Local NO2 concentrations and asthma among over-50s in Ireland: A microdata analysis.

BACKGROUND: Links between air pollution and asthma are less well established for older adults than some younger groups. Nitrogen dioxide (NO2) concentrations are widely used as an indicator of transport-related air pollution, and some literature suggests NO2 may directly affect asthma. METHODS: This study used data on 8162 adults >50 years old in the Republic of Ireland to model associations between estimated annual outdoor concentration of NO2 and the probability of having asthma. Individual-level geo-coded survey data from The Irish Longitudinal Study on Ageing (TILDA) were linked to model-based estimates of annual average NO2 at 50 m resolution. Asthma was identified using two methods: self-reported diagnoses and respondents' use of medications related to obstructive airway diseases. Logistic regressions were used to model the relationships. RESULTS: NO2 concentrations were positively associated with the probability of asthma [marginal effect (ME) per 1 ppb of airborne NO2 = 0.24 percentage points asthma self-report, 95% confidence interval (CI) 0.06-0.42, mean asthma prevalence 0.09; for use of relevant medications ME = 0.21 percentage points, 95% CI 0.049-0.37, mean prevalence 0.069]. Results were robust to varying model specification and time period. Respondents in the top fifth percentile of NO2 exposure had a larger effect size but also greater standard error (ME = 2.4 percentage points asthma self-report, 95% CI -0. 49 to 5.3). CONCLUSIONS: Associations between local air pollution and asthma among older adults were found at relatively low concentrations. To illustrate this, the marginal effect of an increase in annual average NO2 concentration from sample minimum to median (2.5 ppb) represented about 7-8% of the sample average prevalence of asthma.

Short-Term Air Pollution as a Risk for Stroke Admission: A Time-Series Analysis.

BACKGROUND: The harmful effects of outdoor air pollution on stroke incidence are becoming increasingly recognised. We examined the impact of different air pollutants (PM2.5, PM10, NO2, ozone, and SO2) on admission for all strokes in two Irish urban centres from 2013 to 2017. METHODS: Using an ecological time series design with Poisson regression models, we analysed daily hospitalisation for all strokes and is-chaemic stroke by residence in Dublin or Cork, with air pollution level monitoring data with a lag of 0-2 days from exposure. Splines of temperature, relative humidity, day of the week, and time were included as confounders. Analysis was also performed across all four seasons. Data are presented as relative risks (RRs) and 95% confidence intervals (95% CI) per interquartile range (IQR) increase in each pollutant. RESULTS: There was no significant association between all stroke admission and any individual air pollutant. On seasonal analysis, during winter in the larger urban centre (Dublin), we found an association between all stroke cases and an IQR increase in NO2 (RR 1.035, 95% CI: 1.003-1.069), PM10 (RR 1.032, 95% CI: 1.007-1.057), PM2.5 (RR 1.024, 95% CI: 1.011-1.039), and SO2 (RR 1.035, 95% CI: 1.001-1.071). There was no significant association found in the smaller urban area of Cork. On meta-analysis, there remained a significant association between NO2 (RR 1.013, 95% CI: 1.001-1.024) and PM2.5 (1.009, 95% CI 1.004-1.014) per IQR increase in each. DISCUSSION: Short-term air pollution in winter was found to be associated with hospitalisation for all strokes in a large urban centre in Ireland. As Ireland has relatively low air pollution internationally, this highlights the need to introduce policy changes to reduce air pollution in all countries.

How Urban Parks Offer Opportunities for Physical Activity in Dublin, Ireland.

Parks are an important part of the urban fabric of cities. They offer people the opportunity to connect with nature, engage in physical activity, find a haven away from the city noise, or spend time alone or with family and friends. This study examines the relative importance of park and park visit characteristics for 865 survey participants in Dublin, Ireland. The data is analyzed using a multinomial logistic regression model which can distinguish the relative importance of attributes. The model results demonstrate an improvement over proportional by chance accuracy, indicating that the model is useful. The results suggest that when and why individuals go to the park along with the proximity of their residence to the park influence visit frequency more than their age and gender and more than their impression of the sound levels in the park. The contribution of the results, in terms of their potential usefulness to planners, suggest that the priority should be on the provision of park space close to residential areas, so that individuals can engage in activities such as walking and relaxation, and that the quality of that space, in the context of noise levels at least, is less important.

Modeling of surface acoustic wave strain sensors using coupling-of-modes analysis.

SAW devices may be configured as strain sensors, providing passive, wireless strain measurement in demanding conditions. A key consideration is the modeling of the sensors, enabling different device designs to be considered. This paper presents a simulation scheme using coupling-of-modes (COM) analysis which allows both the frequency response of a SAW strain sensor and its bias sensitivity to be evaluated. Example applications are presented to demonstrate the use of the model.