Air pollution, weather and positive airway pressure treatment adherence in adults with sleep apnea: a retrospective community-based repeated-measures longitudinal study

We assessed the relation between air pollution, weather, and adherence to positive airway pressure (PAP) therapy in a retrospective community-based repeated-measures study of adults with obstructive sleep apnea who purchased PAP devices from a registered provider between 2013 and 2017 (Ottawa, Ontario, Canada) and had at least one day of data. Daily PAP-derived data, air pollution, and weather databases were linked using postal code. The exposures were mean nocturnal (8:00 p.m. to 8:00 a.m.) (i) residential concentrations of nitrogen dioxide (NO2 ), fine particulate matter <=2.5 μm (PM2.5 ), ozone (O3 ), and Air Quality Health Index (AQHI), and (ii) temperature, relative humidity, and barometric pressure. Covariates in the main model were demographics, season, exposure year, and PAP therapy mode. We analysed 8148 adults (median age of 54 years and 61% men) and 2,071,588 days of data. Based on daily data, the median (interquartile range) daily PAP usage was 416 (323-487) min. Using mixed-effect regression analyses to incorporate daily data and clustering by individuals, we found a statistically significant decrease in adherence for increased levels of NO2 , PM2.5 , and AQHI. The largest effect was for NO2 : a decrease in daily PAP use while comparing the highest versus lowest quartiles (Qs) was 3.4 (95% confidence interval [CI] 2.8-3.9) min. Decreased PAP adherence was also associated with increased temperature (Q4 versus Q1: 2.6 [95% CI: 1.5-3.7] min) and decreased barometric pressure (Q1 versus Q4: 2.0 [95% CI 1.5-2.5] min). We observed modest but statistically significant acute effects of air pollution and weather on daily PAP adherence.

Urban air pollution and emergency department visits related to central nervous system diseases

Ambient air pollution has been associated with adverse neurological health outcomes. Ambient pollutants are thought to trigger oxidative stress and inflammation to which vulnerable populations, such as elderly may be particularly susceptible. Our study investigated the possible association between concentrations of ambient air pollutants and the number of emergency department (ED) visits for nervous system disorders among people residing in a large Canadian city. A time-stratified case-crossover study design combining data from the National Ambulatory Care Reporting System (NACRS) and the National Air Pollution Surveillance (NAPS) between 2004 and 2015 was used. Two air quality health indices were considered in additional to specific pollutants, including carbon monoxide (CO), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃) and fine particulate matter (PM_2.5). Weather condition data were included in the models. ED visits with a discharge diagnosis were identified using ICD-10 codes (G00-G99). The analysis was stratified by sex and age, also by seasons. The associations were investigated in arrays organized as 18 strata and 15 time lags (in days) for each pollutant. Overall, 140,511 ED visits were included for the analysis. Most ED visits were related to episodic and paroxysmal diagnoses (G40-G47, 64%), with a majority of visits for migraines (G43, 39%). Among females, an increase of 0.1ppm ambient CO was associated with an increased risk of paroxysmal diagnoses at day 1 (RR = 1.019 (95%CI 1.004–1.033)), day 6 (1.024 (1.010–1.039)) and day 7 (1.022 (1.007–1.036). PM_2.5 and SO₂, and air quality indices were similarly associated with ED visits for episodic and paroxysmal disorders in days 6 and 7. Findings highlight that ambient air pollution is associated with an increased number of ED visits for nervous system disorders, particularly visits for paroxysmal diagnoses.

Urban Air Pollution and Emergency Department Visits for Neoplasms and Outcomes of Blood Forming and Metabolic Systems

This study focused on investigating possible associations between exposure to urban air pollution and the number of emergency department (ED) visits for various health outcomes. The outcomes were grouped into four chapters of the International Classification of Diseases Tenth Revision (ICD-10) system (i.e., Chapter II-IV: “Neoplasms”, “Diseases of the blood”, “Endocrine, nutritional and metabolic diseases”, and XVIII: “Symptoms, signs and abnormal clinical and laboratory findings“). The data were collected for the city of Toronto, Canada, (2004–2015, 4292 days). Four gaseous air pollutants (carbon monoxide (CO), nitrogen dioxide (NO₂), ground level ozone (O₃), and sulfur dioxide (SO₂)) and fine particulate matter (PM_2.5), and two calculated air quality health indexes (AQHI) based on Toronto were used. The statistical models were constructed by applying the conditional Poisson regression. The exposure was assessed over a maximum of 15 days (time lags 0–14 days). An analysis was performed with the following strata: sex, age, and seasons. Relative risks (RR) and their 95% confidence intervals (95%CI) were estimated for an increase in concentration by a one interquartile range (IQR). For the AQHI (composed of NO₂, O₃, and PM_2.5), IQR = 1, the estimations for lag 1 and all patients, are RR = 1.023 (95%CI: 1.008, 1.038), 1.026 (1.012, 1.040), 1.013 (1.003, 1.024), and 1.007 (1.003, 1.010) for Chapters II–IV and XVIII, respectively. The results show that in the four large, analyzed health groups, the impact of air quality mainly occurs over a short period (from current day to a maximum of 3 days after exposure).

Air Pollution and Emergency Department Visits for Disease of the Genitourinary System

The aim of this study is to determine associations between ambient air pollution and the number of emergency department (ED) visits for diseases of the genitourinary tract in Toronto, Canada. We used the National Ambulatory Care Reporting System (NACRS) database to obtain the related ED visits and developed statistical models using daily data on ED visits, temperature, relative humidity, and outdoor air pollution concentration levels. The NACRS database contains data on hospital-based and community-based ambulatory care. The environmental data were retrieved from the National Air Pollution Surveillance (NAPS) program. The NAPS is the main source of ambient air quality data in Canada. We considered 2 air quality health indexes and 6 air pollutants: daily means of fine particulate matter PM_2.5, O₃, CO, NO₂, SO₂, and also maximum 8-hour average ozone. For every air pollutant, we fit 270 models (15 lags × 18 strata). We found that same-day air pollution concentrations have the highest number of statistically significantly positive associations with ED visits for genitourinary health outcomes. A total of 133 positive associations were identified over the 14 days lag. In subgroup (strata) analysis, females older than 60 years of age were found to have the most positive associations. In particular, nitrogen dioxide was found to be highly associated with ED visits for females over 60; an increase in NO₂ was associated with an increased relative risk (RR) of ED visits when lagged over 0, 1, and 2 days (RR = 1.040 [95% confidence interval: 1.028, 1.052], 1.020 [1.009, 1.032], and 1.025 [1.013, 1.036], respectively). The values of risks are reported for a 1 interquartile range increase in concentration (8.8 ppb). Our results suggest that urban ambient air pollution affect the number of ED visits due to genitourinary system conditions.

Ambient air pollution and emergency department visits in Toronto, Canada

To investigate the acute impact of various air pollutants on various disease groups in the urban area of the city of Toronto, Canada. Statistical models were developed to estimate the relative risk of an emergency department visit associated with ambient air pollution concentration levels. These models were generated for 8 air pollutants (lagged from 0 to 14 days) and for 18 strata (based on sex, age group, and season). Twelve disease groups extracted from the International Classification of Diseases 10th Revision (ICD-10) were used as health classifications in the models. The qualitative results were collected in matrices composed of 18 rows (strata) and 15 columns (lags) for each air pollutant and the 12 health classifications. The matrix cells were assigned a value of 1 if the association was positively statistically significant; otherwise, they were assigned to a value of 0. The constructed matrices were totalized separately for each air pollutant. The resulting matrices show qualitative associations for grouped diseases, air pollutants, and their corresponding lagged concentrations and indicate the frequency of statistically significant positive associations. The results are presented in colour-gradient matrices with the number of associations for every combination of patient strata, pollutant, and lag in corresponding cells. The highest number of the associations was 8 (of 12 possible) obtained for the same day exposure to carbon monoxide, nitrogen dioxide, and days with elevated air quality health index (AQHI) values. For carbon monoxide, the number of the associations decreases with the increasing lags. For this air pollutant, there were almost no associations after 8 days of lag. In the case of nitrogen dioxide, the associations persist even for longer lags. The numerical values obtained from the models are provided for every pollutant. The constructed matrices are a useful tool to analyze the impact of ambient air pollution concentrations on public health.

The Air Quality Health Index and all emergency department visits

Through a variety of media formats, the Air Quality Health Index (AQHI) has served as a valuable communication tool for the general Canadian population for several years. This index, calculated and communicated to the public on an hourly basis, is designed to provide important information on the impact of air quality on health. This presentation outlines the association between AQHI values and, for the first time, all-cause emergency department (ED) visits (over one million diagnosed ED visits). It is assumed that a higher AQHI value, reflecting increased health risk, will encourage people to take steps to reduce their exposure, by limiting the duration and intensity of outdoor activity. The case-crossover methodology was used to assess the associations between the considered exposure and ED visits. The results, the estimated odds ratios, are presented as non-linear concentration-response functions. We argue that air health effects, measured as the total number of all-cause ED visits, are related to the values of the AQHI. We postulate that there are differences in this association between males and females, possibly due to gender-specific behavior and/or health conditions.

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.

Ambient air pollution exposure and emergency department visits for substance abuse

There is growing evidence supporting the notion that exposure to air pollution can contribute to cognitive and psychiatric disorders, including depression and suicide. Given the relationship between exposure to acute stressors and substance abuse, the present study assessed the association between exposure to ambient air pollution and emergency department (ED) visits for alcohol and drug abuse. ED visit data selected according to International Classification of Disease (ICD-9) coding 303 (alcohol dependence syndromes) and 305 (non-dependent abuse of drugs) were collected in five hospitals in Edmonton, Canada. A time-stratified case crossover design was used. Conditional logistic regression was applied to calculate odds ratios (OR) and 95% confidence intervals (95% CI). Season, temperature, and relative humidity were adjusted for using natural splines.

Results are reported for an increase in pollutant concentrations equivalent to one interquartile range (IQR). Statistically significant positive associations with substance abuse were observed for CO, NO₂ and particulate matter with an aerodynamic diameter less than 10 μm (PM₁₀) and 2.5 μm (PM_2.5). The strongest results were obtained in the cold period (October–March) for 1-day lagged CO (OR = 1.03, 95% CI: 1.01, 1.05, IQR = 0.4 ppm) and NO₂ (OR = 1.04, 95% CI: 1.01, 1.07, IQR = 12.8 ppb); ORs were also significant for CO and NO₂ with lags of 2 to 6 days and 2 to 7 days, respectively. The study suggests that, even at low levels, increases in ambient CO, NO₂, and PMs are associated with increased hospital admissions for substance abuse, possibly as a result of impacts of air quality on mental health or depression.

Air pollution and emergency department visits for respiratory diseases: A multi-city case crossover study

Increasing evidence suggests that ambient air pollution is a major risk factor for both acute and chronic respiratory disease exacerbations and emergencies. The objective of this study was to determine the association between ambient air pollutants and emergency department (ED) visits for respiratory conditions in nine districts across the province of Ontario in Canada. Health, air pollutant (PM_2.5, NO₂, O₃, and SO₂), and meteorological data were retrieved from April 2004 to December 2011. Respiratory diseases were categorized as: chronic obstructive pulmonary disease (COPD, including bronchiectasis) and acute upper respiratory diseases. A case-crossover design was used to test the associations between ED visits and ambient air pollutants, stratified by sex and season. For COPD among males, positive results were observed for NO₂ with lags of 3-6 days, for PM_2.5 with lags 1-8, and for SO₂ with lags of 4-8 days. For COPD among females, positive results were observed for O₃ with lags 2-4 days, and for SO₂ among lags of 3-6 days. For upper respiratory disease emergencies among males, positive results were observed for NO₂ (lags 5-8 days), for O₃, (lags 0-6 days), PM_2.5 (all lags), and SO₂ (lag 8), and among females, positive results were observed for NO₂ for lag 8 days, for O₃, PM_2.5 among all lags. Our study provides evidence of the associations between short-term exposure to air pollution and increased risk of ED visits for upper and lower respiratory diseases in an environment where air pollutant concentrations are relatively low.

UNMIX Methods Applied to Characterize Sources of Volatile Organic Compounds in Toronto, Ontario

UNMIX, a sensor modeling routine from the U.S. Environmental Protection Agency (EPA), was used to model volatile organic compound (VOC) receptors in four urban sites in Toronto, Ontario. VOC ambient concentration data acquired in 2000-2009 for 175 VOC species in four air quality monitoring stations were analyzed. UNMIX, by performing multiple modeling attempts upon varying VOC menus-while rejecting the results that were not reliable-allowed for discriminating sources by their most consistent chemical characteristics. The method assessed occurrences of VOCs in sources typical of the urban environment (traffic, evaporative emissions of fuels, banks of fugitive inert gases), industrial point sources (plastic-, polymer-, and metalworking manufactures), and in secondary sources (releases from water, sediments, and contaminated urban soil). The remote sensing and robust modeling used here produces chemical profiles of putative VOC sources that, if combined with known environmental fates of VOCs, can be used to assign physical sources' shares of VOCs emissions into the atmosphere. This in turn provides a means of assessing the impact of environmental policies on one hand, and industrial activities on the other hand, on VOC air pollution.

Air Pollution and Emergency Department Visits for Depression: A Multicity Case-Crossover Study

BACKGROUND

The aim of this study was to investigate the associations between ambient air pollution and emergency department (ED) visits for depression.

METHODS

Health data were retrieved from the National Ambulatory Care Reporting System. ED visits for depression were retrieved from the National Ambulatory Care Reporting System using the International Classification of Diseases (ICD-10), Tenth revision codes; ICD-10: F32 (mild depressive episode) and ICD-10: F33 (recurrent depressive disorder). A case-crossover design was employed for this study. Conditional logistic regression models were used to estimate odds ratios.

RESULTS

For females, exposure to ozone was associated with increased risk of an ED visit for depression between 1 and 7 days after exposure, for males, between 1 and 5, and 8 days after exposure, with odds ratios ranging between 1.02 and 1.03.

CONCLUSIONS

These findings suggest that, as hypothesized, there is a positive association between exposure to air pollution and ED visits for depression.

A class of non-linear exposure-response models suitable for health impact assessment applicable to large cohort studies of ambient air pollution

The effectiveness of regulatory actions designed to improve air quality is often assessed by predicting changes in public health resulting from their implementation. Risk of premature mortality from long-term exposure to ambient air pollution is the single most important contributor to such assessments and is estimated from observational studies generally assuming a log-linear, no-threshold association between ambient concentrations and death. There has been only limited assessment of this assumption in part because of a lack of methods to estimate the shape of the exposure-response function in very large study populations. In this paper, we propose a new class of variable coefficient risk functions capable of capturing a variety of potentially non-linear associations which are suitable for health impact assessment. We construct the class by defining transformations of concentration as the product of either a linear or log-linear function of concentration multiplied by a logistic weighting function. These risk functions can be estimated using hazard regression survival models with currently available computer software and can accommodate large population-based cohorts which are increasingly being used for this purpose. We illustrate our modeling approach with two large cohort studies of long-term concentrations of ambient air pollution and mortality: the American Cancer Society Cancer Prevention Study II (CPS II) cohort and the Canadian Census Health and Environment Cohort (CanCHEC). We then estimate the number of deaths attributable to changes in fine particulate matter concentrations over the 2000 to 2010 time period in both Canada and the USA using both linear and non-linear hazard function models.

Ambient Sulphur Dioxide and Female ED Visits for Migraine

Ambient sulphur dioxide (SO(2)) concentrations may affect the number of female emergency department (ED) visits for migraine. ED visits diagnosed as migraine among females in two cities in Canada, Toronto (N = 704) and Ottawa (N = 3, 358), were analyzed. In the study case-crossover design was used. Conditional logistic regression was realized to estimate odds ratios (ORs) and their 95% confidence intervals (CIs) relative to an increase in an interquartile range (IQR, in Toronto IQR = 2.9 ppb, in Ottawa IQR = 3.9 ppb) of sulphur dioxide. In the constructed conditional logistic regression models, temperature and relative humidity were adjusted in the form of natural splines. In Toronto positive and statistically significant associations of sulphur dioxide with migraine ED visits were obtained: all ages, OR = 1.04 (95% CI: 1.00, 1.08); age group [15, 50], OR = 1.05 (95% CI: 1.01, 1.09). In Ottawa positive correlations were observed: all ages, OR = 1.05 (95% CI: 0.97, 1.13); age group [15, 50], OR = 1.06 (95% CI: 0.97, 1.15). The results suggest that female migraine may be affected by ambient sulphur dioxide.

Air pollution and emergency department visits for otitis media: a case-crossover study in Edmonton, Canada

BACKGROUND

Otitis media (OM) is one of the most common early childhood infections, resulting in an enormous economic burden to the health care system through unscheduled doctor visits and antibiotic prescriptions.

OBJECTIVES

The objective of this study was to investigate the potential association between ambient air pollution exposure and emergency department (ED) visits for OM.

MATERIALS AND METHODS

Ten years of ED data were obtained from Edmonton, Alberta, Canada, and linked to levels of air pollution: carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), sulfur dioxide, and particulate matter (PM) of median aerometric diameter < or = 10 and 2.5 pm (PM10 and PM2.5 respectively). A time-stratified case-crossover technique was applied to analyze the associations between ambient air pollution and health outcomes. Conditional logistic regression analysis with the subject's identification number as a stratum variable was used to obtain odds ratios (ORs) and their corresponding 95% confidence intervals after adjustment for meteorological factors.

RESULTS

We based the analysis on 14,527 ED visits for OM over 10 years in children 1-3 years of age. We observed statistically significant positive associations between ED visits for OM and interquartile increases in CO and NO2 levels after adjusting for ambient temperature and relative humidity. We observed the strongest associations (expressed by ORs) in the warmer months (April-September) in girls and all patients for exposure to CO and NO2, and in boys for exposure to CO, for 2 days before an OM ED visit.

CONCLUSIONS

These results support the hypothesis that ED visits for OM are associated with ambient air pollution.

Ambient ozone and emergency department visits for cellulitis

Objectives were to assess and estimate an association between exposure to ground-level ozone and emergency department (ED) visits for cellulitis. All ED visits for cellulitis in Edmonton, Canada, in the period April 1992-March 2002 (N = 69,547) were examined. Case-crossover design was applied to estimate odds ratio (OR, and 95% confidence interval) per one interquartile range (IQR) increase in ozone concentration (IQR = 14.0 ppb). Delay of ED visit relating to exposure was probed using 0- to 5-day exposure lags. For all patients in the all months (January-December) and lags 0 to 2 days, OR = 1.05 (1.02, 1.07). For male patients during the cold months (October-March): OR = 1.05 (1.02, 1.09) for lags 0 and 2 and OR = 1.06 (1.02, 1.10) for lag 3. For female patients in the warm months (April-September): OR = 1.12 (1.06, 1.18) for lags 1 and 2. Cellulitis developing on uncovered (more exposed) skin was analyzed separately, observed effects being stronger. Cellulitis may be associated with exposure to ambient ground level ozone; the exposure may facilitate cellulitis infection and aggravate acute symptoms.

Air pollution and emergency department visits for suicide attempts in vancouver, Canada

BACKGROUND

Comorbidity of depression, heart disease, and migraine has been observed in clinical practice, while ambient air pollution has been identified among different risk factors for these health conditions. Suicide attempts and ideations as the result of depression may be linked to air pollution exposure. Therefore the effects of ambient air pollution on emergency department (ED) visits for suicide attempts were investigated.

METHODS

Emergency visit data were collected in a hospital in Vancouver, Canada. The generalized linear mixed models technique was applied in the analysis of these data. A natural hierarchical structure of the data was used to define the clusters, with days nested in a 3-level structure (day of week, month, year). Poisson models were fitted to the clustered counts of ED visits with a single air pollutant, temperature and relative humidity. In addition, the case-crossover methodology was used with the same data for comparison. The analysis was performed by gender (all, males, females) and month (all: January-December, warm: April-September, cold: October-March).

RESULTS

Both hierarchical and case-crossover methods confirmed positive and statistically significant associations among carbon monoxide (CO), nitrogen dioxide (NO(2)), sulphur dioxide (SO(2)), and particulate matter (PM(10)) for all suicide attempts in the cold period. The largest increase was observed for males in the cold period for a 1-day lagged exposure to NO(2), with an excess risk of 23.9% (95% CI: 7.8, 42.4) and odds ratio of 1.21 (95% CI: 1.03, 1.41). In warm months the associations were not statistically significant, and the highest positive value was obtained for ozone lagged by 1 day.

CONCLUSION

The results indicate a potential association between air pollution and emergency department visits for suicide attempts.

Air pollution and emergency department visits for ischemic heart disease in Montreal, Canada

OBJECTIVES

We examined the associations between emergency department (ED) visits for ischemic heart disease (IHD) and short-term elevations in ambient air pollutants (CO and NO(2)).

MATERIALS AND METHODS

A hierarchical clusters design was used to study ED visits (n = 4979) for ischemic heart disease (ICD-9: 410-414) that occurred at a Montreal hospital between 1997 and 2002. The generalized linear mixed models technique was applied to create Poisson models for the clustered counts of ED visits for IHD. The analysis was done by gender for two age categories, all patients and patients aged over 64 years.

RESULTS

The results are presented as an excess risk increase associated with the interquartile range (IQR) of daily average of the pollutant concentration. The results for NO(2) (IQR = 9.5 ppb) were 5.9% (95% CI: 2.1-9.9) for all patients and 6.2% (95% CI: 1.2-11.4) for males; for patients aged over 64: 7.1% (95% CI: 2.5-11.9) for all patients, 9.1% (95% CI: 2.8-15.7) for males, and 6.5% (95% CI: 0.7-12.7) for females (for exposure lagged by 1-day). The results for CO (IQR = 0.2 ppm): 5.4% (95% CI: 2.3-8.5) for all patients, and 7.5% (95% CI: 3.6-11.6) for males. For patients aged over 64 years, 4.9% (95% CI: 1.3-8.7) for all patients, and 7.5% (95% CI: 2.6-12.6) for males. The results show the associations for the same day exposures.

CONCLUSIONS

The short-term effects of nitrogen dioxide and carbon monoxide are associated significantly with daily ED visits for ischemic heart disease. For NO(2) the associations are stronger for patients aged over 64 years. As indicated by our results, it is likely that vehicular traffic, a producer of NO(2) and CO, contributes to an increased number of ED visits for IHD.

Use of generalized linear mixed models to examine the association between air pollution and health outcomes

BACKGROUND

Time-series and case-crossover are two techniques that are widely used for assessing the short-term impact of ambient air pollution exposure on health.

MATERIALS AND METHODS

The generalized linear mixed model (GLMM) methodology is proposed here to study the association between ambient air pollution and health outcomes. Poisson random-effects models are applied to analyze the clustered counts, where the groups of days, determined by the triplet <day of week, month, year>, form the clusters. The proposed technique uses a nested structure for the clusters and allows random-effects for hierarchical factors. A random intercept in the models adjusts for different levels of counts among the clusters. A fixed slope represents a common response to the exposure.

RESULTS AND CONCLUSIONS

The obtained results are consistent with those generated by a classical approach (for example the case-crossover technique). The GLMM technique is a valid alternative methodology for studying air health effects.

Weather and emergency room visits for migraine headaches in Ottawa, Canada

BACKGROUND

Self-reported surveys have indicated that weather can trigger migraine headaches. However, to date, we know of no previous study that has examined the relationship between weather and emergency room (ER) visits for this condition.

OBJECTIVE

To examine associations between ER visits for migraines and selected meteorological conditions within the 24 hours preceding the visit.

DESIGN AND METHODS

A case-crossover design was used to study 4039 visits for migraines (ICD-9: 346) that occurred at an Ottawa hospital between 1993 and 2000. Meteorological conditions were defined using hourly readings from a fixed-site monitoring station. Conditional logistic regression was used to compare the occurrence of meteorological conditions during the 24 hours leading up to the time of the visit to control periods occurring 1 week before and after.

RESULTS

Precipitation-related weather events (fog, snow, rain, thunder) were not associated with migraine visits. Similarly, no associations were observed with changes in atmospheric pressure, wind speed, and relative humidity during the 24 hours preceding presentation. No statistically significant differences in the frequency distribution of clusters defined by relative humidity, atmospheric pressure, and temperature were found between case and control intervals. Conversely, a mean wind speed in excess of 19 km per hour was associated with a reduction in ER visits 8 to 12 hours later.

CONCLUSIONS

Our findings provide little support for the hypothesis that ER visits for migraines are related to weather conditions occurring within the 24 hours preceding presentation. These results should be interpreted cautiously as some comparisons are based on a small number of cases, and ER visits for migraine may represent a highly selective group of patients who suffer from this condition.

An overview of the report: correlation between carcinogenic potency and the maximum tolerated dose: implications for risk assessment

Current practice in carcinogen bioassay calls for exposure of experimental animals at doses up to and including the maximum tolerated dose (MTD). Such studies have been used to compute measures of carcinogenic potency such as the TD50 as well as unit risk factors such as q1 * for predicting low-dose risks. Recent studies have indicated that these measures of carcinogenic potency are highly correlated with the MTD. Carcinogenic potency has also been shown to be correlated with indicators of mutagenicity and toxicity. Correlation of the MTDs for rats and mice implies a corresponding correlation in TD50 values for these two species. The implications of these results for cancer risk assessment are examined in light of the large variation in potency among chemicals known to induce tumors in rodents.

A model-free approach to low-dose extrapolation

Estimates of risk associated with exposure to low levels of carcinogenic substances present in the environment are generally obtained by linear extrapolation from higher exposure levels at which risks can be estimated directly. In this paper, we examine the scientific basis for the assumption of low-dose linearity in carcinogenic risk assessment and the different statistical methods that have been proposed for linear extrapolation. A model-free approach to linear extrapolation is described and illustrated using epidemiological data on radiation carcinogenesis. The statistical properties of this method are empirically assessed using 572 selected sets of bioassay data.

Quantitative factors in chemical carcinogenesis: variation in carcinogenic potency

The quantitative assessment of toxicological data on the carcinogenic potential of chemicals requires consideration of a number of factors, including mathematical models of the mechanism of carcinogenic action and pharmacokinetic models for the metabolic activation of the parent compound to its reactive metabolite. In this article, the use of such models in estimating carcinogenic potency and in predicting risks at low levels of exposure is discussed, along with other factors involved in the evaluation of carcinogen bioassay data. The Carcinogenic Potency Database (CPDB) established by Gold et al. (1984, Environ. Health Perspect. 58, 9-322) is used to illustrate the application of quantitative approaches to carcinogenic risk assessment and to examine the variation in the potency of chemical carcinogens. Based on an analysis of 585 experiments selected from the CPDB, the risk-specific (10(-6) doses (RSDs) obtained by linear extrapolation from the TD50 were generally within a factor of 5-10 of those derived from the linearized multistage model. The RSDs obtained by linear extrapolation from the TD50 are roughly log-normally distributed with a median of about 20-90 ng/kg/day, depending on the subset of the CPDB considered. This distribution has been used by Rulis (1986, in Food Protection Technology (C. W. Felix, Ed.), pp. 29-37, Lewis, Chelsea, MI) to explore the concept of a threshold of regulation for chemical carcinogens present in the environment at low levels.