1,720,970 research outputs found
Association between air pollution and emergency room visits for atrial fibrillation
Full text linkDespite the large prevalence in the population, possible factors responsible for the
induction of atrial fibrillation (AF) events in susceptible individuals remain incompletely understood.
We investigated the association between air pollution levels and emergency department admissions
for AF in Rome. We conducted a 14 years’ time-series study to evaluate the association between the
daily levels of air pollution (particulate matter, PM10 and PM2.5, and nitrogen dioxide, NO2) and
the daily count of emergency accesses for AF (ICD-9 code: 427.31). We applied an over-dispersed
conditional Poisson model to analyze the associations at different lags after controlling for time,
influenza epidemics, holiday periods, temperature, and relative humidity. Additionally, we evaluated
bi-pollutant models by including the other pollutant and the influence of several effect modifiers
such as personal characteristics and pre-existing medical conditions. In the period of study,
79,892 individuals were admitted to the emergency departments of Rome hospitals because of
AF (on average, 15.6 patients per day: min = 1, max = 36). Air pollution levels were associated
with increased AF emergency visits within 24 h of exposure. Effect estimates ranged between 1.4%
(0.7–2.3) for a 10 μg/m3 increase of PM10 to 3% (1.4–4.7) for a 10 μg/m3
increase of PM2.5 at lag 0–1 day. Those effects were higher in patients ≥75 years for all pollutants, male patients for PM10,
and female patients for NO2. The presence of previous cardiovascular conditions, but not other effect
modifiers, increase the pollution effects by 5–8% depending on the lag. This study found evidence
that air pollution is associated with AF emergency visits in the short term
Estimating the risk of Dengue, Chikungunya and Zika outbreaks in a large European city
Full text linkOutbreaks of arbovirus infections vectored by invasive Aedes albopictus have already occurred and
are predicted to become increasingly frequent in Southern Europe. We present a probabilistic model
to assess risk of arbovirus outbreaks based on incident cases worldwide, on the probability of arrival
of infected travelers, and on the abundance of the vector species. Our results show a signifcant risk of
Chikungunya outbreak in Rome from mid June to October in simulations with high human biting rates
(i.e. when ≥50% of the population is bitten every day). The outbreak risk is predicted to be highest for
Chikungunya and null for Zika. Simulated increase of incident cases in selected endemic countries has
no major impact on the outbreak risk. The model correctly estimated the number of imported cases and
can be easily adapted to other urban areas where Ae. albopictus is the only potential vector presen
Long-term exposure to air pollution and risk of venous thromboembolism in a large administrative cohort
Full text linkBackground: Venous thromboembolisms (VTE) are one of the most frequent cause among the cardiovascular diseases. Despite the association between long-term exposure to air pollution and cardiovascular outcomes have been widely explored in epidemiological literature, little is known about the air pollution related effects on VTE. We aimed to evaluate this association in a large administrative cohort in 15 years of follow-up. Methods: Air pollution exposure (NO2, PM10 and PM2.5) was derived by land use regression models obtained by the ESCAPE framework. Administrative health databases were used to identify VTE cases. To estimate the association between air pollutant exposures and risk of hospitalizations for VTE (in total and divided in deep vein thrombosis (DVT) and pulmonary embolism (PE)), we used Cox regression models, considering individual, environmental (noise and green areas), and contextual characteristics. Finally, we considered potential effect modification for individual covariates and previous comorbidities. Results: We identified 1,954 prevalent cases at baseline and 20,304 cases during the follow-up period. We found positive associations between PM2.5 exposures and DVT, PE and VTE with hazard ratios (HRs) up to 1.082 (95% confidence intervals: 0.992, 1.181), 1.136 (0.994, 1.298) and 1.074 (0.996, 1.158) respectively for 10 μg/m3 increases. The association was stronger in younger subjects (< 70 years old compared to > 70 years old) and among those who had cancer. Conclusion: The effect of pollutants on PE and VTE hospitalizations, although marginally non-significant, should be interpreted as suggestive of a health effect that deserves attention in future studies
Association between PM10, PM2.5, NO2, O3 and self-reported diabetes in Italy: A cross-sectional, ecological study.
Full text linkIntroductionAir pollution represents a serious threat to health on a global scale, being responsible for a large portion of the global burden of disease from environmental factors. Current evidence about the association between air pollution exposure and Diabetes Mellitus (DM) is still controversial. We aimed to evaluate the association between area-level ambient air pollution and self-reported DM in a large population sample in Italy.Materials and methodsWe extracted information about self-reported and physician diagnosed DM, risk factors and socio-economic status from 12 surveys conducted nationwide between 1999 and 2013. We obtained annual averaged air pollution levels for the years 2003, 2005, 2007 and 2010 from the AMS-MINNI national integrated model, which simulates the dispersion and transformation of pollutants. The original maps, with a resolution of 4 x 4 km2, were normalized and aggregated at the municipality class of each Italian region, in order to match the survey data. We fit logistic regression models with a hierarchical structure to estimate the relationship between PM10, PM2.5, NO2 and O3 four-years mean levels and the risk of being affected by DM.ResultsWe included 376,157 individuals aged more than 45 years. There were 39,969 cases of DM, with an average regional prevalence of 9.8% and a positive geographical North-to-South gradient, opposite to that of pollutants' concentrations. For each 10 μg/m3 increase, the resulting ORs were 1.04 (95% CI 1.01-1.07) for PM10, 1.04 (95% CI 1.02-1.07) for PM2.5, 1.03 (95% CI 1.01-1.05) for NO2 and 1.06 (95% CI 1.01-1.11) for O3, after accounting for relevant individual risk factors. The associations were robust to adjustment for other pollutants in two-pollutant models tested (ozone plus each other pollutant).ConclusionsWe observed a significant positive association between each examined pollutant and prevalent DM. Risk estimates were consistent with current evidence, and robust to sensitivity analysis. Our study adds evidence about the effects of air pollution on diabetes and suggests a possible role of ozone as an independent factor associated with the development of DM. Such relationship is of great interest for public health and deserves further investigation
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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