Long-term exposure to ambient air pollution and risk of lung cancer - A comparative analysis of incidence and mortality in four administrative cohorts in the ELAPSE study.

BACKGROUND: Studies have linked air pollution to lung cancer incidence and mortality, but few have compared these associations, which may differ due to cancer survival variations. We aimed to evaluate the association between long-term air pollution exposure and lung cancer incidence and compare findings with previous lung cancer mortality analyses within the same cohorts. METHODS: We analyzed four population-based administrative cohorts in Denmark (2000-2015), England (2011-2017), Norway (2001-2016) and Rome (2001-2015). We assessed residential exposure to annual average fine particulate matter (PM2.5), nitrogen dioxide (NO2), black carbon (BC), and warm-season ozone (O3) using Europe-wide land use regression models. We used Cox proportional hazard models to evaluate cohort-specific hazard ratios (HRs) and 95% confidence intervals (CIs) for lung cancer incidence identified using hospital admission records (English and Roman cohorts) or cancer registries (Danish and Norwegian cohorts). We evaluated the associations at low exposure levels using subset analyses and natural cubic splines. Cohort-specific HRs were pooled using random-effects meta-analyses, separately for incidence and mortality. RESULTS: Over 93,733,929 person-years of follow-up, 111,949 incident lung cancer cases occurred. Incident lung cancer was positively associated with PM2.5, NO2 and BC, and negatively associated with O3. The negative O3 association became positive after adjustment for NO2. Associations were almost identical or slightly stronger for lung cancer incidence than mortality in the same cohorts, with respective meta-analytic HRs (95% CIs) of 1.14 (1.06, 1.22) and 1.12 (1.02, 1.22) per 5 µg/m3 increase in PM2.5, and 1.10 (1.04, 1.16) and 1.09 (1.02, 1.16) per 10 µg/m3 increase in NO2. Positive associations persisted for both incidence and mortality at low pollution levels with similar magnitude. CONCLUSIONS: We found similarly elevated risks of lung cancer incidence and mortality in association with residential exposure to PM2.5, NO2 and BC in meta-analyses of four European administrative cohorts, which persisted at low pollution levels.

Long-term exposure to elemental components of fine particulate matter and all-natural and cause-specific mortality in a Danish nationwide administrative cohort study.

BACKGROUND: Fine particulate matter (PM2.5) is a well-recognized risk factor for premature death. However, evidence on which PM2.5 components are most relevant is unclear. METHODS: We evaluated the associations between mortality and long-term exposure to eight PM2.5 elemental components [copper (Cu), iron (Fe), zinc (Zn), sulfur (S), nickel (Ni), vanadium (V), silicon (Si), and potassium (K)]. Studied outcomes included death from diabetes, chronic kidney disease (CKD), dementia, and psychiatric disorders as well as all-natural causes, cardiovascular disease (CVD), respiratory diseases (RD), and lung cancer. We followed all residents in Denmark (aged ≥30 years) from January 1, 2000 to December 31, 2017. We used European-wide land-use regression models at a 100 × 100 m scale to estimate the residential annual mean levels of exposure to PM2.5 components. The models were developed with supervised linear regression (SLR) and random forest (RF). The associations were evaluated by Cox proportional hazard models adjusting for individual- and area-level socioeconomic factors and total PM2.5 mass. RESULTS: Of 3,081,244 individuals, we observed 803,373 death from natural causes during follow-up. We found significant positive associations between all-natural mortality with Si and K from both exposure modeling approaches (hazard ratios; 95% confidence intervals per interquartile range increase): SLR-Si (1.04; 1.03-1.05), RF-Si (1.01; 1.00-1.02), SLR-K (1.03; 1.02-1.04), and RF-K (1.06; 1.05-1.07). Strong associations of K and Si were detected with most causes of mortality except CKD and K, and diabetes and Si (the strongest associations for psychiatric disorders mortality). In addition, Fe was relevant for mortality from RD, lung cancer, CKD, and psychiatric disorders; Zn with mortality from CKD, RD, and lung cancer, and; Ni and V with lung cancer mortality. CONCLUSIONS: We present novel results of the relevance of different PM2.5 components for different causes of death, with K and Si seeming to be most consistently associated with mortality in Denmark.

Association between exposure to multiple air pollutants, transportation noise and cause-specific mortality in adults in Switzerland.

BACKGROUND: Long-term exposure to air pollution and noise is detrimental to health; but studies that evaluated both remain limited. This study explores associations with natural and cause-specific mortality for a range of air pollutants and transportation noise. METHODS: Over 4 million adults in Switzerland were followed from 2000 to 2014. Exposure to PM2.5, PM2.5 components (Cu, Fe, S and Zn), NO2, black carbon (BC) and ozone (O3) from European models, and transportation noise from source-specific Swiss models, were assigned at baseline home addresses. Cox proportional hazards models, adjusted for individual and area-level covariates, were used to evaluate associations with each exposure and death from natural, cardiovascular (CVD) or non-malignant respiratory disease. Analyses included single and two exposure models, and subset analysis to study lower exposure ranges. RESULTS: During follow-up, 661,534 individuals died of natural causes (36.6% CVD, 6.6% respiratory). All exposures including the PM2.5 components were associated with natural mortality, with hazard ratios (95% confidence intervals) of 1.026 (1.015, 1.038) per 5 µg/m3 PM2.5, 1.050 (1.041, 1.059) per 10 µg/m3 NO2, 1.057 (1.048, 1.067) per 0.5 × 10-5/m BC and 1.045 (1.040, 1.049) per 10 dB Lden total transportation noise. NO2, BC, Cu, Fe and noise were consistently associated with CVD and respiratory mortality, whereas PM2.5 was only associated with CVD mortality. Natural mortality associations persisted < 20 µg/m3 for PM2.5 and NO2, < 1.5 10-5/m BC and < 53 dB Lden total transportation noise. The O3 association was inverse for all outcomes. Including noise attenuated all outcome associations, though many remained significant. Across outcomes, noise was robust to adjustment to air pollutants (e.g. natural mortality 1.037 (1.033, 1.042) per 10 dB Lden total transportation noise, after including BC). CONCLUSION: Long-term exposure to air pollution and transportation noise in Switzerland contribute to premature mortality. Considering co-exposures revealed the importance of local traffic-related pollutants such as NO2, BC and transportation noise.

Screening patients for unintentional carbon monoxide exposure in the Emergency Department: a cross-sectional multi-centre study.

BACKGROUND: Low-level exposure to carbon monoxide (CO) is a significant health concern but is difficult to diagnose. This main study aim was to establish the prevalence of low-level CO poisoning in Emergency Department (ED) patients. METHODS: A prospective cross-sectional study of patients with symptoms of CO exposure was conducted in four UK EDs between December 2018 and March 2020. Data on symptoms, a CO screening tool and carboxyhaemoglobin were collected. An investigation of participants' homes was undertaken to identify sources of CO exposure. RESULTS: Based on an ED assessment of 4175 participants, the prevalence of suspected CO exposure was 0.62% (95% CI; 0.41-0.91%). CO testing in homes confirmed 1 case of CO presence and 21 probable cases. Normal levels of carboxyhaemoglobin were found in 19 cases of probable exposure and in the confirmed case. CONCLUSION: This study provides evidence that ED patients with symptoms suggestive of CO poisoning but no history of CO exposure are at risk from CO poisoning. The findings suggest components of the CO screening tool may be an indicator of CO exposure over and above elevated COHb. Clinicians should have a high index of suspicion for CO exposure so that this important diagnosis is not missed.

Long-term exposure to low-level air pollution and incidence of asthma: the ELAPSE project.

BACKGROUND: Long-term exposure to ambient air pollution has been linked to childhood-onset asthma, although evidence is still insufficient. Within the multicentre project Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE), we examined the associations of long-term exposures to particulate matter with a diameter <2.5 µm (PM2.5), nitrogen dioxide (NO2) and black carbon (BC) with asthma incidence in adults. METHODS: We pooled data from three cohorts in Denmark and Sweden with information on asthma hospital diagnoses. The average concentrations of air pollutants in 2010 were modelled by hybrid land-use regression models at participants' baseline residential addresses. Associations of air pollution exposures with asthma incidence were explored with Cox proportional hazard models, adjusting for potential confounders. RESULTS: Of 98 326 participants, 1965 developed asthma during a mean follow-up of 16.6 years. We observed associations in fully adjusted models with hazard ratios of 1.22 (95% CI 1.04-1.43) per 5 µg·m-3 for PM2.5, 1.17 (95% CI 1.10-1.25) per 10 µg·m-3 for NO2 and 1.15 (95% CI 1.08-1.23) per 0.5×10-5 m-1 for BC. Hazard ratios were larger in cohort subsets with exposure levels below the European Union and US limit values and possibly World Health Organization guidelines for PM2.5 and NO2. NO2 and BC estimates remained unchanged in two-pollutant models with PM2.5, whereas PM2.5 estimates were attenuated to unity. The concentration-response curves showed no evidence of a threshold. CONCLUSIONS: Long-term exposure to air pollution, especially from fossil fuel combustion sources such as motorised traffic, was associated with adult-onset asthma, even at levels below the current limit values.

Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter.

Exposure to ambient fine particulate matter (PM2.5) is a major global health concern. Quantitative estimates of attributable mortality are based on disease-specific hazard ratio models that incorporate risk information from multiple PM2.5 sources (outdoor and indoor air pollution from use of solid fuels and secondhand and active smoking), requiring assumptions about equivalent exposure and toxicity. We relax these contentious assumptions by constructing a PM2.5-mortality hazard ratio function based only on cohort studies of outdoor air pollution that covers the global exposure range. We modeled the shape of the association between PM2.5 and nonaccidental mortality using data from 41 cohorts from 16 countries-the Global Exposure Mortality Model (GEMM). We then constructed GEMMs for five specific causes of death examined by the global burden of disease (GBD). The GEMM predicts 8.9 million [95% confidence interval (CI): 7.5-10.3] deaths in 2015, a figure 30% larger than that predicted by the sum of deaths among the five specific causes (6.9; 95% CI: 4.9-8.5) and 120% larger than the risk function used in the GBD (4.0; 95% CI: 3.3-4.8). Differences between the GEMM and GBD risk functions are larger for a 20% reduction in concentrations, with the GEMM predicting 220% higher excess deaths. These results suggest that PM2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations.

Measurement error in a multi-level analysis of air pollution and health: a simulation study.

BACKGROUND: Spatio-temporal models are increasingly being used to predict exposure to ambient outdoor air pollution at high spatial resolution for inclusion in epidemiological analyses of air pollution and health. Measurement error in these predictions can nevertheless have impacts on health effect estimation. Using statistical simulation we aim to investigate the effects of such error within a multi-level model analysis of long and short-term pollutant exposure and health. METHODS: Our study was based on a theoretical sample of 1000 geographical sites within Greater London. Simulations of "true" site-specific daily mean and 5-year mean NO2 and PM10 concentrations, incorporating both temporal variation and spatial covariance, were informed by an analysis of daily measurements over the period 2009-2013 from fixed location urban background monitors in the London area. In the context of a multi-level single-pollutant Poisson regression analysis of mortality, we investigated scenarios in which we specified: the Pearson correlation between modelled and "true" data and the ratio of their variances (model versus "true") and assumed these parameters were the same spatially and temporally. RESULTS: In general, health effect estimates associated with both long and short-term exposure were biased towards the null with the level of bias increasing to over 60% as the correlation coefficient decreased from 0.9 to 0.5 and the variance ratio increased from 0.5 to 2. However, for a combination of high correlation (0.9) and small variance ratio (0.5) non-trivial bias (> 25%) away from the null was observed. Standard errors of health effect estimates, though unaffected by changes in the correlation coefficient, appeared to be attenuated for variance ratios > 1 but inflated for variance ratios < 1. CONCLUSION: While our findings suggest that in most cases modelling errors result in attenuation of the effect estimate towards the null, in some situations a non-trivial bias away from the null may occur. The magnitude and direction of bias appears to depend on the relationship between modelled and "true" data in terms of their correlation and the ratio of their variances. These factors should be taken into account when assessing the validity of modelled air pollution predictions for use in complex epidemiological models.

Long-term Concentrations of Nitrogen Dioxide and Mortality: A Meta-analysis of Cohort Studies.

BACKGROUND: Concentrations of outdoor nitrogen dioxide (NO2) have been associated with increased mortality. Hazard ratios (HRs) from cohort studies are used to assess population health impact and burden. We undertook meta-analyses to derive concentration-response functions suitable for such evaluations and assessed their sensitivity to study selection based upon cohort characteristics. METHODS: We searched online databases and existing reviews for cohort studies published to October 2016 that reported HRs for NO2 and mortality. We calculated meta-analytic summary estimates using fixed/random-effects models. RESULTS: We identified 48 articles analyzing 28 cohorts. Meta-analysis of HRs found positive associations between NO2 and all cause (1.02 [95% confidence interval (CI): 1.01, 1.03]; prediction interval [PI]: [0.99, 1.06] per 10 µg/m increment in NO2), cardiovascular (1.03 [95% CI: 1.02, 1.05]; PI: [0.98, 1.08]), respiratory (1.03 [95% CI: 1.01, 1.05]; PI: [0.97, 1.10]), and lung cancer mortality (1.05 [95% CI: 1.02, 1.08]; PI: [0.94, 1.17]) with evidence of substantial heterogeneity between studies. In subgroup analysis, summary HRs varied by age at cohort entry, spatial resolution of pollution estimates, and adjustment for smoking and body mass index at the individual level; for some subgroups, the HR was close to unity, with lower confidence limits below 1. CONCLUSIONS: Given the many uncertainties inherent in the assessment of this evidence base and the sensitivity of health impact calculations to small changes in the magnitude of the HRs, calculation of the impact on health of policies to reduce long-term exposure to NO2 should use prediction intervals and report ranges of impact rather than focusing upon point estimates.

Associations of short-term exposure to traffic-related air pollution with cardiovascular and respiratory hospital admissions in London, UK.

OBJECTIVES: There is evidence of adverse associations between short-term exposure to traffic-related pollution and health, but little is known about the relative contribution of the various sources and particulate constituents. METHODS: For each day for 2011-2012 in London, UK over 100 air pollutant metrics were assembled using monitors, modelling and chemical analyses. We selected a priori metrics indicative of traffic sources: general traffic, petrol exhaust, diesel exhaust and non-exhaust (mineral dust, brake and tyre wear). Using Poisson regression models, controlling for time-varying confounders, we derived effect estimates for cardiovascular and respiratory hospital admissions at prespecified lags and evaluated the sensitivity of estimates to multipollutant modelling and effect modification by season. RESULTS: For single day exposure, we found consistent associations between adult (15-64 years) cardiovascular and paediatric (0-14 years) respiratory admissions with elemental and black carbon (EC/BC), ranging from 0.56% to 1.65% increase per IQR change, and to a lesser degree with carbon monoxide (CO) and aluminium (Al). The average of past 7 days EC/BC exposure was associated with elderly (65+ years) cardiovascular admissions. Indicated associations were higher during the warm period of the year. Although effect estimates were sensitive to the adjustment for other pollutants they remained consistent in direction, indicating independence of associations from different sources, especially between diesel and petrol engines, as well as mineral dust. CONCLUSIONS: Our results suggest that exhaust related pollutants are associated with increased numbers of adult cardiovascular and paediatric respiratory hospitalisations. More extensive monitoring in urban centres is required to further elucidate the associations.

Searching for the best modeling specification for assessing the effects of temperature and humidity on health: a time series analysis in three European cities.

Epidemiological time series studies suggest daily temperature and humidity are associated with adverse health effects including increased mortality and hospital admissions. However, there is no consensus over which metric or lag best describes the relationships. We investigated which temperature and humidity model specification most adequately predicted mortality in three large European cities. Daily counts of all-cause mortality, minimum, maximum and mean temperature and relative humidity and apparent temperature (a composite measure of ambient and dew point temperature) were assembled for Athens, London, and Rome for 6 years between 1999 and 2005. City-specific Poisson regression models were fitted separately for warm (April-September) and cold (October-March) periods adjusting for seasonality, air pollution, and public holidays. We investigated goodness of model fit for each metric for delayed effects up to 13 days using three model fit criteria: sum of the partial autocorrelation function, AIC, and GCV. No uniformly best index for all cities and seasonal periods was observed. The effects of temperature were uniformly shown to be more prolonged during cold periods and the majority of models suggested separate temperature and humidity variables performed better than apparent temperature in predicting mortality. Our study suggests that the nature of the effects of temperature and humidity on mortality vary between cities for unknown reasons which require further investigation but may relate to city-specific population, socioeconomic, and environmental characteristics. This may have consequences on epidemiological studies and local temperature-related warning systems.

Effects of heat waves on mortality: effect modification and confounding by air pollutants.

BACKGROUND: Heat waves and air pollution are both associated with increased mortality. Their joint effects are less well understood. METHODS: We explored the role of air pollution in modifying the effects of heat waves on mortality, within the EuroHEAT project. Daily mortality, meteorologic, and air pollution data from nine European cities for the years 1990-2004 were assembled. We defined heat waves by taking both intensity and duration into account. The city-specific effects of heat wave episodes were estimated using generalized estimating equation models, adjusting for potential confounders with and without inclusion of air pollutants (particles, ozone, nitrogen dioxide, sulphur dioxide, carbon monoxide). To investigate effect modification, we introduced an interaction term between heat waves and each single pollutant in the models. Random effects meta-analysis was used to summarize the city-specific results. RESULTS: The increase in the number of daily deaths during heat wave episodes was 54% higher on high ozone days compared with low, among people age 75-84 years. The heat wave effect on high PM10 days was increased by 36% and 106% in the 75-84 year and 85+ year age groups, respectively. A similar pattern was observed for effects on cardiovascular mortality. Effect modification was less evident for respiratory mortality, although the heat wave effect itself was greater for this cause of death. The heat wave effect was smaller (15-30%) after adjustment for ozone or PM10. CONCLUSIONS: The heat wave effect on mortality was larger during high ozone or high PM10 days. When assessing the effect of heat waves on mortality, lack of adjustment for ozone and especially PM10 overestimates effect parameters. This bias has implications for public health policy.

Mortality associations with long-term exposure to outdoor air pollution in a national English cohort.

RATIONALE: Cohort evidence linking long-term exposure to outdoor particulate air pollution and mortality has come largely from the United States. There is relatively little evidence from nationally representative cohorts in other countries. OBJECTIVES: To investigate the relationship between long-term exposure to a range of pollutants and causes of death in a national English cohort. METHODS: A total of 835,607 patients aged 40-89 years registered with 205 general practices were followed from 2003-2007. Annual average concentrations in 2002 for particulate matter with a median aerodynamic diameter less than 10 (PM(10)) and less than 2.5 µm (PM(2.5)), nitrogen dioxide (NO(2)), ozone, and sulfur dioxide (SO(2)) at 1 km(2) resolution, estimated from emission-based models, were linked to residential postcode. Deaths (n = 83,103) were ascertained from linkage to death certificates, and hazard ratios (HRs) for all- and cause-specific mortality for pollutants were estimated for interquartile pollutant changes from Cox models adjusting for age, sex, smoking, body mass index, and area-level socioeconomic status markers. MEASUREMENTS AND MAIN RESULTS: Residential concentrations of all pollutants except ozone were positively associated with all-cause mortality (HR, 1.02, 1.03, and 1.04 for PM(2.5), NO(2), and SO(2), respectively). Associations for PM(2.5), NO(2), and SO(2) were larger for respiratory deaths (HR, 1.09 each) and lung cancer (HR, 1.02, 1.06, and 1.05) but nearer unity for cardiovascular deaths (1.00, 1.00, and 1.04). CONCLUSIONS: These results strengthen the evidence linking long-term ambient air pollution exposure to increased all-cause mortality. However, the stronger associations with respiratory mortality are not consistent with most US studies in which associations with cardiovascular causes of death tend to predominate.

Economic valuation of the mortality benefits of a regulation on SO2 in 20 European cities.

BACKGROUND: Since the 1970s, legislation has led to progress in tackling several air pollutants. We quantify the annual monetary benefits resulting from reductions in mortality from the year 2000 onwards following the implementation of three European Commission regulations to reduce the sulphur content in liquid fuels for vehicles. METHODS: We first compute premature deaths attributable to these implementations for 20 European cities in the Aphekom project by using a two-stage health impact assessment method. We then justify our choice to only consider mortality effects as short-term effects. We rely on European studies when selecting the central value of a life-year estimate (€ 2005 86 600) used to compute the monetary benefits for each of the cities. We also conduct an independent sensitivity analysis as well as an integrated uncertainty analysis that simultaneously accounts for uncertainties concerning epidemiology and economic valuation. RESULTS: The implementation of these regulations is estimated to have postponed 2212 (95% confidence interval: 772-3663) deaths per year attributable to reductions in sulphur dioxide for the 20 European cities, from the year 2000 onwards. We obtained annual mortality benefits related to the implementation of the European regulation on sulphur dioxide of € 2005 191.6 million (95% confidence interval: € 2005 66.9-€ 2005 317.2). CONCLUSION: Our approach is conservative in restricting to mortality effects and to short-term benefits only, thus only providing the lower-bound estimate. Our findings underline the health and monetary benefits to be obtained from implementing effective European policies on air pollution and ensuring compliance with them over time.

Short-Term Nitrogen Dioxide Exposure and Emergency Hospital Admissions for Asthma in Children: A Case-Crossover Analysis in England.

Background: There is an increasing body of evidence associating short-term ambient nitrogen dioxide (NO2) exposure with asthma-related hospital admissions in children. However, most studies have relied on temporally resolved exposure information, potentially ignoring the spatial variability of NO2. We aimed to investigate how daily NO2 estimates from a highly resolved spatio-temporal model are associated with the risk of emergency hospital admission for asthma in children in England. Methods: We conducted a time-stratified case-crossover study including 111,766 emergency hospital admissions for asthma in children (aged 0-14 years) between 1st January 2011 and 31st December 2015 in England. Daily NO2 levels were predicted at the patients' place of residence using spatio-temporal models by combining land use data and chemical transport model estimates. Conditional logistic regression models were used to obtain the odds ratios (OR) and confidence intervals (CI) after adjusting for temperature, relative humidity, bank holidays, and influenza rates. The effect modifications by age, sex, season, area-level income deprivation, and region were explored in stratified analyses. Results: For each 10 µg/m³ increase in NO2 exposure, we observed an 8% increase in asthma-related emergency admissions using a five-day moving NO2 average (mean lag 0-4) (OR 1.08, 95% CI 1.06-1.10). In the stratified analysis, we found larger effect sizes for male (OR 1.10, 95% CI 1.07-1.12) and during the cold season (OR 1.10, 95% CI 1.08-1.12). The effect estimates varied slightly by age group, area-level income deprivation, and region. Significance: Short-term exposure to NO2 was significantly associated with an increased risk of asthma emergency admissions among children in England. Future guidance and policies need to consider reflecting certain proven modifications, such as using season-specific countermeasures for air pollution control, to protect the at-risk population.

Long-term exposure to outdoor air pollution and incidence of cardiovascular diseases.

BACKGROUND: Evidence based largely on US cohorts suggests that long-term exposure to fine particulate matter is associated with cardiovascular mortality. There is less evidence for other pollutants and for cardiovascular morbidity. By using a cohort of 836,557 patients age 40 to 89 years registered with 205 English general practices in 2003, we investigated relationships between ambient outdoor air pollution and incident myocardial infarction, stroke, arrhythmia, and heart failure over a 5-year period. METHODS: Events were identified from primary care records, hospital admissions, and death certificates. Annual average concentrations in 2002 for particulate matter with a median aerodynamic diameter <10 (PM10) and <2.5 microns, nitrogen dioxide (NO2), ozone, and sulfur dioxide at a 1 × 1 km resolution were derived from emission-based models and linked to residential postcode. Analyses were performed using Cox proportional hazards models adjusting for relevant confounders, including social and economic deprivation and smoking. RESULTS: While evidence was weak for relationships with myocardial infarction, stroke, or arrhythmia, we found consistent associations between pollutant concentrations and incident cases of heart failure. An interquartile range change in PM10 and in NO2 (3.0 and 10.7 µg/m, respectively) both produced a hazard ratio of 1.06 (95% confidence interval = 1.01-1.11) after adjustment for confounders. There was some evidence that these effects were greater in more affluent areas. CONCLUSIONS: This study of an English national cohort found evidence linking long-term exposure to particulate matter and NO2 with the development of heart failure. We did not, however, replicate associations for other cardiovascular outcomes that have been reported elsewhere.

Measurement error in time-series analysis: a simulation study comparing modelled and monitored data.

BACKGROUND: Assessing health effects from background exposure to air pollution is often hampered by the sparseness of pollution monitoring networks. However, regional atmospheric chemistry-transport models (CTMs) can provide pollution data with national coverage at fine geographical and temporal resolution. We used statistical simulation to compare the impact on epidemiological time-series analysis of additive measurement error in sparse monitor data as opposed to geographically and temporally complete model data. METHODS: Statistical simulations were based on a theoretical area of 4 regions each consisting of twenty-five 5 km × 5 km grid-squares. In the context of a 3-year Poisson regression time-series analysis of the association between mortality and a single pollutant, we compared the error impact of using daily grid-specific model data as opposed to daily regional average monitor data. We investigated how this comparison was affected if we changed the number of grids per region containing a monitor. To inform simulations, estimates (e.g. of pollutant means) were obtained from observed monitor data for 2003-2006 for national network sites across the UK and corresponding model data that were generated by the EMEP-WRF CTM. Average within-site correlations between observed monitor and model data were 0.73 and 0.76 for rural and urban daily maximum 8-hour ozone respectively, and 0.67 and 0.61 for rural and urban loge(daily 1-hour maximum NO2). RESULTS: When regional averages were based on 5 or 10 monitors per region, health effect estimates exhibited little bias. However, with only 1 monitor per region, the regression coefficient in our time-series analysis was attenuated by an estimated 6% for urban background ozone, 13% for rural ozone, 29% for urban background loge(NO2) and 38% for rural loge(NO2). For grid-specific model data the corresponding figures were 19%, 22%, 54% and 44% respectively, i.e. similar for rural loge(NO2) but more marked for urban loge(NO2). CONCLUSION: Even if correlations between model and monitor data appear reasonably strong, additive classical measurement error in model data may lead to appreciable bias in health effect estimates. As process-based air pollution models become more widely used in epidemiological time-series analysis, assessments of error impact that include statistical simulation may be useful.

Evidence Synthesis of Observational Studies in Environmental Health: Lessons Learned from a Systematic Review on Traffic-Related Air Pollution.

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

Comparison of traditional Cox regression and causal modeling to investigate the association between long-term air pollution exposure and natural-cause mortality within European cohorts.

Most studies investigating the health effects of long-term exposure to air pollution used traditional regression models, although causal inference approaches have been proposed as alternative. However, few studies have applied causal models and comparisons with traditional methods are sparse. We therefore compared the associations between natural-cause mortality and exposure to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) using traditional Cox and causal models in a large multicenter cohort setting. We analysed data from eight well-characterized cohorts (pooled cohort) and seven administrative cohorts from eleven European countries. Annual mean PM2.5 and NO2 from Europe-wide models were assigned to baseline residential addresses and dichotomized at selected cut-off values (PM2.5: 10, 12, 15 µg/m³; NO2: 20, 40 µg/m³). For each pollutant, we estimated the propensity score as the conditional likelihood of exposure given available covariates, and derived corresponding inverse-probability weights (IPW). We applied Cox proportional hazards models i) adjusting for all covariates ("traditional Cox") and ii) weighting by IPW ("causal model"). Of 325,367 and 28,063,809 participants in the pooled and administrative cohorts, 47,131 and 3,580,264 died from natural causes, respectively. For PM2.5 above vs. below 12 µg/m³, the hazard ratios (HRs) of natural-cause mortality were 1.17 (95% CI 1.13-1.21) and 1.15 (1.11-1.19) for the traditional and causal models in the pooled cohort, and 1.03 (1.01-1.06) and 1.02 (0.97-1.09) in the administrative cohorts. For NO2 above vs below 20 µg/m³, the HRs were 1.12 (1.09-1.14) and 1.07 (1.05-1.09) for the pooled and 1.06 (95% CI 1.03-1.08) and 1.05 (1.02-1.07) for the administrative cohorts. In conclusion, we observed mostly consistent associations between long-term air pollution exposure and natural-cause mortality with both approaches, though estimates partly differed in individual cohorts with no systematic pattern. The application of multiple modelling methods might help to improve causal inference. 299 of 300 words.

Cross-sectional study of carbon monoxide alarm use in patients attending the emergency department: a multicentre survey protocol.

INTRODUCTION: The most common place for unintentional, non-fire-related carbon monoxide (CO) exposure to occur is in the home, but this is preventable if CO producing sources are properly maintained and CO alarms/detectors are in use. It is estimated that less than half of all homes have a CO alarm, but there is variation across countries, housing types and different demographic and socioeconomic groups. The purpose of this study is to provide up-to-date data on the use of CO alarms by surveying attendees to emergency departments using an online anonymous questionnaire. METHODS AND ANALYSIS: A multicentre prospective, cross-sectional survey of 4000 patients or carers in three emergency departments will be used. A questionnaire comprising of a maximum of 14 items will be administered following completion of an informed consent process. Data collected include participant demographics, household information and CO alarm use. Statistical analyses will comprise descriptive techniques to present respondents' use of CO alarms and examine associations between alarm use and participant characteristics. The proportion of homes with CO alarms installed will be calculated for all subjects and for selected subgroups. ETHICS AND DISSEMINATION: The study obtained ethical approval from the Westminster Research Ethics Committee (REC number 1/PR/1657). Informed consent will be obtained prior to the participant undergoing any activities that are specifically for the purposes of the study. Findings will be published in scientific journals, presented to national and international conferences and disseminated to CO safety groups. TRIAL REGISTRATION NUMBER: ISRCTN registry 12562718.

Long-term exposure to low ambient air pollution concentrations and mortality among 28 million people: results from seven large European cohorts within the ELAPSE project.

BACKGROUND: Long-term exposure to ambient air pollution has been associated with premature mortality, but associations at concentrations lower than current annual limit values are uncertain. We analysed associations between low-level air pollution and mortality within the multicentre study Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE). METHODS: In this multicentre longitudinal study, we analysed seven population-based cohorts of adults (age ≥30 years) within ELAPSE, from Belgium, Denmark, England, the Netherlands, Norway, Rome (Italy), and Switzerland (enrolled in 2000-11; follow-up until 2011-17). Mortality registries were used to extract the underlying cause of death for deceased individuals. Annual average concentrations of fine particulate matter (PM2·5), nitrogen dioxide (NO2), black carbon, and tropospheric warm-season ozone (O3) from Europe-wide land use regression models at 100 m spatial resolution were assigned to baseline residential addresses. We applied cohort-specific Cox proportional hazard models with adjustment for area-level and individual-level covariates to evaluate associations with non-accidental mortality, as the main outcome, and with cardiovascular, non-malignant respiratory, and lung cancer mortality. Subset analyses of participants living at low pollutant concentrations (as per predefined values) and natural splines were used to investigate the concentration-response function. Cohort-specific effect estimates were pooled in a random-effects meta-analysis. FINDINGS: We analysed 28 153 138 participants contributing 257 859 621 person-years of observation, during which 3 593 741 deaths from non-accidental causes occurred. We found significant positive associations between non-accidental mortality and PM2·5, NO2, and black carbon, with a hazard ratio (HR) of 1·053 (95% CI 1·021-1·085) per 5 µg/m3 increment in PM2·5, 1·044 (1·019-1·069) per 10 µg/m3 NO2, and 1·039 (1·018-1·059) per 0·5 × 10-5/m black carbon. Associations with PM2·5, NO2, and black carbon were slightly weaker for cardiovascular mortality, similar for non-malignant respiratory mortality, and stronger for lung cancer mortality. Warm-season O3 was negatively associated with both non-accidental and cause-specific mortality. Associations were stronger at low concentrations: HRs for non-accidental mortality at concentrations lower than the WHO 2005 air quality guideline values for PM2·5 (10 µg/m3) and NO2 (40 µg/m3) were 1·078 (1·046-1·111) per 5 µg/m3 PM2·5 and 1·049 (1·024-1·075) per 10 µg/m3 NO2. Similarly, the association between black carbon and non-accidental mortality was highest at low concentrations, with a HR of 1·061 (1·032-1·092) for exposure lower than 1·5× 10-5/m, and 1·081 (0·966-1·210) for exposure lower than 1·0× 10-5/m. INTERPRETATION: Long-term exposure to concentrations of PM2·5 and NO2 lower than current annual limit values was associated with non-accidental, cardiovascular, non-malignant respiratory, and lung cancer mortality in seven large European cohorts. Continuing research on the effects of low concentrations of air pollutants is expected to further inform the process of setting air quality standards in Europe and other global regions. FUNDING: Health Effects Institute.