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      Long-term effects of PM 2·5 on neurological disorders in the American Medicare population: a longitudinal cohort study

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          Summary

          Background

          Accumulating evidence links fine particulate matter (PM 2·5) to premature mortality, cardiovascular disease, and respiratory disease. However, less is known about the influence of PM 2·5 on neurological disorders. We aimed to investigate the effect of long-term PM 2·5 exposure on development of Parkinson’s disease or Alzheimer’s disease and related dementias.

          Methods

          We did a longitudinal cohort study in which we constructed a population-based nationwide open cohort including all fee-for-service Medicare beneficiaries (aged ≥65 years) in the contiguous United States (2000–16) with no exclusions. We assigned PM 2·5 postal code (ie, ZIP code) concentrations based on mean annual predictions from a high-resolution model. To accommodate our very large dataset, we applied Cox-equivalent Poisson models with parallel computing to estimate hazard ratios (HRs) for first hospital admission for Parkinson’s disease or Alzheimer’s disease and related dementias, adjusting for potential confounders in the health models.

          Findings

          Between Jan 1, 2000, and Dec 31, 2016, of 63 038 019 individuals who were aged 65 years or older during the study period, we identified 1·0 million cases of Parkinson’s disease and 3·4 million cases of Alzheimer’s disease and related dementias based on primary and secondary diagnosis billing codes. For each 5 μg/m 3 increase in annual PM 2·5 concentrations, the HR was 1·13 (95% CI 1·12–1·14) for first hospital admission for Parkinson’s disease and 1·13 (1·12–1·14) for first hospital admission for Alzheimer’s disease and related dementias. For both outcomes, there was strong evidence of linearity at PM 2·5 concentrations less than 16 μg/m 3 (95th percentile of the PM 2·5 distribution), followed by a plateaued association with increasingly larger confidence bands.

          Interpretation

          We provide evidence that exposure to annual mean PM 2·5 in the USA is significantly associated with an increased hazard of first hospital admission with Parkinson’s disease and Alzheimer’s disease and related dementias. For the ageing American population, improving air quality to reduce PM 2·5 concentrations to less than current national standards could yield substantial health benefits by reducing the burden of neurological disorders.

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          Most cited references34

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          Global, regional, and national burden of neurological disorders, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

          Summary Background Neurological disorders are increasingly recognised as major causes of death and disability worldwide. The aim of this analysis from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 is to provide the most comprehensive and up-to-date estimates of the global, regional, and national burden from neurological disorders. Methods We estimated prevalence, incidence, deaths, and disability-adjusted life-years (DALYs; the sum of years of life lost [YLLs] and years lived with disability [YLDs]) by age and sex for 15 neurological disorder categories (tetanus, meningitis, encephalitis, stroke, brain and other CNS cancers, traumatic brain injury, spinal cord injury, Alzheimer's disease and other dementias, Parkinson's disease, multiple sclerosis, motor neuron diseases, idiopathic epilepsy, migraine, tension-type headache, and a residual category for other less common neurological disorders) in 195 countries from 1990 to 2016. DisMod-MR 2.1, a Bayesian meta-regression tool, was the main method of estimation of prevalence and incidence, and the Cause of Death Ensemble model (CODEm) was used for mortality estimation. We quantified the contribution of 84 risks and combinations of risk to the disease estimates for the 15 neurological disorder categories using the GBD comparative risk assessment approach. Findings Globally, in 2016, neurological disorders were the leading cause of DALYs (276 million [95% UI 247–308]) and second leading cause of deaths (9·0 million [8·8–9·4]). The absolute number of deaths and DALYs from all neurological disorders combined increased (deaths by 39% [34–44] and DALYs by 15% [9–21]) whereas their age-standardised rates decreased (deaths by 28% [26–30] and DALYs by 27% [24–31]) between 1990 and 2016. The only neurological disorders that had a decrease in rates and absolute numbers of deaths and DALYs were tetanus, meningitis, and encephalitis. The four largest contributors of neurological DALYs were stroke (42·2% [38·6–46·1]), migraine (16·3% [11·7–20·8]), Alzheimer's and other dementias (10·4% [9·0–12·1]), and meningitis (7·9% [6·6–10·4]). For the combined neurological disorders, age-standardised DALY rates were significantly higher in males than in females (male-to-female ratio 1·12 [1·05–1·20]), but migraine, multiple sclerosis, and tension-type headache were more common and caused more burden in females, with male-to-female ratios of less than 0·7. The 84 risks quantified in GBD explain less than 10% of neurological disorder DALY burdens, except stroke, for which 88·8% (86·5–90·9) of DALYs are attributable to risk factors, and to a lesser extent Alzheimer's disease and other dementias (22·3% [11·8–35·1] of DALYs are risk attributable) and idiopathic epilepsy (14·1% [10·8–17·5] of DALYs are risk attributable). Interpretation Globally, the burden of neurological disorders, as measured by the absolute number of DALYs, continues to increase. As populations are growing and ageing, and the prevalence of major disabling neurological disorders steeply increases with age, governments will face increasing demand for treatment, rehabilitation, and support services for neurological disorders. The scarcity of established modifiable risks for most of the neurological burden demonstrates that new knowledge is required to develop effective prevention and treatment strategies. Funding Bill & Melinda Gates Foundation.
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            Summary of the evidence on modifiable risk factors for cognitive decline and dementia: A population-based perspective.

            An estimated 47 million people worldwide are living with dementia in 2015, and this number is projected to triple by 2050. In the absence of a disease-modifying treatment or cure, reducing the risk of developing dementia takes on added importance. In 2014, the World Dementia Council (WDC) requested the Alzheimer's Association evaluate and report on the state of the evidence on modifiable risk factors for cognitive decline and dementia. This report is a summary of the Association's evaluation, which was presented at the October 2014 WDC meeting. The Association believes there is sufficient evidence to support the link between several modifiable risk factors and a reduced risk for cognitive decline, and sufficient evidence to suggest that some modifiable risk factors may be associated with reduced risk of dementia. Specifically, the Association believes there is sufficiently strong evidence, from a population-based perspective, to conclude that regular physical activity and management of cardiovascular risk factors (diabetes, obesity, smoking, and hypertension) reduce the risk of cognitive decline and may reduce the risk of dementia. The Association also believes there is sufficiently strong evidence to conclude that a healthy diet and lifelong learning/cognitive training may also reduce the risk of cognitive decline. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
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              Cox's Regression Model for Counting Processes: A Large Sample Study

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                Author and article information

                Journal
                101704339
                46425
                Lancet Planet Health
                Lancet Planet Health
                The Lancet. Planetary health
                2542-5196
                22 November 2020
                19 October 2020
                December 2020
                07 December 2020
                : 4
                : 12
                : e557-e565
                Affiliations
                Department of Environmental Health (L Shi ScD, M Danesh Yazdi PhD, Y Wei MS, Prof J Schwartz PhD, A Zanobetti PhD) and Department of Biostatistics (X Wu MS, D Braun PhD, Y Wang PhD, Prof F Dominici PhD), Harvard T H Chan School of Public Health, Boston, MA, USA; Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA (L Shi); Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA (D Braun); Department of Psychology, Concordia University, Montreal, QC, Canada (Y Abu Awad ScD); School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA, USA (P Liu PhD); Vanke School of Public Health, Tsinghua University, Beijing, China (Q Di ScD); and Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA (M-A Kioumourtzoglou ScD)
                Author notes
                [*]

                Contributed equally

                [†]

                Co-senior authors

                Contributors

                AZ and M-AK designed the research and directed its implementation. MDY, DB, YAA, YWe, YWa, PL, QD, JS, and FD prepared datasets. LS and XW analysed data. LS, XW, and PL made the figures. LS, XW, M-AK, and AZ wrote the paper, and all authors contributed to the revision of the manuscript.

                Correspondence to: Dr Antonella Zanobetti, Department of Environmental Health, Harvard T H Chan School of Public Health, Boston, MA 02215, USA azanobet@ 123456hsph.harvard.edu
                Article
                NIHMS1647889
                10.1016/S2542-5196(20)30227-8
                7720425
                33091388
                0b9b74de-e757-4298-ad86-5cf4829296b0

                This is an Open Access article under the CC BY-NC-ND 4.0 license.

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