subgroup with the use of DLNMs. To quantify the mortality burden, we used relative risk changes for every 10 µg/m 3 increase in air pollution concentrations as the primary effect estimates [86,87]. After conducting a specific analysis using a lag structure, which has great heterogeneity among literature, we determined thes most suitable lag for this work to be defined at days 0-6, similar to other studies [62,64]. ...
This study examines the effects of short-term exposure to PM10 and O3 on all-cause, cardiorespiratory, and cerebrovascular mortality in the urban area of Thessaloniki, Greece. An analysis was performed on the vulnerable subgroup (the elderly population). The primary effect estimates employed were the relative risks for every 10 µg/m3 increase in air pollutant concentrations. Strong associations between PM10 and O3 levels on mortality were reported, with the elderly people becoming frailer. An increase of 10 μgr/m3 in PM10 concentration resulted in a 2.3% (95% CI: 0.8–3.8) and 2% (95% CI: 0.1–4.5) increase in total and cardiorespiratory mortality, respectively. O3 concentrations showed even stronger associations for all-cause (3.9%, 95% CI: 2.5–5.3) and cardiorespiratory deaths (5.3%, 95% CI: 3.1–7.7) with 10 μgr/m3 increases; no statistically significant associations were found for cerebrovascular causes, while both pollutants presented stronger impacts on health between day 0 and 3. Concerning the elderly, the total mortality rose by 3.2% (95% CI: 1.5–5) due to PM10 concentrations and by 4.4% (95% CI: 2.9–6) due to O3 concentrations. In total, 242 (170) all-cause deaths were annually attributed to the PM10 (O3) level in Thessaloniki. In the efforts towards achieving a sustainable environment for humanity, health benefits resulting from two air pollution abatement scenarios (a 20% reduction in PM10 levels and full compliance to the European Union PM10 limits) were quantified. The analysis led to a respective decrease in total excess mortality by 0.4% and 1.8%, respectively. This outcome stresses the necessity of appropriate civil protection actions and provides valuable scientific knowledge to national and regional administrations in order to develop proper health and air quality plans.
... Meteorological effects were incorporated as distributed lags (Gasparrini et al. 2010), which are commonly used in epidemiology to model the delayed effects of environmental exposures on health outcomes (Braga et al. 2001;Schwartz 2000). Using this approach, each county-week was associated with a 120-d environmental history extending from the day the week began (lag 0) back to 120 d in the past (lag 120). ...
Background:
West Nile virus (WNV), a global arbovirus, is the most prevalent mosquito-transmitted infection in the United States. Forecasts of WNV risk during the upcoming transmission season could provide the basis for targeted mosquito control and disease prevention efforts. We developed the Arbovirus Mapping and Prediction (ArboMAP) WNV forecasting system and used it in South Dakota from 2016 to 2019. This study reports a post hoc forecast validation and model comparison.
Objectives:
Our objective was to validate historical predictions of WNV cases with independent data that were not used for model calibration. We tested the hypothesis that predictive models based on mosquito surveillance data combined with meteorological variables were more accurate than models based on mosquito or meteorological data alone.
Methods:
The ArboMAP system incorporated models that predicted the weekly probability of observing one or more human WNV cases in each county. We compared alternative models with different predictors including a) a baseline model based only on historical WNV cases, b) mosquito models based on seasonal patterns of infection rates, c) environmental models based on lagged meteorological variables, including temperature and vapor pressure deficit, d) combined models with mosquito infection rates and lagged meteorological variables, and e) ensembles of two or more combined models. During the WNV season, models were calibrated using data from previous years and weekly predictions were made using data from the current year. Forecasts were compared with observed cases to calculate the area under the receiver operating characteristic curve (AUC) and other metrics of spatial and temporal prediction error.
Results:
Mosquito and environmental models outperformed the baseline model that included county-level averages and seasonal trends of WNV cases. Combined models were more accurate than models based only on meteorological or mosquito infection variables. The most accurate model was a simple ensemble mean of the two best combined models. Forecast accuracy increased rapidly from early June through early July and was stable thereafter, with a maximum AUC of 0.85. The model predictions captured the seasonal pattern of WNV as well as year-to-year variation in case numbers and the geographic pattern of cases.
Discussion:
The predictions reached maximum accuracy early enough in the WNV season to allow public health responses before the peak of human cases in August. This early warning is necessary because other indicators of WNV risk, including early reports of human cases and mosquito abundance, are poor predictors of case numbers later in the season. https://doi.org/10.1289/EHP10287.
... In 1993, the Harvard Six Cities Study was the first prospective study that Abbreviations: Coronary Heart Disease, (CHD); Cardiovascular Disease, (CVD); National Priority Contaminated Sites, (NPCSs); Standardized Mortality Ratios, (SMRs%); 90% Confidence Intervals, (90%CI); Direct Standardized Death Rates, (SDRs); Mediterranean Diet, (MeD).. associated environmental pollution with cardiovascular mortality in six cities in the United States [11]. The same association was found in the 90s in other prospective [12][13][14] and historical [15,16] epidemiological investigations and, subsequently, confirmed by case-crossover and timeseries studies [17,18]. ...
Background
Coronary Heart Disease (CHD) is associated with various risk factors, including environmental stressors. The aim of our paper is to study the mortality patterns in Italy with a focus on provinces of the Apulia Region from 1931 to 2015 to analyze the burden of the disease over time.
Methods
We conducted an ecological analysis of mortality from all causes and from CHD in main Italian geographical areas and in the Apulian provinces, from 1931 to 2015. Sex-specific mortality and population data were obtained from the Italian National Institute of Statistics since 1969. Direct standardized mortality rates (SDRs) per 10,000 inhabitants with 90% confidence intervals (90%CI) were calculated from 1969, using the European population as standard. The standardized mortality ratios (SMRs%) were calculated with 90%CI and the Italian population as reference.
Results
The SDRs indicate a decline in mortality from CHD in all geographical Italian areas and in the Apulian provinces for both sexes. However, this decline slowed over time, particularly in the South. The highest values of SMRs% were observed in the industrialized areas of Taranto and especially Brindisi, in both sexes.
Conclusions
The historical reconstruction over about 80 years highlighted critical issues for CHD at the start of the industrial development in the provinces of Brindisi and Taranto. This might suggest environmental pollution as risk factor for cardiovascular diseases. Furthermore, it would be necessary to verify how much other risk factors (eg. diabetes and obesity) affect the slowdown in the CHD mortality decline over the last decade.
... Particularly, the association between acute exposure to air particulate matter and mortality or morbidity has been extensively studied. Many such studies have indicated that the short-term lagged effects of air particulate matter are likely to be present [Samet et al., 2000, Schwartz, 2000, Braga et al., 2001, Zanobetti et al., 2003. In other words, the current measure of health outcome such as mortality count on a given day is not only affected by the current/same-day measure of the exposure but also its lagged measures within a time window preceding the health event. ...
There is growing interest in investigating the short-term delayed lag effects of environmental pollutants (e.g. air particulate matter and ozone) on a health outcome of interest measured at a certain time (e.g. daily mortality counts). Previous studies have shown that not only the current level of the exposure but exposure levels up to past few days may be associated with health event/outcome measured on current day. Distributed lag model (DLM) has been used in environmental epidemiology to characterize the lag structure of exposure effects. These models assume that the coefficients corresponding to exposures at different lags follow a given function of the lags. Under mis-specification of this function, DLM can lead to seriously biased estimates. In this dissertation, we first explore different methods to make the traditional DLM more robust. We then extend the single pollutant DLM to multi-pollutant scenarios. We illustrate the proposed methods using air pollution data from the National Morbidity, Mortality and Air Pollution Study (NMMAPS) and a dataset from Brigham and Women's Hospital (BWH) prospective birth cohort study. In the first project, we propose three classes of shrinkage methods to combine an unconstrained DLM estimator and a constrained DLM estimator and achieve a balance between robustness and efficiency. The three classes of methods can be broadly described as (1) empirical Bayes-type shrinkage, (2) hierarchical Bayes, and (3) generalized ridge regression. A two-step double shrinkage approach that enforces the effect estimates approach zero at larger lags is also considered. A simulation study shows that all four approaches are effective in trading off between bias and variance to attain lower mean squared error with the two-step approaches having edge over others. In the second project, we extend DLM to two-pollutant scenarios and focus on characterizing pollutant-by-pollutant interaction. We first consider to model the interaction surface by assuming the underlying basis functions are tensor products of the basis functions that generate the main-effect distributed lag functions. We also extend Tukey's one-degree-of-freedom interaction model to two-dimensional DLM context as a parsimonious way to model the interaction surface between two pollutants. Data adaptive approaches to allow departure from the specified Tukey's structure are also considered. A simulation study shows that shrinkage approach Bayesian constrained DLM has the best average performance in terms of relative efficiency. In the third project, we extend DLM to a truly multi-dimensional space and focus on identifying important pollutants and pairwise interactions associated with a health outcome. Penalization-based approaches that induce sparsity in solution are considered. We propose a Hierarchical integrative Group LASSO (HiGLASSO) approach to perform variable selection at a group level while maintaining strong heredity constraints. Empirically, HiGLASSO identifies the correct set of important variables more frequently than other approaches. Theoretically, we show that HiGLASSO enjoys Oracle properties including selection and estimation consistency.
... thế giới, chiếm phần lớn nhất của nguyên nhân tử vong và số năm sống bị mất [6]. Các mối liên hệ ngắn hạn giữa ô nhiễm không khí dạng hạt và tử vong do tim mạch ở các mức độ khác nhau đã được báo cáo trước đây ở Bắc Mỹ [7,8], Châu Âu [9]. Các nghiên cứu về tác động của vật chất hạt cũng được nghiên cứu rộng rãi ở các nước phát triển của Châu Á, tuy nhiên vẫn đang tập trung vào các hạt vật chất lơ lửng có đường kính < 10µm (PM10) [10,11]. ...
Nghiên cứu nhằm xây dựng bản đồ phân bố nồng độ bụi mịn PM2.5 và đánh giá tác động của PM2.5 lên tửvong do tim mạch tại thành phố Hồ Chí Minh (TP.HCM) năm 2018. Bản đồ PM2.5 được xây dựng giữa sự kết hợp quan trắc 96 điểm vào mùa mưa và khô trên toàn địa bàn TP.HCM bằng thiết bị quan trắc giá rẻ AirBeam2 và thuật toán nội suy khoảng cách nghịch đảo có trọng số (IDW). Tác động của PM2.5 đến tử vong do tim mạch cũng như ảnh hưởng kinh tế được ước tính bằng mô hình BenMAP dựa trên dữ liệu tử vong A6/YTCS Bộ Y tế. Ở tất cả các quận/huyện, nồng độ PM2.5 trung bình cả năm cao hơn tiêu chuẩn chất lượng không khí của WHO (PM2.5 < 10µg/m3). PM2.5 gây tác động đến 6,4% số ca tử vong do tim mạch (327/5134) và 1,1% số ca tử vong do tất cả các nguyên nhân (327/29.173), đồng thời gây thiệt hại 2.942 tỷ VNĐ (chiếm 0,052% GDP VN) vào năm 2018. Nghiên cứu đề xuất cần có những biện pháp giảm thiểu tác hại và ô nhiễm bụi PM2.5 tại TPHCM.
... In addition, the proposed relationship model allows for the daily air pollution and confirmed cases as variables, while it has not considered the lag effect that confirmed case changes influenced by air pollution might have in the future [39]. Although the impact of historical air pollution trends on the COVID-19 pandemic progress in independent countries is investigated in some research [20,40], the lag effect at the global scale has not been fully discussed. ...
The novel coronavirus disease 2019 (COVID-19) has caused significantly changes in worldwide environmental and socioeconomics, especially in the early stage. Previous research has found that air pollution is potentially affected by these unprecedented changes and it affects COVID-19 infections. This study aims to explore the non-linear association between yearly and daily global air pollution and the confirmed cases of COVID-19. The concentrations of tropospheric air pollution (CO, NO2, O3, and SO2) and the daily confirmed cases between 23 January 2020 and 31 May 2020 were collected at the global scale. The yearly discrepancies of air pollutions and daily air pollution are associated with total and daily confirmed cases, respectively, based on the generalized additive model. We observed that there are significant spatially and temporally non-stationary variations between air pollution and confirmed cases of COVID-19. For the yearly assessment, the number of confirmed cases is associated with the positive fluctuation of CO, O3, and SO2 discrepancies, while the increasing NO2 discrepancies leads to the significant peak of confirmed cases variation. For the daily assessment, among the selected countries, positive linear or non-linear relationships are found between CO and SO2 concentrations and the daily confirmed cases, whereas NO2 concentrations are negatively correlated with the daily confirmed cases; variations in the ascending/declining associations are identified from the relationship of the O3-confirmed cases. The findings indicate that the non-linear relationships between global air pollution and the confirmed cases of COVID-19 are varied, which implicates the needs as well as the incorporation of our findings in the risk monitoring of public health on local, regional, and global scales.
... In consideration of the lagging effects of air pollution on PROM, we used the models with different lag structures (lag 0 day to lag 10 days) to evaluate the effects of air pollutants on PROM. As single-day lag models may underestimate the effects of pollutants (Bell et al. 2004;Braga et al. 2001), the cumulative lag models were adopted in this study using moving averages of daily air pollutants concentrations for the current day and the previous days. ...
Numerous studies had focused on the association between air pollution and health outcomes in recent years. However, little evidence is available on associations between air pollutants and premature rupture of membranes (PROM). Therefore, we performed time-series analysis to evaluate the association between PROM and air pollution. The daily average concentrations of PM2.5, SO2 and NO2 were 54.58 μg/m³, 13.06 μg/m³ and 46.09 μg/m³, respectively, and daily maximum 8-h average O3 concentration was 95.67 μg/m³. The strongest effects of SO2, NO2 and O3 were found in lag4, lag06 and lag09, and an increase of 10 μg/m³ in SO2, NO2 and O3 was corresponding to increase in incidence of PROM of 8.74% (95% CI 2.12–15.79%), 3.09% (95% CI 0.64–5.59%) and 1.68% (95% CI 0.28–3.09%), respectively. There were no significant effects of PM2.5 on PROM. Season-specific analyses found that the effects of PM2.5, SO2 and O3 on PROM were more obvious in cold season, but the statistically significant effect of NO2 was observed in warm season. We also found the modifying effects by maternal age on PROM, and we found that the effects of SO2 and NO2 on PROM were higher among younger mothers (< 35 years) than advanced age mothers (≥ 35 years); however, ≥ 35 years group were more vulnerable to O3 than < 35 years group. This study indicates that air pollution exposure is an important risk factor for PROM and we wish this study could provide evidence to local government to take rigid approaches to control emissions of air pollutants.
... C. Liu et al., 2017aLiu et al., , 2017b, although no associations were observed with cardiovascular hospitalizations. In addition to differences in study outcomes on CVD hospitalizations, our reports confirm findings that the lags for PM 2.5 exposure and hospitalizations tend to be shorter for CVD hospitalizations compared to respiratory hospitalizations (Braga et al., 2001;Dominici et al., 2006). ...
Abstract We estimated cardiopulmonary morbidity and mortality associated with wildfire smoke (WFS) fine particulate matter (PM2.5) in the Front Range of Colorado from 2010 to 2015. To estimate WFS PM2.5, we developed a daily kriged PM2.5 surface at a 15 × 15 km resolution based on the Environmental Protection Agency Air Quality System monitors for the western United States; we subtracted out local seasonal‐average PM2.5 of nonsmoky days, identified using satellite‐based smoke plume estimates, from the local daily estimated PM2.5 if smoke was identified by National Oceanic and Atmospheric Administration’s Hazard Mapping System. We implemented time‐stratified case‐crossover analyses to estimate the effect of a 10 µg/m3 increase in WFS PM2.5 with cardiopulmonary hospitalizations and deaths using single and distributed lag models for lags 0–5 and distinct annual impacts based on local and long‐range smoke during 2012, and long‐range transport of smoke in 2015. A 10 µg/m3 increase in WFS was associated with all respiratory, asthma, and chronic obstructive pulmonary disease hospitalizations for lag day 3 and hospitalizations for ischemic heart disease at lag days 2 and 3. Cardiac arrest deaths were associated with WFS PM2.5 at lag day 0. For 2012 local wildfires, asthma hospitalizations had an inverse association with WFS PM2.5 (OR: 0.716, 95% CI: 0.517–0.993), but a positive association with WFS PM2.5 during the 2015 long‐range transport event (OR: 1.455, 95% CI: 1.093–1.939). Cardiovascular mortality was associated with the 2012 long‐range transport event (OR: 1.478, 95% CI: 1.124–1.944).
... To date, several studies have proposed potential biological mechanisms how air pollution contributes to the occurrence of MI including oxidative stress and inflammation (8)(9)(10); only a limited number of studies have explored the association of short-term exposure to PM 2.5 (11)(12)(13)(14)(15)(16)(17)(18)(19), PM 10 (15,20,21), SO 2 (11,15,20,22), NO 2 (11,15,22), CO (15,20), or O 3 (11,15,23) with MI mortality, and the results remain largely inconsistent and inconclusive. In 2012, Mustafic et al. (10) conducted a systematic review and meta-analysis, and concluded that short-term exposures to PM 2.5 , PM 10 , SO 2 , NO 2 , and CO, but not O 3 , were significantly associated with a near-term increase in MI risk; however, this study included both the occurrence of MI and its death as the outcome of interest, and did not investigate MI mortality separately. ...
Background
Short-term exposure to ambient air pollution has been linked to occurrence of myocardial infarction (MI); however, only a limited number of studies investigated its association with death from MI, and the results remain inconsistent.
Objectives
This study sought to investigate the association of short-term exposure to air pollution across a wide range of concentrations with MI mortality.
Methods
A time-stratified case-crossover study was conducted to investigate 151,608 MI death cases in Hubei province (China) from 2013 to 2018. Based on each case’s home address, exposure to particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5), particulate matter with an aerodynamic diameter ≤10 μm (PM10), sulfur dioxide, nitrogen dioxide (NO2), carbon monoxide, and ozone on each of the case and control days was assessed as the inverse distance–weighted average concentration at neighboring air quality monitoring stations. Conditional logistic regression models were implemented to quantify exposure-response associations.
Results
Exposure to PM2.5, PM10, and NO2 (mean exposure on the same day of death and 1 day prior) was significantly associated with increased odds of MI mortality. The odds associated with PM2.5 and PM10 exposures increased steeply before a breakpoint (PM2.5, 33.3 μg/m³; PM10, 57.3 μg/m³) and flattened out at higher exposure levels, while the association for NO2 exposure was almost linear. Each 10-μg/m³ increase in exposure to PM2.5 (<33.3 μg/m³), PM10 (<57.3 μg/m³), and NO2 was significantly associated with a 4.14% (95% confidence interval [CI]: 1.25% to 7.12%), 2.67% (95% CI: 0.80% to 4.57%), and 1.46% (95% CI: 0.76% to 2.17%) increase in odds of MI mortality, respectively. The association between NO2 exposure and MI mortality was significantly stronger in older adults.
Conclusions
Short-term exposure to PM2.5, PM10, and NO2 was associated with increased risk of MI mortality.
... A relação entre poluição atmosférica e saúde humana começou a ser mais estudada a partir da Revolução Industrial, principalmente nos centros urbanos que se formaram nessa época. A rápida urbanização, a atividade industrial e o consequente aumento de veículos refletiram, e ainda refletem, na qualidade do ar, afetando-a negativamente (BRAGA; ZANOBETTI; SCHWARTZ, 2001;OLIVEIRA et al., 2011;ARBEX et al., 2012;DAPPER;SPOHR;ZANINI, 2016). Alguns episódios extremos de mortalidade associada à poluição atmosférica, especialmente o ocorrido em Londres, em 1952, que ocasionou cerca de três mil mortes, foram decisivos para a adoção de medidas de controle da qualidade do ar e para a realização de estudos que avaliassem a relação entre as emissões e os impactos à saúde (BELL; DAVIS, 2001). ...
O objetivo deste estudo foi analisar a associação da exposição à poluição
atmosférica e as internações hospitalares por doenças respiratórias
(CID‑10: J00-J99) de residentes em Volta Redonda (RJ), no período de 2013 a
2015, bem como estimar seus custos. Foram considerados dados do Instituto
Estadual do Ambiente (INEA) para partículas totais em suspensão (PTS), PM10 e
ozônio (O3) e dados disponíveis no DATASUS referentes à morbidade por doenças
respiratórias por faixa etária (total, crianças e idosos). Para estimar tal associação,
foi utilizado o modelo aditivo generalizado de regressão de Poisson. Observou-se
a elevação do risco de admissão hospitalar para a elevação de 10 μg/m3 de PM10
para o total de internações — lag 2: 1,39% (IC95% 0,23–2,55%) e lag 3 1,36%
(IC95% 0,21–2,52%) — e para os idosos — lag 3: 1,89% (IC95% 0,02–3,69%) e
lag 4 1,9% (IC95% 0,02–3,85%) —, de PTS para o total de internações — lag 2
0,84% (IC95% 0,40–1,64%) — e para crianças menores que 5 anos (lag 4: 2,2%
(IC95% 0,05–4,02%) — e de O3 para os idosos (lag 6: 2,41% (IC95% 0,31–4,57%).
Destaca‑se que as associações ocorreram mesmo quando os níveis de poluentes
não ultrapassaram os limites estabelecidos pela legislação. Do total de internações
para o período, 99 foram atribuídas à exposição ao PM10, gerando custo de
R$ 115.165,25 para o Sistema Único de Saúde. Espera-se que essas informações
contribuam para a discussão da problemática ambiental na região.
Palavras-chave: doenças respiratórias; qualidade do ar; séries temporais;
custos hospitalares.
... A study in 38 Chinese large cities found that PM 10 exposure was significantly associated with daily mortality with lag-days of up to 2 days . In another study in 10 US cities, 7-day and 2day averages of PM 10 were associated with respiratory and cardiovascular health outcomes, including pneumonia (relative risk (RR) = 2.7% on average), chronic obstructive pulmonary disease (1.7%), all cardiovascular diseases (1.0%), and myocardial infarction (0.7%) (Braga et al. 2001). In a systematic review by Atkinson et al. (2014), 110 time-series studies investigating the daily mortality and hospitalization were identified through 2011. ...
This study investigated the association of short-term exposure to PM10, PM2.5, NO2, O3, and CO with daily all-cause, cardiovascular, ischemic heart disease (IHD), cerebrovascular, and respiratory deaths in Mashhad, a tourist megacity in Iran (2014–2018). A distributed-lag-day, nonlinear model (DLNM) and generalized additive model (GAM) based on the quasi-Poisson distribution were used to explore the exposure-lag-day-response associations. The average (± standard deviation) concentrations of PM10, PM2.5, NO2, O3, and CO were 67.1 (± 35.5), 29.6 (± 14.2), 57.3 (± 24.1), 55.9 (± 16.9), and 1907.6 (± 1362.7) μg/m3, respectively. NO2 was associated with IHD mortality in lag-days 0 to 0–7, and lag-day 1. The relative risks (RRs) for a 10 μg/m3 increase in NO2 ranged from 1.01 (95% CI 0.93, 1.11) at lag-day 0 to 1.04 (95% CI 0.94, 1.16) and 1.03 (95% CI 0.93, 1.14) for lag-day 0–1 (cumulative) and lag-day 1 (non-cumulative), respectively. For all-cause mortality, cumulative exposure to PM2.5 for lag-day 0–7 (1.07, 95% CI 1.00, 1.15) and non-cumulative exposure to NO2 at lag-day 6 (1.02, 95% CI 1.00, 1.03) were significant. Exposure to PM10 (per 10 μg/m3) was significantly associated with respiratory mortality at several lag-days. Adjusting for Ramadan did not significantly affect the results. PM10 had significant associations with respiratory mortality of people > 65 years old, and men for several lag-days. For IHD, NO2 affected older people, and men and women over different lag-days. Results of multi-pollutant models were similar to the single-pollutant model outcomes. In conclusion, NO2 and PM10 had more significant relationships with adverse health outcomes than the other pollutants.
... In their study, all of the annual mean concentrations of the same year were included similar to those exposed to death, but our study used, only the average exposure from the day of the event until a year ago. The effect of PM 10 on total mortality in COPD patients was evaluated in a number of studies investigating short-term exposure, which mainly assessed daily exposure (within 7 days of the lag day) [16][17][18] . Very few studies investigated the long-term exposure, involving an average exposure for 1 to 4 years 19,20 . ...
We investigated the effects of particulate matter (PM) on mortality in patients diagnosed with asthma-COPD overlap (ACO) or ‘pure COPD’. Subjects from the National Health Insurance Service–National Sample Cohort of Korea, who were aged 40 years or above and had newly diagnosed COPD since 2009 were selected. Finally, 6,313 patients were enrolled and divided into ‘pure COPD’ and ACO groups. Average PM10 exposure data were obtained using Kriging interpolation from 2001 to 2013. Hazard ratios(HR) were estimated using a time-varying Cox regression model. Exposure to PM10 for 1, 3, and 6 months was associated with an increase in non-accidental mortality in the entire COPD group, especially the ACO group. When a stratified analysis of 3-month exposure was performed by sex, the highest HR was found in women with ACO (HR = 1.153; 95% confidence intervals [CI]: 1.121, 1.185). A stratified analysis according to smoking status showed that ACO patients had the highest HR among never smokers (HR = 1.151; 95% CI; 1.124, 1.178). Average exposure to PM10 was associated with non-accidental mortality in patients with COPD, especially those diagnosed with ACO. In addition, the adverse effects of PM10 exposure are more severe in women and never-smokers.
... El PM está formado por partículas sólidas y/o líquidas, con excepción del agua, que entran en la atmósfera por vías naturales o, por la acción del hombre, el PM es un contaminante atmosférico asociado a efectos adversos para la salud humana (BRAGA et al., 2001;DOCKERY et al., 1993). La contaminación de los humanos ocurre a través de la respiración y el contacto con la piel, mediante la inhalación de partículas que pueden contaminar los pulmones o el tracto digestivo (SEVERO 2017). ...
ResumenEste manuscrito presenta a través de un estudio tipo no experiemental la caracterización de la contaminación atmosférica por la calcinación de yeso en los municipios de Araripina y Trindade del estado de Pernambuco, en el noreste de Brasil. Esos municipios son importantes por conformar el Complejo Yesero de Araripe que representa la mayor parte de la producción de yeso de Brasil, considerada una de las mayores del mundo. La investigación se realizó utilizando datos de informes de pruebas de caracterización de emisiones atmosféricas realizadas en 20 empresas, 9 de Trindade y 11 de Araripina, de 2015 a 2018. Según los resultados, no hubo una reducción significativa en las emisiones de contaminantes entre 2015 y 2016, lo que evidencia pocas inversiones en el mantenimiento y mejora de los procesos. Sin embargo, para el período 2017-2018, los datos muestran una disminución en las emisiones de contaminantes, con un número considerable de empresas que cumplen con los límites establecidos por la ley. Dado lo anterior, existe la necesidad de intensificar la supervisión de las empresas de yeso en la región debido los hornos se encuentran en condiciones precarias sin mantenimiento y mejora en el proceso de combustión donde las emisiones de monóxido de carbono y otros contaminantes que exceden en mucho el límite permitido por la legislación ambiental. Palabras-clave: Contaminación del aire, Residuos de yeso, Análisis isocinético. AbstractThis manuscript presents through a non-experimental type study, the characterization of air pollution by the calcination of plaster in the municipalities of Araripina and Trindade in the state of Pernambuco, in northeastern Brazil. These municipalities are important for shaping the Plaster Complex of Araripe, which represents the majority of the plaster production in Brazil, considered one of the largest in the world. The research was conducted using data from reports of atmospheric emissions characterization tests carried out in 20 companies, 9 from Trindade and 11 from Araripina, from 2015 to 2018. According to the results, there was no significant reduction in pollutant emissions between 2015 and 2016, which shows few investments in the maintenance and improvement of the processes. However, for the 2017-2018 period, the data shows a decrease in pollutant emissions, with a considerable number of companies that meet the limits established by law. Given the above, there is a need to intensify the supervision of gypsum companies in the region because the furnaces are in precarious conditions without maintenance and improvement in the combustion process where emissions of carbon monoxide and other pollutants that greatly exceed the limit allowed by environmental legislation.Keywords: Atmospheric pollution, Plaster waste, Isokinetic analysis.
... Lagged effects have been identified in respiratory disease, but not cardiovascular disease, while mortality has shown both lagged and non-lagged effects. 29, [38][39][40] In our investigation, we observed no delayed risk of violence from PM 2.5 exposure and a slight decrease in violence risk from lagged ozone. These findings are similar to an observed null response between lagged exposure to coarse particulate matter and carbon monoxide on violent crime in Chicago. ...
Background:
Violence is a leading cause of death and an important public health threat, particularly among adolescents and young adults. However, the environmental causes of violent behavior are not well understood. Emerging evidence suggests exposure to air pollution may be associated with aggressive or impulsive reactions in people.
Methods:
We applied a two-stage hierarchical time series model to estimate change in risk of violent and non-violent criminal behavior associated with short-term air pollution in U.S. counties (2000-2013). We used daily monitoring data for ozone and fine particulate matter (PM2.5) from the Environmental Protection Agency and daily crime counts from the Federal Bureau of Investigation. We evaluated the exposure-response relationship and assessed differences in risk by community characteristics of poverty, urbanicity, race, and age.
Results:
Our analysis spans 301 counties in 34 states, representing 86.1 million people and 721,674 days. Each 10µg/m change in daily PM2.5 was associated with a 1.17% (95% CI: 0.90, 1.43) and a 10ppb change in ozone with a 0.59% (95% CI: 0.41, 0.78) relative risk increase (RRI) for violent crime. However, we observed no risk increase for non-violent property crime due to PM2.5 (RRI: 0.11%; 95% CI: -0.09, 0.31) or ozone (RRI: -0.05%; 95% CI: -0.22, 0.12). Our results were robust across all community types, except rural regions. Exposure-response curves indicated increased violent crime risk at concentrations below regulatory standards.
Conclusions:
Our results suggest that short-term changes in ambient air pollution may be associated with greater risk of violent behavior, regardless of community type.
... The evidence gathered from epidemiological studies shows that both short-and long-term exposures to APM have deleterious effects on human health, (WHO -World Health Organisation, 2000;Pope and Dockery, 2006), with PM 10 affecting mostly the former, and PM 2.5 identified as a stronger risk factor with respect to the latter. Various time series studies, spanning across different cities, have found a statistically robust association between increases in daily mortality and daily increases in both PM 10 (Levy et al., 2000;Stieb et al., 2002;Braga et al., 2001) and PM 2.5 levels (Schwartz, 2000(Schwartz, , 2003. For both aerosol fractions mortality results from inter alia cardiovascular or respiratory causes (Samet et al., 2000;Analitis et al., 2006). ...
Results of a methodological study on the use of Positive Matrix Factorization (PMF) with smaller datasets are being reported in this work. This study is based on 29 PM10 and 33 PM2.5 samples from a receptor in a rural setup in Apulia (Southern Italy). Running PMF on the two size fractions separately resulted in the model not functioning correctly. We therefore, augmented the size of the dataset by aggregating the PM10 and PM2.5 data. The 5-factor solution obtained for the aggregated data was fairly rotationally stable, and was further refined by the rotational tools included in USEPA PMF version 5. These refinements include the imposition of constraints on the solution, based on our knowledge of the chemical composition of the aerosol sources affecting the receptor. Additionally, the uncertainties associated with this solution were fully characterised using the improved error estimation techniques in this version of PMF. Five factors in all, were isolated by PMF: ammonium sulfate, marine aerosol, mixed carbonaceous aerosol, crustal/Saharan dust and total traffic. The results obtained by PMF were further tested inter alia, by comparing them to those obtained by two other receptor modelling techniques: Constrained Weighted Non-negative Matrix Factorization (CW – NMF) and Chemical Mass Balance (CMB). The results of these tests suggest that the solution obtained by PMF, is valid, indicating that for this particular airshed PMF managed to extract most of the information about the aerosol sources affecting the receptor – even from a dataset with a limited number of samples.
... Therefore, to observe the aspect of time in revealing some delayed effects of the air pollutants on respiratory mortality, a lag analysis was conducted using the following lag structures [single-day lag (0-4) and multi-day lag (01-04)]. For the lag analysis, a single day concentration of air pollution (lag 0-current day only) and a 2-day average of air pollutant concentration (lag 01-currentday and previous-day) were used to determine the single day and cumulative effects of the pollutants [19,20]. ...
Background:
Although air pollution is a known fundamental problem in China, few studies have investigated the associations between ambient air pollution and respiratory mortality in non-metropolitan cities of China. The study aimed to investigate a potential relationship between short-term exposure to ambient air pollutants and respiratory mortality in Xi'an, China.
Methods:
Daily averages of PM2.5, SO2, O3, temperature, relative humidity and daily counts of respiratory mortality were obtained (2014-2016). Using a single and multi-pollutant approach in time-series analysis, the generalized additive model with natural splines was used for analysis. Subgroup analysis stratified by gender and age group (≤ 64 years and ≥ 65 years) was conducted.
Results:
Seven thousand nine hundred sixty-five cases of respiratory mortality were assessed, with 62.9, 28.5, and 8.6% of mortality attributed to chronic lower respiratory diseases, influenza and pneumonia, as well as other forms of respiratory diseases, respectively. Observed pollutants were significantly associated with respiratory mortality. In the single pollutant model, 10 μg/m3 increase in a two-day moving average of PM2.5, and SO2 concentrations were significantly associated with relative risk 1.313(1.032, 1.708) and 1.4020(0.827, 2.854) of respiratory mortality, respectively. The effects of both air pollutants remained statistically significant after adjusting for collinearity in the multi-pollutant model. Ozone was only statistically associated with respiratory mortality in females at lag 0 [RR: 0.964(0.938, 0.991)].
Conclusion:
This study provided evidence that respiratory mortality in Xi'an was significantly associated with exposure to ambient air pollutants from 2014 to 2016.
... To examine the statistical difference in PM 2:5 risk on health outcomes between smoke and non-smoke days, we used the interaction coefficient b s2 . The percentage difference in cardiopulmonary hospitalizations for a 10-lg=m 3 increase in PM 2:5 was examined at single-day lags ranging from the day of exposure [lag day 0 (L0)] up through 6 d postexposure (L6) (Braga et al. 2001). Estimated relative risks were expressed as percentage difference in hospitalization rates per 10-lg=m 3 increase in PM 2:5 on both smoke and non-smoke days (ðexp ðE½b × 10Þ − 1Þ × 100%). ...
Background:
The effects of exposure to fine particulate matter ([Formula: see text]) during wildland fires are not well understood in comparison with [Formula: see text] exposures from other sources.
Objectives:
We examined the cardiopulmonary effects of short-term exposure to [Formula: see text] on smoke days in the United States to evaluate whether health effects are consistent with those during non-smoke days.
Methods:
We examined cardiopulmonary hospitalizations among adults [Formula: see text] y of age, in U.S. counties ([Formula: see text]) within [Formula: see text] of 123 large wildfires during 2008-2010. We evaluated associations during smoke and non-smoke days and examined variability with respect to modeled and observed exposure metrics. Poisson regression was used to estimate county-specific effects at lag days 0-6 (L0-6), adjusted for day of week, temperature, humidity, and seasonal trend. We used meta-analyses to combine county-specific effects and estimate overall percentage differences in hospitalizations expressed per [Formula: see text] increase in [Formula: see text].
Results:
Exposure to [Formula: see text], on all days and locations, was associated with increased hospitalizations on smoke and non-smoke days using modeled exposure metrics. The estimated effects persisted across multiple lags, with a percentage increase of 1.08% [95% confidence interval (CI): 0.28, 1.89] on smoke days and 0.67% (95% CI: [Formula: see text], 1.44) on non-smoke days for respiratory and 0.61% (95% CI: 0.09, 1.14) on smoke days and 0.69% (95% CI: 0.19, 1.2) on non-smoke days for cardiovascular outcomes on L1. For asthma-related hospitalizations, the percentage increase was greater on smoke days [6.9% (95% CI: 3.71, 10.11)] than non-smoke days [1.34% (95% CI: [Formula: see text], 3.77)] on L1.
Conclusions:
The increased risk of [Formula: see text]-related cardiopulmonary hospitalizations was similar on smoke and non-smoke days across multiple lags and exposure metrics, whereas risk for asthma-related hospitalizations was higher during smoke days. https://doi.org/10.1289/EHP3860.
... They reported a positive correlation between PM 10 and ACS; however, they did not provide specific conclusions for different gender and age groups. Most studies have focused on the correlation between particulate matter, especially PM 10 and MI, with conflicting results [8,[13][14][15][16][17][18][19][20][21][22][23][24][25]. Moreover, the delayed effect of PM 10 exposure on ACS events has only been partially studied to date. ...
(1) Background: In recent decades, studies have reported on the increased cardiovascular risk associated with increased levels of air pollutants, especially particulate matters (PM). It remains unclear whether the specific subgroups share the same involvement and whether the effect is delayed. (2) Methods: Data for acute coronary syndrome (ACS) incidences from 2008 to 2011 were gathered in two major medical centres in Slovenia. A time series analysis was conducted in which daily ACS incidence data were linked with daily concentrations of PM10 (PM with a median aerodynamic diameter less than 10 μm) using a well-established generalized linear model with a log link function and a Poisson distribution of ACS. We specifically focused on groups based simultaneously on age and gender. (3) Results: On the basis of the presented models, it appears that daily average concentrations of PM10 have a significant impact on ACS incidence for the entire population, with a higher impact on older populations and the highest impact on older men. The analysis of the delayed effect in PM10-related ACS incidences observed the strongest effect at a one day lag. (4) Conclusions: Our study detected the presence of a “rise and fall” lag pattern observed in three aforementioned population groups; however, no significant association was detected for women and younger populations.
... In exposure-response analyses, the potential lag relation has important implications given the time difference between the exposure events and adverse health outcomes. One may get inaccurate effect estimates if the lag relation undertaken improperly (Braga et al., 2001;Schwartz, 2000). ...
Background: Acute mortality effects of air pollution have been recognized in plenty of environmental epidemiologic studies. However, existing studies usually assume a universal lag association across sites and seasons. Such a strategy ignores the heterogeneity of lag structures and may lead to bias in the estimation of effects. Methods: A Bayesian hierarchical model with flexible lag structures was applied to estimate the impact of particulate matter less than 10 μm (PM10) on mortality and determine whether the lag structure varied by season and location. Data from nine US communities, obtained from the National Morbidity, Mortality, and Air Pollution Study (NMMAPS), was used to examine the lagged associations between PM10 and daily mortality. The estimates obtained from the flexible lag approaches were compared with those from the universal lag approach. Results: Of potential varying lag structures, a 10-μg/m³ increase in PM10 was associated with 0.32% (95% credible interval: 0.16, 0.45) and 0.36% (0.18, 0.52) increases in mortality from nonaccidental and cardiovascular-respiratory death. The community-specific estimates of PM10 mortality effects were distinct between the flexible and the universal lag approaches, with relative change of the effects ranged from −7.21% to 9.25% for nonaccidental morality, and from −5.78% to 4.16% for cardiovascular-respiratory morality. Moreover, the lag structure varied by location and season. For instance, the nonaccidental mortality effect of PM10 attributable to the current and previous day was 29.8% in El Paso while 55.0% in Chicago; the overall effect attributable to the previous two to five days were 60.6%, 51.9%, 59.5%, and 59.3% in winter, spring, summer, and fall, respectively. Conclusion: The results indicated that a universal lag association across sites and seasons may bias the mortality effect of air pollution. The varying lag structures should be considered in studies of short-term environmental exposures to get a more precise effect estimate.
... Regarding the association between fine particles' exposure and deaths due to respiratory causes we found an association with COPD deaths significant at the 10% level and a non-significant association with LRTI-related deaths. Previous studies have reported an association between COPD mortality and PM 10 exposure (Braga et al., 2001;Romieu et al., 2012;Zeka et al., 2005) or have addressed hospital admissions (Atkinson et al., 2001;Dominici et al., 2006;Faustini et al., 2013). A recent review by Schikowski et al. (2014) that focused on the long term association between air pollution and COPD concluded that acute and long term effects on the development of the underlying patho-physiological changes are not easily distinguished from each other under the epidemiological designs evaluated, and that evidence was suggestive though not conclusive. ...
... The air pollution effects on health could occur in the day of exposure or on consecutive days, named lag structures (Braga et al., 2001;Martins et al., 2006). In a recent study, Costa et al. (2016) found that single-day lag and cumulative effects up to 5 days pointed out relevant increases in mortality in elderly population in association with air pollutant levels, including particulate matter smaller than 10 µm (PM 10 ) (Costa et al., 2016). ...
Air pollution is an important health risk concern and an economic burden, notably on low-and middle-income countries. The aim of this study was to determine the mortality burden of cardiovascular and respiratory diseases, specifically, the relative risk due to air pollution and the economic valuation derived from life-years lost within the population of São Paulo, Brazil. This study was conducted using a retrospective Health Impact Assessment (HIA) approach via daily time series of cardiovascular and respiratory deaths for the population of São Paulo from 2000 to 2011. The effects of particulate matter smaller than 10 µm (PM 10 ) were estimated with Poisson generalized additive models. The single-day lag effects of air pollutant exposure were estimated for 0–3-day lags. Therefore, we obtained the years of life lost (YLL) through the disability-adjusted life years (DALY) method to estimate the burden of disease due to air pollution in São Paulo. The value of a life year (VOLY) was then applied to convert the YLL component to economic loss. The results showed an association between PM 10 and cardiovascular and respiratory mortality, lagging 3 days. The YLL totaled 231,691.8 years, meaning an overall economic loss of more than US$14.1 billion. In conclusion, knowledge regarding the costs of premature deaths related to air pollution can be used to improve public policy and to facilitate decision making in the context of scarce resources.
... Hundreds of studies have reported associations between short-term exposure to air pollution and daily deaths (Baccini et al. 2006;Bell et al. 2004;Braga et al. 2001;Chen et al. 2014;Jhun et al. 2014;Katsouyanni et al. 1997;Katsouyanni et al. 2009;Levy et al. 2012;Peng et al. 2005;Peng et al. 2013;Schwartz 1991;Tao et al. 2012;Zanobetti et al. 2002;Schwartz 2008, 2009). The most common findings are that associations with particulate air pollution and ozone exist and that these two exposures do not confound each other. ...
Background
Studies have long associated PM2.5 with daily mortality, but few applied causal-modeling methods, or at low exposures. Short-term exposure to NO2, a marker of local traffic, has also been associated with mortality but is less studied. We previously found a causal effect between local air pollution and mortality in Boston.
Objectives
We aimed to estimate the causal effects of local pollution, PM2.5, and NO2 on mortality in 135 U.S. cities.
Methods
We used three methods which, under different assumptions, provide causal marginal estimates of effect: a marginal structural model, an instrumental variable analysis, and a negative exposure control. The instrumental approach used planetary boundary layer, wind speed, and air pressure as instruments for concentrations of local pollutants; the marginal structural model separated the effects of NO2 from the effects of PM2.5, and the negative exposure control provided protection against unmeasured confounders.
Results
In 7.3 million deaths, the instrumental approach estimated that mortality increased 1.5% [95% confidence interval (CI): 1.1%, 2.0%] per 10 μg/m3 increase in local pollution indexed as PM2.5. The negative control exposure was not associated with mortality. Restricting our analysis to days with PM2.5 below 25 μg/m3, we found a 1.70% (95% CI 1.11%, 2.29%) increase. With marginal structural models, we found positive significant increases in deaths with both PM2.5 and NO2. On days with PM2.5 below 25 μg/m3, we found a 0.83% (95% CI 0.39%, 1.27%) increase. Including negative exposure controls changed estimates minimally.
Conclusions
Causal-modeling techniques, each subject to different assumptions, demonstrated causal effects of locally generated pollutants on daily deaths with effects at concentrations below the current EPA daily PM2.5 standard. https://doi.org/10.1289/EHP2732
... [8] More broadly our findings are in line with previous studies that have found evidence of a lag between exposure to criteria pollutants and mortality. For PM 10 , a single days exposure has been shown to have an effect for up to 5 days[46,47] and numbers of respiratory deaths appear to be more affected by air pollution levels on previous days, than cardiovascular deaths that are impacted by same-day pollution.[48] For example myocardial infarction represents an acute response to a For peer review only -http://bmjopen.bmj.com/site/about/guidelines.xhtml ...
... For PM10, a single days exposure has been shown to have an effect for up to 5 days [Schwartz 2000] [Massimo 2013] and numbers of respiratory deaths appear to be more affected by air pollution levels on previous days, than cardiovascular deaths that are impacted by same-day pollution. [Braga et al 2001]. For example myocardial infarction represents an acute response to a trigger [Gold 2000]. ...
... For PM 10 , a single-day exposure has been shown to have an effect for up to 5 days 46 47 and numbers of respiratory deaths appear to be more affected by air pollution levels on previous days, than cardiovascular deaths that are impacted by same-day pollution. 48 For example, myocardial infarction represents an acute response to a trigger. 49 This is biologically plausible when considering how a wider and more lagged response can be expected for deaths from respiratory responses to pollution (eg, chronic obstructive pulmonary disease) via the proposed Open Access mechanisms, such as pulmonary or systemic inflammation and modulated immunity. ...
Objectives:
Air pollution has been associated with increased mortality and morbidity in several studies with indications that its effect could be more severe in children. This study examined the relationship between short-term variations in criteria air pollutants and occurrence of sudden infant death syndrome (SIDS).
Design:
We used a case-crossover study design which is widely applied in air pollution studies and particularly useful for estimating the risk of a rare acute outcome associated with short-term exposure.
Setting:
The study used data from the West Midlands region in the UK.
Participants:
We obtained daily time series data on SIDS mortality (ICD-9: 798.0 or ICD-10: R95) for the period 1996-2006 with a total of 211 SIDS events.
Primary outcome measures:
Daily counts of SIDS events.
Results:
For an IQR increase in previous day pollutant concentration, the percentage increases (95% CI) in SIDS were 16 (6 to 27) for PM10, 1 (-7 to 10) for SO2, 5 (-4 to 14) for CO, -17 (-27 to -6) for O3, 16 (2 to 31) for NO2 and 2 (-3 to 8) for NO after controlling for average temperature and national holidays. PM10 and NO2 showed relatively consistent association which persisted across different lag structures and after adjusting for copollutants.
Conclusions:
The results indicated ambient air pollutants, particularly PM10 and NO2, may show an association with increased SIDS mortality. Thus, future studies are recommended to understand possible mechanistic explanations on the role of air pollution on SIDS incidence and the ways in which we might reduce pollution exposure among infants.
... Since the concentration of PM could affect not only the mortality on the same day of exposure, but also the mortality on a few days after exposure, we considered lag effects in this study. Previous studies have found that the associations between mortality and PM were generally larger with lagged exposures than a single-day exposure (Braga et al., 2001;Zanobetti et al., 2002;Franklin et al., 2007;Dai et al., 2014). Therefore, we used 2-day moving averages in the study (lag01, cumulative exposures of the same day of exposure and the day after exposure). ...
While many epidemiological studies have examined the health effects of different sizes of ambient particulate matter (PM), the findings have been mixed. PM is a heterogeneous mixture, and its chemical components differ by size, with more combustion related materials in the fine mode and more crustal materials in the coarse mode. This study estimates the risk of mortality associated with exposure to PM2.5 (particulate matter less than 2.5 µm in aerodynamic diameter) and PM2.5-10 (particulate matter less than 10 µm and greater than 2.5 µm in aerodynamic diameter). Long-term measurements of PM2.5 and PM2.5-10 were compared with the all-cause, cardiovascular, and respiratory mortality observed from January 2006 till December 2012 in three large cities in Korea (viz., Seoul, Busan, and Incheon). A time-series analysis based on a quasi-Poisson distribution was used to evaluate the associations of PM2.5 and PM2.5-10 with mortality. A 10 µg m⁻³ increase in PM2.5 (lag01) was associated with an increase of 1.18% (95% CI: 0.64, 1.72), 0.34% (95% CI: 0.03, 0.64), and 0.43% (90% CI: 0.02, 0.95) in the all-cause mortality in Busan, Seoul, and Incheon, respectively, during the study period. An increase in respiratory mortality of 0.52% (95% CI: 0.09, 0.96) and 2.25% (95% CI: 0.38, 4.15) was associated with a 10 µg m–3 increase in PM2.5 (lag01) in Seoul and Busan, respectively. Overall, the strongest associations were observed in Busan as well as among the elderly population. Statistically significant associations between ambient PM2.5 and PM2.5-10, and mortality were observed in this study. Exposure to fine particles, which mostly originate in combustion and mobile emissions, showed stronger effects on human health than coarse particles, which mostly originate in natural sources such as soil and mechanical processes. © 2018, AAGR Aerosol and Air Quality Research. All rights reserved.
... Distributed-lag models have primarily been used in time-series studies of environmental exposures such as ambient air pollutants (22,(37)(38)(39). Recent studies have presented extensions of DLNMs beyond time-series designs, including survival data (17), as well as a penalized framework for DLNMs (23). ...
Prolonged exposures can have complex relationships with health outcomes, as timing, duration, and intensity of exposure are all potentially relevant. Summary measures such as cumulative exposure or average intensity of exposure may not fully capture these relationships. We applied penalized and unpenalized distributed lag non-linear models (DLNMs) with flexible exposure-response and lag-response functions in order to examine the association between crystalline silica exposure and mortality from lung cancer and non-malignant respiratory disease in a cohort study of 2,342 California diatomaceous earth workers, followed 1942-2011. We also assessed associations using simple measures of cumulative exposure assuming linear exposure-response and constant lag-response. Measures of association from DLNMs were generally higher than from simpler models. Rate ratios from penalized DLNMs corresponding to average daily exposures of 0.4 mg/m3 during lag years 31-50 prior to the age of observed cases were 1.47 (95% confidence interval (CI) 0.92, 2.35) for lung cancer and 1.80 (95% CI: 1.14, 2.85) for non-malignant respiratory disease. Rate ratios from the simpler models for the same exposure scenario were 1.15 (95% CI: 0.89-1.48) and 1.23 (95% CI: 1.03-1.46) respectively. Longitudinal cohort studies of prolonged exposures and chronic health outcomes should explore methods allowing for flexibility and non-linearities in the exposure-lag-response.
... Smoke exposure might not result in an immediate visit to the ED (Pope et al., 2008;Braga et al., 2001); as such we considered a window for ED visitation due to a single initial day of heavy smoke exposure. Rappold et al. (2011) employed a distributed lag model (Peng et al., 2009) to determine a 5-day lag period in which those who have been exposed to heavy smoke plumes may experience symptoms related to exposure. ...
The Great Dismal Swamp (GDS) National Wildlife Refuge delivers multiple ecosystem services, including air quality and human health via fire mitigation. Our analysis estimates benefits of this service through its potential to reduce catastrophic wildfire related impacts on the health of nearby human populations. We used a combination of high-frequency satellite data, ground sensors, and air quality indices to determine periods of public exposure to dense emissions from a wildfire within the GDS. We examined emergency department (ED) visitation in seven Virginia counties during these periods, applied measures of cumulative Relative Risk to derive the effects of wildfire smoke exposure on ED visitation rates, and estimated economic losses using regional Cost of Illness values established within the US Environmental Protection Agency BenMAP framework. Our results estimated the value of one avoided catastrophic wildfire in the refuge to be $3.69 million (2015 USD), or $306 per hectare of burn. Reducing the frequency or severity of extensive, deep burning peatland wildfire events has additional benefits not included in this estimate, including avoided costs related to fire suppression during a burn, carbon dioxide emissions, impacts to wildlife, and negative outcomes associated with recreation and regional tourism. We suggest the societal value of the public health benefits alone provides a significant incentive for refuge mangers to implement strategies that will reduce the severity of catastrophic wildfires.
Rheumatoid arthritis (RA) is an involving chronic systemic inflammatory disease which mainly affects the joints. Several factors including genetic, environment and infections have been acknowledged as being involved in the pathogenesis and aggravation of RA. Air pollution, particularly particulate matter is widely recognized as a cause of health problems. This review is to summarize and discuss the association between air pollutants and the development or the aggravation of RA based on evidence from in vitro, in vivo and clinical studies. The results from the review found that air pollutants can stimulate immunological processes and stimulate inflammatory mediators and autoantibodies productions, both in intro and in vivo studies. In addition, air pollutants can induce RA and aggravate RA disease activity. Unfortunately, there also are some discrepancies in the results, which might be due to the type cell line and the concentration of air pollutants used in the in vitro and in vivo studies, as well as the concentration and duration of exposure in human studies. These findings suggest that future studies focused on elucidating these mechanisms using advanced techniques and identifying reliable biomarkers to assess individual susceptibility and disease activity should be carried out. Longitudinal studies, intervention strategies, and policy implications also should be explored. A comprehensive understanding on these association will facilitate targeted approaches for prevention and management of air pollutant-induced RA and improve health outcome.
Background
Air pollution is a consequence of industrial development that is exacerbated as a result of population growth, and urbanisation.
Aim
The goal of the study is to investigate the effects of air pollution on the number of cases of acute myocardial infarction (AMI) according to gender using the Zero-inflated Poisson Regression model in Hamadan, Iran.
Methods
The study used an ecological design, and data collected from March 2016 to September 2020 in Hamadan were included. The intended response was the number of cases of AMI recorded in the investigated period. The time lag of the pollutants was used to investigate the effect of air pollution on the number of AMIs.
Results
The number of AMI recorded for men and women was 1,195 and 553, respectively. The average age (±SD) for men and women was 64.60 (±12.27) and 70.98 (±11.79) years, respectively. According to the air quality index in Hamadan, the values of particulate matter (PM)2.5, SO2, O3, and CO were below moderate levels. Also, according to NO2 and PM10, the air quality index of Hamadan was in the very unhealthy mode just for 2 and 3 days, respectively. The O3 and NO2 are significant positive effects on AMI among men. But, PM2.5, PM10, and SO2 are negative impacts on hospitalisation in men due to AMI. For women, PM2.5 and O3 had positive effects on AMI. But, NO2 and PM10 had a significant negative impact on hospitalisation in women during different time lags.
Conclusions
The results of the study showed that if the analyses are based on gender, the responses to pollutants are different and hence the stratified analysis is important.
ObjectThe association between ambient air pollution and several health conditions, including dermatologic disorders, has been heavily investigated. The mechanism involves an interplay of oxidative stress, inflammation and altered gene expression. Our study aims to investigate the association between air pollution and urticaria, an association not thoroughly investigated in the literature.Methods
Prospective data collection was performed during 2012 from emergency department (ED) medical records. Air pollution and meteorological data were obtained from Air Quality Research Unit stations situated close to each hospital. Stratification by age group was performed. Distributed lag model and generalized additive model analysis was performed. Relative risk (RR) and their 95% confidence intervals for ED visits diagnosed with urticaria associated with a 10-unit increase in PM2.5 and PM10 concentrations from reference value were calculated.ResultsStatistically significant associations were observed at lag 2 and lag 3 for individuals younger than 16 years of age. Statistically significant associations were not demonstrated for other age groups or at different lags.Conclusion
These findings demonstrate that air pollution is associated with increased risk of developing or experiencing manifestations of urticaria, particularly among children and adolescents.
The association between air pollution and infant mortality has been inconsistently reported. A few studies have estimated short-term effects of air pollution on infants’ health. This population-based case–control study aimed to examine the potential effects of air pollution on sudden infant death syndrome (SIDS) in the post-neonatal period in Taiwan during 1997–2002. Each case of infant death was matched with 20 randomly selected sex-matched controls who were born on the same day and were still alive. We obtained 24-h measurements of air pollutants and meteorological factors in each case and control with 1- to 14-day lags from 55 air-quality monitoring stations. After controlling for potential confounders, conditional logistic regression analysis was performed to estimate effects of air pollutants on SIDS (n=398) and respiratory death (n=121) among neonates. In single- and multi-pollutant models, we found that 100-ppb increment in carbon monoxide (Odds Ratio=1.04-1.07) and 10-ppb increment in nitrogen dioxide (Odds Ratio=1.20-1.35) with 1- to 14-day lags were associated with significant increase in SIDS, although a significant relationship between air pollution and respiratory death was not determined in 1- to 14-day lags. Short-term carbon monoxide and nitrogen dioxide exposure were associated with significant increase in SIDS in the post-neonatal period, with latency estimated within days before death.
Evidence for effects of PM2.5 on systemic oxidative stress in pregnant women is limited, especially in early pregnancy. To estimate the associations between ambient PM2.5 exposures and biomarkers of lipid peroxidation and total antioxidant capacity (T-AOC) in women with normal early pregnancy (NEP) and women with clinically recognized early pregnancy loss (CREPL), 206 early pregnant women who had measurements of serum malondialdehyde (MDA) and T-AOC were recruited from a larger case-control study in Tianjin, China from December 2017 to July 2018. Ambient PM2.5 concentrations of eight single-day lags exposure time windows before blood collection at the women’s residential addresses were estimated using temporally-adjusted land use regression models. Effects of PM2.5 exposures on percentage change in the biomarkers were estimated using multivariable linear regression models adjusted for month, temperature, relative humidity, gestational age and other covariates. Unconstrained distributed lag models were used to estimate net cumulative effects. Increased serum MDA and T-AOC were significantly associated with increases in PM2.5 at several lag exposure time windows in both groups. The net effects of each interquartile range increase in PM2.5 over the preceding 8 days on MDA were significantly higher (p < 0.001) in CREPL [52% (95% CI: 41%, 62%)] than NEP [22% (95% CI: 9%, 36%)] women. Net effects of each interquartile range increase in PM2.5 over the preceding 5 days on T-AOC were significantly lower (p = 0.010) in CREPL [14% (95% CI: 9%, 19%)] than NEP [24% (95% CI: 18%, 29%)] women. Exposure to ambient PM2.5 may induce systemic lipid peroxidation and antioxidant response in early pregnant women. More severe lipid peroxidation and insufficient antioxidant capacity associated with PM2.5 was found in CREPL women than NEP women. Future studies should focus on mechanisms of individual susceptibility and interventions to reduce PM2.5-related oxidative stress in the first trimester.
PurposeShort-term exposure to outdoor air pollution has been positively associated with numerous measures of acute morbidity and mortality, most consistently as excess cardiorespiratory disease associated with fine particulate matter (PM2.5), particularly in vulnerable populations. It is unknown if the critically ill, a vulnerable population with high levels of cardiorespiratory disease, is affected by air pollution.Methods
We performed a time series analysis of emergency cardiorespiratory, stroke and sepsis intensive care (ICU) admissions for the years 2008–2016, using data from the Australian and New Zealand Intensive Care Society Adult Patient Database (ANZICS-APD). Case-crossover analysis was conducted to assess the relationship between air pollution and the frequency and severity of ICU admissions having adjusted for temperature, humidity, public holidays and influenza activity.Results46,965 episodes in 87 separate ICUs were analysed. We found no statistically significant associations with admission counts. However, ICU admissions ending in death within 30 days were significantly positively associated with short-term exposure to PM2.5 [RR 1.18, 95% confidence interval (CI) 1.02–1.37, per 10 µg/m3 increase]. This association was more pronounced in those aged 65 and over (RR 1.33, 95% CI 1.11–1.58, per 10 µg/m3).Conclusions
Increased ICU mortality was associated with higher levels of PM2.5. Larger studies are required to determine if the frequency of ICU admissions is positively associated with short-term exposure to air pollution.
Background: The aim of this study was to evaluate and summarize the short-term effects of air pollutants exposure (O3, CO, NO2, SO2, PM10, PM2.5) on chronic obstructive pulmonary disease (COPD) using the meta-analysis approach.
Methods: Eight databases were searched by keywords on air pollutions and COPD risk. Based on the criteria [near-term exposure (0-7days) to the air pollutants and subsequent COPD risk], eligible studies were selected and evaluated. Pooled relative risks (RRs) and 95% confidence intervals (95% CIs) were estimated by random-effects model. The population attributable fractions (PAFs) were estimated. Publication bias and heterogeneity (I2) were tested by subgroup and meta-regression analysis respectively. Sensitivity and categorial analyses by national income were also performed.
Results: 60 studies were included based on the selection criteria. Under single-pollutant model, the risk of COPD mortality or hospitalization was associated with increases in pollutant concentrations (RR 95%CIs; I2): CO (1.01, 1.00-1.01; 97.0%); NO2 (1.04, 1.03-1.06; 98.0%); SO2 (1.01, 1.01-1.01; 80.8%); O3 (1.03, 1.01-1.04; 98.8%); PM2.5 (1.02, 1.01-1.04; 97.1%); PM10 (1.02, 1.01-1.02; 86.6%). Subgroup analysis provided similar trend as above. Study design might be the source of heterogeneity through meta-regression analysis. Publication bias was observed in air pollutants of SO2, O3 and PM10 by Egger’s test, but not in CO (P=0.187), NO2 (P=0.147) and PM2.5 (P=0.447). Besides, the categorial analysis showed that short-term SO2 and NO2 exposure had stronger associations with COPD hospitalization or mortality in developing countries SO2 [1.034 (1.012-1.096)] and NO2 [1.019(1.014-1.024)].
Conclusion: Short-term exposure to air pollutants have significant impacts on COPD mortality or hospital admission, which contribute to socioeconomic burden. This remains a key priority in public health research.
In recent decades, several national and international legislative efforts have aimed to improve air quality standards and limit major
pollutants, such as carbon monoxide, sulfur dioxide, and nitrogen dioxide, linked to several public health problems. In recent
years, particulate matter sources have become an important cause of several pulmonary and systemic diseases. Specifically,
several studies examining cigarette smoke particulates have discovered the important contribution that mast cells play in the
pathogenesis and progression of smoking-related lung disease and other particulate matter–related lung injury. By understanding
the mechanisms of activation and signaling cascades involved in cigarette smoke and mast cell activation, novel pharmacological
therapies for particulate matter–induced lung diseases could be developed.
It is generally acknowledged that claims from observational studies often fail to replicate. An exploratory study was undertaken to assess the reliability of base studies used in meta-analysis of short-term air quality-myocardial infarction risk and to judge the reliability of statistical evidence from meta-analysis that uses data from observational studies. A highly cited meta-analysis paper examining whether short-term air quality exposure triggers myocardial infarction was evaluated as a case study. The paper considered six air quality components - carbon monoxide, nitrogen dioxide, sulphur dioxide, particulate matter 10 μm and 2.5 μm in diameter (PM10 and PM2.5), and ozone. The number of possible questions and statistical models at issue in each of 34 base papers used were estimated and p-value plots for each of the air components were constructed to evaluate the effect heterogeneity of p-values used from the base papers. Analysis search spaces (number of statistical tests possible) in the base papers were large, median = 12,288 (interquartile range = 2496 − 58,368), in comparison to actual statistical test results presented. Statistical test results taken from the base papers may not provide unbiased measures of effect for meta-analysis. Shapes of p-value plots for the six air components were consistent with the possibility of analysis manipulation to obtain small p-values in several base papers. Results suggest the appearance of heterogeneous, researcher-generated p-values used in the meta-analysis rather than unbiased evidence of real effects for air quality. We conclude that this meta-analysis does not provide reliable evidence for an association of air quality components with myocardial risk.
https://www.publichealth.ie/sites/default/files/documents/files/Fuel%20Poverty%20Report%20December%202011.pdf
Objective:
Air pollution is considered one of the most important risk factors for ischemic heart disease (IHD), which is a major public health concern. The disease burden of IHD has continued to rise in China in the past two decades. However, epidemiological studies examining the associations between air pollution and IHD have been scarce in China, and the only studies were conducted in severe air pollution areas, where air pollution levels seriously exceed the World Health Organization Air Quality Guidelines. Whether the influence of air pollution on IHD in areas with relatively low levels of air pollution differs from the influence of high pollution levels in heavily studied areas was unknown until now. Furthermore, the estimation of the disease burden of IHD related to air pollution has been very limited.
Methods:
We conducted a time-series study to estimate the short-term burden of ambient air pollution on IHD using the indicator of years of life lost (YLL), based on 10 322 IHD deaths from 2011 to 2015 in Ningbo, a coastal city in South China.
Results:
The mean concentrations of fine particle (PM2.5), sulfur dioxide (SO2) and nitrogen dioxide (NO2) were 49.58 μg/m3, 21.34 μg/m3and 43.41 μg/m3, respectively. A 10 μg/m3increase in PM2.5, SO2and NO2was associated with changes in YLL of 0.71 (95%CI: - 0.21,1.64), 3.31 (95%CI: 0.78, 5.84), and 2.27 (95%CI: 0.26, 4.28) years, respectively. Relatively stronger impacts were found for gaseous pollutants than PM2.5. A larger increase in YLL was found in the younger population than in the older population for NO2exposure. In addition, estimations of the effects of SO2and NO2on YLL were higher for males than females. SO2exposure was positively associated with YLL in widowed group.
Conclusions:
The findings highlighted the importance of stringent air pollution control, especially for gaseous pollutants. Furthermore, using the indicator of YLL, considering the occurrence of death at different ages, provided more information for resource allocation and protection of vulnerable populations.
Objective: To test the efficacy of a graded aerobic exercise programme in the chronic fatigue syndrome. Design: Randomised controlled trial with control treatment crossover after the first follow up examination. Setting: Chronic fatigue clinic in a general hospital department of psychiatry.
Air pollution episodes have been associated with increased cardiovascular hospital admissions and mortality in time-series studies. We tested the hypothesis that patients with implanted cardioverter defibrillators experience potentially life-threatening arrhythmias after such air pollution episodes. We compared defibrillator discharge interventions among 100 patients with such devices in eastern Massachusetts, according to variations in concentrations of particulate matter, black carbon, and gaseous air pollutants that were measured daily for the years 1995 through 1997. A 26-ppb increase in nitrogen dioxide was associated with increased defibrillator interventions 2 days later (odds ratio = 1.8; 95% confidence interval = 1.1-2.9). Patients with ten or more interventions experienced increased arrhythmias in association with nitrogen dioxide, carbon monoxide, black carbon, and fine particle mass. These results suggest that elevated levels air pollutants are associated with potentially life-threatening arrhythmia leading to therapeutic interventions by an implanted cardioverter defibrillator.
Cause-specific deaths by day for the years 1973 to 1980 in Philadelphia, Pennsylvania, were extracted from National Center for Health Statistics mortality tapes. Death from accidents (International Classification of Disease, Revision 9 greater than or equal to 800) and deaths outside of the city were excluded. Daily counts of deaths were regressed using Poisson regression on total suspended particulate (TSP) and/or SO2 on the same day and on the preceding day, controlling for year, season, temperature, and humidity. A significant positive association was found between total mortality (mean of 48 deaths/day) and both TSP (second highest daily mean, 222 micrograms/m3) and SO2 (second highest daily mean, 299 micrograms/m3). The strongest associations were found with the mean pollution of the current and the preceding days. Total mortality was estimated to increase by 7% (95% CI, 4 to 10%) with each 100-micrograms/m3 increase in TSP, and 5% (95% CI, 3 to 7%) with each 100-micrograms/m3 increase in SO2. When both pollutants were considered simultaneously, the SO2 association was no longer significant. Mortality increased monotonically with TSP. The effect of 100 micrograms/m3 TSP was stronger in subjects older than 65 yr of age (10% increase) compared with those younger than 65 yr of age (3% increase). Cause-specific mortality was also associated with a 100-micrograms/m3 increase in TSP: chronic obstructive pulmonary disease (ICD9 490-496), +19% (95% CI, 0 to 42%), pneumonia (ICD9 480-486 & 507), +11% (95% CI, -3 to +27%), and cardiovascular disease (ICD9 390-448), +10% (95% CI, 6 to 14%). These results are somewhat higher than previously reported associations, and they add to the body of evidence showing that particulate pollution is associated with increased daily mortality at current levels in the United States.
The relationship between daily mortality of elderly (65+ y) persons and air pollution in the metropolitan area of Sao Paulo, Brazil, for the period May 1990 to April 1991 was evaluated by time series regression, controlling for season, weather, and other factors. Mortality was associated with respirable particles (PM10), nitrogen oxides (NOx), sulfur dioxide (SO2), and carbon monoxide (CO). The association with PM10 was most statistically significant, robust, and independent of other air pollutants. An increase in PM10 equal to 100 micrograms/m3 was associated with an increase in overall mortality equal to approximately 13%. This association was consistent across various model specifications and estimation techniques. The dose-response relationship between mortality and respirable particulate pollution was almost linear, with no evidence of a "safe" threshold level. The results were similar to those observed in London and several U.S. cities. The results were also supportive of recent animal studies that have observed adverse health outcomes in experimental animals exposed to air pollution in Sao Paulo.
The association between daily variations in all-cause mortality from 1983-1991 in Rotterdam, the Netherlands, and ambient air pollution was investigated. Twenty-four-hour average concentrations of total suspended particulates, Black Smoke, ozone, sulfur dioxide, and carbon monoxide were available on a daily basis. Every other day, total iron content in total suspended particulates samples was available. Poisson regression analysis was used to study associations between air pollution and mortality; generalized additive models were used to adjust for confounders (e.g., seasonal trends, weather). Daily mortality was associated most consistently with previous-day concentrations of total suspended particulates (relative risk = 1.05 for a change of 91 microg/m3) and ozone (relative risk = 1.06 for a change of 67 microg/m3). Total iron was associated less consistently with mortality than total suspended particulate mass was. The associations of mortality with ozone and total suspended particulates were independent of sulfur dioxide and carbon monoxide. The relative risks of total suspended particulates and particularly ozone were higher for subjects older than 78 y. The relationship between mortality and ozone did not deviate significantly from linear. The relationship between mortality and total suspended particulates was linear below 100 microg/m3 and leveled off at higher concentrations. If a threshold exists for the effects on mortality of these components, it exists at very low levels.
In several studies, investigators have reported associations among air pollution, weather, and daily deaths, usually from all causes. In the current study, we focused on the difference in lag time between exposure to total suspended particulates or extreme weather and cause-specific mortality in an effort to understand the potential underlying mechanism. We used a robust Poisson regression in a generalized additive model to investigate the association between air pollution and daily mortality. We used a loess smooth function to model season, weather, and humidity; indicator variables for hot days were also used. To examine the relationship in a currently meaningful range, we excluded all days with a total suspended particulate concentration higher than 200 microg/m3. We found a significant association on the concurrent day, both for respiratory infection deaths (11% increase/100 microg/m3 increase in total suspended particulate; 95% confidence interval = 5, 17) and for heart-failure deaths (7% increase; 95% confidence interval = 3, 11). The associations with myocardial infarction (i.e., 10% increase; 95% confidence interval = 3, 18) and chronic obstructive pulmonary disease (12% increase, 95% confidence interval = 6, 17) were found for the means of 3 and 4 d prior to death. We observed an effect of cold weather at lag 1 for respiratory infections and an effect of hot weather at lag 0 for heart failure and myocardial infarctions. The association for all causes and cause-specific deaths was almost identical to that noted previously in Philadelphia, Pennsylvania. Smoothed functions of total suspended particulates suggested a higher slope at lower concentrations, and this finding may account for differences noted between European and U.S. studies. Given that both the dependence between weather and daily mortality and the lag between exposure and death varies by cause of death, analyses by specific causes of death would be very useful in the future.
We investigated associations between ambient pollution levels and cardiovascular function in a repeated measures study including 163 observations on twenty-one 53- to 87-year-old active Boston residents observed up to 12 times from June to September 1997. Particles with aerodynamic diameter </=2.5 microm (PM(2.5)) were measured continuously using a tapered element oscillating microbalance.
The protocol involved 25 minutes per week of continuous Holter ECG monitoring, including 5 minutes of rest, 5 minutes of standing, 5 minutes of exercise outdoors, 5 minutes of recovery, and 20 cycles of slow breathing. Heart rate variability (HRV) was assessed through time domain variables: the standard deviation of normal RR intervals (SDNN) and the square root of the mean of the squared differences between adjacent normal RR intervals (r-MSSD). Mean 4-hour PM(2.5) levels ranged from 3 to 49 microg/m(3); 1-hour ozone levels ranged from 1 to 77 ppb. In multivariate analyses, significantly less HRV (SDNN and r-MSSD) was associated with elevated PM(2.5). During slow breathing, a reduction in r-MSSD of 6.1 ms was associated with an interquartile (14.3 microg/m(3)) increase in PM(2.5) during the hour of and the 3 hours previous to the Holter session (P=0.006). During slow breathing, a multiple pollution model was associated with a reduction in r-MSSD of 5.4 ms (P=0.02) and 5.5 ms (P=0.03) for interquartile changes in PM(2.5) and ozone, respectively, resulting in a combined effect equivalent to a 33% reduction in the mean r-MSSD.
Particle and ozone exposure may decrease vagal tone, resulting in reduced HRV.
I examined the relationship between daily deaths and airborne particles in 10 U.S. cities with varying climatic conditions and seasons in which particle concentrations were high. Airborne particles were associated with significant increases in daily deaths [0.67% increase for a 10 microg/m(3) increase in particles; 95% confidence interval (CI), 0.52-0.81%]. This association was the same in summer and winter. To examine potential confounding by other pollutants, I regressed city- and season-specific effect sizes against the relationship between airborne particles and other pollutants. Controlling for other pollutants did not substantially (or significantly) change the estimated effect of airborne particles. Socioeconomic differences between cities likewise did not modify the effect. The increase in daily deaths that occurred out of hospitals (0.89% per 10 microg/m(3); CI, 0.67-1.10%) was substantially greater than the increase in deaths in hospitals (0. 49%; CI, 0.31-0.68%). This is consistent with results previously reported in Philadelphia, Pennsylvania, and suggests that the particle-associated deaths are not just being brought forward by a few days. It is also consistent with recent animal and human studies of the mechanisms of particle toxicity.
We tested the hypothesis that exposure of healthy volunteers to concentrated ambient particles (CAPS) is associated with an influx of inflammatory cells into the lower respiratory tract. Thirty-eight volunteers were exposed to either filtered air or particles concentrated from the immediate environment of the Environmental Protection Agency (EPA) Human Studies Facility in Chapel Hill, North Carolina. Particle concentrations in the chamber during the exposures ranged from 23.1 to 311.1 microgram/m(3). While in the exposure chamber, volunteers alternated between moderate exercise (15 min) and rest (15 min) for a total exposure time of 2 h. There were no symptoms noted by volunteers after the exposure. Similarly, there were no decrements in pulmonary function. Eighteen hours after exposure, analysis of cells and fluid obtained by bronchoalveolar lavage showed a mild increase in neutrophils in both the bronchial and alveolar fractions in those individuals exposed to CAPS (8.44 +/- 1.99 and 4.20 +/- 1.69%, respectively, in those with the greatest exposure) relative to filtered air (2.69 +/- 0.55 and 0.75 +/- 0.28%, respectively). Blood obtained 18 h after exposure to CAPS contained significantly more fibrinogen relative to samples obtained before exposure. We conclude that ambient air particles are capable of inducing a mild inflammation in the lower respiratory tract, as well as an increased concentration of blood fibrinogen.
The relation between air pollution and mortality in London was examined for the winters of 1958–1972. The data exhibited a high degree of autocorrelation, requiring analyses using autoregressive models. There was a highly significant relation between mortality and either particulate matter or sulfur dioxide (after controlling for temperature and humidity), both overall and in each individual year. Graphic analysis revealed a nonlinear relation with no threshold, and a steeper exposure-response curve at lower air pollution levels. in models with both pollutants, particulate matter remained a significant predictor with about a 10% reduction in its estimated coefficients, while sulfur dioxide was insignificant, with a large drop in its estimated coefficient The authors conclude that particulates are strongly associated with mortality rates in London, and the relation is likely causal.
Environmental epidemiologists often encounter time series data in the form of discrete or other nonnormal outcomes; for example, in modeling the relationship between air pollution and hospital admissions or mortality rates. We present a case study examining the association between pollen counts and meteorologic covariates. Although such time series data are inadequately described by standard methods for Gaussian time series, they are often autocorrelated, and warrant an analysis beyond those provided by ordinary generalized linear models (GLMs). Transitional regression models (TRMs), signifying nonlinear regression models expressed in terms of conditional means and variances given past observations, provide a unifying framework for two mainstream approaches to extending the GLM for autocorrelated data. The first approach models current outcomes with a GLM that incorporates past outcomes as covariates, whereas the second models individual outcomes with marginal GLMs and then couples the error terms with an autoregressive covariance matrix. Although the two approaches coincide for the Gaussian GLM, which serves as a helpful introductory example, in general they yield fundamentally different models. We analyze the pollen study using TRM's of both types and present parameter estimates together with asymptotic and bootstrap standard errors. In several cases we find evidence of residual autocorrelation; however, when we relax the TRM to allow for a nonparametric smooth trend, the autocorrelation disappears. This kind of trade-off between autocorrelation and flexibility is to be expected, and has a natural interpretation in terms of the covariance function for a nonparametric smoother. We provide an algorithm for fitting these flexible TRM's that is relatively easy to program with the generalized additive model software in S-PLUS.
Athens has a serious air pollution problem which became evident in the early 1970s. Studies for the years 1975-1982 have indicated a positive association of sulphur dioxide (SO2) with total daily mortality. Since 1983 the pollution profile in Athens has gradually changed but the levels of smoke, SO2 and carbon monoxide (CO) remain relatively high.
The association of air pollution with daily all-cause mortality in Athens for the years 1984-1988 was investigated using daily values of SO2, smoke and CO. Autoregressive models with log-transformed daily mortality as the dependent variable, were used to adjust for temperature and relative humidity (both lagged by 1 day), year, season and day of week, as well as for serial correlations in mortality.
Graphic analysis revealed non-linear monotonically increasing relationships between total mortality and SO2, smoke and CO, with steeper exposure-response slopes at lower air pollution levels. Air pollution data lagged by 1 day had the strongest association with daily mortality. In three separate autoregression models for log(SO2), log(smoke) and log(CO) the regression coefficients for each were highly statistically significant (P < 0.001). Further multiple regression modelling showed that SO2 and smoke are both independent predictors of daily mortality, though to a lesser extent than temperature and relative humidity. The inclusion of CO in the model did not further improve the prediction of daily mortality. The magnitude of association is small, for instance, a 10% reduction in smoke is estimated to decrease daily mortality by 0.75% (95% confidence interval [CI]: 0.51-0.99). However, it cannot be accounted for by climatic and seasonal effects, so that a causal influence of air pollution on daily mortality seems plausible.
These findings suggest that current air pollution levels in Athens (and many other industrialized cities) may be responsible for substantial numbers of premature deaths, and hence remain an important public health issue.
Several recent studies have reported associations between short-term changes in air pollution and respiratory hospital admissions. Most of those studies analyzed locations where there was a high correlation between airborne particles and sulfur dioxide (SO2), and between all air pollutants and temperature. Here, I seek to replicate the previous findings in a location where SO2 concentrations were trivial, and the correlation between both airborne particles and ozone with temperature was considerably lower than in previous studies. I constructed daily counts of admissions to all hospitals in Spokane, WA, for respiratory disease (International Classification of Diseases, 9th revision, codes 460-519) for persons age 65 years and older. I computed average daily concentrations of airborne particles whose diameter is 10 microns or less (PM10) and ozone (O3) from all monitors in each city, and I obtained daily average temperature and humidity from the U.S. weather service. SO2 concentrations in Spokane were so low that monitoring was discontinued. I regressed daily respiratory admission counts on temperature, humidity, day of the week indicators, and air pollution. I used a Poisson regression analysis and removed long wavelength patterns using a nonparametric smooth function of day of study. I dealt with a possible U-shaped dependence of admissions on temperature and/or humidity by using nonparametric smooth functions of weather variables as well. I then examined sensitivity analyses to control for weather. Both PM10 and ozone were associated with increased risk of respiratory hospital admissions [relative risk (RR) = 1.085; 95% confidence interval (CI) = 1.036-1.136 for a 50-microgram per m3 increase in PM10, and RR = 1.244; 95% CI = 1.002-1.544 for a 50-microgram per m3 increase in peak-hour ozone]. The PM10 association was insensitive to alternative methods of control for weather, including exclusion of extreme temperature days and control for temperature on multiple days. The ozone results were more sensitive to the approach for weather control. The magnitude of the PM10 effect in this location, where SO2 was essentially not present, and where the correlation between PM10 and temperature was close to zero, was similar to that reported in other locations in the eastern United States and Europe, where confounding by weather and SO2 is a more substantial concern.
Analyses involving data from many locations throughout the world have now been conducted to assess the association between
air pollution and mortality. To date, six independent analyses of mortality data for Philadelphia, Pennsylvania, have been
reported. In this new analysis of Philadelphia data for 1974–1988, Poisson regression models were developed to estimate the
increased risk of daily mortality associated with air pollution while controlling for longer-term time trends and season and
for weather. Model development was based on prior understanding of the effects of these factors on mortality and on consideration
of model fit. The authors found moderate correlations of daily concentrations of total suspended particles (TSP), sulfur dioxide
(SO2), nitrogen dioxide (NO2), and carbon monoxide (CO), and only slight correlations of ozone (O3) with other pollutants. When included individually in the model, the means of current and previous days' levels of TSP, SO2 and O3 had statistically significant effects on total mortality; pollutant increases of an interquartile range (34.5 μg/m3 12.9 ppb, and 20.2 ppb, respectively) were associated with increases in mortality of around 1% for TSP and SO2 and of around 2% for O3. The effects of TSP and SO2 were diminished when both pollutants were simultaneously included in the model, whether pairwise or in the full multi-pollutant
model. These analyses confirm the association between TSP and mortality found in previous studies in Philadelphia and show
that the association is robust to consideration of other pollutants in the model.
This study examines the consistency of the association between particulate matter less than 10 microm in aerodynamic diameter (PM10), carbon monoxide (CO), and hospital admissions for cardiovascular disease across eight urban counties with different levels of correlation between pollutants and between the pollutants and weather. I fit Poisson regression models controlling for day-of-week effects and using nonparametric smoothing to control for season and weather. Daily variation in PM10 was associated with hospital admissions for heart disease in the elderly (2.48% increase, for an interquartile range increase in exposure; 95% confidence limits = 1.82%, 3.15%). Daily variation in CO was also associated with admissions (2.79% increase, for an interquartile range (1.75 parts per million) increase in exposure; 95% confidence limits = 1.89%, 3.68%). These associations held in both humid and dry locations and were independent of the correlation between the pollutants and weather or other pollutants. The effect size estimates for PM10 and CO likewise showed no association with their correlation in each location, as one would expect if one pollutant were merely a proxy for the other. The PM10 effects are consistent with recent animal data showing cardiovascular effects and with preliminary human data showing effects on heart rate variability and plasma viscosity. The CO results are consistent with literature on angina exacerbations.
Many studies have reported associations between air pollution and daily deaths. Those studies have not consistently specified the lag between exposure and response, although most have found associations that persisted for more than 1 day. A systematic approach to specifying the lag association would allow better comparison across sites and give insight into the nature of the relation. To examine this question, I fit unconstrained and constrained distributed lag relations to the association between daily deaths of persons 65 years of age and older with PM10 in 10 U.S. cities (New Haven, Birmingham, Pittsburgh, Canton, Detroit, Chicago, Minneapolis, Colorado Springs, Spokane, and Seattle) that had daily monitoring for PM10. After control for temperature, humidity, barometric pressure, day of the week, and seasonal patterns, I found evidence in each city that the effect of a single day's exposure to PM10 was manifested across several days. Averaging over the 10 cities, the overall effect of an increase in exposure of 10 microg/m3 on a single day was a 1.4% increase in deaths (95% confidence intervals (CI) = 1.15-1.68) using a quadratic distributed lag model, and a 1.3% increase (95% CI = 1.04-1.56) using an unconstrained distributed lag model. In contrast, constraining the model to assume the effect all occurs in one day resulted in an estimate of only 0.65% (95% CI = 0.49-0.81), indicating that this constraint leads to a substantial underestimate of effect. Combining the estimated effect at each day's lag across the 10 cities showed that the effect was spread over several days and did not reach zero until 5 days after the exposure. Given the distribution of sensitivities likely in the general population, this result is biologically plausible. I also found a protective effect of barometric pressure in all 10 locations.
- Cleveland