Temperature, air pollution, and hospitalization for cardiovascular diseases among elderly people in Denver

Analysis of weather exposure 7 days before occurrence of ST-segment elevation myocardial infarction

BACKGROUND

Several studies have highlighted the relationship between weather patterns and the occurrence of ST-elevation myocardial infarction (STEMI).

AIM

To evaluate the statistical association between the occurrence of STEMI and meteorological variables over the preceding 7 days.

METHODS

This was a retrospective study, using prespecified data from the ORBI (Breton Regional Observatory on Myocardial Infarction) registry, which includes all consecutive patients hospitalized for STEMI in the geographical area of Brest, France. Over a 7-year period, we compared the number of STEMIs per week with the mean values of meteorological variables over the preceding 7 days.

RESULTS

Overall, 7517 patients with STEMI were recorded in the ORBI registry between January 2009 and January 2016. After exclusion of patients not living in the geographical area of interest, 742 patients were included. The weekly incidence of STEMI ranged from 0 to 7 (median 2, interquartile range 1-3). In the univariate analysis, air temperature (odds ratio [OR] 1.05, 95% confidence interval [CI] 1.005-1.01 per 1°C decrease; P=0.03) and atmospheric pressure (OR 1.03, 95% CI 1.01-1.06 per 1 hPa increase; P=0.008) were associated with the weekly incidence of STEMI. In the multivariable analysis, air temperature (OR 1.06, 95% CI 1.01-1.10 per 1°C decrease; P=0.01), atmospheric pressure (OR 1.05, 95% CI 1.02-1.08 per 1 hPa increase; P<0.001) and duration of humidity>80% (OR 1.09, 95% CI 1.02-1.15 per 1hour increase; P=0.007) in the previous 7 days were associated with the occurrence of STEMI.

CONCLUSIONS

In this specific geographical area, occurrence of STEMI was statistically associated with a decrease in air temperature, an increase in atmospheric pressure and an increase in humidity over the preceding 7-day period.

Elderly Mortality and Exposure to Fine Particulate Matter and Ozone

BACKGROUND

The effects on particulate matter (PM) and ozone on health are being reported by a number of studies. The effects of these air pollutants are likely to be stronger in the elderly population, but studies in this regard are scarce. The purpose of this study was to study the effects of PM ≤ 2.5 μ and ozone on chronic health effects of the elderly population.

METHODS

In order to analyze the health status of the elderly population, National Statistical Office Mortality records were used. In this study, we calculated the number of deaths in Seoul of people who were 60 years or older between 2002 and 2012. The current study analyzed each disorder separately and the lag effect. PM and ozone were analyzed using the single exposure model, as well as the adjusted multi exposure model.

RESULTS

In the single exposure analysis with PM2.5 as the exposure variable, with the increase of 10 μ/m³, the number of deaths increased by 1.0039 fold, and vascular disease 1.0053 fold. In the multi exposure model adjusting for ozone, the number of deaths increased by 1.0037 fold, and vascular disease 1.0049 fold. In the single exposure analysis with ozone as the exposure variable, with the increase of 10 ppb, the number of deaths increased by 1.0038 fold, and in the multi exposure model adjusting for PM2.5, the number of deaths increased by 1.0027 fold. These results differed depending on the period or season. There was a 5-day lag effect between PM2.5 and deaths in the multi exposure model, and 1.0028 fold when adjusted for ozone. There was a 1-day lag effect in single exposure models with ozone as the main variable, and 1.0027 fold increase in deaths.

CONCLUSION

In our study, an increase in the number of deaths in the elderly population in accordance with the increase in the PM2.5 and ozone was found. The association found in our study could also influence socioeconomic burden. Future studies need to be performed in regards to younger population, as well as other air pollutants.

Daily ambient temperature is associated with biomarkers of kidney injury in older Americans

BACKGROUND

Increases in ambient temperature have recently been associated with increased emergency department visits and hospital admissions for acute renal failure. However, potential biological mechanisms through which short-term ambient temperature affects kidney function are not known.

METHODS

We used multiple regression models to evaluate the association between 1- and 3-day average, ambient temperature levels and two biomarkers of kidney injury (neutrophil gelatinase-associated lipocalin (NGAL) and adiponectin), among 3377 individuals over 57 years of age enrolled in the National Social Life, Health, and Aging Project. Ambient temperature was estimated on a 6-km grid covering the conterminous United States using ambient temperature measurements obtained from the National Climatic Data Center (NCDC). NGAL and adiponectin levels were measured from whole blood collected for each participant. All health effect models were adjusted for a number of demographics, socioeconomic, health behavior, medical history variables, with non-linear exposure-response relationships examined using natural cubic splines.

RESULTS

The relationship between 1- and 3-day average temperature and both NGAL and adiponectin levels was significant and non-linear, with largely null associations below 10 °C, and positive association for temperatures >10 °C. In fully adjusted, linear multiple regression models restricted to >10 °C, NGAL and adiponectin levels increased by 1.89% (95% CI: 0.77, 3.91) and 2.51% (95% CI: 1.34, 3.69), respectively, for a 1 °C increase in daily average temperature. Additionally, every 1 °C increase in temperature over 10 °C was associated with a 1.83% increased odds of having plasma NGAL levels consistent with acute kidney injury (>150 μg/L).

CONCLUSIONS

In a cohort of older men and women in the United States, our study is the first to observe that short-term ambient temperature exposures were significantly associated with biomarkers of kidney injury. These associations suggest that ambient temperature exposures could be an important risk factor for renal pathology.

Ambient temperature and mortality due to acute myocardial infarction in Brazil: an ecological study of time-series analyses

Ambient temperature may lead to decompensation of cardiovascular diseases and deaths by acute myocardial infarction (AMI). Little is known about this relationship in South American countries located in regions of a hot climate. This study aims to investigate the effects of ambient temperature on mortality due to AMI in six Brazilian micro-regions, which present different climates. We analyzed daily records of deaths by AMI between 1996 and 2013. We estimated the accumulate relative and attributable risks with lags of up to 14 days, using distributed non-linear lag model. Micro-regions that were closest to the equator did not show an association between temperature and mortality. The lowest risk temperatures varied between 22 °C and 28 °C, in the Southern region of Brazil and the Midwest region, respectively. Low temperatures associated with the highest mortality risk were observed in the same areas, varying between 5 °C and 15 °C. The number of deaths attributed to cold temperatures varied from 176/year in Brasilia to 661/year in São Paulo and those deaths attributed to hot temperatures in Rio de Janeiro amounted to 115/year. We showed the relative risk and the attributable risk of warmer and colder days in tropical regions. The estimate of the number of deaths due to climate, varying according to each area, is a way of bringing information to those responsible for health policies based on easily-understood measurements.

Impact of Extremely Hot Days on Emergency Department Visits for Cardiovascular Disease among Older Adults in New York State

Prior studies have reported the impact of ambient heat exposure on heat-related illnesses and mortality in summer, but few have assessed its effect on cardiovascular diseases (CVD) morbidity, and the association difference by demographics and season. This study examined how extremely hot days affected CVD-related emergency department (ED) visits among older adults from 2005-2013 in New York State. A time-stratified case-crossover design was used to assess the heat-CVD association in summer and transitional months (April-May and September-October). Daily mean temperature >95th percentile of regional monthly mean temperature was defined as an extremely hot day. Extremely hot days were found to be significantly associated with increased risk of CVD-related ED visits at lag day 5 (OR: 1.02, 95% CI: 1.01-1.04) and lag day 6 (OR: 1.01, 95% CI: 1.00-1.03) among older adults in summer after controlling for PM2.5 concentration, relative humidity, and barometric pressure. Specifically, there was a 7% increased risk of ischemic heart disease on the day of extreme heat, and increased risks of hypertension (4%) and cardiac dysrhythmias (6%) occurred on lag days 5 and 6, respectively. We also observed large geographic variations in the heat-CVD associations.

Exploration of the heterogeneous effect of climate change on ozone concentration in an urban environment

Ozone is a significant causative agent of mortality in cities. Urban environments are expressly vulnerable to global warming because of the extensive emission of air pollutants with urban heat island effect enhancing much rapidly the ozone concentration than in the less urbanized regions. This effect previously was not studied in local scale. It was hypothesized that climate change will cause heterogenic increase of ozone concentration in the different parts of the cities. To study this effect, the near-surface ozone concentration of 10 points of a Hungarian city was measured and modeled. At first step, the local correlations between solar radiation, air temperature, relative humidity and the near surface ozone concentrations at 3 m height were determined, specifying the local ozone-producing conditions. Then, based on the scenario of the Intergovernmental Panel on Climate Change 5th assessment report, the future seasonal near-surface ozone concentrations were modeled. Based on the model, it was determined that climate change will result in a heterogenic increase of near-surface ozone concentration.

Impacts of air pollution, temperature, and relative humidity on leukocyte distribution: An epigenetic perspective

BACKGROUND

Exploring the associations of air pollution and weather variables with blood leukocyte distribution is critical to understand the impacts of environmental exposures on the human immune system.

OBJECTIVES

As previous analyses have been mainly based on data from cell counters, which might not be feasible in epidemiologic studies including large populations of long-stored blood samples, we aimed to expand the understanding of this topic by employing the leukocyte distribution estimated by DNA methylation profiles.

METHODS

We measured DNA methylation profiles in blood samples using Illumina HumanMethylation450 BeadChip from 1519 visits of 774 Caucasian males participating in the Normative Aging Study. Leukocyte distribution was estimated using Houseman's and Horvath's algorithms. Data on air pollution exposure, temperature, and relative humidity within 28 days before each blood draw was obtained.

RESULTS

After fully adjusting for potential covariates, PM_2.5, black carbon, particle number, carbon monoxide, nitrogen dioxide, sulfur dioxide, temperature, and relative humidity were associated with the proportions of at least one subtype of leukocytes. Particularly, an interquartile range-higher 28-day average exposure of PM_2.5 was associated with 0.147-, 0.054- and 0.101-unit lower proportions (z-scored) of plasma cells, naïve CD8+ T cells, and natural killers, respectively, and 0.059- and 0.161-unit higher proportions (z-scored) of naïve CD4+ T cells and CD8+ T cells, respectively.

CONCLUSIONS

Our study suggests that short-term air pollution exposure, temperature, and relative humidity are associated with leukocyte distribution. Our study further provides a successful attempt to use epigenetic patterns to assess the influences of environmental exposures on human immune profiles.

Estimating policy-relevant health effects of ambient heat exposures using spatially contiguous reanalysis data

BACKGROUND

Regional National Weather Service (NWS) heat advisory criteria in New York State (NYS) were based on frequency of heat events estimated by sparse monitoring data. These may not accurately reflect temperatures at which specific health risks occur in large geographic regions. The objectives of the study were to use spatially resolved temperature data to characterize health risks related to summertime heat exposure and estimate the temperatures at which excessive risk of heat-related adverse health occurs in NYS. We also evaluated the need to adjust current heat advisory threshold and messaging based on threshold temperatures of multiple health outcomes.

METHODS

We assessed the effect of multi-day lag exposure for maximum near-surface air temperature (Tmax) and maximum Heat Index derived from the gridded National Land Data Assimilation System (NLDAS) reanalysis dataset on emergency department (ED) visits/ hospitalizations for heat stress, dehydration, acute kidney failure (AKF) and cardiovascular diseases (CVD) using a case-crossover analysis during summers of 2008-2012. We assessed effect modification using interaction terms and stratified analysis. Thresholds were estimated using piecewise spline regression.

RESULTS

We observed an increased risk of heat stress (Risk ratio (RR) = 1.366, 95% confidence interval (CI): 1.347, 1.386) and dehydration (RR = 1.024, 95% CI: 1.021, 1.028) for every 1 °C increase in Tmax on the day of exposure. The highest risk for AKF (RR = 1.017, 95% CI: 1.014, 1.021) and CVD (RR = 1.001, 95% CI: 1.000, 1.002) were at lag 1 and 4 respectively. The increased risk of heat-health effects persists up to 6 days. Rural areas of NYS are at as high a risk of heat-health effects as urban areas. Heat-health risks start increasing at temperatures much lower than the current NWS criteria.

CONCLUSION

Reanalysis data provide refined exposure-response functions for health research, in areas with sparse monitor observations. Based on this research, rural areas in NYS had similar risk for health effects of heat. Heat advisories in New York City (NYC) had been reviewed and lowered previously. As such, the current NWS heat advisory threshold was lowered for the upstate region of New York and surrounding areas. Enhanced outreach materials were also developed and disseminated to local health departments and the public.

Impact of temperature and air pollution on cardiovascular disease and death in Iran: A 15-year follow-up of Tehran Lipid and Glucose Study

In this, the first study to be conducted in the Middle East and North Africa (MENA) on the subject, we examined the impact of temperature and air pollution on cardiovascular disease (CVD) and all-cause mortality. The Tehran Lipid and Glucose Study followed 9731 participants, aged ≥30years (men=4409), during the period 1999-2014, reporting 1350 CVDs (men=796) and 725 deaths (men=447). Air pollution level was measured using the air quality index (AQI). Data were analyzed using the distributed lag nonlinear model, with 30°C temperature and AQI=50 minimum risk values, as the relative risks' (RR) reference values. Although for the whole sample, no significant effect of air pollution was observed on CVD, for the under 60year olds, two significant peaks occurred in AQI=180 at lags 2 and 6days (RR=1.94, 95% CI: 1.02-3.67 and 2.06, 95% CI: 1.09-3.88, respectively). Temperature had no significant effect on CVD, yet the closest case to significance happened at 36°C and lag 5days (RR=1.43, 95% CI: 0.97-2.11), for ages ≥60y. The largest significant effects of air pollution on death, occurred in AQI=180 and lag 1day (RR=2.40, 95% CI: 1.0.-5.59 and 3.29, 95% CI: 1.15-9.36, for the whole sample and the <60year olds, respectively). Interestingly, for those aged over 60years, the peak belonged to AQI=180 and lag 7days (RR=2.16, 95% CI: 1.11-4.19). Regarding the effect of temperature on death among the whole sample, the highest risk was for 6°C and lag 0 (RR=3.91, 95% CI: 1.12-13.61). For the ≥60year olds, it occurred in 9⁺ and lag 0 (RR=6.81, 95% CI: 1.69-27.44), though notably, the peak went to -3°C and lag 3 (RR=5.69, 95% CI: 1.12-28.87), for those aged <60years. Overall, the effect of low temperature on death had the highest risk, for the over 60-year-olds, without any lag. Moreover, the <60-year-olds were the most vulnerable group to air pollution with a one day lag, in terms of mortality risk.

Asian Culturally Specific Predictors in a Large-Scale Land Use Regression Model to Predict Spatial-Temporal Variability of Ozone Concentration

This paper developed a land use regression (LUR) model to study the spatial-temporal variability of O₃ concentrations in Taiwan, which has typical Asian cultural characteristics with diverse local emission sources. The Environmental Protection Agency's (EPA) data of O₃ concentrations from 2000 and 2013 were used to develop this model, while observations from 2014 were used as the external data verification to assess model reliability. The distribution of temples, cemeteries, and crematoriums was included for a potential predictor as an Asian culturally specific source for incense and joss money burning. We used stepwise regression for the LUR model development, and applied 10-fold cross-validation and external data for the verification of model reliability. With the overall model R² of 0.74 and a 10-fold cross-validated R² of 0.70, this model presented a mid-high prediction performance level. Moreover, during the stepwise selection procedures, the number of temples, cemeteries, and crematoriums was selected as an important predictor. By using the long-term monitoring data to establish an LUR model with culture specific predictors, this model can better depict O₃ concentration variation in Asian areas.

Study of the Effects of Air Pollutants on Human Health Based on Baidu Indices of Disease Symptoms and Air Quality Monitoring Data in Beijing, China

There is an increasing body of evidence showing the impact of air pollutants on human health such as on the respiratory, and cardio- and cerebrovascular systems. In China, as people begin to pay more attention to air quality, recent research focused on the quantitative assessment of the effects of air pollutants on human health. To assess the health effects of air pollutants and to construct an indicator placing emphasis on health impact, a generalized additive model was selected to assess the health burden caused by air pollution. We obtained Baidu indices (an evaluation indicator launched by Baidu Corporation to reflect the search popularity of keywords from its search engine) to assess daily query frequencies of 25 keywords considered associated with air pollution-related diseases. Moreover, we also calculated the daily concentrations of major air pollutants (including PM10, PM2.5, SO₂, O₃, NO₂, and CO) and the daily air quality index (AQI) values, and three meteorological factors: daily mean wind level, daily mean air temperature, and daily mean relative humidity. These data cover the area of Beijing from 1 March 2015 to 30 April 2017. Through the analysis, we produced the relative risks (RRs) of the six main air pollutants for respiratory, and cardio- and cerebrovascular diseases. The results showed that O₃ and NO₂ have the highest health impact, followed by PM10 and PM2.5. The effects of any pollutant on cardiovascular diseases was consistently higher than on respiratory diseases. Furthermore, we evaluated the currently used AQI in China and proposed an RR-based index (health AQI, HAQI) that is intended for better indicating the effects of air pollutants on respiratory, and cardio- and cerebrovascular diseases than AQI. A higher Pearson correlation coefficient between HAQI and RRTotal than that between AQI and RRTotal endorsed our efforts.

Effects of Extreme Temperatures on Mortality and Hospitalization in Ho Chi Minh City, Vietnam

There is a lack of research focusing on the association of temperature with mortality and hospitalization in developing countries with tropical climates and a low capacity to cope with the influences of extreme weather events. This study aimed to examine and compare the effect of temperature, including heat waves, on mortality and hospitalization in the most populous city of Vietnam. We used quasi-Poisson time series regression coupled with the distributed lag non-linear model (DLNM) to examine the overall pattern and compare the temperature-health outcome relationship. The main and added effects of heat waves were evaluated. The main effect of heat waves significantly increased the risk of all cause-specific mortality. Significant main effects of heat waves on hospitalization were observed only for elderly people and people with respiratory diseases (elderly, relative risk (RR) = 1.28, 95% confidence interval (CI) = 1.14–3.45; respiratory diseases, RR = 1.3, 95% CI = 1.19–1.42). The RRs of the main effect were substantially higher than those of the added effect in mortality; the same was applicable for hospitalizations of people with respiratory diseases and elderly people. The findings of this study have important implications for public health adaptation and prevention program implementation in the protection of residents from the adverse health effects of temperature.

Satellite-Based Spatiotemporal Trends of Canopy Urban Heat Islands and Associated Drivers in China’s 32 Major Cities

The urban heat island (UHI) effect, in which urbanized areas tend to have warmer conditions compared to their rural surroundings, has drawn increasing attention in recent years. Using ground-based and satellite remote sensing data, we present a method to quantify the spatial pattern and diurnal and seasonal variations in canopy layer heat islands (CLHIs) in China’s 32 major cities during 2009 and investigate their relationships with built-up intensity (BI), nighttime lights, vegetation activity, surface albedo, and surface urban heat island intensity (SUHII). The results show that both the annual daytime and nighttime CLHI intensities (CLHIIs) were positive ranging from 0.2 °C to 2.2 °C and from 0.3 °C to 2.4 °C for these major cities, respectively. Higher CLHIIs were observed in the night, especially for northern parts of China. Along urban–rural gradients, the CLHI effect had an exponential decay shape and differed greatly by season. The CLHII distribution correlated positively and significantly to BI and nighttime lights. Vegetation activity was negatively correlated with the CLHII and more strongly in summer. Surface albedo showed an extremely weak correlation with the CLHII. In addition, CLHII had a strong correlation with SUHII. The annual daytime SUHII was 1.2 ± 1.1 °C (mean ± standard deviation) with 0.40 °C (95% confidence interval 0.36 to 0.44 °C) of annual daytime CLHII. The annual nighttime SUHII was 2.0 ± 0.8 °C with 1.04 °C (0.99 to 1.09 °C) of annual nighttime CLHII. Our results suggest that, reducing built-up intensity and anthropogenic heat emissions and increasing urban vegetation provide a co-benefit of mitigating SUHI and CLHI effects.

The reliability of an environmental epidemiology meta-analysis, a case study

Claims made in science papers are coming under increased scrutiny with many claims failing to replicate. Meta-analyses are questionable when based on data from observational studies which are often unreliable. We examine the reliability of the base studies used in an air quality/heart attack meta-analysis and the resulting meta-analysis. A meta-analysis study that includes 14 observational air quality/heart attack studies is examined for its statistical reliability. We use simple counting to evaluate the reliability of the base papers and a p-value plot of the p-values from the base studies to examine study heterogeneity. We find that the base papers have the potential for massive multiple testing and multiple modeling with no statistical adjustments. Statistics coming from the base papers are not guaranteed to be unbiased, a requirement for a valid meta-analysis. There is study heterogeneity for the base papers with strong evidence for so called p-hacking in some, possibly many, of the studies. We make two observations: there are many claims at issue in each of the 14 base studies so uncorrected multiple testing is a serious issue. We find that some of the base papers exhibit the characteristics of p-hacking and are therefore not reliable; the resulting meta-analysis is not reliable.

Effects of ambient carbon monoxide on daily hospitalizations for cardiovascular disease: a time-stratified case-crossover study of 460,938 cases in Beijing, China from 2013 to 2017

BACKGROUND

Evidence focused on exposure to ambient carbon monoxide (CO) and the risk of hospitalizations for cardiovascular diseases (CVD) is lacking in developing countries. This study aimed to examine the effect of CO exposure on hospitalizations for CVD in Beijing, China.

METHODS

A total of 460,938 hospitalizations for cardiovascular diseases were obtained from electronic hospitalization summary reports from 2013 to 2017. A time-stratified case-crossover design was conducted to investigate the association between CO exposure and hospitalizations for total and cause-specific CVD, including coronary heart disease (CHD), atrial fibrillation (AF), and heart failure (HF). Stratified analysis was also conducted by age group (18-64 years and ≥ 65 years) and sex.

RESULTS

Linear exposure-response curves for the association between ambient CO exposure and hospitalizations for CVD was observed. Ambient CO was positively associated with hospitalizations for total CVD and CHD. However, the observed increased risk was not statistically significant for hospitalizations for AF and HF. The strongest effect of CO concentration was observed on the current- and previous-day of exposure (lag _0-1 day). For a 1 mg/m³ increase in a 2-day moving average CO concentration, an increase of 2.8% [95% confidence interval (CI): 2.2 to 3.3%] and 3.0% (95% CI: 2.4 to 3.6%) in daily hospital admissions for CVD and CHD were estimated, respectively. This association was robust after adjusting for other copollutants and did not vary by age group and sex.

CONCLUSIONS

Ambient CO exposure increased the risk of hospitalizations for CVD, especially for CHD in Beijing. Further studies are warranted to explore the association between ambient CO and hospitalizations for AF and HF.

Health effects of seasonal variation in cardiovascular hemodynamics among workers in forest environments

Seasonal variation in cardiovascular functions (CVFs) associated with climatic changes is an important emerging public health issue. The objectives of this study were to demonstrate seasonal variation in CVFs by comparing intra-individual differences between winter and summer among people working in a forest environment and to discuss the possible mechanisms accounting for the health effects of seasonal variation in cardiovascular hemodynamics. A total of 72 staff members of the Experimental Forest of National Taiwan University were recruited for continuous health monitoring during two seasons to investigate the intra-individual seasonal variation in CVFs, complete blood counts, and biochemical examinations. CVFs were assessed by measuring the arterial pressure waveform by a cuff sphygmomanometer using an oscillometric blood pressure device, and aortic stiffness was measured by brachial-ankle pulse wave velocity (baPWV). The results showed that cholesterol levels, white and red blood cell counts, and platelet counts were higher in winter than in summer. Subjects showed not only higher vascular stress, as indicated by higher levels of brachial systolic and diastolic blood pressure (SBP and DBP), central end-SBP and DBP, systemic vascular resistance (SVR), and baPWV, but also lower cardiac activities, including lower levels of heart rate, left ventricular contractility, and cardiac output in winter than in summer. The central and brachial BP, cardiac output, SVR, and baPWV were significantly associated with temperature changes in seasonal variation after controlling related confounding factors. This study provides evidence of higher vascular stress and susceptibility to atherothrombosis during winter compared with summer.

Effects of ambient temperature on myocardial infarction: A systematic review and meta-analysis

Previous studies have suggested that ambient temperature is associated with the mortality and morbidity of myocardial infarction (MI) although consistency among these investigations is lacking. We performed a meta-analysis to investigate the relationship between ambient temperature and MI. The PubMed, Web of Science, and China National Knowledge Infrastructure databases were searched back to August 31, 2017. The pooled estimates for different temperature exposures were calculated using a random-effects model. The Cochran's Q test and coefficient of inconsistency (I²) were used to evaluate heterogeneity, and the Egger's test was used to assess publication bias. The exposure-response relationship of temperature-MI mortality or hospitalization was modeled using random-effects meta-regression. A total of 30 papers were included in the review, and 23 studies were included in the meta-analysis. The pooled estimates for the relationship between temperature and the relative risk of MI hospitalization was 1.016 (95% confidence interval [CI]: 1.004-1.028) for a 1 °C increase and 1.014 (95% CI: 1.004-1.024) for a 1 °C decrease. The pooled estimate of MI mortality was 1.639 (95% CI: 1.087-2.470) for a heat wave. The heterogeneity was significant for heat exposure, cold exposure, and heat wave exposure. The Egger's test revealed potential publication bias for cold exposure and heat exposure, whereas there was no publication bias for heat wave exposure. An increase in latitude was associated with a decreased risk of MI hospitalization due to cold exposure. The association of heat exposure and heat wave were immediate, and the association of cold exposure were delayed. Consequently, cold exposure, heat exposure, and exposure to heat waves were associated with an increased risk of MI. Further research studies are required to understand the relationship between temperature and MI in different climate areas and extreme weather conditions.

The Impact of Heat Waves on Emergency Department Admissions in Charlottesville, Virginia, U.S.A

Heat waves have been linked to increases in emergency-related morbidity, but more research is needed on the demographic and disease-specific aspects of these morbidities. Using a case-crossover approach, over 700,000 daily emergency department hospital admissions in Charlottesville, Virginia, U.S.A. from 2005–2016 are compared between warm season heat wave and non-heat wave periods. Heat waves are defined based on the exceedance, for at least three consecutive days, of two apparent temperature thresholds (35 °C and 37 °C) that account for 3 and 6% of the period of record. Total admissions and admissions for whites, blacks, males, females, and 20–49 years old are significantly elevated during heat waves, as are admissions related to a variety of diagnostic categories, including diabetes, pregnancy complications, and injuries and poisoning. Evidence that heat waves raise emergency department admissions across numerous demographic and disease categories suggests that heat exerts comorbidity influences that extend beyond the more well-studied direct relationships such as heat strokes and cardiac arrest.

The Impact of Industrial Odors on the Subjective Well-Being of Communities in Colorado

Odor pollution was identified as a top priority of the community of North Denver. Previous studies that investigated the impact of air pollution in North Denver focused on adverse health effects, rather than mental well-being. This study assessed the impact of odors from industrial sources on the subjective well-being (SWB) of North Denver residents, and of four similar communities in Colorado for comparison. An online survey was sent to participants from Greeley, Fort Collins, Fort Lupton, North Denver, and Pueblo, asking questions about SWB and odors in their areas (n = 351). The evaluation of SWB was performed using a novel approach that appraises three aspects of SWB. This approach of evaluating SWB has not been used in odor exposure studies. A proportional odds logistic regression model was used to estimate nine measures of SWB. The results showed that participants who reported that the air is very fresh or the odor is highly acceptable had higher levels of SWB. This association suggests that residents who live in areas exposed to strong industrial odors had lower levels of SWB. A subset of participants in this study took the survey four times in one year. Longitudinal analysis showed that evaluative satisfaction was slightly associated with seasonality. Both satisfaction with how life turned out and satisfaction with standards of living slightly increased during the fourth quarter of the year. The study also found that four of the nine measures can be used to represent SWB in future studies. Two of those measures were evaluative SWB, and the other two were positive hedonic SWB measures. A comparison between the five communities showed that well-being levels in North Denver and Greeley were not significantly different than those in Fort Collins or Fort Lupton. The comparison, however, showed that Pueblo had the lowest levels of well-being among all communities.

Associations between ambient air pollution and daily mortality in a cohort of congestive heart failure: Case-crossover and nested case-control analyses using a distributed lag nonlinear model

BACKGROUND

Persons with congestive heart failure may be at higher risk of the acute effects related to daily fluctuations in ambient air pollution. To meet some of the limitations of previous studies using grouped-analysis, we developed a cohort study of persons with congestive heart failure to estimate whether daily non-accidental mortality were associated with spatially-resolved, daily exposures to ambient nitrogen dioxide (NO₂) and ozone (O₃), and whether these associations were modified according to a series of indicators potentially reflecting complications or worsening of health.

METHODS

We constructed the cohort from the linkage of administrative health databases. Daily exposure was assigned from different methods we developed previously to predict spatially-resolved, time-dependent concentrations of ambient NO₂ (all year) and O₃ (warm season) at participants' residences. We performed two distinct types of analyses: a case-crossover that contrasts the same person at different times, and a nested case-control that contrasts different persons at similar times. We modelled the effects of air pollution and weather (case-crossover only) on mortality using distributed lag nonlinear models over lags 0 to 3 days. We developed from administrative health data a series of indicators that may reflect the underlying construct of "declining health", and used interactions between these indicators and the cross-basis function for air pollutant to assess potential effect modification.

RESULTS

The magnitude of the cumulative as well as the lag-specific estimates of association differed in many instances according to the metric of exposure. Using the back-extrapolation method, which is our preferred exposure model, we found for the case-crossover design a cumulative mean percentage changes (MPC) in daily mortality per interquartile increment in NO₂ (8.8 ppb) of 3.0% (95% CI: -0.4, 6.6%) and for O₃ (16.5 ppb) 3.5% (95% CI: -4.5, 12.1). For O₃ there was strong confounding by weather (unadjusted MPC = 7.1%; 95% CI: 1.7, 12.7%). For the nested case-control approach the cumulative MPC for NO₂ in daily mortality was 2.9% (95% CI: -0.9, 6.9%) and for O₃ 7.3% (95% CI: 3.0, 11.9%). We found evidence of effect modification between daily mortality and cumulative NO₂ and O₃ according to the prescribed dose of furosemide in the nested case-control analysis, but not in the case-crossover analysis.

CONCLUSIONS

Mortality in congestive heart failure was associated with exposure to daily ambient NO₂ and O₃ predicted from a back-extrapolation method using a land use regression model from dense sampling surveys. The methods used to assess exposure can have considerable influence on the estimated acute health effects of the two air pollutants.

Heat stress mortality and desired adaptation responses of healthcare system in Poland

Heat stress is one of the environmental factors influencing the health of individuals and the wider population. There is a large body of research to document significant increases in mortality and morbidity during heat waves all over the world. This paper presents key results of research dealing with heat-related mortality (HRM) in various cities in Poland which cover about 25% of the country's population. Daily mortality and weather data reports for the years 1991-2000 were used. The intensity of heat stress was assessed by the universal thermal climate index (UTCI). The research considers also the projections of future bioclimate to the end of twenty-first century. Brain storming discussions were applied to find necessary adaptation strategies of healthcare system (HCS) in Poland, to minimise negative effects of heat stress. In general, in days with strong and very strong heat stress, ones must expect increase in mortality (in relation to no thermal stress days) of 12 and 47%, respectively. Because of projected rise in global temperature and heat stress frequency, we must expect significant increase in HRM to the end of twenty-first century of even 165% in comparison to present days. The results of research show necessity of urgent implementation of adaptation strategies to heat in HCS.

Mapping relative humidity, average and extreme temperature in hot summer over China

Air temperature and relative humidity are the key variables in environmental health research. Both of them are difficult to map especially at national scale because of spatial heterogeneity. This paper presents a methodology for mapping relative humidity, average and extreme temperature in hot summer (June to August) over China. Several data as explanatory variables were applied to random forest regression models to predict relative humidity and temperatures, including surface reflectance, land cover, digital elevation model (DEM), enhanced vegetation index (EVI), latitude, nighttime lights (NLs), as well as buffer zones of road, railroad, river system and administration center. Results based on cross-validation reflect acceptable prediction errors in estimating relative humidity (RMSE=7.4%), average temperature (RMSE=2.4°C), average maximum temperature (RMSE=2.5°C), and extreme maximum temperature (RMSE=2.6°C). Despite the strong correlation between average and extreme temperatures, significant differences exist in their spatial distribution along the latitude direction, especially in the areas such as Hebei, Szechwan, Hubei, Henan, Shandong, and Inner Mongolia. Specifically, social economic activity, relative humidity and vegetation tend to affect extreme heat events, and both latitude and DEM (i.e., geographical position) determine the average level of temperature. Compared with interpolation technology and statistical methods, the proposed methodology demonstrates the ability to generate relative humidity and temperature maps with finer gradients in hot summer over China.

Humidity May Modify the Relationship between Temperature and Cardiovascular Mortality in Zhejiang Province, China

Background: The evidence of increased mortality attributable to extreme temperatures is widely characterized in climate-health studies. However, few of these studies have examined the role of humidity on temperature-mortality association. We investigated the joint effect between temperature and humidity on cardiovascular disease (CVD) mortality in Zhejiang Province, China. Methods: We collected data on daily meteorological and CVD mortality from 11 cities in Zhejiang Province during 2010–2013. We first applied time-series Poisson regression analysis within the framework of distributed lag non-linear models to estimate the city-specific effect of temperature and humidity on CVD mortality, after controlling for temporal trends and potential confounding variables. We then applied a multivariate meta-analytical model to pool the effect estimates in the 11 cities to generate an overall provincial estimate. The joint effects between them were calculated by the attributable fraction (AF). The analyses were further stratified by gender, age group, education level, and location of cities. Results: In total, 120,544 CVD deaths were recorded in this study. The mean values of temperature and humidity were 17.6 °C and 72.3%. The joint effect between low temperature and high humidity had the greatest impact on the CVD death burden over a lag of 0–21 days with a significant AF of 31.36% (95% eCI: 14.79–38.41%), while in a condition of low temperature and low humidity with a significant AF of 16.74% (95% eCI: 0.89, 24.44). The AFs were higher at low temperature and high humidity in different subgroups. When considering the levels of humidity, the AFs were significant at low temperature and high humidity for males, youth, those with a low level of education, and coastal area people. Conclusions: The combination of low temperature and high humidity had the greatest impact on the CVD death burden in Zhejiang Province. This evidence has important implications for developing CVD interventions.

The association of air temperature with cardiac arrhythmias

The body response to meteorological influences may activate pathophysiological mechanisms facilitating the occurrence of cardiac arrhythmias in susceptible patients. Putative underlying mechanisms include changes in systemic vascular resistance and blood pressure, as well as a network of proinflammatory and procoagulant processes. Such a chain reaction probably occurs within the time window of several hours, so use of daily average values of meteorological elements do not seem appropriate for investigation in this area. In addition, overall synoptic situation, and season-specific combinations of meteorological elements and air pollutant levels probably cause the overall effect rather than a single atmospheric element. Particularly strong interrelations have been described among wind speed, air pressure and temperature, relative air humidity, and suspended particulate matter. This may be the main reason why studies examining the association between temperature and ventricular arrhythmias have found linear positive, negative, J-shaped or no association. Further understanding of the pathophysiological adaptation to atmospheric environment may help in providing recommendations for protective measures during "bad" weather conditions in patients with cardiac arrhythmias.

Short-term effects of ozone air pollution on hospital admissions for myocardial infarction: A time-stratified case-crossover study in Taipei

This study was undertaken to determine whether there was a correlation between ambient ozone (O₃) levels and number of hospital admissions for myocardial infarction (MI) in Taipei, Taiwan. Hospital admissions for MI and ambient air pollution data for Taipei were obtained for the period from 2006 to 2010. The relative risk (RR) of hospital admissions for MI was estimated using a time-stratified case-crossover approach, controlling for weather variables, day of the week, seasonality, and long-term time trends. For the single-pollutant model (without adjustment for other pollutants), increased RR for a number of MI admissions was significantly associated with higher O₃ levels both on warm days (>23°C) and on cool days (<23°C). This observation was accompanied by an interquartile range elevation correlated with a 7% (95% CI = 2%-12%) and 17% (95% CI = 11%-25%) rise in number of MI admissions, respectively. In the two-pollutant models, no significant associations between ambient O₃ concentrations and number of MI admissions were observed on warm days. However, on cool days, correlation between ambient O₃ after inclusion of each of the other five pollutants, particulate matter (PM₁₀ or PM_2.5), sulfur dioxide (SO₂), nitrogen dioxide (NO₂) or carbon monoxide (CO), and number of MI admissions remained significant. This study provides evidence that higher levels of ambient O₃ increase the RR of number of hospital admissions for MI.

Short-term effects of air temperature and mitochondrial DNA lesions within an older population

BACKGROUND

Previous studies have linked both extreme and sub-optimal air temperature to cardiopulmonary morbidity and mortality, especially in older individuals. However, the underlying mechanisms are yet to be determined.

OBJECTIVES

We hypothesized that short-term increases in air temperature may induce blood mitochondrial DNA (mtDNA) lesions in older individuals, which could contribute to temperature-related pathogenesis.

METHODS

We repeatedly measured mtDNA lesions in blood samples from 654 participants in the Normative Aging Study from 1999 to 2013 (1142 observations) by quantitative long-amplicon polymerase chain reaction assay. Hourly temperature data were obtained from the Boston Logan Airport weather station (located approximately 12km from the clinical site). We calculated 2-, 7-, and 14-day moving averages of 24-hour mean and 24-hour variability of temperature. We fit covariate-adjusted linear-mixed models accounting for repeated measures to evaluate the association between short-term increases in mean and variability of temperature with mtDNA lesions within each season.

RESULTS

Interquartile increases in 7- and 14-day moving averages of 24-hour mean temperature in summer were associated with a 0.17 (95% CI: 0.07, 0.27; p=0.0007) and 0.21 (95% CI: 0.10, 0.32; p=0.0001) increase in the number of mtDNA lesions per 10kb, respectively. Results were similar when we further adjusted for temperature variability. We also observed significant associations between increases in temperature variability and mtDNA lesions independent of mean air temperature. An interquartile range increase in the 7-day moving average of 24-hour standard deviation in summer was associated with a 0.19 (95% CI: 0.07, 0.31; p=0.0023) increase in the number of mtDNA lesions per 10kb.

CONCLUSIONS

Short-term exposure to higher mean air temperature was associated with increased mtDNA lesions in older adults, supporting the hypothesis that sub-optimal meteorological conditions may induce pathophysiological responses among susceptible populations.

Impact of Ambient Temperature on Incidence of Acute Lower Limb Ischemia

BACKGROUND

This was a retrospective study to explore the possible association between atmospheric temperatures with the occurrence of acute leg ischemia (ALI).

METHODS

A linear regression analysis was performed for a period of 10 years on the impact of ambient temperature on the incidence of ALI. Mean ambient temperature on a daily basis was retrieved electronically from our observatory, and the daily incidence of ALI was retrieved from the Clinical Data Analysis and Reporting (CDAR) system. CDAR system could retrieve clinical data from all 42 public hospitals in our region, which provided almost 90% inpatient care of the population. Daily incidence was defined as total number of emergency admissions from all 42 pubic hospitals due to ALI from 00:00 till 23:59 hr of that day.

RESULTS

For the 10-year period, spanning from January 2005 to December 2014, there were a total of 634 recorded ALI with revascularization, 608 (95.9%) of which underwent emergency femoral embolectomy, 15 (2.4%) underwent thrombolysis, and 11 (1.7%) underwent thrombolysis and embolectomy. ALIs with primary amputation or conservative management were excluded from the study. The average daily incidence of ALI was 0.170. A linear regression model was built using mean ambient temperature as independent variable and incidence of ALI as dependent variables. The line of best fit was drawn through the data points. The daily incidence of ALI could be predicted by ambient temperature (in °C) with the equation: incidence = 0.274-0.004 × temperature (linear regression; r = -0.053, r² = 0.003, F = 10.42, and P = 0.001). In other words, daily incidence was 0.274 at 0°C; and for every 10°C increase, the incidence would drop by 0.040. At 30°C, daily incidence of ALI was 0.154.

CONCLUSIONS

This study showed an association of cold temperature and ALI in our population. Measures to protect the susceptible population from cold temperatures should be considered.

Summertime extreme heat events and increased risk of acute myocardial infarction hospitalizations

Few studies have examined the association between exposure to extreme heat events and risk of acute myocardial infarction (AMI) or demonstrated which populations are most vulnerable to the effects of extreme heat. We defined extreme heat events as days when the daily maximum temperature (TMAX) exceeded the location- and calendar day-specific 95th percentile of the distribution of daily TMAX during the 30-year baseline period (1960-1989). We used a time-stratified case-crossover design to analyze the association between exposure to extreme heat events and risk of hospitalization for AMI in the summer months (June-August) with 0, 1, or 2 lag days. There were a total of 32,670 AMI hospitalizations during the summer months in Maryland between 2000 and 2012. Overall, extreme heat events on the day of hospitalization were associated with an increased risk of AMI (lag 0 OR=1.11; 95% CI: 1.05-1.17). Results considering lag periods immediately before hospitalization were comparable, but effect estimates varied among several population subgroups. As extreme weather events are expected to become more frequent and intense in response to our changing climate, community-specific adaptation strategies are needed to account for the differential susceptibility across ethnic subgroups and geographic areas.

Vulnerability to extreme-heat-associated hospitalization in three counties in Michigan, USA, 2000-2009

With climate change, extreme heat (EH) events are increasing, so it is important to understand who is vulnerable to heat-associated morbidity. We determined the association between EH and hospitalizations for all natural causes; cardiovascular, respiratory, and renal diseases; diabetes mellitus; and acute myocardial infarction in Michigan, USA, at different intensities and durations. We assessed confounding by ozone and how individual characteristics and health insurance payer (a proxy for income) modified these associations. We obtained Michigan Inpatient Database, National Climatic Data Center, and US Environmental Protection Agency ozone data for May-September, 2000-2009 for three Michigan counties. We employed a case-crossover design and modeled EH as an indicator for temperature above the 95th, 97th, or 99th percentile thresholds for 1, 2, 3, or 4 days. We examined effect modification by patient age, race, sex, and health insurance payer and pooled the county results. Among non-whites, the pooled odds ratio for hospitalization on EH (97th percentile threshold) vs. non-EH days for renal diseases was 1.37 (95 % CI = 1.13-1.66), which increased with increasing EH intensity, but was null among whites (OR = 1.00, 95 % CI = 0.81, 1.25). We observed a null association between EH and cardiovascular hospitalization. EH (99th percentile threshold) was associated with myocardial infarction hospitalizations. Confounding by ozone was minimal. EH was associated with hospitalizations for renal disease among non-whites. This information on vulnerability to heat-associated morbidity helps characterize the public health burden of EH and target interventions including patient education.

Ambient Air Pollutant Exposures and Hospitalization for Kawasaki Disease in Taiwan: A Case-Crossover Study (2000-2010)

BACKGROUND

Kawasaki disease (KD) is an acute and multi-systemic vasculitis that occurs predominantly in infants and young children. Although the etiological agent of KD remains unclear, limited studies have reported that windborne environmental factors may trigger KD.

OBJECTIVES

We conducted a time-stratified case-crossover study to assess the associations between air pollutants and KD in Taiwan.

METHODS

We identified children < 5 years old with a diagnosis of KD from the Longitudinal Health Insurance Database 2000 (LHID2000) between 2000 and 2010. We obtained data regarding carbon monoxide (CO), nitrogen dioxide (NO₂), ozone (O₃), particulate matter with aerodynamic diameter < 10 μm (PM₁₀), and sulfate dioxide (SO₂) from 70 monitoring stations and used inverse distance weighting to calculate average daily exposures for the residential postal code of each case. We performed conditional logistic regression to estimate associations between KD and each air pollutant according to interquartile range (IQR) increases and quartiles of exposure on the day of hospitalization versus 3-4 reference days during the same month for each case. Additionally, we estimated associations with single-day exposures lagged 1-2 days.

RESULTS

We identified 695 KD hospital admissions during the study period. An IQR increase (28.73 ppb) of O₃ was positively associated with KD after adjusting for temperature, humidity, northward wind, and eastward wind [adjusted odds ratio = 1.21; 95% confidence interval (CI): 1.01, 1.44]. There were no significant associations between KD and CO, NO₂, PM₁₀, or SO₂. The association with O₃ was limited to exposure on the day of hospitalization and to exposure during the summer months (June-August).

CONCLUSIONS

Our results provide new evidence that exposure to O₃ may increase the risk of KD in children. However, further investigation is needed to confirm the association and identify a potential biological mechanism.

Air quality environmental epidemiology studies are unreliable

Ever since the London Great Smog of 1952 is estimated to have killed over 4000 people, scientists have studied the relationship between air quality and acute mortality. There are many hundreds of papers examining the question. There is a serious statistical problem with most of these papers. If there are many questions under consideration, and there is no adjustment for multiple testing or multiple modeling, then unadjusted p-values are totally unreliable making claims unreliable. Our idea is to determine the statistical reliability of eight papers published in Environmental Health Perspectives that were used in meta-analysis papers appearing in Lancet and JAMA. We counted the number of outcomes, air quality predictors, time lags and covariates examined in each paper. We estimate the multiplicity of questions that could be asked and the number of models that could be constructed. The results were that the median numbers of comparisons possible for multiplicity, models and search space were 135, 128, and 9568 respectively. Given the large search spaces, finding a small number of nominally significant results is not unusual at all. The claims in these eight papers are not statistically supported so these papers are unreliable as are the meta-analysis papers that use them.

Influence of ambient temperature on the heterogeneity of ambient fine particle chemical composition and disease prevalence

In this study, we present the associations of fine particle nitrate, sulfate, and four organic carbon fractions with ambient temperature in urban and background monitoring sites in the United States for the 2011-2012 period. Nitrate concentrations increased for decreasing temperatures, while sulfate levels increased for temperatures higher than 14 °C. The profiles of organic carbon fractions for different temperatures were comparable to that observed for elemental carbon, a thermally stable and non-reactive component emitted from combustion-related sources. The trends for all parameters were comparable for the nine regions and independent to emission estimates of fine particles and their precursors. These patterns demonstrated that ambient temperature may manipulate fine particulate composition. These differences may be augmented by rising temperatures due to changing climate. Considering the causal associations between particulate pollution and pulmonary and cardiovascular diseases, changes in the composition of particulate pollution may imply adjustments on the human health impacts.

Heatwave and risk of hospitalization: A multi-province study in Vietnam

The effects of heatwaves on morbidity in developing and tropical countries have not been well explored. The purpose of this study was to examine the relationship between heatwaves and hospitalization and the potential influence of socio-economic factors on this relationship in Vietnam. Generalized Linear Models (GLM) with Poisson family and Distributed Lag Models (DLM) were applied to evaluate the effect of heatwaves for each province (province-level effect). A random-effects meta-analysis was applied to calculate the pooled estimates (country-level effects) for 'all causes', infectious, cardiovascular, and respiratory admissions queried by lag days, regions, sex, and ages. We used random-effects meta-regression to explore the potential influence of socio-economic factors on the relationship between heatwaves and hospitalization. The size of province-level effects varied across provinces. The pooled estimates show that heatwaves were significantly associated with a 2.5% (95%CI: 0.8-4.3) and 3.8% (95%CI, 1.5-6.2) increase in all causes and infectious admissions at lag 0. Cardiovascular and respiratory admissions (0.8%, 95%CI: -1.6-3.3; 2.2%, 95%CI: -0.7-5.2) were not significantly increased after a heatwave event. The risk of hospitalization due to heatwaves was higher in the North than in the South for all causes (5.4%, 95%CI: -0.1-11.5 versus 1.3%, 95%CI: 0.1-2.6), infectious (11.2%, 95%CI: 3.1-19.9 versus 3.2%, 95%CI: 0.7-5.7), cardiovascular (7.5%, 95%CI: 1.1-14.4 versus -1.2%, 95%CI: -2.6-2.3), and respiratory diseases (2.7%, 95%CI: -5.4-11.5 versus 2.1%, 95%CI: -0.8-1.2). A non-significant influence of socio-economic factors on the relationship between heatwave and hospitalization was observed. This study provides important evidence and suggests implications for the projected impacts of climate change related extreme weather. Climate change adaptation programs of the health sector should be developed to protect residents from the effects of extreme weather events such as heatwaves in Vietnam.

Impact of meteorological parameters and air pollution on emergency department visits for cardiovascular diseases in the city of Zagreb, Croatia

The aim of this study was to investigate whether nitrogen dioxide (NO2), ozone (O3), and certain meteorological conditions had an impact on cardiovascular disease (CVD)-related emergency department (ED) visits in the metropolitan area of Zagreb. This retrospective, ecological study included 20,228 patients with a cardiovascular disease as their primary diagnosis who were examined in the EDs of two Croatian University Hospitals, Sisters of Charity and Holy Spirit, in the study period July 2008-June 2010. The median of daily CVD-related ED visits during the study period was 28 and was the highest during winter. A significant negative correlation was found between CVD-related emergency visits and air temperature measured no more than three days prior to the visit, and the highest negative correlation coefficient was measured two days earlier (R=0.266, p≤0.001). The number of CVD-related emergency visits significantly correlated with the average NO2 concentration on the same day (R=0.191, p<0.001). The results of multiple stepwise regression analysis showed that the number of CVD-related emergency visits depended on air temperature, and NO2 and O3 concentrations. The higher the air temperatures, the lower the number of daily CVD-related emergency visits (p<0.001). An increase in NO2 concentrations (p=0.005) and a decrease in O3 concentrations of two days earlier (p=0.006) led to an increase in CVD-related ED visits. In conclusion, the decrease in O3 concentrations and the increase in NO2, even if below the legally binding thresholds, could be associated with an increase in CVD-related emergency visits and a similar effect was observed with lower temperature measured no more than three days prior to the visit.

Can green structure reduce the mortality of cardiovascular diseases?

Previous studies have shown that green spaces are beneficial to health; however, few studies have analyzed the relationship between green structure and mortality of cardiovascular disease. Green structure may mediate the effects of air pollution and temperature on health. This work applies partial least squares (PLS) modeling to analyze the degree to which green structure reduces mortality of cardiovascular disease, using Taipei Metropolitan Area as an empirical case. In addition to clarifying the complex relationships and effects of green structure, air pollution, temperature, and mortality of cardiovascular disease, this study demonstrates that green structure has a significant influence on mortality of cardiovascular disease because it reduces the effects of air pollution and heat. The most crucial elements for planning a healthy living environment are the maximization of the largest green patch proportion and the minimization of green space fragmentation. Moreover, to enhance the benefits of greening city spaces on health, this work proposes several strategies for connecting fragmentary green spaces, expanding green patches to the largest possible proportion, and managing green spaces. The proposed strategies may serve as a reference for other metropolitan areas with features similar to those of the study area.

Distributional changes in gene-specific methylation associated with temperature

Temperature has been related to mean differences in DNA methylation. However, heterogeneity in these associations may exist across the distribution of methylation outcomes. This study examined whether the association between three-week averaged of temperature and methylation differs across quantiles of the methylation distributions in nine candidate genes. We measured gene-specific blood methylation repeatedly in 777 elderly men participating in the Normative Aging Study (1999-2010). We fit quantile regressions for longitudinal data to investigate whether the associations of temperature on methylation (expressed as %5mC) varied across the distribution of the methylation outcomes. We observed heterogeneity in the associations of temperature across percentiles of methylation in F3, TLR-2, CRAT, iNOS, and ICAM-1 genes. For instance, an increase in three-week temperature exposure was associated with a longer left-tail of the F3 methylation distribution. A 5°C increase in temperature was associated with a 0.15%5mC (95% confidence interval (CI): -0.27,-0.04) decrease on the 20th quantile of F3 methylation, but was not significantly related to the 80th quantile of this distribution (Estimate:0.06%5mC, 95%CI: -0.22, 0.35). Individuals with low values of F3, TLR-2, CRAT, and iNOS methylation, as well as a high value of ICAM-1 methylation, may be more susceptible to temperature effects on systemic inflammation.

Effects of Air Pollutant Exposure on Acute Myocardial Infarction, According to Gender

Background:

There is evidence of the effects of air pollution on hospital admissions due to cardiovascular diseases, including myocardial infarction.

Objective:

To estimate the association between exposure to air pollutants and hospital admissions due to myocardial infarction according to gender, between January 1^st 2012 and December 31^st 2013, in São Jose dos Campos-SP.

Methods:

An ecological time series study was carried out with daily data of admissions due to AMI, pollutants CO, O₃, PM₁₀, SO₂, and NO₂, according to gender. We used the Poisson regression generalized linear model to estimate the relative risks of hospital admissions with lags of 0-5 days, adjusted for temperature, humidity, seasonality and days of the week.

Results:

There were 1837 admissions for ischemic heart diseases, with 636 women and 1201 men. For females, the risks were significant for CO in lag 0 (RR = 1,09), lag1 (RR = 1,08) and lag 5 (RR = 1,10) and SO₂ in lag 0 (RR = 1,10) and 3 (RR = 1,09). For men there was significance of the CO in, lag 3 and lag 5 (RR = 1,05). There was significance, regardless of gender, for CO at lag 1 (RR = 1,05) and lag 5 (RR = 1,07) and lag 0 for SO₂ (RR = 1,06).

Conclusion:

The data presented show the important role of CO and SO₂ in the genesis of myocardial infarction admissions, and responses to pollutant exposure are different if analyzed by gender and together - hence the importance of a stratified analyses.

Bayesian model averaging method for evaluating associations between air pollution and respiratory mortality: a time-series study

OBJECTIVE

To demonstrate an application of Bayesian model averaging (BMA) with generalised additive mixed models (GAMM) and provide a novel modelling technique to assess the association between inhalable coarse particles (PM10) and respiratory mortality in time-series studies.

DESIGN

A time-series study using regional death registry between 2009 and 2010.

SETTING

8 districts in a large metropolitan area in Northern China.

PARTICIPANTS

9559 permanent residents of the 8 districts who died of respiratory diseases between 2009 and 2010.

MAIN OUTCOME MEASURES

Per cent increase in daily respiratory mortality rate (MR) per interquartile range (IQR) increase of PM10 concentration and corresponding 95% confidence interval (CI) in single-pollutant and multipollutant (including NOx, CO) models.

RESULTS

The Bayesian model averaged GAMM (GAMM+BMA) and the optimal GAMM of PM10, multipollutants and principal components (PCs) of multipollutants showed comparable results for the effect of PM10 on daily respiratory MR, that is, one IQR increase in PM10 concentration corresponded to 1.38% vs 1.39%, 1.81% vs 1.83% and 0.87% vs 0.88% increase, respectively, in daily respiratory MR. However, GAMM+BMA gave slightly but noticeable wider CIs for the single-pollutant model (-1.09 to 4.28 vs -1.08 to 3.93) and the PCs-based model (-2.23 to 4.07 vs -2.03 vs 3.88). The CIs of the multiple-pollutant model from two methods are similar, that is, -1.12 to 4.85 versus -1.11 versus 4.83.

CONCLUSIONS

The BMA method may represent a useful tool for modelling uncertainty in time-series studies when evaluating the effect of air pollution on fatal health outcomes.

High temperature and risk of hospitalizations, and effect modifying potential of socio-economic conditions: A multi-province study in the tropical Mekong Delta Region

The Mekong Delta Region (MDR) in Vietnam is highly vulnerable to extreme weather related to climate change. However there have been hardly any studies on temperature-hospitalization relationships. The objectives of this study were to examine temperature-hospitalization relationship and to evaluate the effects of socio-economic factors on the risk of hospitalizations due to high temperature in the MDR. The Generalized Linear and Distributed Lag Models were used to examine hospitalizations for extreme temperature for each of the 13 provinces in the MDR. A random-effects meta-analysis was used to estimate the pooled risk for all causes, and for infectious, cardiovascular, and respiratory diseases sorted by sex and age groups. Random-effects meta-regression was used to evaluate the effect of socio-economic factors on the temperature-hospitalization association. For 1°C increase in average temperature, the risk of hospital admissions increased by 1.3% (95% CI, 0.9-1.8) for all causes, 2.2% (95% CI, 1.4-3.1) for infectious diseases, and 1.1% (95% CI, 0.5-1.7) for respiratory diseases. However the result was inconsistent for cardiovascular diseases. Meta-regression showed population density, poverty rate, and illiteracy rate increased the risk of hospitalization due to high temperature, while higher household income, houses using safe water, and houses using hygienic toilets reduced this risk. In the MDR, high temperatures have a significant impact on hospitalizations for infectious and respiratory diseases. Our findings have important implications for better understanding the future impacts of climate change on residents of the MDR. Adaptation programs that consider the risk and protective factors should be developed to protect residents from extreme temperature conditions.

Short-Term Exposure to Air Pollution and Cardiac Arrhythmia: A Meta-Analysis and Systematic Review

The objective was to assess the transient association between air pollution and cardiac arrhythmia. Five databases were searched for studies investigating the association between daily increases in air pollutants (PM2.5, PM10, carbon monoxide, nitrogen dioxide, sulfur dioxide and ozone) and arrhythmia hospitalization or arrhythmia mortality. Two reviewers independently selected studies, extracted data, and assessed risk of bias. Outcomes were analyzed via a random-effects model and reported as relative risk and 95% confidence interval. 25 studies satisfied our inclusion criteria and 23 contributed to the meta-analysis. Arrhythmia hospitalization or mortality were associated with increases in PM2.5 (RR = 1.015 per 10 μg/m³, 95% CI: 1.006-1.024), PM10 (RR = 1.009 per 10 μg/m³, 95% CI: 1.004-1.014), carbon monoxide (RR = 1.041 per 1 ppm, 95% CI: 1.017-1.065), nitrogen dioxide (RR = 1.036 per 10 ppb, 95% CI: 1.020-1.053), and sulfur dioxide (RR = 1.021 per 10 ppb, 95% CI: 1.003-1.039), but not ozone (RR = 1.012 per 10 ppb, 95% CI: 0.997-1.027). Both particulate and gaseous components, with the exception of ozone, have a temporal association with arrhythmia hospitalization or mortality. Compared with Europe and North America, a stronger association was noted in Asia.

A Comprehensive Evaluation of the Burden of Heat-Related Illness and Death within the Florida Population

The failure of the human body to thermoregulate can lead to severe outcomes (e.g., death) and lasting physiological damage. However, heat-related illness (HRI) is highly preventable via individual- and community-level modification. A thorough understanding of the burden is necessary for effective intervention. This paper describes the burden of severe HRI morbidity and mortality among residents of a humid subtropical climate. Work-related and non-work-related HRI emergency department (ED) visits, hospitalizations, and deaths among Florida residents during May to October (2005–2012) were examined. Sub-groups susceptible to HRI were identified. The age-adjusted rates/100,000 person-years for non-work-related HRI were 33.1 ED visits, 5.9 hospitalizations, and 0.2 deaths, while for work-related HRI/100,000 worker-years there were 8.5 ED visits, 1.1 hospitalizations, and 0.1 deaths. The rates of HRI varied by county, data source, and work-related status, with the highest rates observed in the panhandle and south central Florida. The sub-groups with the highest relative rates regardless of data source or work-relatedness were males, minorities, and rural residents. Those aged 15–35 years had the highest ED visit rates, while for non-work-related hospitalizations and deaths the rates increased with age. The results of this study can be used for targeted interventions and evaluating changes in the HRI burden over time.

Warm season temperatures and emergency department visits in Atlanta, Georgia

PURPOSE

Extreme heat events will likely increase in frequency with climate change. Heat-related health effects are better documented among the elderly than among younger age groups. We assessed associations between warm-season ambient temperature and emergency department (ED) visits across ages in Atlanta during 1993-2012.

METHODS

We examined daily counts of ED visits with primary diagnoses of heat illness, fluid/electrolyte imbalances, renal disease, cardiorespiratory diseases, and intestinal infections by age group (0-4, 5-18, 19-64, 65+years) in relation to daily maximum temperature (TMX) using Poisson time series models that included cubic terms for TMX at single-day lags of 0-6 days, controlling for maximum dew-point temperature, time trends, week day, holidays, and hospital participation periods. We estimated rate ratios (RRs) and 95% confidence intervals (CI) for TMX changes from 27°C to 32°C (25th to 75th percentile) and conducted extensive sensitivity analyses.

RESULTS

We observed associations between TMX and ED visits for all internal causes, heat illness, fluid/electrolyte imbalances, renal diseases, asthma/wheeze, diabetes, and intestinal infections. Age groups with the strongest observed associations were 65+years for all internal causes [lag 0 RR (CI)=1.022 (1.016-1.028)] and diabetes [lag 0 RR=1.050 (1.008-1.095)]; 19-64 years for fluid/electrolyte imbalances [lag 0 RR=1.170 (1.136-1.205)] and renal disease [lag 1 RR=1.082 (1.065-1.099)]; and 5-18 years for asthma/wheeze [lag 2 RR=1.059 (1.030-1.088)] and intestinal infections [lag 1 RR=1.120 (1.041-1.205)].

CONCLUSIONS

Varying strengths of associations between TMX and ED visits by age suggest that optimal interventions and health-impact projections would account for varying heat health impacts across ages.

Ambient temperature and risk of cardiovascular hospitalization: An updated systematic review and meta-analysis

The association between temperatures and risk of cardiovascular mortality has been recognized but the association drawn from previous meta-analysis was weak due to the lack of sufficient studies. This paper presented a review with updated reports in the literature about the risk of cardiovascular hospitalization in relation to different temperature exposures and examined the dose-response relationship of temperature-cardiovascular hospitalization by change in units of temperature, latitudes, and lag days. The pooled effect sizes were calculated for cold, heat, heatwave, and diurnal variation using random-effects meta-analysis, and the dose-response relationship of temperature-cardiovascular admission was modelled using random-effect meta-regression. The Cochrane Q-test and index of heterogeneity (I(2)) were used to evaluate heterogeneity, and Egger's test was used to evaluate publication bias. Sixty-four studies were included in meta-analysis. The pooled results suggest that for a change in temperature condition, the risk of cardiovascular hospitalization increased 2.8% (RR, 1.028; 95% CI, 1.021-1.035) for cold exposure, 2.2% (RR, 1.022; 95% CI, 1.006-1.039) for heatwave exposure, and 0.7% (RR, 1.007; 95% CI, 1.002-1.012) for an increase in diurnal temperature. However no association was observed for heat exposure. The significant dose-response relationship of temperature - cardiovascular admission was found with cold exposure and diurnal temperature. Increase in one-day lag caused a marginal reduction in risk of cardiovascular hospitalizations for cold exposure and diurnal variation, and increase in latitude was associated with a decrease in risk of cardiovascular hospitalizations for diurnal temperature only. There is a significant short-term effect of cold exposure, heatwave and diurnal variation on cardiovascular hospitalizations. Further research is needed to understand the temperature-cardiovascular relationship for different climate areas.

Ambient Particulate Matter (PM2.5/PM10) Exposure and Emergency Department Visits for Acute Myocardial Infarction in Chaoyang District, Beijing, China During 2014: A Case-Crossover Study

BACKGROUND

Epidemiology studies have shown a consistently increased risk of acute myocardial infarction (AMI) correlated with particulate matter (PM) exposure. However, little is known about the association with specific AMI subtypes. In this work, we investigated the association between short-term PM exposure and emergency department visits (EDVs) for AMI, ST-elevation myocardial infarction (STEMI), and non-ST-elevation myocardial infarction (NSTEMI).

METHODS

We based this case-crossover study on 2749 patients from Chaoyang District hospitalized with AMI in Anzhen Hospital during 2014. Meteorological and air pollution data were collected during this period. We used a time-stratified case-crossover design with lag model, adjusted for meteorological conditions and/or other gaseous pollutants, to estimate risk of EDVs for AMI, STEMI, and NSTEMI. We conducted stratified analyses by gender, age, season, and comorbid conditions to examine potential effect modification.

RESULTS

We found that each 10 µg/m³ increment of PM_2.5 concentration (1-day lagged) was associated with an increased risk of EDVs for STEMI (OR 1.05; 95% CI, 1.00-1.11). We found no association of PM_2.5 concentration with overall AMI or NSTEMI. No effect modification was found when stratified by gender, season, or comorbid conditions, even though the effect size was larger in patients who were male, smokers, and comorbid with hypertension. Patients aged ≥65 years showed a significantly increased risk of STEMI associated with PM_2.5 in the previous day than those aged <65 years.

CONCLUSIONS

Our study indicated a transient effect of short-term PM_2.5 exposure on EDVs for STEMI. Patients aged ≥65 years appeared to be particularly susceptible. Our findings suggest that studies of the association between PM exposure and AMI should consider AMI subtypes, lag times, and individual characteristics.