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Is the risk of dementia among persons 55 years or older associated with the use of different types of anticholinergic medication?
In this nested case-control study of 58 769 patients with a diagnosis of dementia and 225 574 matched controls, there were statistically significant associations of dementia risk with exposure to anticholinergic antidepressants, antiparkinson drugs, antipsychotic drugs, bladder antimuscarinics, and antiepileptic drugs after adjusting for confounding variables.
The associations observed for specific types of anticholinergic medication suggest that these drugs should be prescribed with caution in middle-aged and older adults.
Anticholinergic medicines have short-term cognitive adverse effects, but it is uncertain whether long-term use of these drugs is associated with an increased risk of dementia.
To assess associations between anticholinergic drug treatments and risk of dementia in persons 55 years or older.
Design, Setting, and Participants
This nested case-control study took place in general practices in England that contributed to the QResearch primary care database. The study evaluated whether exposure to anticholinergic drugs was associated with dementia risk in 58 769 patients with a diagnosis of dementia and 225 574 controls 55 years or older matched by age, sex, general practice, and calendar time. Information on prescriptions for 56 drugs with strong anticholinergic properties was used to calculate measures of cumulative anticholinergic drug exposure. Data were analyzed from May 2016 to June 2018.
The primary exposure was the total standardized daily doses (TSDDs) of anticholinergic drugs prescribed in the 1 to 11 years prior to the date of diagnosis of dementia or equivalent date in matched controls (index date).
Main Outcomes and Measures
Odds ratios (ORs) for dementia associated with cumulative exposure to anticholinergic drugs, adjusted for confounding variables.
Of the entire study population (284 343 case patients and matched controls), 179 365 (63.1%) were women, and the mean (SD) age of the entire population was 82.2 (6.8) years. The adjusted OR for dementia increased from 1.06 (95% CI, 1.03-1.09) in the lowest overall anticholinergic exposure category (total exposure of 1-90 TSDDs) to 1.49 (95% CI, 1.44-1.54) in the highest category (>1095 TSDDs), compared with no anticholinergic drug prescriptions in the 1 to 11 years before the index date. There were significant increases in dementia risk for the anticholinergic antidepressants (adjusted OR [AOR], 1.29; 95% CI, 1.24-1.34), antiparkinson drugs (AOR, 1.52; 95% CI, 1.16-2.00), antipsychotics (AOR, 1.70; 95% CI, 1.53-1.90), bladder antimuscarinic drugs (AOR, 1.65; 95% CI, 1.56-1.75), and antiepileptic drugs (AOR, 1.39; 95% CI, 1.22-1.57) all for more than 1095 TSDDs. Results were similar when exposures were restricted to exposure windows of 3 to 13 years (AOR, 1.46; 95% CI, 1.41-1.52) and 5 to 20 years (AOR, 1.44; 95% CI, 1.32-1.57) before the index date for more than 1095 TSDDs. Associations were stronger in cases diagnosed before the age of 80 years. The population-attributable fraction associated with total anticholinergic drug exposure during the 1 to 11 years before diagnosis was 10.3%.
Conclusions and Relevance
Exposure to several types of strong anticholinergic drugs is associated with an increased risk of dementia. These findings highlight the importance of reducing exposure to anticholinergic drugs in middle-aged and older people.
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Accepted for Publication: February 19, 2019
Published Online: June 24, 2019. doi:10.1001/jamainternmed.2019.0677
Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2019 Coupland CAC et al. JAMA Internal Medicine.
Corresponding Author: Carol A. C. Coupland, PhD, Division of Primary Care, University of Nottingham, University Park, 13th Floor, Tower Building, Nottingham NG7 2RD, United Kingdom (firstname.lastname@example.org).
Author Contributions: Dr Coupland had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Study concept and design: Coupland, Dening, Morriss, Moore, Hippisley-Cox.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: Coupland, Dening, Hippisley-Cox.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Coupland, Hill.
Obtained funding: Coupland, Morriss, Hippisley-Cox.
Administrative, technical, or material support: Dening, Morriss, Moore, Hippisley-Cox.
Study supervision: Coupland.
Conflict of Interest Disclosures: Dr Coupland reported personal fees from ClinRisk Ltd outside the submitted work. Julia Hippisley-Cox reported nonfinancial support from QResearch and personal fees from ClinRisk Ltd outside the submitted work. No other disclosures were reported.
Funding/Support: The project was funded by the National Institute for Health Research (NIHR) School for Primary Care Research (project number 265). Additional funding was provided by the Faculty of Medicine and Health Sciences Research Board, University of Nottingham. QResearch receives support from the NIHR Nottingham Biomedical Research Centre. Dr Morriss’s contribution to the study has been funded through the NIHR Collaboration for Leadership in Applied Health Research and Care East 15 Midlands (CLAHRC EM), NIHR MindTech, MedTech, and In Vitro Cooperative. Drs Hippisley-Cox, Coupland, and Morriss acknowledge funding from the NIHR Nottingham Biomedical Research Centre.
Role of the Funder/Sponsor: The NIHR approved the study design, but did not play a role in the conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Disclaimer: This article presents independent research funded by the NIHR School for Primary Care Research. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. The Office for National Statistics bears no responsibility for the analysis or interpretation of the data.
Additional Contributions: We acknowledge the contribution of practices who contribute to the QResearch database and to Egton Medical Information Systems (EMIS) and the University of Nottingham for expertise in establishing, developing, and supporting the database. We thank the Office for National Statistics for providing the mortality data. This work uses data provided by patients and collected by the NHS as part of their care and support. None of the additional contributors who assisted with the study received compensation.
Data Sharing Statement: The patient level data from the QResearch database are specifically licensed according to its governance framework. See http://www.qresearch.org for further details.
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