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High burden of neurological disease in the older general population: results from the Canadian Longitudinal Study on Aging.

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Title: High burden of neurological disease in the older general population: results from the Canadian Longitudinal Study on Aging.
Authors: Wolfson, C., Fereshtehnejad, S.‐M., Pasquet, R., Postuma, R., Keezer, M. R.
Source: European Journal of Neurology. Feb2019, Vol. 26 Issue 2, p356-362. 7p. 4 Charts.
Subjects: Parkinson's disease, Neurological disorders, Medical care, Disease prevalence, Neurology
Abstract: Background and purpose: Our objective was to study the association between the presence of a neurological disease and the comorbidity burden as well as healthcare utilization (HCU). Methods: Using baseline data from the Canadian Longitudinal Study on Aging (CLSA), we examined the burden of five neurological conditions. The CLSA is a population‐based study of approximately 50 000 individuals, aged 45–85 years at baseline. We used multivariable Poisson regression to identify correlates of comorbidity burden and HCU. Results: The lifetime prevalence of five neurological diseases is presented: epilepsy, Parkinson's disease/parkinsonism, stroke/transient ischaemic attack, multiple sclerosis and migraine. We found the somatic and psychiatric comorbidity burden to be higher in those individuals with a neurological disease (an 18–45% mean increase in the number of chronic conditions) as compared with the comparison group without a neurological disease, except for Parkinson's disease/parkinsonism. The presence of a neurological disease was associated with only a modest increase in the probability of visiting a general practitioner but was associated with a greatly increased probability of visiting a medical specialist (up to 68% more likely) or an emergency department (up to 79% more likely) and an overnight hospitalization (up to 108% more likely). Conclusions: We found striking associations between our neurological diseases and increased comorbidity burdens and HCU. These findings are important for informing public policy planning as well as driving avenues for future research. The present study established the CLSA as an important research platform for the study of neurological conditions in an aging general population. [ABSTRACT FROM AUTHOR]
Copyright of European Journal of Neurology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: High burden of neurological disease in the older general population: results from the Canadian Longitudinal Study on Aging.
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  Data: <searchLink fieldCode="AR" term="%22Wolfson%2C+C%2E%22">Wolfson, C.</searchLink><br /><searchLink fieldCode="AR" term="%22Fereshtehnejad%2C+S%2E‐M%2E%22">Fereshtehnejad, S.‐M.</searchLink><br /><searchLink fieldCode="AR" term="%22Pasquet%2C+R%2E%22">Pasquet, R.</searchLink><br /><searchLink fieldCode="AR" term="%22Postuma%2C+R%2E%22">Postuma, R.</searchLink><br /><searchLink fieldCode="AR" term="%22Keezer%2C+M%2E+R%2E%22">Keezer, M. R.</searchLink>
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  Data: <searchLink fieldCode="JN" term="%22European+Journal+of+Neurology%22">European Journal of Neurology</searchLink>. Feb2019, Vol. 26 Issue 2, p356-362. 7p. 4 Charts.
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  Data: <searchLink fieldCode="DE" term="%22Parkinson's+disease%22">Parkinson's disease</searchLink><br /><searchLink fieldCode="DE" term="%22Neurological+disorders%22">Neurological disorders</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+care%22">Medical care</searchLink><br /><searchLink fieldCode="DE" term="%22Disease+prevalence%22">Disease prevalence</searchLink><br /><searchLink fieldCode="DE" term="%22Neurology%22">Neurology</searchLink>
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  Data: Background and purpose: Our objective was to study the association between the presence of a neurological disease and the comorbidity burden as well as healthcare utilization (HCU). Methods: Using baseline data from the Canadian Longitudinal Study on Aging (CLSA), we examined the burden of five neurological conditions. The CLSA is a population‐based study of approximately 50 000 individuals, aged 45–85 years at baseline. We used multivariable Poisson regression to identify correlates of comorbidity burden and HCU. Results: The lifetime prevalence of five neurological diseases is presented: epilepsy, Parkinson's disease/parkinsonism, stroke/transient ischaemic attack, multiple sclerosis and migraine. We found the somatic and psychiatric comorbidity burden to be higher in those individuals with a neurological disease (an 18–45% mean increase in the number of chronic conditions) as compared with the comparison group without a neurological disease, except for Parkinson's disease/parkinsonism. The presence of a neurological disease was associated with only a modest increase in the probability of visiting a general practitioner but was associated with a greatly increased probability of visiting a medical specialist (up to 68% more likely) or an emergency department (up to 79% more likely) and an overnight hospitalization (up to 108% more likely). Conclusions: We found striking associations between our neurological diseases and increased comorbidity burdens and HCU. These findings are important for informing public policy planning as well as driving avenues for future research. The present study established the CLSA as an important research platform for the study of neurological conditions in an aging general population. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of European Journal of Neurology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Feb2019
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