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Rationale: Out-of-hospital coronary heart disease death is a major public health problem, but the association with air pollution is not well understood.Objectives: We evaluated the association between daily ambient air pollution levels (particle number concentration [PNC]--a proxy for ultrafine particles [diameter < 0.1 microm], mass of particles with diameter less than 10 microm [PM[10]; CO, NO[2], and O[3]) and the occurrence of fatal, nonhospitalized coronary events.Methods: Subjects were 5,144 out-of-hospital fatalities (410-414, International Classification of Diseases-9; 1998-2000) who had been residents of Rome. Hospitalizations during the 3 yr before death were considered to identify comorbidities (e.g., diabetes, hypertension, heart failure, dysrhythmia, chronic obstructive pulmonary disease). Statistical analyses were performed using a case-crossover design.Measurements and Main Results: The association with out-of-hospital coronary deaths was statistically significant for PNC, PM[10], and CO. Air pollution on the day of death had the strongest effect (e.g., 7.6% increase [95% confidence interval, 2.0-13.6%]) for an interquartile range of PNC, 27,790 particles/cm[3]. The 65-74- and 75+-yr age groups were at higher risk than the 35-64-yr age group, and there was a suggestion of effect modification for people with hypertension and chronic obstructive pulmonary disease.Conclusions: Air pollutants originating from combustion processes, including ultrafine particles, are related to fatal, nonhospitalized coronary events. The effect is stronger among people over 65 years of age, but is not limited to a group with a specific comorbidity. [ABSTRACT FROM AUTHOR]

Abstract Background More people die in the winter from cardiac disease, and there are competing hypotheses to explain this. The authors conducted a study in 48 US cities to determine how much of the seasonal pattern in cardiac deaths could be explained by influenza epidemics, whether that allowed a more parsimonious control for season than traditional spline models, and whether such control changed the short term association with temperature. Methods The authors obtained counts of daily cardiac deaths and of emergency hospital admissions of the elderly for influenza during 1992–2000. Quasi-Poisson regression models were conducted estimating the association between daily cardiac mortality, and temperature. Results Controlling for influenza admissions provided a more parsimonious model with better Generalized Cross-Validation, lower residual serial correlation, and better captured Winter peaks. The temperature-response function was not greatly affected by adjusting for influenza. The pooled estimated increase in risk for a temperature decrease from 0 to −5°C was 1.6% (95% confidence interval (CI) 1.1-2.1%). Influenza accounted for 2.3% of cardiac deaths over this period. Conclusions The results suggest that including epidemic data explained most of the irregular seasonal pattern (about 18% of the total seasonal variation), allowing more parsimonious models than when adjusting for seasonality only with smooth functions of time. The effect of cold temperature is not confounded by epidemics.

Abstract Background Associations between air temperature and mortality have been consistently observed in Europe and the United States; however, there is a lack of studies for Asian countries. Our study investigated the association between air temperature and cardio-respiratory mortality in the urban area of Beijing, China. Methods Death counts for cardiovascular and respiratory diseases for adult residents (≥15 years), meteorological parameters and concentrations of particulate air pollution were obtained from January 2003 to August 2005. The effects of two-day and 15-day average temperatures were estimated by Poisson regression models, controlling for time trend, relative humidity and other confounders if necessary. Effects were explored for warm (April to September) and cold periods (October to March) separately. The lagged effects of daily temperature were investigated by polynomial distributed lag (PDL) models. Results We observed a J-shaped exposure-response function only for 15-day average temperature and respiratory mortality in the warm period, with 21.3°C as the threshold temperature. All other exposure-response functions could be considered as linear. In the warm period, a 5°C increase of two-day average temperature was associated with a RR of 1.098 (95% confidence interval (95%CI): 1.057-1.140) for cardiovascular and 1.134 (95%CI: 1.050-1.224) for respiratory mortality; a 5°C decrease of 15-day average temperature was associated with a RR of 1.040 (95%CI: 0.990-1.093) for cardiovascular mortality. In the cold period, a 5°C increase of two-day average temperature was associated with a RR of 1.149 (95%CI: 1.078-1.224) for respiratory mortality; a 5°C decrease of 15-day average temperature was associated with a RR of 1.057 (95%CI: 1.022-1.094) for cardiovascular mortality. The effects remained robust after considering particles as additional confounders. Conclusions Both increases and decreases in air temperature are associated with an increased risk of cardiovascular mortality. The effects of heat were immediate while the ones of cold became predominant with longer time lags. Increases in air temperature are also associated with an immediate increased risk of respiratory mortality.

Abstract Background According to the hygiene hypothesis, infections in early life protect from allergic diseases. However, in earlier studies surrogate measures of infection rather than clinical infections were associated with decreased frequencies of atopic diseases. Exposure to infection indicating sub-clinical infection rather than clinical infection might protect from atopic diseases. Objective: to investigate whether exposure to acute respiratory infections within pregnancy and the first year of life is associated with atopic conditions at age 5–14 years and to explore when within pregnancy and the first year of life this exposure is most likely to be protective. Methods Historical cohort study: Population level data on acute respiratory infections from the routine reporting system of the former German Democratic Republic were linked with individual data from consecutive surveys on atopic diseases in the same region (n = 4672). Statistical analyses included multivariate logistic regression analysis and polynomial distributed lag models. Results High exposure to acute respiratory infection between pregnancy and age one year was associated with overall reduced odds of asthma, eczema, hay fever, atopic sensitization and total IgE. Exposure in the first 9 months of life showed the most pronounced effect. Adjusted odds ratio's for asthma, hay fever, inhalant sensitization and total IgE were statistical significantly reduced up to around half. Conclusion Exposure to respiratory infection (most likely indicating sub-clinical infection) within pregnancy and the first year of life may be protective in atopic diseases development. The post-natal period thereby seems to be particularly important.

Purpose: TransCelerate BioPharma surveyed its member biopharmaceutical companies to understand current practices and identify opportunities to complement safety signal assessment with rapid real-world data (RWD) analysis., Methods: A voluntary 30-question questionnaire regarding the use of RWD in safety signal assessment was disseminated to subject matter experts at all TransCelerate member companies in July 2022. Responses were blinded, aggregated, summarized, and presented., Results: Eighteen of 20 member companies provided responses to the questionnaire. Sixteen (89%) companies reported actively leveraging RWD in their signal assessment processes. Of 18 respondent companies, 8 (44%) routinely use rapid approaches to RWD analysis, 7 (39%) utilize rapid RWD analysis non-routinely or in a pilot setting, 2 (11%) are considering using rapid RWD analysis, and 1 (6%) has no plans to use rapid RWD analysis for their signal assessment. Most companies reported that RWD adds context to and improves quality of signal assessments. To conduct RWD analysis for signal assessment, 16 of 17 (94%) respondent companies utilize or plan to utilize internally available data, 8 (47%) utilize both internal and external data, and 3 (18%) utilize data networks. Respondents identified key challenges to rapidly performing RWD analyses, including data access/availability, time for analysis execution, and uncertainties regarding acceptance of minimal or non-protocolized approaches by health authorities., Conclusion: Biopharmaceutical companies reported that they see value in the use of rapid RWD analyses for complementing signal assessments. Future work is recommended to offer a framework and process for use of rapid use of RWD analyses in signal assessment., (© 2024. The Author(s).)

Background: Prior studies have reported an association between traffic-related air pollution in urban areas and exacerbation of cardiovascular disease. We assess here whether time spent in different modes of transportation can trigger the onset of acute myocardial infarction (AMI)., Design: We performed a case-crossover study. We interviewed consecutive cases of AMI in the KORA Myocardial Infarction Registry in Augsburg, Southern Germany between February 1999 and December 2003 eliciting data on potential triggers in the four days preceding myocardial infarction onset., Results: A total of 1459 cases with known date and time of AMI symptom onset, who had survived 24 hours after the onset, completed the registry's standard interview on potential triggers of AMI. An association between exposure to traffic and AMI onset 1 hour later was observed (odds ratio: 3.2; 95% confidence interval [CI]: 2.7-3.9, p < 0.001). Using a car was the most common source of traffic exposure; nevertheless, times spent in public transport or on a bicycle were similarly associated with AMI onset 1 hour later. While the highest risk for AMI onset was within 1 hour of exposure to traffic, the elevated risk persisted for up to 6 hours. Women, patients aged 65 years or older, patients not part of the workforce, and those with a history of angina or diabetes exhibited the largest associations between times spent in traffic and AMI onset 1 hour later., Conclusion: The data suggest that transient exposure to traffic regardless of the means of transportation may increase the risk of AMI transiently.

Background: Although several studies have examined associations between temperature and cardiovascular-disease-related mortality, fewer have investigated the association between temperature and the development of acute myocardial infarction (MI). Moreover, little is known about who is most susceptible to the effects of temperature., Methods: We analyzed data from the Worcester Heart Attack Study, a community-wide investigation of acute MI in residents of the Worcester (MA) metropolitan area. We used a case-crossover approach to examine the association of apparent temperature with acute MI occurrence and with all-cause in-hospital and postdischarge mortality. We examined effect modification by sociodemographic characteristics, medical history, clinical complications, and physical environment., Results: A decrease in an interquartile range in apparent temperature was associated with an increased risk of acute MI on the same day (hazard ratio = 1.15 [95% confidence interval = 1.01-1.31]). Extreme cold during the 2 days prior was associated with an increased risk of acute MI (1.36 [1.07-1.74]). Extreme heat during the 2 days prior was also associated with an increased risk of mortality (1.44 [1.06-1.96]). Persons living in areas with greater poverty were more susceptible to heat., Conclusions: Exposure to cold increased the risk of acute MI, and exposure to heat increased the risk of dying after an acute MI. Local area vulnerability should be accounted for as cities prepare to adapt to weather fluctuations as a result of climate change.

Introduction: In empirical studies it has repeatedly been shown that the socioeconomic status (SES) of a region could infl uence the health status of its inhabitants, even if measures of individual SES are controlled for. This research has just started in Germany, but most studies focus on large geographical areas such as rural districts. Taking the example of districts in the city of Augsburg, the analyses focus on the question if these associations can also be found in a small-scale regional comparison., Methods: We included 1 888 participants of the KORA S4 Survey aged 25-74 years. The city districts were grouped according to the unemployment rate (low, medium, high). The dependent variables were self-rated health and 3 risk factors (obesity, high waist-hip ratio, hypertension). Additional individual variables included are age, sex, educational level and unemployment. The analyses were based on multilevel logistic regressions., Results: After adjustment for individual level variables (age, sex, education, unemployment), the analyses show a signifi cantly increased risk of 'high waist-hip ratio' in the regions with the highest unemployment rate (OR 1.53; 95 % conf. interval 1.03-2.26). A similar association was found for obesity. No signifi cant association was observed between unemployment rate on the one hand and hypertension and self-rated health on the other., Conclusion: Some health risks seem to be especially high in city districts characterised by a high unemployment rate. It can be concluded that interventions aimed at reducing these risks should focus on districts with high unemployment rates. Further studies are needed for an understanding of the causes behind the social and regional inequalities shown here., (© Georg Thieme Verlag KG Stuttgart · New York.)

The success of epidemiological studies depends on the use of appropriate exposure variables. The purpose of this study is to extract a relatively small selection of variables characterizing ambient particulate matter from a large measurement data set. The original data set comprised a total of 96 particulate matter variables that have been continuously measured since 2004 at an urban background aerosol monitoring site in the city of Augsburg, Germany. Many of the original variables were derived from measured particle size distribution (PSD) across the particle diameter range 3 nm to 10 μm, including size-segregated particle number concentration, particle length concentration, particle surface concentration and particle mass concentration. The data set was complemented by integral aerosol variables. These variables were measured by independent instruments, including black carbon, sulfate, particle active surface concentration and particle length concentration. It is obvious that such a large number of measured variables cannot be used in health effect analyses simultaneously. The aim of this study is a pre-screening and a selection of the key variables that will be used as input in forthcoming epidemiological studies. In this study, we present two methods of parameter selection and apply them to data from a two-year period from 2007 to 2008. We used the agglomerative hierarchical cluster method to find groups of similar variables. In total, we selected 15 key variables from 9 clusters which are recommended for epidemiological analyses. We also applied a two-dimensional visualization technique called "heatmap" analysis to the Spearman correlation matrix. 12 key variables were selected using this method. Moreover, the positive matrix factorization (PMF) method was applied to the PSD data to characterize the possible particle sources. Correlations between the variables and PMF factors were used to interpret the meaning of the cluster and the heatmap analyses., (Copyright © 2012 Elsevier B.V. All rights reserved.)

Background and Objectives: self-reported road traffic noise annoyance is commonly used in epidemiological studies for assessment of potential health effects. Alternatively, some studies have used geographic information system (GIS) modelled exposure to road traffic noise as an objective parameter. The aim of this study was to analyse the association between noise exposure due to neighbouring road traffic and the noise annoyance of adults, taking other determinants into consideration., Methods: parents of 951 Munich children from the two German birth cohorts GINIplus and LISAplus reported their annoyance due to road traffic noise at home. GIS modelled road traffic noise exposure (L(den), maximum within a 50 m buffer) from the noise map of the city of Munich was available for all families. GIS-based calculated distance to the closest major road (≥10,000 vehicles per day) and questionnaire based-information about family income, parental education and the type of the street of residence were explored for their potential influence. An ordered logit regression model was applied. The noise levels (L(den)) and the reported noise annoyance were compared with an established exposure-response function., Results: the correlation between noise annoyance and noise exposure (L(den)) was fair (Spearman correlation r(s) = 0.37). The distance to a major road and the type of street were strong predictors for the noise annoyance. The annoyance modelled by the established exposure-response function and that estimated by the ordered logit model were moderately associated (Pearson's correlation r(p) = 0.50)., Conclusions: road traffic noise annoyance was associated with GIS modelled neighbouring road traffic noise exposure (L(den)). The distance to a major road and the type of street were additional explanatory factors of the noise annoyance appraisal.

Background: Associations between air temperature and mortality have been consistently observed in Europe and the United States; however, there is a lack of studies for Asian countries. Our study investigated the association between air temperature and cardio-respiratory mortality in the urban area of Beijing, China., Methods: Death counts for cardiovascular and respiratory diseases for adult residents (≥15 years), meteorological parameters and concentrations of particulate air pollution were obtained from January 2003 to August 2005. The effects of two-day and 15-day average temperatures were estimated by Poisson regression models, controlling for time trend, relative humidity and other confounders if necessary. Effects were explored for warm (April to September) and cold periods (October to March) separately. The lagged effects of daily temperature were investigated by polynomial distributed lag (PDL) models., Results: We observed a J-shaped exposure-response function only for 15-day average temperature and respiratory mortality in the warm period, with 21.3°C as the threshold temperature. All other exposure-response functions could be considered as linear. In the warm period, a 5°C increase of two-day average temperature was associated with a RR of 1.098 (95% confidence interval (95%CI): 1.057-1.140) for cardiovascular and 1.134 (95%CI: 1.050-1.224) for respiratory mortality; a 5°C decrease of 15-day average temperature was associated with a RR of 1.040 (95%CI: 0.990-1.093) for cardiovascular mortality. In the cold period, a 5°C increase of two-day average temperature was associated with a RR of 1.149 (95%CI: 1.078-1.224) for respiratory mortality; a 5°C decrease of 15-day average temperature was associated with a RR of 1.057 (95%CI: 1.022-1.094) for cardiovascular mortality. The effects remained robust after considering particles as additional confounders., Conclusions: Both increases and decreases in air temperature are associated with an increased risk of cardiovascular mortality. The effects of heat were immediate while the ones of cold became predominant with longer time lags. Increases in air temperature are also associated with an immediate increased risk of respiratory mortality.

Although ambient particulate matter contributes to atherosclerosis in animal models, its role in atherogenesis in humans needs to be established. This article discusses concepts, study design, and choice of health outcomes to efficiently investigate the atherogenic role of ambient air pollution, with an emphasis on early preclinical biomarkers of atherosclerosis that are unaffected by short-term exposure to air pollution (eg, carotid intima-media thickness [CIMT] and functional performance of the vessel). Air pollution studies using these end points are summarized. The CIMT is currently the most frequently used outcome in this field (6 studies). The continuous nature of CIMT, the lack of short-term variation, its relationship to atherosclerotic changes in the artery wall, its predictive value for coronary heart disease, and the noninvasiveness of the assessment make it a useful candidate for cross-sectional and longitudinal studies investigating the role of air pollution in atherogenesis., (Copyright © 2011 Elsevier Inc. All rights reserved.)