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  • Forouzanfar, Mohammad H, et al. (författare)
  • Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990-2013 : a systematic analysis for the Global Burden of Disease Study 2013.
  • 2015
  • Ingår i: The Lancet. - 0140-6736 .- 1474-547X. ; 386:10010, s. 2287-2323
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) is the first of a series of annual updates of the GBD. Risk factor quantification, particularly of modifiable risk factors, can help to identify emerging threats to population health and opportunities for prevention. The GBD 2013 provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution.METHODS: Attributable deaths, years of life lost, years lived with disability, and disability-adjusted life-years (DALYs) have been estimated for 79 risks or clusters of risks using the GBD 2010 methods. Risk-outcome pairs meeting explicit evidence criteria were assessed for 188 countries for the period 1990-2013 by age and sex using three inputs: risk exposure, relative risks, and the theoretical minimum risk exposure level (TMREL). Risks are organised into a hierarchy with blocks of behavioural, environmental and occupational, and metabolic risks at the first level of the hierarchy. The next level in the hierarchy includes nine clusters of related risks and two individual risks, with more detail provided at levels 3 and 4 of the hierarchy. Compared with GBD 2010, six new risk factors have been added: handwashing practices, occupational exposure to trichloroethylene, childhood wasting, childhood stunting, unsafe sex, and low glomerular filtration rate. For most risks, data for exposure were synthesised with a Bayesian meta-regression method, DisMod-MR 2.0, or spatial-temporal Gaussian process regression. Relative risks were based on meta-regressions of published cohort and intervention studies. Attributable burden for clusters of risks and all risks combined took into account evidence on the mediation of some risks such as high body-mass index (BMI) through other risks such as high systolic blood pressure and high cholesterol.FINDINGS: All risks combined account for 57·2% (95% uncertainty interval [UI] 55·8-58·5) of deaths and 41·6% (40·1-43·0) of DALYs. Risks quantified account for 87·9% (86·5-89·3) of cardiovascular disease DALYs, ranging to a low of 0% for neonatal disorders and neglected tropical diseases and malaria. In terms of global DALYs in 2013, six risks or clusters of risks each caused more than 5% of DALYs: dietary risks accounting for 11·3 million deaths and 241·4 million DALYs, high systolic blood pressure for 10·4 million deaths and 208·1 million DALYs, child and maternal malnutrition for 1·7 million deaths and 176·9 million DALYs, tobacco smoke for 6·1 million deaths and 143·5 million DALYs, air pollution for 5·5 million deaths and 141·5 million DALYs, and high BMI for 4·4 million deaths and 134·0 million DALYs. Risk factor patterns vary across regions and countries and with time. In sub-Saharan Africa, the leading risk factors are child and maternal malnutrition, unsafe sex, and unsafe water, sanitation, and handwashing. In women, in nearly all countries in the Americas, north Africa, and the Middle East, and in many other high-income countries, high BMI is the leading risk factor, with high systolic blood pressure as the leading risk in most of Central and Eastern Europe and south and east Asia. For men, high systolic blood pressure or tobacco use are the leading risks in nearly all high-income countries, in north Africa and the Middle East, Europe, and Asia. For men and women, unsafe sex is the leading risk in a corridor from Kenya to South Africa.INTERPRETATION: Behavioural, environmental and occupational, and metabolic risks can explain half of global mortality and more than one-third of global DALYs providing many opportunities for prevention. Of the larger risks, the attributable burden of high BMI has increased in the past 23 years. In view of the prominence of behavioural risk factors, behavioural and social science research on interventions for these risks should be strengthened. Many prevention and primary care policy options are available now to act on key risks.FUNDING: Bill & Melinda Gates Foundation.
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  • Raaschou-Nielsen, O., et al. (författare)
  • Particulate matter air pollution components and risk for lung cancer
  • 2016
  • Ingår i: Environment International. - : Elsevier BV. - 0160-4120 .- 1873-6750. ; 87, s. 66-73
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Particulate matter (PM) air pollution is a human lung carcinogen; however, the components responsible have not been identified. We assessed the associations between PM components and lung cancer incidence. Methods: We used data from 14 cohort studies in eight European countries. We geocoded baseline addresses and assessed air pollution with land-use regression models for eight elements (Cu, Fe, K, Ni, S, Si, V and Zn) in size fractions of PM2.5 and PM10. We used Cox regression models with adjustment for potential confounders for cohort-specific analyses and random effect models for meta-analysis. Results: The 245,782 cohort members contributed 3,229,220 person-years at risk. During follow-up (mean, 13.1 years), 1878 incident cases of lung cancer were diagnosed. In the meta-analyses, elevated hazard ratios (HRs) for lung cancer were associated with all elements except V; none was statistically significant In analyses restricted to participants who did not change residence during follow-up, statistically significant associations were found for PM2.5 Cu (HR, 125; 95% Cl, 1.01-1.53 per 5 ng/m(3)), PM10 Zn (1.28; 1.02-1.59 per 20 ng/m3), PMio S (1.58; 1.03-2.44 per 200 ng/m(3)), PM10 Ni (1.59; 1.12-2.26 per 2 ng/m(3)) and PM10K (1.17; 1.02-1.33 per 100 ng/m(3)). In two-pollutant models, associations between PMio and PM2.5 and lung cancer were largely explained by PM2.5 S. Conclusions: This study indicates that the association between PM in air pollution and lung cancer can be attributed to various PM components and sources. PM containing S and Ni might be particularly important.
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  • Alemany, S., et al. (författare)
  • Associations between air pollution and biomarkers of Alzheimer's disease in cognitively unimpaired individuals
  • 2021
  • Ingår i: Environment International. - : Elsevier BV. - 0160-4120. ; 157
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Air quality contributes to incidence of Alzheimer's disease (AD) although the underlying neurobiological mechanisms are unclear. This study was aimed to examine the association between air pollution and concentrations of cerebrospinal fluid (CSF) AD biomarkers and amyloid-beta (A beta) deposition. Participants and methods The sample included 156 cognitively unimpaired adults aged 57 years (61 at biomarkers assessment) with increased risk of AD from the ALFA + Study. We examined CSF levels of A beta 42, A beta 40, p-Tau, t-Tau, neurofilament light (NfL) and cerebral amyloid load (Centiloid). A Land Use Regression model from 2009 was used to estimate residential exposure to air pollutants including nitrogen dioxide (NO2,) and particulate matter (PM2.5, PM2.5 abs, PM10). This model was considered a surrogate of long-term exposure until time of data collection in 2013-2014. Participants have resided in the same residence for at least the previous 3 years. Multiple linear regression models were used to estimate associations between air pollutants and biomarkers. The effect modification by CSF A beta status and APOE-epsilon 4 carriership was also assessed. Results: A consistent pattern of results indicated that greater exposure to NO2 and PM2.5 absorbance was associated with higher levels of brain A beta deposition, while greater exposure to PM10 and PM(2.5)was associated with higher levels of CSF NfL. Most associations were driven by individuals that were A beta-positive. Although APOE-epsilon 4 status did not significantly modify these associations, the effect of air pollutants exposure on CSF NfL levels was stronger in APOE-epsilon 4 carriers. Conclusion: In a population of cognitively unimpaired adults with increased risk of AD, long-term exposure to air pollution was associated with higher levels in biomarkers of AD pathology. While further research is granted to elucidate the mechanisms involved in such associations, our results reinforce the role of air pollution as an environmental risk factor for AD.
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