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

The effect of "smoky" coal bans on chronic lung disease among older people in Ireland

Globally, coal is still widely used for heating. However, there are concerns about its effect on ambient air quality and health. We estimated the effect of bans prohibiting the sale and use of so-called "smoky coal" on the prevalence of chronic lung disease in older people. Our identification strategy relied on the phased extension of smoky coal bans to Irish towns after 2010. We examined five waves of The Irish Longitudinal Study on Ageing (TILDA), a large nationally representative survey containing detailed information on health, housing, and socio-economic status. Controlling for relevant factors, smoky coal bans reduced the probability that an older person reports being diagnosed with chronic lung disease by between three and five percentage points. In models where we estimated the effect of the ban on the incidence of new cases of chronic lung disease, rather than existing cases, we found the effect was between -0.96 and -2.5 percentage points. Our findings were robust to estimating the model using different sub-samples and control variables. Furthermore, to address potential endogeneity of the ban, we examined subsamples defined by whether participants lived in towns within a range of the population threshold at which the ban was imposed. Estimating our model using these subsamples showed a consistently negative effect of the ban. We also showed parallel trends in health outcomes before the treatment, and that the treatment did not affect attrition from the sample.

Relationship of long-term air pollution exposure with asthma and rhinitis in Italy: an innovative multipollutant approach

BACKGROUND

air pollution is a complex mixture; novel multipollutant approaches could help understanding the health effects of multiple concomitant exposures to air pollutants.

AIM

to assess the relationship of long-term air pollution exposure with the prevalence of respiratory/allergic symptoms and diseases in an Italian multicenter study using single and multipollutant approaches.

METHODS

14420 adults living in 6 Italian cities (Ancona, Pavia, Pisa, Sassari, Turin, Verona) were investigated in 2005-2011 within 11 different study cohorts. Questionnaire information about risk factors and health outcomes was collected. Machine learning derived mean annual concentrations of PM₁₀, PM_2.5, NO₂ and mean summer concentrations of O₃ (μg/m³) at residential level (1-km resolution) were used for the period 2013-2015. The associations between the four pollutants and respiratory/allergic symptoms/diseases were assessed using two approaches: a) logistic regression models (single-pollutant models), b) principal component logistic regression models (multipollutant models). All the models were adjusted for age, sex, education level, smoking habits, season of interview, climatic index and included a random intercept for cohorts.

RESULTS

the three-year average (± standard deviation) pollutants concentrations at residential level were: 20.3 ± 6.8 μg/m³ for PM_2.5, 29.2 ± 7.0 μg/m³ for PM₁₀, 28.0 ± 11.2 μg/m³ for NO₂, and 70.9 ± 4.3 μg/m³ for summer O_3. Through the multipollutant models the following associations emerged: PM₁₀ and PM_2.5 were related to 14-25% increased odds of rhinitis, 23-34% of asthma and 30-33% of night awakening; NO₂ was related to 6-9% increased odds of rhinitis, 7-8% of asthma and 12% of night awakening; O₃ was associated with 37% increased odds of asthma attacks. Overall, the Odds Ratios estimated through the multipollutant models were attenuated when compared to those of the single-pollutant models.

CONCLUSIONS

this study enabled to obtain new information about the health effects of air pollution on respiratory/allergic outcomes in adults, applying innovative methods for exposure assessment and multipollutant analyses.

Impacts of residential indoor air quality and environmental risk factors on adult asthma-related health outcomes in Chicago, IL

BACKGROUND

Residential environments are known to contribute to asthma.

OBJECTIVE

To examine the joint impacts of exposures to residential indoor and outdoor air pollutants and housing risk factors on adult asthma-related health outcomes.

METHODS

We analyzed >1-year of data from 53 participants from 41 homes in the pre-intervention period of the Breathe Easy Project prior to ventilation and filtration retrofits. Health outcomes included surveys of asthma control, health-related quality of life, stress, and healthcare utilizations. Environmental assessments included quarterly measurements of indoor and outdoor pollutants (e.g., HCHO, CO, CO2, NO2, O3, and PM), home walk-throughs, and surveys of environmental risk factors. Indoor pollutant concentrations were also matched with surveys of time spent at home to estimate indoor pollutant exposures.

RESULTS

Cross-sectional analyses using mixed-effects models indicated that lower annual average asthma control test (ACT) scores were associated (p < 0.05) with higher indoor NO2 (concentration/exposure: β = -2.42/-1.57), indoor temperature (β = -1.03 to -0.94), and mold/dampness (β = -3.09 to -2.41). In longitudinal analysis, lower ACT scores were also associated (p < 0.05) with higher indoor NO2 concentrations (β = -0.29), PM1 (concentration/exposure: β = -0.12/-0.24), PM2.5 (concentration/exposure: β = -0.12/-0.26), and PM10 (concentration/exposure: β = 10.14/-0.28). Emergency department visits were associated with poorer asthma control [incidence rate ratio (IRR) = 0.84; p < 0.001], physical health (IRR = 0.95; p < 0.05), mental health (IRR = 0.95; p < 0.05), higher I/O NO2 ratios (IRR = 1.30; p < 0.05), and higher indoor temperatures (IRR = 1.41; p < 0.05).

SIGNIFICANCE

Findings suggest that residential risk factors, including indoor air pollution (especially NO2 and particulate matter), higher indoor temperature, and mold/dampness, may contribute to poorer asthma control.

IMPACT

This study highlights the importance of residential indoor air quality and environmental risk factors for asthma control, health-related quality of life, and emergency department visits for asthma. Two timescales of mixed models suggest that exposure to indoor NO2 and particulate matter, higher indoor temperature, and mold/dampness was associated with poorer asthma control. Additionally, emergency department visits were associated with poorer asthma control and health-related quality of life, as well as higher I/O NO2 ratios and indoor temperatures. These findings deepen our understanding of the interrelationships between housing, air quality, and health, and have important implications for programs and policy.

Cytokine profiles in cord blood in relation to prenatal traffic-related air pollution: The NELA cohort

BACKGROUND

Outdoor air pollution may disturb immune system development. We investigated whether gestational exposure to traffic-related air pollutants (TRAP) is associated with unstimulated cytokine profiles in newborns.

METHODS

Data come from 235 newborns of the NELA cohort. Innate response-related cytokines (IL-6, IFN-α, IL1-β, and TNF-α), Th1-related (IFN-γ and IL-2), Th2-related (IL-4, IL-5, and IL-13), Th17-related (IL-17 and IL-23), and immunomodulatory cytokine IL-10 were quantified in the supernatant of unstimulated whole umbilical cord blood cells after 7 days of culture using the Luminex technology. Dispersion/chemical transport modeling was used to estimate long-term (whole pregnancy and trimesters) and short-term (15 days before delivery) residential exposures to traffic-related nitrogen dioxide (NO₂ ), particulate matter (PM_2.5 and PM₁₀ ), and ozone (O₃ ). We fitted multivariable logistic regression, Bayesian kernel machine regression (BKMR), and weighted quantile sum (WQS) regression models.

RESULTS

NO₂ during the whole pregnancy increased the odds of detection of IL-1β (OR per 10 µg/m³ increase = 1.37; 95% CI, 1.02, 1.85) and IL-6 (OR per 10 µg/m³ increase = 1.32; 95% CI 1.00, 1.75). Increased odds of detected concentrations of IL-10 was found in newborns exposed during whole pregnancy to higher levels of NO₂ (OR per 10 µg/m³ increase = 1.30; 95% CI 0.99, 1.69), PM₁₀ (OR per 10 µg/m³ increase = 1.49; 95% CI 0.95, 2.33), and PM_2.5 (OR per 5 µg/m³ increase = 1.56; 95% CI 0.97, 2.51). Exposure to O₃ during the whole pregnancy increased the odds of detected IL-13 (OR per 10 µg/m³ increase = 1.22; 95% CI 1.01, 1.49). WQS model revealed first and third trimesters of gestation as windows of higher susceptibility.

CONCLUSIONS

Gestational exposure to TRAP may increase detection of pro-inflammatory, Th2-related, and T regulatory cytokines in newborns. These changes might influence immune system responses later in life.

Modelling COVID-19 severity in the Republic of Ireland using patient co-morbidities, socioeconomic profile and geographic location, February to November 2020

Understanding patient progression from symptomatic COVID-19 infection to a severe outcome represents an important tool for improved diagnoses, surveillance, and triage. A series of models have been developed and validated to elucidate hospitalization, admission to an intensive care unit (ICU) and mortality in patients from the Republic of Ireland. This retrospective cohort study of patients with laboratory-confirmed symptomatic COVID-19 infection included data extracted from national COVID-19 surveillance forms (i.e., age, gender, underlying health conditions, occupation) and geographically-referenced potential predictors (i.e., urban/rural classification, socio-economic profile). Generalised linear models and recursive partitioning and regression trees were used to elucidate COVID-19 progression. The incidence of symptomatic infection over the study-period was 0.96% (n = 47,265), of whom 3781 (8%) required hospitalisation, 615 (1.3%) were admitted to ICU and 1326 (2.8%) died. Models demonstrated an increasingly efficacious fit for predicting hospitalization [AUC 0.816 (95% CI 0.809, 0.822)], admission to ICU [AUC 0.885 (95% CI 0.88 0.89)] and death [AUC of 0.955 (95% CI 0.951 0.959)]. Severe obesity (BMI ≥ 40) was identified as a risk factor across all prognostic models; severely obese patients were substantially more likely to receive ICU treatment [OR 19.630] or die [OR 10.802]. Rural living was associated with an increased risk of hospitalization (OR 1.200 (95% CI 1.143-1.261)]. Urban living was associated with ICU admission [OR 1.533 (95% CI 1.606-1.682)]. Models provide approaches for predicting COVID-19 prognoses, allowing for evidence-based decision-making pertaining to targeted non-pharmaceutical interventions, risk-based vaccination priorities and improved patient triage.