Influence of air pressure, humidity, solar radiation, temperature, and wind speed on ambulatory visits due to chronic obstructive pulmonary disease in Bavaria, Germany

Methods to Advance Climate Science in Respiratory Health: Satellite-Based Environmental Modeling for Temperature Exposure Assessment in Epidemiological Studies

Climate change is a major concern with significant impacts on human health including respiratory outcomes, particularly through changes in air temperature. The rise in global temperature has led to an increase in heat waves and extreme weather events, which pose serious risks to respiratory health. Accurately assessing the effects of air temperature on respiratory health requires a comprehensive approach that incorporates fine-scale exposure assessment to characterize the geospatial environment impacting population health. Recent advances in open-source earth observation data have allowed for improved exposure assessment through temperature modeling.

Predicting emergency health care demands due to respiratory diseases

BACKGROUND

Timely care in the health sector is essential for the recovery of patients, and even more so in the case of a health emergency. In these cases, appropriate management of human and technical resources is essential. These are limited and must be mobilised in an optimal and efficient manner.

OBJECTIVE

This paper analyses the use of the health emergency service in a city, Jaén, in the south of Spain. The study is focused on the most recurrent case in this service, respiratory diseases.

METHODS

Machine Learning algorithms are used in which the input variables are multisource data and the target attribute is the prediction of the number of health emergency demands that will occur for a selected date. Health, social, economic, environmental, and geospatial data related to each of the emergency demands were integrated and related. Linear and nonlinear regression algorithms were used: support vector machine (SVM) with linear kernel and generated linear model (GLM), and the nonlinear SVM with Gaussian kernel.

RESULTS

Predictive models of emergency demand due to respiratory disseases were generated with am absolute error better than 35 %.

CONCLUSIONS

This model helps to make decisions on the efficient sizing of emergency health resources to manage and respond in the shortest possible time to patients with respiratory diseases requiring urgent care in the city of Jaén.

Air quality and individual-level academic performance in Brazil: A nationwide study of more than 15 million students between 2000 and 2020

Studies have shown that living and studying in places with poor air quality is associated with cognitive deficits. However, there is still a limitation in the literature in terms of study design and geographic location. Also, only a few studies have looked at the effects of more than one air pollutant. To address this research gap, in this study we estimated the association between air pollution (considering three criteria air pollutants - PM_2.5, NO₂, and O₃) and academic performance (a proxy of cognitive performance) at the student level in Brazil between 2000 and 2020. We assessed academic performance data from a nationwide high school exam. The data included 15,443,772 students who took this national test between 2000 and 2020 in Brazil. Air pollution data was derived from satellite remote sensing observations. We fit mixed-effects regression models with a state-specific random intercept and adjusted for school characteristics, spatio-temporal factors, and socioeconomic status. We performed sub-group analyses by stratifying the analysis by type of school management (private or public), location of the school (urban or rural), sex, and periods. Our findings suggest air pollution exposure was associated with drops in the students' marks varying from 0.13% to 5.39%. To our knowledge, this is the first study that estimates the association between air pollution and individual-level academic performance in Brazil. This study is of substantial environmental and educational importance by supporting policymakers to improve the air quality surrounding schools.

Association of high ambient temperature with daily hospitalization for cardiorespiratory diseases in Brazil: A national time-series study between 2008 and 2018

Further research is needed to examine the nationwide impact of temperature on health in Brazil, a region with particular challenges related to climate conditions, environmental characteristics, and health equity. To address this gap, in this study, we looked at the relationship between high ambient temperature and hospital admissions for circulatory and respiratory diseases in 5572 Brazilian municipalities between 2008 and 2018. We used an extension of the two-stage design with a case time series to assess this relationship. In the first stage, we applied a distributed lag non-linear modeling framework to create a cross-basis function. We next applied quasi-Poisson regression models adjusted by PM_2.5, O₃, relative humidity, and time-varying confounders. We estimated relative risks (RRs) of the association of heat (percentile 99th) with hospitalization for circulatory and respiratory diseases by sex, age group, and Brazilian regions. In the second stage, we applied meta-analysis with random effects to estimate the national RR. Our study population includes 23,791,093 hospital admissions for cardiorespiratory diseases in Brazil between 2008 and 2018. Among those, 53.1% are respiratory diseases, and 46.9% are circulatory diseases. The robustness of the RR and the effect size varied significantly by region, sex, age group, and health outcome. Overall, our findings suggest that i) respiratory admissions had the highest RR, while circulatory admissions had inconsistent or null RR in several subgroup analyses; ii) there was a large difference in the cumulative risk ratio across regions; and iii) overall, women and the elderly population experienced the greatest impact from heat exposure. The pooled national results for the whole population (all ages and sex) suggest a relative risk of 1.29 (95% CI: 1.26; 1.32) associated with respiratory admissions. In contrast, national meta-analysis for circulatory admissions suggested robust positive associations only for people aged 15-45, 46-65, >65 years old; for men aged 15-45 years old; and women aged 15-45 and 46-65 years old. Our findings are essential for the body of scientific evidence that has assisted policymakers to promote health equity and to create adaptive measures and mitigations.

Climate and human health: a review of publication trends in the International Journal of Biometeorology

The climate-health nexus is well documented in the field of biometeorology. Since its inception, Biometeorology has in many ways become the umbrella under which much of this collaborative research has been conducted. Whilst a range of review papers have considered the development of biometeorological research and its coverage in this journal, and a few have reviewed the literature on specific diseases, none have focused on the sub-field of climate and health as a whole. Since its first issue in 1957, the International Journal of Biometeorology has published a total of 2183 papers that broadly consider human health and its relationship with climate. In this review, we identify a total of 180 (8.3%, n = 2183) of these papers that specifically focus on the intersection between meteorological variables and specific, named diagnosable diseases, and explore the publication trends thereof. The number of publications on climate and health in the journal increases considerably since 2011. The largest number of publications on the topic was in 2017 (18) followed by 2021 (17). Of the 180 studies conducted, respiratory diseases accounted for 37.2% of the publications, cardiovascular disease 17%, and cerebrovascular disease 11.1%. The literature on climate and health in the journal is dominated by studies from the global North, with a particular focus on Asia and Europe. Only 2.2% and 8.3% of these studies explore empirical evidence from the African continent and South America respectively. These findings highlight the importance of continued research on climate and human health, especially in low- and lower-middle-income countries, the populations of which are more vulnerable to climate-sensitive illnesses.

How Vulnerable Are Patients with COPD to Weather Extremities?—A Pilot Study from Hungary

Chronic obstructive pulmonary disease (COPD) is one of the most common causes of death globally, with increasing prevalence and years lived with disability (YLD). We aimed to investigate how extreme weather conditions were associated with the number of daily COPD-related emergency visits. We collected data regarding the number of daily emergency department (ED) visits made by patients with COPD in 2017, along with all relevant daily meteorological data for the same year. An analysis of the relationship between the number of COPD-related ED visits and extreme meteorological events was carried out. Extremely low temperatures (OR = 1.767) and dew points (OR = 1.795), extremely high atmospheric pressure (OR = 1.626), a high amount of precipitation (OR = 1.270), and light wind speed (OR = 1.560) were identified as possible risk factors for a higher number of COPD-related ED visits. In contrast, extremely high temperatures (OR = 0.572) and dew points (OR = 0.606) were found to be possible protective factors for COPD-related ED visits. By determining the meteorological risk factors for a high number of COPD-related ED visits, our study may help provide invaluable data for identifying vulnerable patient groups based on weather events, thus making more optimal capacity planning at the ED possible.

Climate-mediated air pollution associated with COPD severity

Air pollution has been reported to be associated with chronic obstructive pulmonary disease (COPD). Our study aim was to examine the mediating effects of air pollution on climate-associated health outcomes of COPD patients. A cross-sectional study of 117 COPD patients was conducted in a hospital in Taiwan. We measured the lung function, 6-min walking distance, oxygen desaturation, white blood cell count, and percent emphysema (low attenuation area, LAA) and linked these to 0-1-, 0-3-, and 0-5-year lags of individual-level exposure to relative humidity (RH), temperature, and air pollution. Linear regression models were conducted to examine associations of temperature, RH, and air pollution with severity of health outcomes. A mediation analysis was conducted to examine the mediating effects of air pollution on the associations of RH and temperature with health outcomes. We observed that a 1 % increase in the RH was associated with increases in forced expiratory volume in 1 s (FEV₁), eosinophils, and lymphocytes, and a decrease in the total-lobe LAA. A 1 °C increase in temperature was associated with decreases in oxygen desaturation, and right-, left-, and upper-lobe LAA values. Also, a 1 μg/m³ increase in PM_2.5 was associated with a decrease in the FEV₁ and an increase in oxygen desaturation. A 1 μg/m³ increases in PM₁₀ and PM_2.5 was associated with increases in the total-, right-, left, upper-, and lower-lobe (PM_2.5 only) LAA. A one part per billion increase in NO₂ was associated with a decrease in the FEV₁ and an increase in the upper-lobe LAA. Next, we found that NO₂ fully mediated the association between RH and FEV₁. We found PM_2.5 fully mediated associations of temperature with oxygen saturation and total-, right-, left-, and upper-lobe LAA. In conclusion, climate-mediated air pollution increased the risk of decreasing FEV₁ and oxygen saturation and increasing emphysema severity among COPD patients. Climate change-related air pollution is an important public health issue, especially with regards to respiratory disease.

Web-Based Data to Quantify Meteorological and Geographical Effects on Heat Stroke: Case Study in China

Heat stroke is a serious heat-related health outcome that can eventually lead to death. Due to the poor accessibility of heat stroke data, the large-scale relationship between heat stroke and meteorological factors is still unclear. This work aims to clarify the potential relationship between meteorological variables and heat stroke, and quantify the meteorological threshold that affected the severity of heat stroke. We collected daily heat stroke search index (HSSI) and meteorological data for the period 2013-2020 in 333 Chinese cities to analyze the relationship between meteorological variables and HSSI using correlation analysis and Random forest (RF) model. Temperature and relative humidity (RH) accounted for 62% and 9% of the changes of HSSI, respectively. In China, cases of heat stroke may start to occur when temperature exceeds 36°C and RH exceeds 58%. This threshold was 34.5°C and 79% in the north of China, and 36°C and 48% in the south of China. Compared to RH, the threshold of temperature showed a more evident difference affected by altitude and distance from the ocean, which was 35.5°C in inland cities and 36.5°C in coastal cities; 35.5°C in high-altitude cities and 36°C in low-altitude cities. Our findings provide a possible way to analyze the interaction effect of meteorological variables on heat-related illnesses, and emphasizes the effects of geographical environment. The meteorological threshold quantified in this research can also support policymaker to establish a better meteorological warning system for public health.

Impacts of air pollution on COVID-19 case fatality rate: a global analysis

The coronavirus disease 2019 (COVID-19) pandemic is still rapidly spreading globally. To probe high-risk cities and the impacts of air pollution on public health, this study explores the relationship between the long-term average concentration of air pollution and the city-level case fatality rate (CFR) of COVID-19 globally. Then, geographically weighted regression (GWR) is applied to examine the spatial variability of the relationships. Six air pollution factors, including nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃), PM_2.5 (particles with diameter ≤2.5 μm), PM₁₀ (particles with diameter ≤10 μm), and air quality index (AQI), are positively associated with the city-level COVID-19 CFR. Our results indicate that a 1-unit increase in NO₂ (part per billion, PPB), SO₂ (PPB), O₃ (PPB), PM_2.5 (microgram per cubic meter, μg/m³), PM₁₀ (μg/m³), AQI (score), is related to a 1.450%, 1.005%, 0.992%, 0.860%, 0.568%, and 0.776% increase in the city-level COVID-19 CFR, respectively. Additionally, the effects of NO₂, O₃, PM_2.5, AQI, and probability of living with poor AQI on COVID-19 spatially vary in view of the estimation of the GWR. In other words, the adverse impacts of air pollution on health are different among the cities. In summary, long-term exposure to air pollution is negatively related to the COVID-19 health outcome, and the relationship is spatially non-stationary. Our research sheds light on the impacts of slashing air pollution on public health in the COVID-19 pandemic to help governments formulate air pollution policies in light of the local situations.

Asthma and COPD exacerbation in relation to outdoor air pollution in the metropolitan area of Berlin, Germany

Background

Ambient air pollution poses a major risk for the development and aggravation of respiratory diseases. Evidence suggests that even in low-level air pollution environments there is a risk for an increase in adverse respiratory symptoms. We examined whether variations in daily air pollution levels of nitrogen dioxide, ozone, or particulate matter in Berlin, Germany were associated with hospital admissions of chronic obstructive pulmonary disease (COPD) and asthma patients in a time series analysis.

Methods

We calculated single and multi-pollutant models, investigated possible lags in effect, and analysed the influence of meteorological variables on the results. Data from January 2005 through December 2015 were used to quantify the concentration–response.

Results

The risk ratio for asthma patients to be hospitalised on the same day of NO₂ exposure was 1.101 per 10 µg/m³ NO₂ increase (95% CI: 1.013 to 1.195), for COPD patients 1.123 (95% CI: 1.081 to 1.168). Neither the exposure to ozone (95% CI: 0.904 to 1.020), PM₁₀ (95% CI: 0.990 to 1.127), nor PM_2.5 (95% CI: 0.981 to 1.148) was associated with an increased risk ratio for asthma patients to be hospitalised. Risk ratios for the hospital admission of COPD patients were also not increased due to ozone (95% CI: 0.981 to 1.033), PM₁₀ (95% CI: 0.988 to 1.032), or PM_2.5 (95% CI: 0.966 to 1.019) exposure. The presented risk ratios and confidence intervals relate to the day of exposure. We found no increased hospitalisation risks with a delayed occurrence on subsequent days.

Conclusions

A quantifiable, statistically significant increase in risk for asthma and COPD exacerbations owing to NO₂ exposure at levels well below European regulatory limit values was observed.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-022-01983-1.

Machine Learning Models for Predicting the Occurrence of Respiratory Diseases Using Climatic and Air-Pollution Factors

Objectives

Because climatic and air-pollution factors are known to influence the occurrence of respiratory diseases, we used these factors to develop machine learning models for predicting the occurrence of respiratory diseases.

Methods

We obtained the daily number of respiratory disease patients in Seoul. We used climatic and air-pollution factors to predict the daily number of patients treated for respiratory diseases per 10,000 inhabitants. We applied the relief-based feature selection algorithm to evaluate the importance of feature selection. We used the gradient boosting and Gaussian process regression (GPR) methods, respectively, to develop two different prediction models. We also employed the holdout cross-validation method, in which 75% of the data was used to train the model, and the remaining 25% was used to test the trained model. We determined the estimated number of respiratory disease patients by applying the developed prediction models to the test set. To evaluate the performance of each model, we calculated the coefficient of determination (R²) and the root mean square error (RMSE) between the original and estimated numbers of respiratory disease patients. We used the Shapley Additive exPlanations (SHAP) approach to interpret the estimated output of each machine learning model.

Results

Features with negative weights in the relief-based algorithm were excluded. When applying gradient boosting to unseen test data, R² and RMSE were 0.68 and 13.8, respectively. For GPR, the R² and RMSE were 0.67 and 13.9, respectively. SHAP analysis showed that reductions in average temperature, daylight duration, average humidity, sulfur dioxide (SO₂), total solar insolation amount, and temperature difference increased the number of respiratory disease patients, whereas increases in atmospheric pressure, carbon monoxide (CO), and particulate matter ≤2.5 μm in aerodynamic diameter (PM_2.5) increased the number of respiratory disease patients.

Conclusion

We successfully developed models for predicting the occurrence of respiratory diseases using climatic and air-pollution factors. These models could evolve into public warning systems.

Health impacts of wildfire-related air pollution in Brazil: a nationwide study of more than 2 million hospital admissions between 2008 and 2018

We quantified the impacts of wildfire-related PM2.5 on 2 million hospital admissions records due to cardiorespiratory diseases in Brazil between 2008 and 2018. The national analysis shows that wildfire waves are associated with an increase of 23% (95%CI: 12%-33%) in respiratory hospital admissions and an increase of 21% (95%CI: 8%-35%) in circulatory hospital admissions. In the North (where most of the Amazon region is located), we estimate an increase of 38% (95%CI: 30%-47%) in respiratory hospital admissions and 27% (95%CI: 15%-39%) in circulatory hospital admissions. Here we report epidemiological evidence that air pollution emitted by wildfires is significantly associated with a higher risk of cardiorespiratory hospital admissions.

Associations between Dust Exposure and Hospitalizations in El Paso, Texas, USA

The Southwestern USA has been identified as one of the most persistent dust-producing regions of North America, where exposure to inhalable particulate matter (PM10) originating from desertic landscape during dust events/dust exposures (DEs) can reach hazardous levels. El Paso, Texas’s ambient air has reached hazardous levels of PM10 from dust with near zero visibility due to these natural events originating in the surrounding Chihuahuan Desert. The aim of this study was to investigate whether dust exposures in El Paso (generally acute, short-term exposures from nearby source areas) are associated with significant increases in hospitalizations on the day of the exposure and up to seven days afterwards. Using a Poisson regression, it was found that the relative risks of hospitalizations due to a variety of conditions were associated with dust exposures (through increases of 100 μg/m3 maximum hourly PM10 and/or increases of 4.5 m/s maximum hourly wind speed) in El Paso County, Texas between 2010 and 2014. Valley fever, coronary atherosclerosis, genitourinary diseases, neurodegenerative diseases, injury and poisoning, circulatory system conditions, respiratory system diseases, births, septicemia, Associated Diseases (the aggregation of hospital admissions for all causes, each associated with at least 5% of hospitalizations), and all ICD-9 admissions were significantly positively associated with dust exposures, indicated from higher to lower significant risk, at different lag periods after exposure. These findings, showing that an association does exist between dust exposures and hospitalizations, have important implications for residents of the world’s dryland cities.

The Impact of Air Pollutants and Meteorological Factors on Chronic Obstructive Pulmonary Disease Exacerbations: A Nationwide Study

RATIONALE Chronic obstructive lung disease (COPD) is a chronic progressive disease. Although smoking is the most important risk factor, 30% of COPD patients are never smokers, and environmental agents are also influential. The effects of air pollutants and meteorological factors on COPD exacerbations have not been studied extensively. OBJECTIVE We aimed to investigate the air pollutants and meteorological factors that impact the incidence of COPD exacerbations. METHODS We obtained clinical data of COPD exacerbation cases from The National Health Insurance Service (NHIS) and merged it with 24-hour average values of air pollutants and meteorological factors from national databases. Patients who reside in eight metropolitan cities, where observatory stations are densely located, were selected for analysis. RESULTS In 1,404,505 COPD patients between 2013 and 2018, 15,282 COPD exacerbations leading to hospitalization or emergency room visits were identified. Among the various air pollutants and meteorological factors, particulate matter (PM)2.5, PM10, NO2, SO2, CO, O3, average temperature and diurnal temperature range (DTR) were associated with COPD exacerbations. GAM model analysis with cubic splines showed an inverted U-shaped relationship with PM2.5, PM10, CO, NO2, SO2, O3, DTR and humidity, while it displayed a U-shaped pattern with the average temperature. Distinct patterns were found from 2015-2016 to 2017-2018. CONCLUSIONS PM2.5, PM10, CO, NO2, O3, SO2, average temperature, humidity, and DTR affected the incidence of COPD exacerbations in various patterns, up to 10 lag days.

The short-term associations of chronic obstructive pulmonary disease hospitalizations with meteorological factors and air pollutants in Southwest China: a time-series study

Chronic obstructive pulmonary disease (COPD) is the fourth major cause of mortality and morbidity worldwide and is projected to be the third by 2030. However, there is little evidence available on the associations of COPD hospitalizations with meteorological factors and air pollutants in developing countries/regions of Asia. In particular, no study has been done in western areas of China considering the nonlinear and lagged effects simultaneously. This study aims to evaluate the nonlinear and lagged associations of COPD hospitalizations with meteorological factors and air pollutants using time-series analysis. The modified associations by sex and age were also investigated. The distributed lag nonlinear model was used to establish the association of daily COPD hospitalizations of all 441 public hospitals in Chengdu, China from Jan/2015-Dec/2017 with the ambient meteorological factors and air pollutants. Model parameters were optimized based on quasi Akaike Information Criterion and model diagnostics was conducted by inspecting the deviance residuals. Subgroup analysis by sex and age was also performed. Temperature, relative humidity, wind and Carbon Monoxide (CO) have statistically significant and consistent associations with COPD hospitalizations. The cumulative relative risk (RR) was lowest at a temperature of 19℃ (relative humidity of 67%). Both extremely high and low temperature (and relative humidity) increase the cumulative RR. An increase of wind speed above 4 mph (an increase of CO above 1.44 mg/m³) significantly decreases (increases) the cumulative RR. Female populations were more sensitive to low temperature and high CO level; elderly (74+) populations are more sensitive to high relative humidity; younger populations (< = 74) are more susceptible to CO higher than 1.44 mg/m³. Therefore, people with COPD should avoid exposure to adverse environmental conditions of extreme temperatures and relative humidity, low wind speed and high CO level, especially for female and elderly patients who were more sensitive to extreme temperatures and relative humidity.

The Association between Weather Conditions and Admissions to the Paediatric Intensive Care Unit for Respiratory Syncytial Virus Bronchiolitis

Respiratory syncytial virus (RSV) bronchiolitis is a leading cause of global child morbidity and mortality. Every year, seasonal RSV outbreaks put high pressure on paediatric intensive care units (PICUs) worldwide, including in the Netherlands, and this burden appears to be increasing. Weather conditions have a strong influence on RSV activity, and climate change has been proposed as a potential important determinant of future RSV-related health care utilisation. In this national study spanning a total of 13 years with 2161 PICU admissions for RSV bronchiolitis, we aimed (1) to identify meteorological variables that were associated with the number of PICU admissions for RSV bronchiolitis in the Netherlands and (2) to determine if longitudinal changes in these variables occurred over time as a possible explanation for the observed increase in PICU burden. Poisson regression modelling was used to identify weather variables (aggregated in months and weeks) that predicted PICU admissions, and linear regression analysis was used to assess changes in the weather over time. Maximum temperature and global radiation best predicted PICU admissions, with global radiation showing the most stable strength of effect in both month and week data. However, we did not observe a significant change in these weather variables over the 13-year time period. Based on our study, we could not identify changing weather conditions as a potential contributing factor to the increased RSV-related PICU burden in the Netherlands.

What Are the Effects of Meteorological Factors on Exacerbations of Chronic Obstructive Pulmonary Disease?

Chronic obstructive pulmonary disease (COPD) is one of the greatest global public health challenges. Acute exacerbations of COPD lead to the accelerated deterioration of lung function, reduced quality of life, a higher number of hospitalizations, and increased mortality. The factor causing the exacerbation is usually an infectious agent, but the impact of environmental factors is being studied more thoroughly. Among them, meteorological factors are the least examined. Multiple studies have shown that lower temperatures during the cold season, as well as sudden temperature changes regardless of the season, have the most significant negative effect on patients with COPD. However, higher temperatures, especially during summer heatwaves, can also cause COPD exacerbation and it is expected that this will be an even more important health problem in the future considering climate changes. The effects of other meteorological factors on acute exacerbation of COPD, such as atmospheric pressure, solar radiation, rainfall, wind speed, and humidity are far less investigated and opposing results have been obtained in different studies. Thus, there is a need for further research in this area that would result in clinical recommendations and public health interventions that could decrease the global burden of COPD.

Effects of weather, air pollution and Oktoberfest on ambulance-transported emergency department admissions in Munich, Germany

BACKGROUND

Climate change and increasing risks of extreme weather events affect human health and lead to changes in the emergency department (ED) admissions and the emergency medical services (EMS) operations. For a better allocation of resources in the healthcare system, it is essential to predict ED numbers based on environmental variables. This publication aims to quantify weather, air pollution and calendar-related effects on daily ED admissions.

METHODS

Analyses were based on 575,725 admissions from the web-based IVENA system recording all patients in the greater Munich area with pre-hospital emergency care in ambulance operations during 2014-2018. Linear models were used to identify statistically significant associations between daily ED admissions and calendar, meteorological and pollution factors, allowing for lag effects of one to three days. Separate analyses were performed for seasons, with additional subset analyses by sex, age and surgical versus internal department.

RESULTS

ED admissions were exceptionally high during the three-week Oktoberfest, particularly for males and on the weekends, as well as during the New Year holiday. Admissions significantly increased during the years of study, decreased in spring and summer holidays, and were lower on Sundays while higher on Mondays. In the warmer seasons, admissions were significantly associated with higher temperature, adjusting for the effects of sunshine and humidity in all age groups except for the elderly. Adverse weather conditions in non-summer seasons were either linked to increasing ED admissions (from storms, gust) or decreasing them from rain. Mostly, but not exclusively, in winter, increasing ED admissions were associated with colder minimum temperatures as well as with higher NO and PM₁₀ concentrations.

CONCLUSIONS

In addition to standard calendar-related factors, incorporating seasonal weather, air pollutant and interactions with patient demographics into resource planning models can improve the daily allocation of resources and staff of EMS operations at hospital and city levels.

Effect of extreme hot and cold weather on cause-specific hospitalizations in Sweden: A time series analysis

Considering that several meteorological variables can contribute to weather vulnerability, the estimation of their synergetic effects on health is particularly useful. The spatial synoptic classification (SSC) has been used in biometeorological applications to estimate the effect of the entire suite of weather conditions on human morbidity and mortality. In this study, we assessed the relationships between extremely hot and dry (dry tropical plus, DT+) and hot and moist (moist tropical plus, MT+) weather types in summer and extremely cold and dry (dry polar plus, DP+) and cold and moist (moist polar, MP+) weather types in winter and cardiovascular and respiratory hospitalizations by age and sex. Time-series quasi-Poisson regression with distributed lags was used to assess the relationship between oppressive weather types and daily hospitalizations over 14 subsequent days in the extended summer (May to August) and 28 subsequent days during the extended winter (November to March) over 24 years in 4 Swedish locations from 1991 to 2014. In summer, exposure to hot weather types appeared to reduce cardiovascular hospitalizations while increased the risk of hospitalizations for respiratory diseases, mainly related to MT+. In winter, the effect of cold weather on both cause-specific hospitalizations was small; however, MP+ was related to a delayed increase in cardiovascular hospitalizations, whilst MP+ and DP + increased the risk of hospitalizations due to respiratory diseases. This study provides useful information for the staff of hospitals and elderly care centers who can help to implement protective measures for patients and residents. Also, our results could be helpful for vulnerable people who can adopt protective measures to reduce health risks.

Hot and cold weather based on the spatial synoptic classification and cause-specific mortality in Sweden: a time-stratified case-crossover study

The spatial synoptic classification (SSC) is a holistic categorical assessment of the daily weather conditions at specific locations; it is a useful tool for assessing weather effects on health. In this study, we assessed (a) the effect of hot weather types and the duration of heat events on cardiovascular and respiratory mortality in summer and (b) the effect of cold weather types and the duration of cold events on cardiovascular and respiratory mortality in winter. A time-stratified case-crossover design combined with a distributed lag nonlinear model was carried out to investigate the association of weather types with cause-specific mortality in two southern (Skåne and Stockholm) and two northern (Jämtland and Västerbotten) locations in Sweden. During summer, in the southern locations, the Moist Tropical (MT) and Dry Tropical (DT) weather types increased cardiovascular and respiratory mortality at shorter lags; both hot weather types substantially increased respiratory mortality mainly in Skåne. The impact of heat events on mortality by cardiovascular and respiratory diseases was more important in the southern than in the northern locations at lag 0. The cumulative effect of MT, DT and heat events lagged over 14 days was particularly high for respiratory mortality in all locations except in Jämtland, though these did not show a clear effect on cardiovascular mortality. During winter, the dry polar and moist polar weather types and cold events showed a negligible effect on cardiovascular and respiratory mortality. This study provides valuable information about the relationship between hot oppressive weather types with cause-specific mortality; however, the cold weather types may not capture sufficiently effects on cause-specific mortality in this sub-Arctic region.

The effect of atmospheric pressure on oxygen saturation and dyspnea: the Tromsø study

A drop in atmospheric pressure, as observed at high altitudes, leads to decreased oxygen saturation. The effect of regular changes in barometric pressure at sea level has never been studied in a general population. A cohort of adults aged 40 years were examined with pulse oximetry at two separate visits, and the local barometric pressure was available from the local weather station. The study aimed at determining the effect of atmospheric pressure on oxygen saturation also called SpO₂, as well as on shortness of breath. Based on spirometry, the participants were divided into two groups, with normal and decreased lung function. Decreased lung function was defined as forced expiratory volume in 1 s (FEV₁) below lower limit or normal (LLN) or FEV₁/FVC (FVC, forced vital capacity) below LLN, with GLI 2012 reference values. The statistical analysis included uni/multivariable linear and logistic regression. A total of 7439 participants of the Tromsø 7 cohort study were included. There was a significant association between barometric pressure and SpO₂ < 96%, and we found that a reduction of 166.67 hPa was needed to get a 1% reduction in SpO₂. The change in atmospheric pressure was not significantly associated with shortness of breath, also not in subjects with reduced lung function.

Effects of Ambient Temperature on Acute Exacerbations of Chronic Obstructive Pulmonary Disease: Results from a Time-Series Analysis of 143318 Hospitalizations

Purpose

To evaluate the associations between acute exacerbations of chronic obstructive pulmonary disease (AECOPD) hospitalizations and daily mean temperature (Tmean) as well as daily apparent temperature (AT), and to explore the practical values of these two indices in policymaking and patient education.

Methods

Daily AECOPD hospitalizations and Meteorological data in Beijing were obtained between 2013 and 2016. Distributed lag non-linear model was adopted to investigate the association between daily ambient temperature and AECOPD hospitalizations. The cumulative effects of cold/hot temperature were abstracted. For the extreme and moderate low-temperature effect estimates, we, respectively, computed the RR of AECOPD hospitalizations at the 1st and 10th percentiles of temperature in comparison with that at the 25th percentile of temperature. For the extreme and moderate high temperature effect estimates, we, respectively, computed the RR of AECOPD hospitalizations at the 99th and 90th percentiles of temperature in comparison with that at the 75th percentile of temperature.

Results

During the study period, 143, 318 AECOPD hospitalizations were collected. A reverse J-shape relationship was found between temperature and AECOPD hospitalizations. When comparing the effect of Tmean, higher RRs were associated with increases in AT on AECOPD hospitalizations but a lower value of Akaike’s Information Criterion for quasi-Poisson (Q-AIC). The RR of extremely low temperature of Tmean and AT were 1.55 (95% CI: 1.21,2.00) and 2.08 (95% CI: 1.44,3.01), respectively. Moderate low temperature also had an adverse impact on AECOPD hospitalizations. No associations were found between high temperature and AECOPD risk. We found the females and those aged <65 years to be more susceptible to temperature change.

Conclusion

Lower temperature is associated with a higher risk for AECOPD hospitalizations. Ambient temperature is probably a better predictor in terms of quantifying risk than mean temperature when studying temperature impact on health.

The hospitalization attributable burden of acute exacerbations of chronic obstructive pulmonary disease due to ambient air pollution in Shijiazhuang, China

Few studies have investigated the acute exacerbations of chronic obstructive pulmonary disease (AECOPD)-associated attributable burden under exposure to high levels of air pollution among Asians. Data on hospitalization for AECOPD, air pollution and meteorological factors from 1 January 2013 to 31 December 2016 were collected in Shijiazhuang, China. We used a Poisson generalized linear regression model combined with a distributed lag nonlinear model (DLNM) to evaluate the relative cumulative risk for a lag of 0-7 days and examined the potential effect modifications by age and sex via stratification analyses, controlling for long-term trends, seasonal patterns, meteorological factors, and other possible confounders. Then, we computed hospitalization percentages attributable to air pollutants. The AECOPD-associated relative cumulative risks for PM_2.5, PM₁₀, NO₂, SO₂, and CO for a lag of 0-7 days were significantly positively correlated with hospitalization. The associations were stronger in females and retired patients. The NO₂ Cum RR of AECOPD admission was the greatest. A 10μg/m³ increase in daily NO₂ concentration was associated with 6.7% and 5.7% increases in COPD hospitalizations in the retired and female groups, respectively. The results showed that 13%, 9.4%, 1.7%, 9.7%, and 8.8% of AECOPD hospitalizations were attributable to exposure to PM_2.5, PM₁₀, SO₂, NO₂, and CO, respectively. If the air pollutant concentration was reduced to the 24-h average grade II levels of NAAQS of China, the AECOPD attributable percentage for PM_2.5 and PM₁₀ would decrease by 80%. The air pollutants PM_2.5, PM₁₀, SO₂, NO₂, and CO were significantly relevant to AECOPD-associated hospitalization. The associations differed by individual characteristics. The retired and female populations were highly vulnerable.

Comparison of air pollutant-related hospitalization burden from AECOPD in Shijiazhuang, China, between heating and non-heating season

Few researches have been investigated on the effects of ambient air pollutants from coal combustion on acute exacerbation of chronic obstructive pulmonary disease (AECOPD) hospitalizations. The whole time series was split into heating season and non-heating season. We used a quasi-Poisson generalized linear regression model combined with distributed lag non-linear models (DLNMs) to estimate the relative cumulative risk and calculate the air pollutant hospitalization burden of AECOPD for lag 0-7 days in heating season and non-heating season. There were higher PM_2.5, PM₁₀, NO₂, SO₂, and CO concentrations in heating seasons than non-heating season in Shijiazhuang; however, O₃ was higher in non-heating season than heating season. The AECOPD-associated relative cumulative risks for PM_2.5, PM₁₀, NO₂, and SO₂ for lag 0-7 days were significantly positively associated with hospitalization in heating and non-heating season; we found that the cumulative relative risk of NO₂ was the greatest in every 1 unit of air pollutants during the heating season and the cumulative relative risk of SO₂ was the greatest during the non-heating season. The results showed that 17.8%, 12.9%, 1.7%, 16.7%, and 10.5% of AECOPD hospitalizations could be attributable to PM_2.5, PM₁₀, SO₂, NO₂, and CO exposure in heating season, respectively. However, the results showed that 19.5%, 22.4%, 15%, 8.3%, and 10.4% of AECOPD hospitalizations could be attributable to PM_2.5, PM₁₀, SO₂, NO_2, and O₃ exposure in non-heating season, respectively. The attributable burden of AECOPD hospitalization in heating season and non-heating season are different. PM_2.5, PM₁₀, NO₂, and CO are the main factors of heating season, while PM₁₀, PM_2.5, SO₂, and O₃ are the main factors of non-heating season. In conclusions, the centralized heating can change the influence of attributable risk. When government departments formulate interventions to reduce the risk of acute hospitalization of chronic obstructive pulmonary disease (COPD), the influence of heating on disease burden should be considered.

Association between Weather Types based on the Spatial Synoptic Classification and All-Cause Mortality in Sweden, 1991⁻2014

Much is known about the adverse health impact of high and low temperatures. The Spatial Synoptic Classification is a useful tool for assessing weather effects on health because it considers the combined effect of meteorological factors rather than temperature only. The aim of this study was to assess the association between oppressive weather types and daily total mortality in Sweden. Time-series Poisson regression with distributed lags was used to assess the relationship between oppressive weather (Dry Polar, Dry Tropical, Moist Polar, and Moist Tropical) and daily deaths over 14 days in the extended summer (May to September), and 28 days during the extended winter (November to March), from 1991 to 2014. Days not classified as oppressive weather served as the reference category. We computed relative risks with 95% confidence intervals, adjusting for trends and seasonality. Results of the southern (Skåne and Stockholm) and northern (Jämtland and Västerbotten) locations were pooled using meta-analysis for regional-level estimates. Analyses were performed using the dlnm and mvmeta packages in R. During summer, in the South, the Moist Tropical and Dry Tropical weather types increased the mortality at lag 0 through lag 3 and lag 6, respectively. Moist Polar weather was associated with mortality at longer lags. In the North, Dry Tropical weather increased the mortality at shorter lags. During winter, in the South, Dry Polar and Moist Polar weather increased mortality from lag 6 to lag 10 and from lag 19 to lag 26, respectively. No effect of oppressive weather was found in the North. The effect of oppressive weather types in Sweden varies across seasons and regions. In the North, a small study sample reduces precision of estimates, while in the South, the effect of oppressive weather types is more evident in both seasons.

Emergency department asthma diagnosis risk associated with the 2012 heat wave and drought in Douglas County NE, USA

BACKGROUND

Global climate change concerns are forcing local public health agencies to assess potential disease risk.

OBJECTIVE

Determine if risk of an emergency department asthma diagnosis in Douglas County, NE, was higher during the 2012 heatwave compared to 2011.

METHODS

Retrospective, observational, case-control design selecting subjects from 2011 and 2012 emergency department (ED) admissions. Risk was estimated by conditional logistic regression.

RESULTS

The asthma ED risk estimate was 1.23 (95%CI = 0.96-1.57) times higher in 2012 than 2011, for the same calendar period. Asthma ED diagnosis risk was 3.37 (95%CI = 2.27-4.17) times higher among subjects <19years old compared to older subjects, and 3.25 (95%CI = 2.63-4.02) times higher among African-Americans than non-African-Americans, adjusted for heatwave exposure. Absolute humidity appears inversely related to asthma diagnosis risk ( χ2 = 16.6; p < 0.001).

CONCLUSION

Asthma ED diagnosis risk was not significantly higher in 2012 compared to 2011. Risk was elevated among subjects less than 19years old, and among African Americans; adjusted for heatwave exposure.

Chronic lifestyle diseases display seasonal sensitive comorbid trend in human population evidence from Google Trends

Seasonal and human physiological changes are important factors in the development of many diseases. But, the study of genuine seasonal impact on these diseases is difficult to measure due to many other environment and lifestyle factors which directly affect these diseases. However, several clinical studies have been conducted in different parts of the world, and it has clearly indicated that certain groups of population are highly subjected to seasonal changes, and their maladaptation can possibly lead to several disorders/diseases. Thus, it is crucial to study the significant seasonal sensitive diseases spread across the human population. To narrow down these disorders/diseases, the study hypothesized that high altitude (HA) associated diseases and disorders are of the strong variants of seasonal physiologic changes. It is because, HA is the only geographical condition for which humans can develop very efficient physiological adaptation mechanism called acclimatization. To study this hypothesis, PubMed was used to collect the HA associated symptoms and disorders. Disease Ontology based semantic similarity network (DSN) and disease-drug networks were constructed to narrow down the benchmark diseases and disorders of HA. The DSN which was further subjected to different community structure analysis uncovered the highly associated or possible comorbid diseases of HA. The predicted 12 lifestyle diseases were assumed to be “seasonal (sensitive) comorbid lifestyle diseases (SCLD)”. A time series analyses on Google Search data of the world from 2004–2016 was conducted to investigate whether the 12 lifestyle diseases have seasonal patterns. Because, the trends were sensitive to the term used as benchmark; the temporal relationships among the 12 disease search volumes and their temporal sequences similarity by dynamic time warping analyses was used to predict the comorbid diseases. Among the 12 lifestyle diseases, the study provides an indirect evidence in the existence of severe seasonal comorbidity among hypertension, obesity, asthma and fibrosis diseases, which is widespread in the world population. Thus, the present study has successfully addressed this issue by predicting the SCLD, and indirectly verified them among the world population using Google Search Trend. Furthermore, based on the SCLD seasonal trend, the study also classified them as severe, moderate, and mild. Interestingly, seasonal trends of the severe seasonal comorbid diseases displayed an inverse pattern between USA (Northern hemisphere) and New Zealand (Southern hemisphere). Further, knowledge in the so called “seasonal sensitive populations” physiological response to seasonal triggers such as winter, summer, spring, and autumn become crucial to modulate disease incidence, disease course, or clinical prevention.

Ontology-Based Model to Support Ubiquitous Healthcare Systems for COPD Patients

Over the past 30 years, information technology has gradually transformed the way health care is provisioned for patients. Chronic Obstructive Pulmonary Disease (COPD) is an incurable malady that threatens the lives of millions around the world. The huge amount of medical information in terms of complex interdependence between progression of health problems and various other factors makes the representation of data more challenging. This study investigated how formal semantic standards could be used for building an ontology knowledge repository to provide ubiquitous healthcare and medical recommendations for COPD patient to reduce preventable harm. The novel contribution of the suggested framework resides in the patient-centered monitoring approach, as we work to create dynamic adaptive protection services according to the current context of patient. This work executes a sequential modular approach consisting of patient, disease, location, devices, activities, environment and services to deliver personalized real-time medical care for COPD patients. The main benefits of this project are: (1) adhering to dynamic safe boundaries for the vital signs, which may vary depending on multiple factors; (2) assessing environmental risk factors; and (3) evaluating the patient’s daily activities through scheduled events to avoid potentially dangerous situations. This solution implements an interrelated set of ontologies with a logical base of Semantic Web Rule Language (SWRL) rules derived from the medical guidelines and expert pneumologists to handle all contextual situations.

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.

Synergistic effects of temperature and humidity on the symptoms of COPD patients

This panel study investigates how temperature, humidity, and their interaction affect chronic obstructive pulmonary disease (COPD) patients' self-reported symptoms. One hundred and six COPD patients from Shanghai, China, were enrolled, and age, smoking status, St. George Respiratory Questionnaire (SGRQ) score, and lung function index were recorded at baseline. The participants were asked to record their indoor temperature, humidity, and symptoms on diary cards between January 2011 and June 2012. Altogether, 82 patients finished the study. There was a significant interactive effect between temperature and humidity (p < 0.0001) on COPD patients. When the indoor humidity was low, moderate, and high, the indoor temperature ORs were 0.969 (95% CI 0.922 to 1.017), 0.977 (0.962 to 0.999), and 0.920 (95% CI 0.908 to 0.933), respectively. Low temperature was a risk factor for COPD patients, and high humidity enhanced its risk on COPD. The indoor temperature should be kept at least on average at 18.2 °C, while the humidity should be less than 70%. This study demonstrates that temperature and humidity were associated with COPD patients' symptoms, and high humidity would enhance the risk of COPD due to low temperature.

Perception of climate change in patients with chronic lung disease

BACKGROUND

Climate change affects human health. The respective consequences are predicted to increase in the future. Patients with chronic lung disease are particularly vulnerable to the involved environmental alterations. However, their subjective perception and reactions to these alterations remain unknown.

METHODS

In this pilot study, we surveyed 172 adult patients who underwent pulmonary rehabilitation and 832 adult tourists without lung disease in the alpine region about their perception of being affected by climate change and their potential reaction to specific consequences. The patients' survey also contained the COPD Assessment Test (CAT) to rate the severity of symptoms.

RESULTS

Most of the patients stated asthma (73.8%), COPD (9.3%) or both (11.0%) as underlying disease while 5.8% suffered from other chronic lung diseases. Patients and tourists feel equally affected by current climate change in general, while allergic subjects in both groups feel significantly more affected (p = 0.04). The severity of symptoms assessed by CAT correlates with the degree of feeling affected (p<0.01). The main disturbing consequences for patients are decreased air quality, increasing numbers of ticks and mosquitos and a rising risk for allergy and extreme weather events such as thunderstroms, while tourists are less disturbed by these factors. Increasing number of heat-days is of little concern to both groups.

CONCLUSION

Overall patients are more sensitive to health-related consequences of climate change. Yet, the hazard of heat-days seems underestimated and awareness should be raised.

Environmental triggers of COPD symptoms: a case cross-over study

INTRODUCTION

This study investigated the hypothesis that common environmental chemical exposures with known irritant or sensitising properties trigger exacerbations for patients with chronic obstructive pulmonary disease (COPD).

METHODS

We conducted a case cross-over study in 168 patients with COPD who were members of a disease management group in central Massachusetts. Participants completed a baseline health survey and several short exposure surveys. Exposure surveys were administered by a nurse when a participant telephoned to report an exacerbation (case periods) and at a maximum of three randomly identified control periods when they were not experiencing an exacerbation. We compared exposures in the week preceding an exacerbation with exposures in normal (non-exacerbation) weeks. The questionnaire assessed short-term (1 week) home, community and workplace activities and exposures that may be associated with COPD exacerbation.

RESULTS

Self-reported exercise was negatively associated with exacerbation (OR=0.59, 95% CI: 0.35 to 1.00). Among the environmental chemical exposures, car and truck exhaust (OR=4.36, 95% CI: 1.76 to 10.80) and use of scented laundry products (OR=2.69, 95% CI: 1.31 to 5.52) showed strong positive effects. Self-reported respiratory infections were strongly associated with exacerbation (OR=7.90, 95% CI 4.29 to 14.50). Variations in outdoor temperature were associated with COPD exacerbation risk (moderate versus cold temperature OR=1.95, 95% CI 1.09 to 3.49 and warm versus cold OR=0.43, 95% CI: 0.26 to 0.70).

CONCLUSIONS

These results suggest that some environmental chemical exposures may play a role in triggering COPD exacerbations. If confirmed, they may provide useful guidance for patients with COPD to better manage their disease.

Desert dust outbreaks and respiratory morbidity in Athens, Greece

BACKGROUND

Ambient particulate matter (PM) has an adverse effect on respiratory morbidity. Desert dust outbreaks contribute to increased PM levels but the toxicity of desert dust mixed with anthropogenic pollutants needs clarification.

METHODS

We identified 132 days with desert dust episodes and 177 matched days by day of the week, season, temperature and humidity between 2001 and 2006 in Athens, Greece. We collected data on regulated pollutants and daily emergency outpatient visits and admissions for respiratory causes. We applied Poisson regression models adjusting for confounding effects of seasonality, meteorology, holidays and influenza epidemics. We evaluated the sensitivity of our results to co-pollutant exposures and effect modification by age and sex.

RESULTS

A 10 μg/m³ increase in PM₁₀ concentration was associated with 1.95% (95% confidence interval (CI): 0.02%, 3.91%) increase in respiratory emergency room visits. No significant interaction with desert dust episodes was observed. Compared with non-dust days, there was a 47% (95% CI: 29%, 68%) increase in visits in dust days not adjusting for PM₁₀. Desert dust days were associated with higher numbers of emergency room visits for asthma, chronic obstructive pulmonary disease and respiratory infections with increases of 38%, 57% and 60%, respectively (p < 0.001 for all comparisons). Analyses of respiratory hospital admissions provided similar results. PM₁₀ effects decreased when adjusting for desert dust days and were further confounded by co-pollutants.

CONCLUSIONS

Desert dust episode days are associated with higher respiratory emergency room visits and hospital admissions. This effect is insufficiently explained by increased PM₁₀ levels.

Urban air pollution and meteorological factors affect emergency department visits of elderly patients with chronic obstructive pulmonary disease in Taiwan

Both air pollution and meteorological factors in metropolitan areas increased emergency department (ED) visits from people with chronic obstructive pulmonary disease (COPD). Few studies investigated the associations between air pollution, meteorological factors, and COPD-related health disorders in Asian countries. This study aimed to investigate the relationship between the environmental factors and COPD-associated ED visits of susceptible elderly population in the largest Taiwanese metropolitan area (Taipei area, including Taipei city and New Taipei city) between 2000 and 2013. Data of air pollutant concentrations (PM₁₀, PM_2.5, O₃, SO₂, NO₂ and CO), meteorological factors (daily temperature, relative humidity and air pressure), and daily COPD-associated ED visits were collected from Taiwan Environmental Protection Administration air monitoring stations, Central Weather Bureau stations, and the Taiwan National Health Insurance database in Taipei area. We used a case-crossover study design and conditional logistic regression models with odds ratios (ORs), and 95% confidence intervals (CIs) for evaluating the associations between the environmental factors and COPD-associated ED visits. Analyses showed that PM_2.5, O₃, and SO₂ had significantly greater lag effects (the lag was 4 days for PM_2.5, and 5 days for O₃ and SO₂) on COPD-associated ED visits of the elderly population (65-79 years old). In warmer days, a significantly greater effect on elderly COPD-associated ED visits was estimated for PM_2.5 with coexistence of O₃. Additionally, either O₃ or SO₂ combined with other air pollutants increased the risk of elderly COPD-associated ED visits in the days of high relative humidity and air pressure difference, respectively. This study showed that joint effect of urban air pollution and meteorological factors contributed to the COPD-associated ED visits of the susceptible elderly population in the largest metropolitan area in Taiwan. Government authorities should review existing air pollution policies, and strengthen health education propaganda to ensure the health of the susceptible elderly population.

Towards a threshold climate for emergency lower respiratory hospital admissions

Identification of 'cut-points' or thresholds of climate factors would play a crucial role in alerting risks of climate change and providing guidance to policymakers. This study investigated a 'Climate Threshold' for emergency hospital admissions of chronic lower respiratory diseases by using a distributed lag non-linear model (DLNM). We analysed a unique longitudinal dataset (10 years, 2000-2009) on emergency hospital admissions, climate, and pollution factors for the Greater London. Our study extends existing work on this topic by considering non-linearity, lag effects between climate factors and disease exposure within the DLNM model considering B-spline as smoothing technique. The final model also considered natural cubic splines of time since exposure and 'day of the week' as confounding factors. The results of DLNM indicated a significant improvement in model fitting compared to a typical GLM model. The final model identified the thresholds of several climate factors including: high temperature (≥27°C), low relative humidity (≤ 40%), high Pm10 level (≥70-µg/m³), low wind speed (≤ 2 knots) and high rainfall (≥30mm). Beyond the threshold values, a significantly higher number of emergency admissions due to lower respiratory problems would be expected within the following 2-3 days after the climate shift in the Greater London. The approach will be useful to initiate 'region and disease specific' climate mitigation plans. It will help identify spatial hot spots and the most sensitive areas and population due to climate change, and will eventually lead towards a diversified health warning system tailored to specific climate zones and populations.

Low level air pollution and exacerbation of existing copd: a case crossover analysis

BACKGROUND

Exacerbations of chronic obstructive pulmonary disease (COPD) contribute greatly to increased morbidity, mortality and diminished quality of life. Recent studies report moderately strong positive associations between exposures to several air pollutants and COPD-related emergency department (ED) visits and hospital admissions (HA). Studies that use clinically defined exacerbations rather than counting ED visits and HA may be more sensitive to environmental triggers like air pollution, but very few such studies exist. Participants in a COPD disease management group living in an area of low air pollution and who were followed closely for the earliest signs of an exacerbation provided an opportunity to study associations between air pollution and COPD exacerbation.

METHODS

Associations between short term exposures to air pollutants, including sulfur dioxide (SO2), nitrogen dioxide (NO2), and particulate matter < 2.5 microns (PM2.5), and COPD exacerbation were assessed among 168 patients residing in central Massachusetts, a region with air pollution levels well below USEPA National Ambient Air Quality Standards (NAAQS). Case-crossover analyses and multivariate conditional logistic regression were used to estimate associations between 7-day average concentrations of each air pollutant, as measured at central site monitors, and COPD exacerbation experienced in the patients' homes during the period 2012-2013, while controlling for temperature and self-reported influenza.

RESULTS

We found that short-term exposures to SO2 were associated with an increase in COPD exacerbation risk (odds ratio (OR) = 2.45, 95 % CI: 1.75-3.45 per 1 ppb increase) after adjustment for PM2.5. Short-term exposures to NO2 concentrations showed a weaker association, (OR = 1.17, 95 % CI: 1.05-1.30 per 1 ppb increase) after adjustment for PM2.5. An unexpectedly modest negative association was seen for short-term exposures to PM2.5.

CONCLUSIONS

Despite living in an area with air pollution concentrations below current USEPA NAAQS, these COPD patients appeared to suffer increased risk of COPD exacerbation following short-term exposures to increased concentrations of SO2 and NO2. An unexpected negative association with PM2.5 may result from the complex air chemistry of low level PM in this region.

Meteorological Factors Related to Emergency Admission of Elderly Stroke Patients in Shanghai: Analysis with a Multilayer Perceptron Neural Network

Background

The aim of this study was to predict the emergency admission of elderly stroke patients in Shanghai by using a multilayer perceptron (MLP) neural network.

Material/Methods

Patients (>60 years) with first-ever stroke registered in the Emergency Center of Neurology Department, Shanghai Tenth People’s Hospital, from January 2012 to June 2014 were enrolled into the present study. Daily climate records were obtained from the National Meteorological Office. MLP was used to model the daily emergency admission into the neurology department with meteorological factors such as wind level, weather type, daily maximum temperature, lowest temperature, average temperature, and absolute temperature difference. The relationships of meteorological factors with the emergency admission due to stroke were analyzed in an MLP model.

Results

In 886 days, 2180 first-onset elderly stroke patients were enrolled, and the average number of stroke patients was 2.46 per day. MLP was used to establish a model for the prediction of dates with low stroke admission (≤4) and those with high stroke admission (≥5). For the days with low stroke admission, the absolute temperature difference accounted for 40.7% of admissions, while for the days with high stroke admission, the weather types accounted for 73.3%.

Conclusions

Outdoor temperature and related meteorological parameters are associated with stroke attack. The absolute temperature difference and the weather types have adverse effects on stroke. Further study is needed to determine if other meteorological factors such as pollutants also play important roles in stroke attack.

Seasonality, ambient temperatures and hospitalizations for acute exacerbation of COPD: a population-based study in a metropolitan area

BACKGROUND

Excluding the tropics, exacerbations of chronic obstructive pulmonary disease (COPD) are more frequent in winter. However, studies that directly relate hospitalizations for exacerbation of COPD to ambient temperature are lacking. The aim of this study was to assess the influence of temperature on the number of hospitalizations for COPD.

METHODS

This was a population-based study in a metropolitan area. All hospital discharges for acute exacerbation of COPD during 2009 in Barcelona and its metropolitan area were analyzed. The relationship between the number of hospitalizations for COPD and the mean, minimum, and maximum temperatures alongside comorbidity, humidity, influenza rate, and environmental pollution were studied.

RESULTS

A total of 9,804 hospitalization discharges coded with COPD exacerbation as a primary diagnosis were included; 75.4% of cases were male with a mean age of 74.9±10.5 years and an average length of stay of 6.5±6.1 days. The highest number of admissions (3,644 [37.2%]) occurred during winter, followed by autumn with 2,367 (24.1%), spring with 2,347 (23.9%), and summer with 1,446 (14.7%; P<0.001). The maximum, minimum, and mean temperatures were associated similarly with the number of hospitalizations. On average, we found that for each degree Celsius decrease in mean weekly temperature, hospital admissions increased by 5.04% (r(2)=0.591; P<0.001). After adjustment for humidity, comorbidity, air pollution, and influenza-like illness, only mean temperatures retained statistical significance, with a mean increase of 4.7% in weekly admissions for each degree Celsius of temperature (r(2)=0.599, P<0.001).

CONCLUSION

Mean temperatures are closely and independently related to the number of hospitalizations for COPD.

Can meteorological factors forecast asthma exacerbation in a paediatric population?

BACKGROUND

Asthma exacerbations attended in emergency departments show a marked seasonality in the paediatric age. This seasonal pattern can change from one population to another and the factors involved are poorly understood.

OBJECTIVES

To evaluate the association between meteorological factors and schooling with asthma exacerbations in children attended in the paediatric emergency department of a district hospital.

METHODS

We conducted a retrospective review of the medical records of children 5-14 years of age attended for asthma exacerbations during a 4-year period (2007-2011). Climatic data were obtained from a weather station located very close to the population studied. The number of asthma exacerbations was correlated to temperature, barometric pressure, relative humidity, rainfall, wind speed, wind distance, solar radiation, water vapour pressure and schooling, using regression analyses.

RESULTS

During the study period, 371 children were attended for asthma exacerbations; median age was eight years (IQR: 6-11), and 59% were males. Asthma exacerbations showed a bimodal pattern with peaks in spring and summer. Maximum annual peak occurred in week 39, within 15 days from school beginning after the summer holidays. A regression model with mean temperature, water vapour pressure, relative humidity, maximum wind speed and schooling could explain 98.4% (p<0.001) of monthly asthma exacerbations.

CONCLUSIONS

The combination of meteorological factors and schooling could predict asthma exacerbations in children attended in a paediatric emergency department.

The effect of the weather on pulmonary exacerbations and viral infections among adults with cystic fibrosis

The effect of changes in the weather on the respiratory health of patients with cystic fibrosis (CF) is unclear. We conducted a prospective study to determine the impact of climate and season on the incidence of viral respiratory infections (VRI) and pulmonary exacerbations (PEx) among adults with CF. Between December 2010 and April 2012, 98 adults with CF were followed for 12 months. Polymerase chain reaction assays for nine viruses were performed on sputum, nose and throat swabs every 2 months and additionally at onset of PEx. Hourly temperature and relative humidity measurements were recorded throughout the study. Statistical analysis utilized generalized estimating equation (GEE) models. Pre-specified criteria for VRI and PEx were met at 29% and 37% of visits, respectively. Rhinovirus accounted for 72% of identified viruses. Incidence of rhinovirus peaked in autumn while non-rhinovirus VRI peaked in winter. Rhinovirus was associated with increased mean temperatures (OR 1.07; p = 0.001), while non-rhinovirus VRI was associated with lower mean temperatures (OR 0.87; p < 0.001). PEx occurred frequently throughout the study with no clear seasonal pattern observed. There was no significant association between climate variables and the incidence of either PEx or antibiotic prescription. There is a seasonal pattern to VRI in adults with CF. The incidence of VRI but not PEx is associated with changes in ambient temperature.

A retrospective study of the impact of a telephone alert service (Healthy Outlook) on hospital admissions for patients with chronic obstructive pulmonary disease

BACKGROUND

Healthy Outlook is a service delivered by the UK Met Office directly to patients with chronic obstructive pulmonary disease (COPD) that has been in place since 2006. Its objective is to reduce the severity and length of COPD exacerbations, hence improving the quality of life and life expectancy.

AIMS

To assess the effect of the Healthy Outlook service on hospital admission rates of all general practitioners that have used the service.

METHODS

Control practices were selected for each of the 661 participating practices. The number of hospital admissions for each practice was extracted from the Hospital Episode Statistics database. The differences in admission rates per practice between the first year of use of the Healthy Outlook service and the previous year were compared by paired t-test analyses.

RESULTS

For admissions with a primary diagnosis of COPD, the difference between participating and control practices was -0.8% (95% confidence interval (CI)=-1.8 to 0.2%; P=0.13). For admissions with a primary or co-morbid diagnosis of COPD, the difference was -2.3% (95% CI=-4.2 to -0.4%; P=0.02).

CONCLUSIONS

Participation in the Healthy Outlook service reduces hospital admission rates for patients coded on discharge with COPD (including co-morbid).

The effect of cold temperature on increased exacerbation of chronic obstructive pulmonary disease: a nationwide study

Background

Seasonal variations in the acute exacerbation of chronic obstructive pulmonary disease (COPD) have been reported. However, the influence of air temperature and other meteorological factors on COPD exacerbation remains unclear.

Methods

National Health Insurance registry data from January 1, 1999 to December 1, 2009 and meteorological variables from the Taiwan Central Weather Bureau for the same period were analyzed. A case-crossover study design was used to investigate the association between COPD exacerbation and meteorological variables.

Results

A total of 16,254 cases who suffered from COPD exacerbation were enrolled. We found that a 1°C decrease in air temperature was associated with a 0.8% increase in the exacerbation rate on event-days (95% confidence interval (CI), 1.015–1.138, p = 0.015). With a 5°C decrease in mean temperature, the cold temperature (28-day average temperature) had a long-term effect on the exacerbation of COPD (odds ratio (OR), 1.106, 95% CI 1.063–1.152, p<0.001). In addition, elderly patients and those who did not receive inhaled medication tended to suffer an exacerbation when the mean temperature dropped 5°C. Higher barometric pressure, more hours of sunshine, and lower humidity were associated with an increase in COPD exacerbation.

Conclusions

This study demonstrated the effect of cold temperatures on the COPD exacerbation rate. Elderly patients and those without inhaled medicine before the exacerbation event were affected significantly by lower mean temperatures. A more comprehensive program to prevent cold stress in COPD patients may lead to a reduction in the exacerbations rate of COPD.

A respiratory alert model for the Shenandoah Valley, Virginia, USA

Respiratory morbidity (particularly COPD and asthma) can be influenced by short-term weather fluctuations that affect air quality and lung function. We developed a model to evaluate meteorological conditions associated with respiratory hospital admissions in the Shenandoah Valley of Virginia, USA. We generated ensembles of classification trees based on six years of respiratory-related hospital admissions (64,620 cases) and a suite of 83 potential environmental predictor variables. As our goal was to identify short-term weather linkages to high admission periods, the dependent variable was formulated as a binary classification of five-day moving average respiratory admission departures from the seasonal mean value. Accounting for seasonality removed the long-term apparent inverse relationship between temperature and admissions. We generated eight total models specific to the northern and southern portions of the valley for each season. All eight models demonstrate predictive skill (mean odds ratio = 3.635) when evaluated using a randomization procedure. The predictor variables selected by the ensembling algorithm vary across models, and both meteorological and air quality variables are included. In general, the models indicate complex linkages between respiratory health and environmental conditions that may be difficult to identify using more traditional approaches.