A propensity score matched approach to assess the associations of commonly prescribed medications with fall risk in a large harmonized cohort of older ambulatory persons
Introduction: Several medication classes are considered to present risk factors for falls. However, the evidence is mainly based on observational studies that often lack adequate adjustment for confounders. Therefore, we aimed to assess the associations of medication classes with fall risk by carefully selecting confounders and by applying propensity score matching (PSM).
Methods: Data from several European cohorts, harmonized into the ADFICE_IT cohort, was used. Our primary outcome was time until the first fall within 1-year follow-up. The secondary outcome was a fall in the past year. Our exposure variables were commonly prescribed medications. We used 1:1 PSM to match the participants with reported intake of specific medication classes with participants without. We constructed Cox regression models stratified by the pairs matched on the propensity score for our primary outcome and conditional logistic regression models for our secondary outcome.
Results: In total, 32.6% of participants fell in the 1-year follow-up and 24.4% reported falling in the past year. ACE inhibitor users (prevalence of use 15.3%) had a lower fall risk during follow-up when matched to non-users, with a hazard ratio (HR) of 0.82 (95% CI 0.68-0.98). Also, statin users (prevalence of use 20.1%) had a lower risk, with an HR of 0.76 (95% CI 0.65-0.90). Other medication classes showed no association with risk of first fall. Also, in our secondary outcome analyses, statin users had a significantly lower risk. Furthermore, β-blocker users had a lower fall risk and proton pump inhibitor use was associated with a higher risk in our secondary outcome analysis.
Conclusion: Many commonly prescribed medication classes showed no associations with fall risk in a relatively healthy population of community-dwelling older persons. However, the treatment effects and risks can be heterogeneous between individuals. Therefore, focusing on identification of individuals at risk is warranted to optimize personalized falls prevention.
Clementine Brigitta Maria Dalderup fund, an Amsterdam University fund.
Netherlands Organization for Health Research and Development (ZonMw, Grant 6130.0031)
NZO (Dutch Dairy Association)
Netherlands Consortium Healthy Ageing (NCHA) Leiden/Rotterdam
Ministry of Economic Affairs, Agriculture and Innovation (project KB-15-004-003), The Hague
Wageningen University, Wageningen
Erasmus Medical Center, Rotterdam
Netherlands Ministry of Health, Welfare and Sports, Directorate of Long-Term Care
Netherlands Organization for Scientific Research (NWO) in the framework of the project “New Cohorts of young old in the 21st century” (File Number 480-10-014)
Government of Ireland through the Office of the Minister for Health and Children
Central Statistics Office, Ireland
Erasmus MC University Medical Center and Erasmus University Rotterdam
The Netherlands Organisation for Scientific Research
The Netherlands Organisation for Health Research and Development (ZonMw)
The Research Institute for Diseases in the Elderly (RIDE)
The Netherlands Genomics Initiative (NGI)
Netherlands Ministry of Education Culture and Science and the Ministry of Health, Welfare and Sports
European Commission (DG XII)
Municipality of Rotterdam
European Union (No. 2005121)
German Ministry of Science, Baden‐Württemberg
German Research Foundation (RO2606/14-1, DE2674/1-1)
CommentsThe original article is available at https://link.springer.com
Published CitationSeppala LJ. et al. A propensity score matched approach to assess the associations of commonly prescribed medications with fall risk in a large harmonized cohort of older ambulatory persons. Drugs Aging. 2021;38(9):797-805.
Publication Date5 July 2021
- HRB Centre for Primary Care Research
- Population Health and Health Services
PublisherSpringer Science and Business Media LLC
- Published Version (Version of Record)