Associations between short/medium-term variations in black smoke air pollution and mortality in the Glasgow conurbation,UK

ObjectivesTo examine associations between short/medium-term variations in black smoke air pollution and mortality in the population of Glasgow and the adjacent towns of Renfrew and Paisley over a 25-year period at different time lags (0–30 days).MethodsGeneralised linear (Poisson) models were used to investigate the relationship between lagged black smoke concentrations and daily mortality, with allowance for confounding by cold temperature, between 1974 and 1998.ResultsWhen a range of lag periods were investigated significant associations were noted between temperature-adjusted black smoke exposure and all-cause mortality at lag periods of 13–18 and 19–24 days, and respiratory mortality at lag periods of 1–6, 7–12, and 13–18 days. Significant associations between cardiovascular mortality and temperature-adjusted black smoke were not observed. After adjusting for the effects of temperature a 10 μg m^− 3 increase in black smoke concentration on a given day was associated with a 0.9% [95% Confidence Interval (CI): 0.3–1.5%] increase in all cause mortality and a 3.1% [95% CI: 1.4–4.9%] increase in respiratory mortality over the ensuing 30-day period. In contrast for a 10 μg m^− 3 increase in black smoke concentration over 0–3 day lag period, the temperature adjusted exposure mortality associations were substantially lower (0.2% [95% CI: − 0.0–0.4%] and 0.3% [95% CI: − 0.2–0.8%] increases for all-cause and respiratory mortality respectively).ConclusionsThis study has provided evidence of association between black smoke exposure and mortality at longer lag periods than have been investigated in the majority of time series analyses.     

Changing patterns of the temperature–mortality association by time and location in the US,and implications for climate change

The shape of the non-linear relationship between temperature and mortality varies among cities with different climatic conditions. There has been little examination of how these curves change over space and time. We evaluated the short-term effects of hot and cold temperatures on daily mortality over six 7-year periods in 211 US cities, comprising over 42 million deaths. Cluster analysis was used to group the cities according to similar temperatures and relative humidity. Temperature–mortality functions were calculated using B-splines to model the heat effect (lag 0) and the cold effect on mortality (moving average lags 1–5). The functions were then combined through meta-smoothing and subsequently analyzed by meta-regression. We identified eight clusters. At lag 0, Cluster 5 (West Coast) had a RR of 1.14 (95% CI: 1.11,1.17) for temperatures of 27 °C vs 15.6 °C, and Cluster 6 (Gulf Coast) has a RR of 1.04 (95% CI: 1.03,1.05), suggesting that people are acclimated to their respective climates. Controlling for cluster effect in the multivariate-meta regression we found that across the US, the excess mortality from a 24-h temperature of 27 °C decreased over time from 10.6% to 0.9%. We found that the overall risk due to the heat effect is significantly affected by summer temperature mean and air condition usage, which could be a potential predictor in building climate-change scenarios.     

Cause-specific premature death from ambient PM2.5 exposure in India: Estimate adjusted for baseline mortality

In India, more than a billion population is at risk of exposure to ambient fine particulate matter (PM_2.5) concentration exceeding World Health Organization air quality guideline, posing a serious threat to health. Cause-specific premature death from ambient PM_2.5 exposure is poorly known for India. Here we develop a non-linear power law (NLP) function to estimate the relative risk associated with ambient PM_2.5 exposure using satellite-based PM_2.5 concentration (2001 − 2010) that is bias-corrected against coincident direct measurements. We show that estimate of annual premature death in India is lower by 14.7% (19.2%) using NLP (integrated exposure risk function, IER) for assumption of uniform baseline mortality across India (as considered in the global burden of disease study) relative to the estimate obtained by adjusting for state-specific baseline mortality using GDP as a proxy. 486,100 (811,000) annual premature death in India is estimated using NLP (IER) risk functions after baseline mortality adjustment. 54.5% of premature death estimated using NLP risk function is attributed to chronic obstructive pulmonary disease (COPD), 24.0% to ischemic heart disease (IHD), 18.5% to stroke and the remaining 3.0% to lung cancer (LC). 44,900 (5900–173,300) less premature death is expected annually, if India achieves its present annual air quality target of 40 μg m^− 3. Our results identify the worst affected districts in terms of ambient PM_2.5 exposure and resulting annual premature death and call for initiation of long-term measures through a systematic framework of pollution and health data archive.     

Effect of heat waves on morbidity and mortality due to Parkinson's disease in Madrid: A time-series analysis

BackgroundParkinson's disease (PD) is one of the factors which are associated with a higher risk of mortality during heat waves. The use of certain neuroleptic medications to control some of this disease's complications would appear to be related to an increase in heat-related mortality.ObjectiveTo analyse the relationship and quantify the short-term effect of high temperatures during heat wave episodes in Madrid on daily mortality and PD-related hospital admissions.MethodsWe used an ecological time-series study and fit Poisson regression models. We analysed the daily number of deaths due to PD and the number of daily PD-related emergency hospital admissions in the city of Madrid, using maximum daily temperature (°C) as the main environmental variable and chemical air pollution as covariates. We controlled for trend, seasonalities, and the autoregressive nature of the series.ResultsThere was a maximum daily temperature of 30 °C at which PD-related admissions were at a minimum. Similarly, a temperature of 34 °C coincides with an increase in the number of admissions. For PD-related admissions, the Relative Risk (RR) for every increase of 1 °C above the threshold temperature was 1.13 IC95%:(1.03–1.23) at lags 1 and 5; and for daily PD-related mortality, the RR was 1.14 IC95%:(1.01–1.28) at lag 3.ConclusionOur results indicate that suffering from PD is a risk factor that contributes to the excess morbidity and mortality associated with high temperatures, and is relevant from the standpoint of public health prevention plans.     

High resolution exposure modelling of heat and air pollution and the impact on mortality

BackgroundElevated temperature and air pollution have been associated with increased mortality. Exposure to heat and air pollution, as well as the density of vulnerable groups varies within cities. The objective was to investigate the extent of neighbourhood differences in mortality risk due to heat and air pollution in a city with a temperate maritime climate.MethodsA case-crossover design was used to study associations between heat, air pollution and mortality. Different thermal indicators and air pollutants (PM₁₀, NO₂, O₃) were reconstructed at high spatial resolution to improve exposure classification. Daily exposures were linked to individual mortality cases over a 15 year period.ResultsSignificant interaction between maximum air temperature (Ta_max) and PM₁₀ was observed. During “summer smog” days (Ta_max > 25 °C and PM₁₀ > 50 μg/m³), the mortality risk at lag 2 was 7% higher compared to the reference (Ta_max 15 °C and PM₁₀ 15 μg/m³). Persons above age 85 living alone were at highest risk.ConclusionWe found significant synergistic effects of high temperatures and air pollution on mortality. Single living elderly were the most vulnerable group. Due to spatial differences in temperature and air pollution, mortality risks varied substantially between neighbourhoods, with a difference up to 7%.     

Associations between ultrafine and fine particles and mortality in five central European cities — Results from the UFIREG study

BackgroundEvidence on health effects of ultrafine particles (UFP) is still limited as they are usually not monitored routinely. The few epidemiological studies on UFP and (cause-specific) mortality so far have reported inconsistent results.ObjectivesThe main objective of the UFIREG project was to investigate the short-term associations between UFP and fine particulate matter (PM) < 2.5 μm (PM_2.5) and daily (cause-specific) mortality in five European Cities. We also examined the effects of PM < 10 μm (PM₁₀) and coarse particles (PM_2.5–10).MethodsUFP (20–100 nm), PM and meteorological data were measured in Dresden and Augsburg (Germany), Prague (Czech Republic), Ljubljana (Slovenia) and Chernivtsi (Ukraine). Daily counts of natural and cardio-respiratory mortality were collected for all five cities. Depending on data availability, the following study periods were chosen: Augsburg and Dresden 2011–2012, Ljubljana and Prague 2012–2013, Chernivtsi 2013–March 2014. The associations between air pollutants and health outcomes were assessed using confounder-adjusted Poisson regression models examining single (lag 0–lag 5) and cumulative lags (lag 0–1, lag 2–5, and lag 0–5). City-specific estimates were pooled using meta-analyses methods.ResultsResults indicated a delayed and prolonged association between UFP and respiratory mortality (9.9% [95%-confidence interval: − 6.3%; 28.8%] increase in association with a 6-day average increase of 2750 particles/cm³ (average interquartile range across all cities)). Cardiovascular mortality increased by 3.0% [− 2.7%; 9.1%] and 4.1% [0.4%; 8.0%] in association with a 12.4 μg/m³ and 4.7 μg/m³ increase in the PM_2.5- and PM_2.5–10-averages of lag 2–5.ConclusionsWe observed positive but not statistically significant associations between prolonged exposures to UFP and respiratory mortality, which were independent of particle mass exposures. Further multi-centre studies are needed investigating several years to produce more precise estimates on health effects of UFP.     

The short-term effect of heat waves on mortality and its modifiers in China: An analysis from 66 communities

BackgroundMany studies have reported increased mortality risk associated with heat waves. However, few have assessed the health impacts at a nation scale in a developing country. This study examines the mortality effects of heat waves in China and explores whether the effects are modified by individual-level and community-level characteristics.MethodsDaily mortality and meteorological variables from 66 Chinese communities were collected for the period 2006–2011. Heat waves were defined as ≥ 2 consecutive days with mean temperature ≥ 95th percentile of the year-round community-specific distribution. The community-specific mortality effects of heat waves were first estimated using a Distributed Lag Non-linear Model (DLNM), adjusting for potential confounders. To investigate effect modification by individual characteristics (age, gender, cause of death, education level or place of death), separate DLNM models were further fitted. Potential effect modification by community characteristics was examined using a meta-regression analysis.ResultsA total of 5.0% (95% confidence intervals (CI): 2.9%–7.2%) excess deaths were associated with heat waves in 66 Chinese communities, with the highest excess deaths in north China (6.0%, 95% CI: 1%–11.3%), followed by east China (5.2%, 95% CI: 0.4%–10.2%) and south China (4.5%, 95% CI: 1.4%–7.6%). Our results indicate that individual characteristics significantly modified heat waves effects in China, with greater effects on cardiovascular mortality, cerebrovascular mortality, respiratory mortality, the elderly, females, the population dying outside of a hospital and those with a higher education attainment. Heat wave mortality effects were also more pronounced for those living in urban cities or densely populated communities.ConclusionHeat waves significantly increased mortality risk in China with apparent spatial heterogeneity, which was modified by some individual-level and community-level factors. Our findings suggest adaptation plans that target vulnerable populations in susceptible communities during heat wave events should be developed to reduce health risks.     

The impact of summer temperatures and heatwaves on mortality and morbidity in Perth,Australia 1994–2008

Climate change projections have drawn attention to the risks of extreme heat and the importance of public health interventions to minimise the impact. The city of Perth, Western Australia, frequently experiences hot summer conditions, with recent summers showing above average temperatures. Daily maximum and minimum temperatures, mortality, emergency department (ED) presentations and hospital admissions data were acquired for Perth for the period 1994 to 2008. Using an observed/expected analysis, the temperature thresholds for mortality were estimated at 34–36 °C (maximum) and 20 °C (minimum). Generalised estimating equations (GEEs) were used to estimate the percentage increase in mortality and morbidity outcomes with a 10 °C increment in temperature, with adjustment for air pollutants. Effect estimates are reported as incidence rate ratios (IRRs). The health impact of heatwave days (three or more days of ≥ 35 °C) was also investigated. A 9.8% increase in daily mortality (IRR 1.098; 95%CI: 1.007–1.196) was associated with a 10 °C increase in maximum temperature above threshold. Total ED presentations increased by 4.4% (IRR 1.044; 95%CI: 1.033–1.054) and renal-related ED presentations by 10.2% (IRR 1.102; 95%CI: 1.071–1.135) per 10 °C increase in maximum temperature. Heatwave days were associated with increases in daily mortality and ED presentations, while total hospital admissions were decreased on heatwave days. Public health interventions will be increasingly important to minimise the adverse health impacts of hot weather in Perth, particularly if the recent trend of rising average temperatures and more hot days continues as projected.     

Saharan dust,particulate matter and cause-specific mortality: A case–crossover study in Barcelona (Spain)

BackgroundStudies measuring health effects of Saharan dust based on large particulate matter (PM) fraction groups may be masking some effects. Long distant transport reduces the amount of heavier and larger particles in the Saharan air masses increasing the relative contribution of smaller particles that may be more innocuous. This study investigates the association between different PM fractions and daily mortality during Saharan and non-Saharan days in Barcelona, Spain.MethodsWe collected daily PM₁, PM_2.5–1 and PM_10–2.5 fractions, and cause-specific mortality (cardiovascular, respiratory and cerebrovascular) between March 2003 and December 2007. Changes of effects between Saharan and non-Saharan dust days were assessed using a time-stratified case–crossover design.ResultsDuring non-Saharan dust days we found statistically significant (p < 0.05) effects of PM_10–2.5 for cardiovascular (odds ratio for increase of an interquartile range, OR = 1.033, 95% confidence interval: 1.006–1.060) and respiratory mortality (OR = 1.044, 95% CI: 1.001–1.089). During Saharan dust days strongest cardiovascular effects were found for the same fraction (OR = 1.085, 95% CI: 1.017–1.158) with an indication of effect modification (p = 0.111). Effects of PM_2.5–1 during Saharan dust days were about the double than in non-dust days for cardiovascular and respiratory mortality, but these differences were not statistically significant.ConclusionOur results using independent fractions of PMs provide further evidence that the effects of short-term exposure to PM during Saharan dust days are associated with both cardiovascular and respiratory mortality. A better understanding of which of the different PM size fractions brought by Saharan dust is more likely to accelerate adverse effects may help better understand mechanisms of toxicity.     

Mortality attributable to extreme temperatures in Spain: A comparative analysis by city

BackgroundThe Low Temperature Days (LTD) have attracted far less attention than that of High Temperature Days (HTD), though its impact on mortality is at least comparable. This lower degree of attention may perhaps be due to the fact that its influence on mortality is less pronounced and longer-term, and that there are other concomitant infectious winters factors. In a climate-change scenario, the studies undertaken to date report differing results. The aim of this study was to analyse mortality attributable to both thermal extremes in Spain's 52 provinces across the period 2000–2009, and estimate the related economic cost to show the benefit or “profitability” of implementing prevention plans against LTD.MethodsPrevious studies enabled us: to obtain the maximum daily temperature above which HTD occurred and the minimum daily temperature below which LTD occurred in the 52 provincial capitals analysed across the same study period; and to calculate the relative and attributable risks (%) associated with daily mortality in each capital. These measures of association were then used to make different calculations to obtain the daily mean mortality attributable to both thermal extremes. To this end, we obtained a summary of the number of degrees whereby the temperature exceeded (excess °C) or fell short (deficit °C) of the threshold temperature for each capital, and calculated the respective number of extreme temperatures days. The economic estimates rated the prevention plans as being 68% effective.ResultsOver the period considered, the number of HTD (4373) was higher than the number of LTD (3006) for Spain as a whole. Notwithstanding this, in every provincial capital the mean daily mortality attributable to heat was lower (3 deaths/day) than that attributable to cold (3.48 deaths/day). In terms of the economic impact of the activation of prevention plans against LTD, these could be assumed to avoid 2.37 deaths on each LTD, which translated as a saving of €0.29M. Similarly, in the case of heat, 2.04 deaths could be assumed to be avoided each day on which the prevention plan against HTD was activated, amounting to a saving of €0.25M. While the economic cost of cold-related mortality across the ten-year period 2000–2009 was €871.7M, that attributable to heat could be put at €1093.2M.ConclusionThe effect of extreme temperatures on daily mortality was similar across the study period for Spain overall. The lower number of days with LTD meant, however, that daily cold-related mortality was higher than daily heat-related mortality, thereby making prevention plans against LTD more “profitable” prevention plans against HTD in terms of avoidable mortality.     

Climate change,extreme events and increased risk of salmonellosis in Maryland,USA: Evidence for coastal vulnerability

BackgroundSalmonella is a leading cause of acute gastroenteritis worldwide. Patterns of salmonellosis have been linked to weather events. However, there is a dearth of data regarding the association between extreme events and risk of salmonellosis, and how this risk may disproportionately impact coastal communities.MethodsWe obtained Salmonella case data from the Maryland Foodborne Diseases Active Surveillance Network (2002–2012), and weather data from the National Climatic Data Center (1960–2012). We developed exposure metrics related to extreme temperature and precipitation events using a 30 year baseline (1960–1989) and linked them with county-level salmonellosis data. Data were analyzed using negative binomial Generalized Estimating Equations.ResultsWe observed a 4.1% increase in salmonellosis risk associated with a 1 unit increase in extreme temperature events (incidence rate ratio (IRR):1.041; 95% confidence interval (CI):1.013–1.069). This increase in risk was more pronounced in coastal versus non-coastal areas (5.1% vs 1.5%). Likewise, we observed a 5.6% increase in salmonellosis risk (IRR:1.056; CI:1.035–1.078) associated with a 1 unit increase in extreme precipitation events, with the impact disproportionately felt in coastal areas (7.1% vs 3.6%).ConclusionsTo our knowledge, this is the first empirical evidence showing that extreme temperature/precipitation events—that are expected to be more frequent and intense in coming decades—are disproportionately impacting coastal communities with regard to salmonellosis. Adaptation strategies need to account for this differential burden, particularly in light of ever increasing coastal populations.     

Association between long-term exposure to air pollution and mortality in France: A 25-year follow-up study

IntroductionLong-term exposure to air pollution (AP) has been shown to have an impact on mortality in numerous countries, but since 2005 no data exists for France.ObjectivesWe analyzed the association between long-term exposure to air pollution and mortality at the individual level in a large French cohort followed from 1989 to 2013.MethodsThe study sample consisted of 20,327 adults working at the French national electricity and gas company EDF-GDF. Annual exposure to PM₁₀, PM_10–2.5, PM_2.5, NO₂, O₃, SO₂, and benzene was assessed for the place of residence of participants using a chemistry-transport model and taking residential history into account. Hazard ratios were estimated using a Cox proportional-hazards regression model, adjusted for selected individual and contextual risk factors. Hazard ratios were computed for an interquartile range (IQR) increase in air pollutant concentrations.ResultsThe cohort recorded 1967 non-accidental deaths. Long-term exposures to baseline PM_2.5, PM_10-25, NO₂ and benzene were associated with an increase in non-accidental mortality (Hazard Ratio, HR = 1.09; 95% CI: 0.99, 1.20 per 5.9 μg/m³, PM_10-25; HR = 1.09;95% CI: 1.04, 1.15 per 2.2 μg/m³, NO₂: HR = 1.14; 95% CI: 0.99, 1.31 per 19.3 μg/m³ and benzene: HR = 1.10; 95% CI: 1.00, 1.22 per 1.7 μg/m³).The strongest association was found for PM₁₀: HR = 1.14; 95% CI: 1.05, 1.25 per 7.8 μg/m³. PM₁₀, PM_10-25 and SO₂ were associated with non-accidental mortality when using time varying exposure. No significant associations were observed between air pollution and cardiovascular and respiratory mortality.ConclusionLong-term exposure to fine particles, nitrogen dioxide, sulfur dioxide and benzene is associated with an increased risk of non-accidental mortality in France. Our results strengthen existing evidence that outdoor air pollution is a significant environmental risk factor for mortality. Due to the limited sample size and the nature of our study (occupational), further investigations are needed in France with a larger representative population sample.     

Non-specific physical symptoms and electromagnetic field exposure in the general population: Can we get more specific? A systematic review

ObjectiveA systematic review of observational studies was performed to address the strength of evidence for an association between actual and perceived exposure to electromagnetic fields (EMF) and non-specific physical symptoms (NSPS) in the general population. To gain more insight into the magnitude of a possible association, meta-analyses were conducted.MethodsLiterature databases Medline, Embase, SciSearch, PsychInfo, Psyndex and Biosis and additional bibliographic sources such as reference sections of key publications were searched for the detection of studies published between January 2000 and April 2011.ResultsTwenty-two studies met our inclusion criteria. Qualitative assessment of the epidemiological evidence showed either no association between symptoms and higher EMF exposure or contradictory results. To strengthen our conclusions, random effects meta-analyses were performed, which produced the following results for the association with actual EMF; for symptom severity: Headache odds ratio (OR) = 1.65; 95% confidence interval (CI) = 0.88–3.08, concentration problems OR = 1.28; 95% CI = 0.56–2.94, fatigue-related problems OR = 1.15; 95% CI = 0.59–2.27, dizziness-related problems OR = 1.38; 95% CI = 0.92–2.07. For symptom frequency: headache OR = 1.01; 95% CI = 0.66–1.53, fatigue OR = 1.12; 95% CI = 0.60–2.07 and sleep problems OR = 1.18; 95% CI = 0.80–1.74. Associations between perceived exposure and NSPS were more consistently observed but a meta-analysis was not performed due to considerable heterogeneity between the studies.ConclusionsThis systematic review and meta-analysis finds no evidence for a direct association between frequency and severity of NSPS and higher levels of EMF exposure. An association with perceived exposure seems to exist, but evidence is still limited because of differences in conceptualization and assessment methods.     

Novel exposure biomarkers of N,N-diethyl-m-toluamide (DEET): Data from the 2007–2010 National Health and Nutrition Examination Survey

BackgroundN,N-diethyl-m-toluamide (DEET) is a widely used insect repellent in the United States.ObjectivesTo assess exposure to DEET in a representative sample of persons 6 years and older in the U.S. general population from the 2007–2010 National Health and Nutrition Examination Survey.MethodsWe analyzed 5348 urine samples by using online solid-phase extraction coupled to isotope dilution-high-performance liquid chromatography-tandem mass spectrometry. We used regression models to examine associations of various demographic parameters with urinary concentrations of DEET biomarkers.ResultsWe detected DEET in ~ 3% of samples and at concentration ranges (> 0.08 μg/L–45.1 μg/L) much lower than those of 3-(diethylcarbamoyl)benzoic acid (DCBA) (> 0.48 μg/L–30,400 μg/L) and N,N-diethyl-3-hydroxymethylbenzamide (DHMB) (> 0.09 μg/L–332 μg/L). DCBA was the most frequently detected metabolite (~ 84%). Regardless of survey cycle and the person's race/ethnicity or income, adjusted geometric mean concentrations of DCBA were higher in May–Sep than in Oct–Apr. Furthermore, non-Hispanic whites in the warm season were more likely than in the colder months [adjusted odds ratio (OR) = 10.83; 95% confidence interval (CI), 3.28–35.79] and more likely than non-Hispanic blacks (OR = 3.45; 95% CI, 1.51–7.87) to have DCBA concentrations above the 95th percentile.ConclusionsThe general U.S. population, including school-age children, is exposed to DEET. However, reliance on DEET as the sole urinary biomarker would likely underestimate the prevalence of exposure. Instead, oxidative metabolites of DEET are the most adequate exposure biomarkers. Differences by season of the year based on demographic variables including race/ethnicity likely reflect different lifestyle uses of DEET-containing products.     

Air pollution,ethnicity and telomere length in east London schoolchildren: An observational study

BackgroundShort telomeres are associated with chronic disease and early mortality. Recent studies in adults suggest an association between telomere length and exposure to particulate matter, and that ethnicity may modify the relationship. However associations in children are unknown.ObjectivesWe examined associations between air pollution and telomere length in an ethnically diverse group of children exposed to high levels of traffic derived pollutants, particularly diesel exhaust, and to environmental tobacco smoke.MethodsOral DNA from 333 children (8–9 years) participating in a study on air quality and respiratory health in 23 inner city London schools was analysed for relative telomere length using monochrome multiplex qPCR. Annual, weekly and daily exposures to nitrogen oxides and particulate matter were obtained from urban dispersion models (2008–10) and tobacco smoke by urinary cotinine. Ethnicity was assessed by self-report and continental ancestry by analysis of 28 random genomic markers. We used linear mixed effects models to examine associations with telomere length.ResultsTelomere length increased with increasing annual exposure to NO_x (model coefficient 0.003, [0.001, 0.005], p < 0.001), NO₂ (0.009 [0.004, 0.015], p < 0.001), PM_2.5 (0.041, [0.020, 0.063], p < 0.001) and PM₁₀ (0.096, [0.044, 0.149], p < 0.001). There was no association with environmental tobacco smoke. Telomere length was increased in children reporting black ethnicity (22% [95% CI 10%, 36%], p < 0.001)ConclusionsPollution exposure is associated with longer telomeres in children and genetic ancestry is an important determinant of telomere length. Further studies should investigate both short and long-term associations between pollutant exposure and telomeres in childhood and assess underlying mechanisms.     

Estimating and projecting the effect of cold waves on mortality in 209 US cities

The frequency, duration, and intensity of cold waves are expected to decrease in the near future under the changing climate. However, there is a lack of understanding on future mortality related to cold waves. The present study conducted a large-scale national projection to estimate future mortality attributable to cold waves during 1960–2050 in 209 US cities. Cold waves were defined as two, three, or at least four consecutive days with daily temperature lower than the 5th percentile of temperatures in each city. The lingering period of a cold wave was defined as the non-cold wave days within seven days following that cold wave period. First, with 168 million residents in 209 US cities during 1962–2006, we fitted over-dispersed Poisson regressions to estimate the immediate and lingering effects of cold waves on mortality and tested if the associations were modified by the duration of cold waves, the intensity of cold waves, and mean winter temperature (MWT). Then we projected future mortality related to cold waves using 20 downscaled climate models. Here we show that the cold waves (both immediate and lingering) were associated with an increased but small risk of mortality. The associations varied substantially across climate regions. The risk increased with the duration and intensity of cold waves but decreased with MWT. The projected mortality related to cold waves would decrease from 1960 to 2050. Such a decrease, however, is small and may not be able to offset the potential increase in heat-related deaths if the adaptation to heat is not adequate.     

Long-term exposure to traffic-related PM10 and decreased heart rate variability: Is the association restricted to subjects taking ACE inhibitors?

BackgroundAlterations in heart rate variability (HRV) are a potential link between exposure to traffic-related air pollution and cardiovascular mortality.ObjectivesWe investigated whether long-term exposure to traffic-related PM₁₀ (TPM₁₀) is associated with HRV in older subjects and/or in participants taking specific cardiovascular treatment or with self-reported heart disease.MethodsWe included 1607 subjects from the general population aged 50 to 72 years. These participants from the SAPALDIA cohort underwent ambulatory 24-hr electrocardiogram monitoring. Associations of average annual exposure to TPM₁₀ over 10 years with HRV parameters from time and frequency domains were estimated using multivariable mixed linear models. Effect estimates are expressed as percent changes in geometric means.ResultsHRV was only associated with TPM₁₀ in participants under ACE inhibitor therapy (N = 94). A 1 μg/m³ increment, approximately equivalent to an interquartile range, in 10 year average TPM₁₀ was associated with decrements of 14.5% (95% confidence interval (CI), − 25.9 to − 1.3) in high frequency (HF) power, of 4.5% (− 8.2 to − 0.5) in the standard deviation of all normal-to-normal RR intervals (SDNN), of 10.6% (− 18.5 to − 1.9) in total power (TP) and an increase of 9.2% (0.8 to 20.2) in the LF/HF power ratio.ConclusionsIn the absence of an overall effect our results suggest that alterations in HRV, a measure of autonomic control of the cardiac rhythm, may not be a central mechanism by which long-term exposure to TPM₁₀ increases cardiovascular mortality. Novel evidence on an effect in persons under ACE inhibitor treatment needs to be confirmed in future studies.     

Tobacco smoke increases the risk of otitis media among Greenlandic Inuit children while exposure to organochlorines remain insignificant

BackgroundPrenatal exposure to environmental levels of organochlorines (OCs) has been demonstrated to have immunotoxic effects in humans. We investigated the relationship between prenatal exposure to OCs and the occurrence of otitis media (OM) among Inuit children in Greenland.MethodsWe estimated the concentration of 14 PCB congeners and 11 pesticides in maternal and cord blood samples and in breast milk in a population-based cohort of 400 mother–child pairs. At follow-up, we examined the children's ears and used their medical records to assess the OM occurrence and severity. Multivariate regression analyses were used with adjustments for passive smoking, crowding, dietary habits, parent's educational level, breast feeding and the use of child-care.ResultsThe children were 4–10 years of age at follow-up and 223 (85%) participated. We found no association between prenatal OC exposure and the development of OM. Factors associated with the child's hazard of OM during the first 4 years of life were: mother's history of OM (HR 1.70, 95% CI 1.11–2.59, p = 0.01); mother's smoking habits: current (HR 2.47, 95% CI 1.45–4.21, p < 0.01) and previous (HR 2.00, 95% CI 1.19–3.36, p < 0.01); number of smokers in the home (HR 1.17, 95% CI 1.05–1.31, p < 0.01). After adjustment mothers' smoking habits remained significant.ConclusionWe found no relationship between high levels of prenatal exposure of OCs and occurrence of OM. Passive smoking was found as the strongest environmental risk factor for the development of OM.Interventions to reduce passive smoke in children's environment are needed.     

Chronic disease prevalence in women and air pollution — A 30-year longitudinal cohort study

BackgroundAir pollution, such as fine particulate matter (PM_2.5), can increase risk of adverse health events among people with heart disease, diabetes, asthma and chronic obstructive pulmonary disease (COPD) by aggravating these conditions. Identifying the influence of PM_2.5 on prevalence of these conditions may help target interventions to reduce disease morbidity among high-risk populations.ObjectivesThe objective of this study is to measure the association of exposure of PM_2.5 with prevalence risk of various chronic diseases among a longitudinal cohort of women.MethodsWomen from Ontario who enrolled in the Canadian National Breast Screening Study (CNBSS) from 1980 to 1985 (n = 29,549) were linked to provincial health administrative data from April 1, 1992 to March 31, 2013 to determine the prevalence of major chronic disease and conditions (heart disease, diabetes, asthma, COPD, acute myocardial infarction, angina, stroke and cancers). Exposure to PM_2.5 was measured using satellite data collected from January 1, 1998 to December 31, 2006 and assigned to resident postal-code at time of entry into study. Poisson regression models were used to describe the relationship between exposure to ambient PM_2.5 and chronic disease prevalence. Prevalence rate ratios (PRs) were estimated while adjusting for potential confounders: baseline age, smoking, BMI, marital status, education and occupation. Separate models were run for each chronic disease and condition.ResultsCongestive heart failure (PR = 1.31, 95% CI: 1.13, 1.51), diabetes (PR = 1.28, 95% CI: 1.16, 1.41), ischemic heart disease (PR = 1.22, 95% CI: 1.14, 1.30), and stroke (PR = 1.21, 95% CI: 1.09, 1.35) showed over a 20% increase in PRs per 10 μg/m³ increase in PM_2.5 after adjusting for risk factors. Risks were elevated in smokers and those with BMI greater than 30.ConclusionsThis study estimated significant elevated prevalent rate ratios per unit increase in PM_2.5 in nine of the ten chronic diseases studied.     

Analysing the health effects of simultaneous exposure to physical and chemical properties of airborne particles

BackgroundAirborne particles are a complex mix of organic and inorganic compounds, with a range of physical and chemical properties. Estimation of how simultaneous exposure to air particles affects the risk of adverse health response represents a challenge for scientific research and air quality management. In this paper, we present a Bayesian approach that can tackle this problem within the framework of time series analysis.MethodsWe used Dirichlet process mixture models to cluster time points with similar multipollutant and response profiles, while adjusting for seasonal cycles, trends and temporal components. Inference was carried out via Markov Chain Monte Carlo methods. We illustrated our approach using daily data of a range of particle metrics and respiratory mortality for London (UK) 2002–2005. To better quantify the average health impact of these particles, we measured the same set of metrics in 2012, and we computed and compared the posterior predictive distributions of mortality under the exposure scenario in 2012 vs 2005.ResultsThe model resulted in a partition of the days into three clusters. We found a relative risk of 1.02 (95% credible intervals (CI): 1.00, 1.04) for respiratory mortality associated with days characterised by high posterior estimates of non-primary particles, especially nitrate and sulphate. We found a consistent reduction in the airborne particles in 2012 vs 2005 and the analysis of the posterior predictive distributions of respiratory mortality suggested an average annual decrease of − 3.5% (95% CI: − 0.12%, − 5.74%).ConclusionsWe proposed an effective approach that enabled the better understanding of hidden structures in multipollutant health effects within time series analysis. It allowed the identification of exposure metrics associated with respiratory mortality and provided a tool to assess the changes in health effects from various policies to control the ambient particle matter mixtures.