https://ogma.newcastle.edu.au/vital/access/ /manager/Index ${session.getAttribute("locale")} 5 https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:34696 Wed 17 Nov 2021 16:30:20 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:29597 Wed 13 Mar 2024 18:28:20 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:22846 Wed 11 Apr 2018 16:46:51 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:22891 Wed 11 Apr 2018 15:21:56 AEST ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:36055 Thu 13 Jan 2022 10:32:01 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:34059 2.5) and smoking and their combined (interactive) effects on depression. Method: Multilevel logistic regression analysis of baseline data of a prospective cohort study (n=41 785). The 3-year average concentrations of PM_2.5 were estimated using US National Aeronautics and Space Administration satellite data, and depression was diagnosed using a standardised questionnaire. Three-level logistic regression models were applied to examine the associations with depression. Results: The odds ratio (OR) for depression was 1.09 (95% Cl 1.01-1.17) per 10μg/m³ increase in ambient PM_2.5, and the association remained after adjusting for potential confounding factors (adjusted OR=1.10, 95% CI 1.02-1.19). Tobacco smoking (smoking status, frequency, duration and amount) was also significantly associated with depression. There appeared to be a synergistic interaction between ambient PM 2.5 and smoking on depression in the additive model, but the interaction was not statistically significant in the multiplicative model. Conclusions: Our study suggests that exposure to ambient PM_2.5 may increase the risk of depression, and smoking may enhance this effect.]]> Thu 09 Dec 2021 11:03:15 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:34713 2.5) has been linked to increased stroke. Few studies, however, have examined the effects of long-term exposure. Methods: A total of 45 625 participants were interviewed and included in this study, the participants came from the Study on Global Ageing and Adult Health, a prospective cohort in 6 low- and middle-income countries. Ambient PM_2.5 levels were estimated for participants' communities using satellite data. A multilevel logistic regression model was used to examine the association between long-term PM_2.5 exposure and stroke. Potential effect modification by physical activity and consumption of fruit and vegetables was assessed. Results: The odds of stroke were 1.13 (95% confidence interval, 1.04-1.22) for each 10 µg/m³ increase in PM_2.5. This effect remained after adjustment for confounding factors including age, sex, smoking, and indoor air pollution (adjusted odds ratio=1.12; 95% confidence interval, 1.04-1.21). Further stratified analyses suggested that participants with higher levels of physical activity had greater odds of stroke, whereas those with higher consumption of fruit and vegetables had lower odds of stroke. These effects remained robust in sensitivity analyses. We further estimated that 6.55% (95% confidence interval, 1.97%-12.01%) of the stroke cases could be attributable to ambient PM_2.5 in the study population. Conclusions: This study suggests that ambient PM_2.5 may increase the risk of stroke and may be responsible for the astounding stroke burden in low- and middle-income countries. In addition, greater physical activity may enhance, whereas greater consumption of fruit and vegetables may mitigate the effect.]]> Thu 04 Nov 2021 10:40:23 AEDT ]]> https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:38481 2) on haemoglobin concentrations and the prevalence of anaemia, respectively, among 10,611 older Chinese adults enrolled in World Health Organization (WHO) Study on global AGEing and adult health (SAGE) China. The average community exposure to ambient air pollutants (PM with an aerodynamic diameter of 10 μm or less (PM₁₀), 2.5 μm or less (PM_2.5), 1 μm or less (PM₁) and nitrogen dioxide (NO₂)) for each participant was estimated using a satellite-based spatial statistical model. Haemoglobin levels were measured for participants from dried blood spots. The models were controlled for confounders. Results: All the studied pollutants were significantly associated with increased anaemia prevalence in single pollutant model (e.g., the prevalence ratios associated with an increase in inter quartile range in three years moving average PM₁₀ (1.05; 95% CI: 1.02–1.09), PM_2.5 (1.11; 95% CI: 1.06–1.16), PM₁ (1.13; 95% CI: 1.06–1.20) and NO₂(1.42; 95% CI: 1.34–1.49), respectively. These air pollutants were also associated with lower concentrations of haemoglobin: PM₁₀ (−0.53; 95% CI: −0.67, −0.38); PM_2.5 (−0.52; 95% CI: −0.71, −0.33); PM₁ (−0.55; 95% CI: −0.69, −0.41); NO₂ (−1.71; 95% CI: −1.85, −1.57) respectively. Conclusions: Air pollution exposure was significantly associated with increased prevalence of anaemia and decreased haemoglobin levels in a cohort of older Chinese adults.]]> Mon 29 Jan 2024 18:02:14 AEDT ]]>