Browsing by Author "Naidu, Ravi"

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    Effect of short-term exposure to air pollution on daily cardio- and cerebrovascular hospitalisations in areas with a low level of air pollution
    (Springer, 2023) Hasnain, Md Golam; Garcia‑Esperon, Carlos; Tomari, Yumi Kashida; Walker, Rhonda; Saluja, Tarunpreet; Rahman, Md Mijanur; Boyle, Andrew; Levi, Christopher R.; Naidu, Ravi; Filippelli, Gabriel; Spratt, Neil J.; Earth and Environmental Sciences, School of Science
    Exposure to air pollution is associated with increased cardio- and cerebrovascular diseases. However, the evidence regarding the short-term effect of air pollution on cardio- and cerebrovascular hospitalisations in areas with relatively low air pollution levels is limited. This study aims to examine the effect of short-term exposure to different air pollutants on hospital admissions due to cardio- and cerebrovascular diseases in rural and regional Australia with low air pollution. The study was conducted in five local Government areas of Hunter New England Local Health District (HNE-LHD). Hospitalisation data from January 2018 to February 2020 (820 days) were accessed from the HNE-LHD admitted patients' dataset. Poisson regression model was used to examine the association between the exposure (air pollutants) and outcome variables (hospitalisation due to cardio- and cerebrovascular disease). The concentrations of gaseous air pollutants, Sulphur Dioxide (SO2), Nitrogen Dioxide (NO2), Ozone (O3), Carbon Monoxide (CO), and Ammonia (NH3) were below national benchmark concentrations for every day of the study period. In single pollutant models, SO2 and NO2 significantly increased the daily number of cardio- and cerebrovascular hospitalisations. The highest cumulative effect for SO2 was observed across lag 0-3 days (Incidence Rate Ratio, IRR: 1.77; 95% Confidence Interval, CI: 1.18-2.65; p-value: 0.01), and for NO2, it was across lag 0-2 days (IRR: 1.13; 95% CI: 1.02-1.25; p-value: 0.02). In contrast, higher O3 was associated with decreased cardio- and cerebrovascular hospitalisations, with the largest effect observed at lag 0 (IRR: 0.94; 95% CI: 0.89-0.98; p-value: 0.02). In the multi-pollutant model, the effect of NO2 remained significant at lag 0 and corresponded to a 21% increase in cardio- and cerebrovascular hospitalisation (95% CI: 1-44%; p-value = 0.04). Thus, the study revealed that gaseous air pollutants, specifically NO2, were positively related to increased cardio- and cerebrovascular hospitalisations, even at concentrations below the national standards.
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    Predictive modeling of indoor dust lead concentrations: Sources, risks, and benefits of intervention
    (Elsevier, 2023) Dietrich, Matthew; Barlow, Cynthia F.; Entwistle, Jane A.; Meza-Figueroa, Diana; Dong, Chenyin; Gunkel-Grillon, Peggy; Jabeen, Khadija; Bramwell, Lindsay; Shukle, John T.; Wood, Leah R.; Naidu, Ravi; Fry, Kara; Taylor, Mark Patrick; Filippelli, Gabriel M.; Earth and Environmental Sciences, School of Science
    Lead (Pb) contamination continues to contribute to world-wide morbidity in all countries, particularly low- and middle-income countries. Despite its continued widespread adverse effects on global populations, particularly children, accurate prediction of elevated household dust Pb and the potential implications of simple, low-cost household interventions at national and global scales have been lacking. A global dataset (∼40 countries, n = 1951) of community sourced household dust samples were used to predict whether indoor dust was elevated in Pb, expanding on recent work in the United States (U.S.). Binned housing age category alone was a significant (p < 0.01) predictor of elevated dust Pb, but only generated effective predictive accuracy for England and Australia (sensitivity of ∼80%), similar to previous results in the U.S. This likely reflects comparable Pb pollution legacies between these three countries, particularly with residential Pb paint. The heterogeneity associated with Pb pollution at a global scale complicates the predictive accuracy of our model, which is lower for countries outside England, the U.S., and Australia. This is likely due to differing environmental Pb regulations, sources, and the paucity of dust samples available outside of these three countries. In England, the U.S., and Australia, simple, low-cost household intervention strategies such as vacuuming and wet mopping could conservatively save 70 billion USD within a four-year period based on our model. Globally, up to 1.68 trillion USD could be saved with improved predictive modeling and primary intervention to reduce harmful exposure to Pb dust sources.