Comparing the performance of air pollution models for nitrogen dioxide and ozone in the context of a multilevel epidemiological analysis.

Using modeled air pollutant predictions as exposure variables in epidemiological analyses can produce bias in health effect estimation. We used statistical simulation to estimate these biases and compare different air pollution models for London. METHODS: Our simulations were based on a sample of 1,000 small geographical areas within London, United Kingdom. "True" pollutant data (daily mean nitrogen dioxide [NO2] and ozone [O3]) were simulated to include spatio-temporal variation and spatial covariance. All-cause mortality and cardiovascular hospital admissions were simulated from "true" pollution data using prespecified effect parameters for short and long-term exposure within a multilevel Poisson model. We compared: land use regression (LUR) models, dispersion models, LUR models including dispersion output as a spline (hybrid1), and generalized additive models combining splines in LUR and dispersion outputs (hybrid2). Validation datasets (model versus fixed-site monitor) were used to define simulation scenarios. RESULTS: For the LUR models, bias estimates ranged from -56% to +7% for short-term exposure and -98% to -68% for long-term exposure and for the dispersion models from -33% to -15% and -52% to +0.5%, respectively. Hybrid1 provided little if any additional benefit, but hybrid2 appeared optimal in terms of bias estimates for short-term (-17% to +11%) and long-term (-28% to +11%) exposure and in preserving coverage probability and statistical power. CONCLUSIONS: Although exposure error can produce substantial negative bias (i.e., towards the null), combining outputs from different air pollution modeling approaches may reduce bias in health effect estimation leading to improved impact evaluation of abatement policies.

The impact of measurement error in modeled ambient particles exposures on health effect estimates in multilevel analysis: A simulation study.

Various spatiotemporal models have been proposed for predicting ambient particulate exposure for inclusion in epidemiological analyses. We investigated the effect of measurement error in the prediction of particulate matter with diameter <10 µm (PM10) and <2.5 µm (PM2.5) concentrations on the estimation of health effects. METHODS: We sampled 1,000 small administrative areas in London, United Kingdom, and simulated the "true" underlying daily exposure surfaces for PM10 and PM2.5 for 2009-2013 incorporating temporal variation and spatial covariance informed by the extensive London monitoring network. We added measurement error assessed by comparing measurements at fixed sites and predictions from spatiotemporal land-use regression (LUR) models; dispersion models; models using satellite data and applying machine learning algorithms; and combinations of these methods through generalized additive models. Two health outcomes were simulated to assess whether the bias varies with the effect size. We applied multilevel Poisson regression to simultaneously model the effect of long- and short-term pollutant exposure. For each scenario, we ran 1,000 simulations to assess measurement error impact on health effect estimation. RESULTS: For long-term exposure to particles, we observed bias toward the null, except for traffic PM2.5 for which only LUR underestimated the effect. For short-term exposure, results were variable between exposure models and bias ranged from -11% (underestimate) to 20% (overestimate) for PM10 and of -20% to 17% for PM2.5. Integration of models performed best in almost all cases. CONCLUSIONS: No single exposure model performed optimally across scenarios. In most cases, measurement error resulted in attenuation of the effect estimate.

Intensive care admissions and outcomes associated with short-term exposure to ambient air pollution: a time series analysis.

PURPOSE: Short-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. RESULTS: 46,965 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.

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.

Ambient air pollution and the prevalence of rhinoconjunctivitis in adolescents: a worldwide ecological analysis.

Whether exposure to outdoor air pollution increases the prevalence of rhinoconjunctivitis in children is unclear. Using data from Phase Three of the International Study of Asthma and Allergies in childhood (ISAAC), we investigated associations of rhinoconjunctivitis prevalence in adolescents with model-based estimates of ozone, and satellite-based estimates of fine (diameter < 2.5 µm) particulate matter (PM2.5) and nitrogen dioxide (NO2). Information on rhinoconjunctivitis (defined as self-reported nose symptoms without a cold or flu accompanied by itchy watery eyes in the past 12 months) was available on 505,400 children aged 13-14 years, in 183 centres in 83 countries. Centre-level prevalence estimates were calculated and linked geographically with estimates of long-term average concentrations of NO2, ozone and PM2.5. Multi-level models were fitted adjusting for population density, climate, sex and gross national income. Information on parental smoking, truck traffic and cooking fuel was available for a restricted set of centres (77 in 36 countries). Between centres within countries, the estimated change in rhinoconjunctivitis prevalence per 100 children was 0.171 (95% confidence interval: - 0.013, 0.354) per 10% increase in PM2.5, 0.096 (- 0.003, 0.195) per 10% increase in NO2 and - 0.186 (- 0.390, 0.018) per 1 ppbV increase in ozone. Between countries, rhinoconjunctivitis prevalence was significantly negatively associated with both ozone and PM2.5. In the restricted dataset, the latter association became less negative following adjustment for parental smoking and open fires for cooking. In conclusion, there were no significant within-country associations of rhinoconjunctivitis prevalence with study pollutants. Negative between-country associations with PM2.5 and ozone require further investigation.

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.

Incorporating Measurement Error from Modeled Air Pollution Exposures into Epidemiological Analyses.

PURPOSE OF REVIEW: Outdoor air pollution exposures used in epidemiological studies are commonly predicted from spatiotemporal models incorporating limited measurements, temporal factors, geographic information system variables, and/or satellite data. Measurement error in these exposure estimates leads to imprecise estimation of health effects and their standard errors. We reviewed methods for measurement error correction that have been applied in epidemiological studies that use model-derived air pollution data. RECENT FINDINGS: We identified seven cohort studies and one panel study that have employed measurement error correction methods. These methods included regression calibration, risk set regression calibration, regression calibration with instrumental variables, the simulation extrapolation approach (SIMEX), and methods under the non-parametric or parameter bootstrap. Corrections resulted in small increases in the absolute magnitude of the health effect estimate and its standard error under most scenarios. Limited application of measurement error correction methods in air pollution studies may be attributed to the absence of exposure validation data and the methodological complexity of the proposed methods. Future epidemiological studies should consider in their design phase the requirements for the measurement error correction method to be later applied, while methodological advances are needed under the multi-pollutants setting.

Myocardial infarction, ST-elevation and non-ST-elevation myocardial infarction and modelled daily pollution concentrations: a case-crossover analysis of MINAP data.

OBJECTIVES: To investigate associations between daily concentrations of air pollution and myocardial infarction (MI), ST-elevation MI (STEMI) and non-ST-elevation MI (NSTEMI). METHODS: Modelled daily ground-level gaseous, total and speciated particulate pollutant concentrations and ground-level daily mean temperature, all at 5 km×5 km horizontal resolution, were linked to 202 550 STEMI and 322 198 NSTEMI events recorded on the England and Wales Myocardial Ischaemia National Audit Project (MINAP) database. The study period was 2003-2010. A case-crossover design was used, stratified by year, month and day of the week. Data were analysed using conditional logistic regression, with pollutants modelled as unconstrained distributed lags 0-2 days. Results are presented as percentage change in risk per 10 µg/m(3) increase in the pollutant relevant metric, having adjusted for daily mean temperature, public holidays, weekly influenza consultation rates and a sine-cosine annual cycle. RESULTS: There was no evidence of an association between MI or STEMI and any of O3, NO2, PM2.5, PM10 or selected PM2.5 components (sulfate and elemental carbon). For NSTEMI, there was a positive association with daily maximum 1-hour NO2 (0.27% (95% CI 0.01% to 0.54%)), which persisted following adjustment for O3 and adjustment for PM2.5. The association appeared to be confined to the midland and southern regions of England and Wales. CONCLUSIONS: The study found no evidence of an association between the modelled pollutants (including components) investigated and STEMI but did find some evidence of a positive association between NO2 and NSTEMI. Confirmation of this association in other studies is required.

Childhood intermittent and persistent rhinitis prevalence and climate and vegetation: a global ecologic analysis.

BACKGROUND: The effect of climate change and its effects on vegetation growth, and consequently on rhinitis, are uncertain. OBJECTIVE: To examine between- and within-country associations of climate measures and the normalized difference vegetation index with intermittent and persistent rhinitis symptoms in a global context. METHODS: Questionnaire data from 6- to 7-year-olds and 13- to 14-year-olds were collected in phase 3 of the International Study of Asthma and Allergies in Childhood. Associations of intermittent (>1 symptom report but not for 2 consecutive months) and persistent (symptoms for ≥2 consecutive months) rhinitis symptom prevalences with temperature, precipitation, vapor pressure, and the normalized difference vegetation index were assessed in linear mixed-effects regression models adjusted for gross national income and population density. The mean difference in prevalence per 100 children (with 95% confidence intervals [CIs]) per interquartile range increase of exposure is reported. RESULTS: The country-level intermittent symptom prevalence was associated with several country-level climatic measures, including the country-level mean monthly temperature (6.09 °C; 95% CI, 2.06-10.11°C per 10.4 °C), precipitation (3.10 mm; 95% CI, 0.46-5.73 mm; per 67.0 mm), and vapor pressure (6.21 hPa; 95% CI, 2.17-10.24 hPa; per 10.4 hPa) among 13- to 14-year-olds (222 center in 94 countries). The center-level persistent symptom prevalence was positively associated with several center-level climatic measures. Associations with climate were also found for the 6- to 7-year-olds (132 center in 57 countries). CONCLUSION: Several between- and within-country spatial associations between climatic factors and intermittent and persistent rhinitis symptom prevalences were observed. These results provide suggestive evidence that climate (and future changes in climate) may influence rhinitis symptom prevalence.

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.

Asthma and occupation in the 1958 birth cohort.

OBJECTIVE: To examine the association of adult onset asthma with lifetime exposure to occupations and occupational exposures. METHODS: We generated lifetime occupational histories for 9488 members of the British 1958 birth cohort up to age 42 years. Blind to asthma status, jobs were coded to the International Standard Classification of Occupations 1988 and an Asthma Specific Job Exposure Matrix (ASJEM) with an expert re-evaluation step. Associations of jobs and ASJEM exposures with adult onset asthma were assessed in logistic regression models adjusting for sex, smoking, social class at birth and childhood hay fever. RESULTS: Of the 7406 cohort members with no asthma or wheezy bronchitis in childhood, 639 (9%) reported asthma by age 42 years. Adult onset asthma was associated with 18 occupations, many previously identified as risks for asthma (eg, farmers: OR 4.26, 95% CI 2.06 to 8.80; hairdressers: OR 1.88, 95% CI 1.24 to 2.85; printing workers: OR 3.04, 95% CI 1.49 to 6.18). Four were cleaning occupations and a further three occupations were likely to use cleaning agents. Adult onset asthma was associated with five of the 18 high-risk specific ASJEM exposures (flour exposure: OR 2.12, 95% CI 1.17 to 3.85; enzyme exposure: OR 2.32, 95% CI 1.22 to 4.42; cleaning/disinfecting products: OR 1.67, 95% CI 1.26 to 2.22; metal and metal fumes: OR 1.45, 95% CI 1.02 to 2.07; textile production: OR 1.71, 95% CI 1.12 to 2.61). Approximately 16% (95% CI 3.8% to 27.1%) of adult onset asthma was associated with known asthmagenic occupational exposures. CONCLUSIONS: This study suggests that about 16% of adult onset asthma in British adults born in the late 1950s could be due to occupational exposures, mainly recognised high-risk exposures.

Twenty-five years of volatile substance abuse mortality: a national mortality surveillance programme.

AIMS: To investigate trends in volatile substance abuse (VSA) deaths over 25 years. DESIGN: A national mortality surveillance programme with standardised data collection procedures. SETTING: The UK and islands. PARTICIPANTS/MEASUREMENTS: All VSA deaths, 1983-2007. FINDINGS: In the five quinquennia from 1983 to 2007 the numbers of VSA deaths were 499, 609, 378, 349 and 258 respectively. There were gradual increases in the mean age at death in males and females and in the number of VSA deaths in women. Coincident with the 1992 Department of Health Advertising Campaign, VSA deaths in boys and girls (<18 years of age) fell by an estimated 56% (95% CI: 36%-70%) and 64% (20%-84%), respectively, from the underlying trend, but there was no evidence of any similar step change in either group following the 1999 Legislation prohibiting sales of cigarette lighter refills containing butane to those under the age of 18 years. Between 1983-1987 and 2003-2007, the ratio of aerosol to gas fuel deaths fell by an estimated 80% (57% to 91%) in adults, while the ratio of glue to gas fuel deaths fell by an estimated 95% (89% to 97%) in adults and an estimated 87% (-1% to 98%) in children. CONCLUSIONS: Between 1983 and 2007, in the United Kingdom, the numbers of deaths associated with volatile substance abuse peaked in the early 1990s and fell to their lowest level in the mid-2000s. The age at death increased in both males and females. There was a fall in the proportion of volatile substance abuse deaths involving glues and a rise, particularly in adults, in the proportion involving gas fuels.

Satellite-based estimates of ambient air pollution and global variations in childhood asthma prevalence.

BACKGROUND: The effect of ambient air pollution on global variations and trends in asthma prevalence is unclear. OBJECTIVES: Our goal was to investigate community-level associations between asthma prevalence data from the International Study of Asthma and Allergies in Childhood (ISAAC) and satellite-based estimates of particulate matter with aerodynamic diameter < 2.5 µm (PM2.5) and nitrogen dioxide (NO2), and modelled estimates of ozone. METHODS: We assigned satellite-based estimates of PM2.5 and NO2 at a spatial resolution of 0.1° × 0.1° and modeled estimates of ozone at a resolution of 1° × 1° to 183 ISAAC centers. We used center-level prevalence of severe asthma as the outcome and multilevel models to adjust for gross national income (GNI) and center- and country-level sex, climate, and population density. We examined associations (adjusting for GNI) between air pollution and asthma prevalence over time in centers with data from ISAAC Phase One (mid-1900s) and Phase Three (2001-2003). RESULTS: For the 13- to 14-year age group (128 centers in 28 countries), the estimated average within-country change in center-level asthma prevalence per 100 children per 10% increase in center-level PM2.5 and NO2 was -0.043 [95% confidence interval (CI): -0.139, 0.053] and 0.017 (95% CI: -0.030, 0.064) respectively. For ozone the estimated change in prevalence per parts per billion by volume was -0.116 (95% CI: -0.234, 0.001). Equivalent results for the 6- to 7-year age group (83 centers in 20 countries), though slightly different, were not significantly positive. For the 13- to 14-year age group, change in center-level asthma prevalence over time per 100 children per 10% increase in PM2.5 from Phase One to Phase Three was -0.139 (95% CI: -0.347, 0.068). The corresponding association with ozone (per ppbV) was -0.171 (95% CI: -0.275, -0.067). CONCLUSION: In contrast to reports from within-community studies of individuals exposed to traffic pollution, we did not find evidence of a positive association between ambient air pollution and asthma prevalence as measured at the community level.

Job choice and the influence of prior asthma and hay fever.

OBJECTIVES: To investigate whether prior symptoms of allergic disease influence first job undertaken on leaving school. METHODS: The study included 5020 members of the 1958 British birth cohort who provided a job history (including start dates) at age 33 and for whom information on allergic disease in childhood and adolescence was reported by parents at ages 7, 11 and 16. Occupational group (high risk, low risk, reference) was based on first job and its probable asthma risk. RESULTS: With occupational group defined using only job title, the RR of taking a high risk over a reference level job was an estimated 30% (RR ratio (RRR) 0.70; 95% CI 0.56 to 0.88) lower among those with than without prior reported symptoms of hay fever/allergic rhinitis but an estimated 60% (RRR 1.60; 1.17 to 2.19) higher among those with symptoms of asthma/wheezy bronchitis in adolescence compared to those with no history of asthma/wheezy bronchitis. With occupational group defined using an asthma specific job exposure matrix, a similar association was observed for prior hay fever/allergic rhinitis (RRR 0.77; 0.62 to 0.96) but not for asthma/wheezy bronchitis (RRR 1.18; 0.85 to 1.64). There was no evidence of an association between prior eczema and occupational group of first job. CONCLUSION: Whether our findings indicate avoidance or residual confounding, it would be prudent for future studies of occupation and the incidence or recurrence of asthma in adult life to adjust for any previous history of hay fever/allergic rhinitis.

Bronchodilator treatment and asthma death: a new analysis of a British case-control study.

We investigated the relationship between asthma mortality and long-acting beta(2)-agonists (LABA), including interactions with age, inhaled corticosteroids (ICS) and social deprivation. We used a new, expanded dataset of recorded medication extracted blind from the anonymised primary care records of an earlier British case-control study. The cases were 532 asthma deaths aged < 65 occurring between 1994 and 1998 and the controls were 532 asthma admissions, matched for age, hospital, and index date (date of death/asthma admission). The exposure periods prior to the index date were current (≤ 2 months) or recent ( > 2-6 months). We found no evidence of an overall association with current (OR = 0.89 [95% confidence interval 0.61-1.30]) or recent (1.08 [0.76-1.53]) mention of LABA, but there was some evidence of a positive interaction with age. Among controls with mention of LABA, a concurrent mention of ICS (within 1 month) was common (85% and 93% for the two respective periods) which limited our power to investigate any interaction between LABA and ICS. There was no coherent evidence of effect modification by social deprivation. In a population based case-control study where prescription of LABA without concomitant ICS was uncommon there was no evidence of an overall association between LABA and asthma death.

Bronchodilator treatment and deaths from asthma: case-control study.

OBJECTIVE: To investigate the association between bronchodilator treatment and death from asthma. DESIGN: Case-control study. SETTING: 33 health authorities or health boards in Great Britain. PARTICIPANTS: 532 patients under age 65 who died from asthma and 532 controls with a hospital admission for asthma matched for period, age, and area. MAIN OUTCOME MEASURES: Odds ratios for deaths from asthma associated with prescription of bronchodilators and other treatment, with sensitivity analyses adjusting for age at onset, previous hospital admissions, associated chronic obstructive lung disease, and number of other drug categories. RESULTS: After full adjustment, there were no significant associations with drugs prescribed in the 4-12 months before the index date. For prescriptions in the 1-5 years before, mortality was positively associated with inhaled short acting beta2 agonists (odds ratio 2.05, 95% confidence interval 1.26 to 3.33) and inversely associated with antibiotics (0.59, 0.39 to 0.89). The former association seemed to be confined to those aged 45-64, and the association with antibiotics was more pronounced in those under 45. Significant age interactions across all periods suggested inverse associations with oral steroids confined to the under 45 age group. An inverse association with long acting beta2 agonists and a positive association with methylxanthines in the 1-5 year period were non-significant. CONCLUSION: There was no evidence of adverse effects on mortality with medium to long term use of inhaled long acting beta2 agonist drugs. The association with short acting beta(2) agonists has several explanations, only one of which may be a direct adverse effect.