David T Gamble1, Allan B Clark2, Robert N Luben3, Nicholas J Wareham4, Kay-Tee Khaw3, Phyo K Myint1. 1. Ageing Clinical & Experimental Research (ACER) Team, Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, UK. 2. Norwich Medical School, University of East Anglia, Norwich, UK. 3. Clinical Gerontology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK. 4. MRC Epidemiology Unit, Cambridge, UK.
Abstract
Background: Stroke is primarily a disease of older age, with a substantial impact on global mortality and morbidity. Medications with anticholinergic effects are widely used, but no studies have been conducted to examine the relationship between anticholinergic burden (ACB) and stroke in a general population. Method: The sample was drawn from the EPIC-Norfolk cohort. Baseline assessments were carried out during 1993-97 and participants were followed up until March 2016. Participants were divided into four groups according to their total ACB score at baseline; these groups were those with a total ACB score of 0, 1, 2-3 and >3. After exclusion, Cox proportional hazards models were constructed to determine the associations between the ACB score groups and the risk of incident stroke and stroke mortality. Sensitivity analysis and propensity score matched analyses were performed. Results: In total 25 639 participants attended the first health check; 3917 participants were excluded, leaving 21 722 participants to be included. Participants had a mean age [standard deviation (SD)] of 58.9 (9.2) years (54.4% women). Of these, 2131 suffered incident stroke and 562 died from stroke. Mean follow-up was approximately 18 years for both outcomes. In the fully adjusted model, those with an ACB of >3 had 59% relative risk of incident stroke {hazard ratio [HR] [95% confidence interval (CI) 1.59 [1.34-1.89]} and 86% relative risk of stroke mortality [1.86 (1.37-2.53)] compared with those in ACB 0 category. Sensitivity analyses and propensity score matched analyses showed similar results. Conclusions: Our results provide an incentive for the cautious use of medications with anticholinergic properties, to help reduce the global burden of stroke.
Background: Stroke is primarily a disease of older age, with a substantial impact on global mortality and morbidity. Medications with anticholinergic effects are widely used, but no studies have been conducted to examine the relationship between anticholinergic burden (ACB) and stroke in a general population. Method: The sample was drawn from the EPIC-Norfolk cohort. Baseline assessments were carried out during 1993-97 and participants were followed up until March 2016. Participants were divided into four groups according to their total ACB score at baseline; these groups were those with a total ACB score of 0, 1, 2-3 and >3. After exclusion, Cox proportional hazards models were constructed to determine the associations between the ACB score groups and the risk of incident stroke and stroke mortality. Sensitivity analysis and propensity score matched analyses were performed. Results: In total 25 639 participants attended the first health check; 3917 participants were excluded, leaving 21 722 participants to be included. Participants had a mean age [standard deviation (SD)] of 58.9 (9.2) years (54.4% women). Of these, 2131 suffered incident stroke and 562 died from stroke. Mean follow-up was approximately 18 years for both outcomes. In the fully adjusted model, those with an ACB of >3 had 59% relative risk of incident stroke {hazard ratio [HR] [95% confidence interval (CI) 1.59 [1.34-1.89]} and 86% relative risk of stroke mortality [1.86 (1.37-2.53)] compared with those in ACB 0 category. Sensitivity analyses and propensity score matched analyses showed similar results. Conclusions: Our results provide an incentive for the cautious use of medications with anticholinergic properties, to help reduce the global burden of stroke.
Authors: Nicholas M Wilson; Sarah N Hilmer; Lyn M March; Jian Sheng Chen; Danijela Gnjidic; Rebecca S Mason; Ian D Cameron; Philip N Sambrook Journal: Drugs Aging Date: 2012-02-01 Impact factor: 3.923
Authors: Kathryn Richardson; Kathleen Bennett; Ian D Maidment; Chris Fox; David Smithard; Rose Anne Kenny Journal: J Am Geriatr Soc Date: 2015-07-22 Impact factor: 5.562
Authors: Anthony Grosso; Ian Douglas; Aroon D Hingorani; Raymond MacAllister; Richard Hubbard; Liam Smeeth Journal: Br J Clin Pharmacol Date: 2009-11 Impact factor: 4.335
Authors: Phyo Kyaw Myint; Chris Fox; Chun Shing Kwok; Robert N Luben; Nicholas J Wareham; Kay-Tee Khaw Journal: Age Ageing Date: 2014-11-27 Impact factor: 10.668
Authors: Jessica E Lockery; Jonathan C Broder; Joanne Ryan; Ashley C Stewart; Robyn L Woods; Trevor T-J Chong; Geoffrey C Cloud; Anne Murray; Jason D Rigby; Raj Shah; Elsdon Storey; Stephanie A Ward; Rory Wolfe; Christopher M Reid; Taya A Collyer; Michael E Ernst Journal: J Gen Intern Med Date: 2021-03-22 Impact factor: 6.473
Authors: Beatriz Poblador-Plou; Jonás Carmona-Pírez; Ignatios Ioakeim-Skoufa; Antonio Poncel-Falcó; Kevin Bliek-Bueno; Mabel Cano-Del Pozo; Luis Andrés Gimeno-Feliú; Francisca González-Rubio; Mercedes Aza-Pascual-Salcedo; Ana Cristina Bandrés-Liso; Jesús Díez-Manglano; Javier Marta-Moreno; Sara Mucherino; Antonio Gimeno-Miguel; Alexandra Prados-Torres Journal: Int J Environ Res Public Health Date: 2020-07-17 Impact factor: 3.390
Authors: Samuel R Neal; Adrian D Wood; Andrew D Ablett; Jenny S Gregory; Jordan Guillot; Helen M Macdonald; David M Reid; Phyo K Myint Journal: Ther Adv Drug Saf Date: 2020-05-27
Authors: Kaisa R Yrjana; Victoria L Keevil; Roy L Soiza; Robert N Luben; Nicholas J Wareham; Kay-Tee Khaw; Phyo K Myint Journal: Maturitas Date: 2020-07-25 Impact factor: 4.342