A systematic review of the statistical methods in prospective cohort studies investigating the effect of medications on cognition in older people

Kris M Jamsen, Jenni Ilomaki, Sarah N Hilmer, Natali Jokanovic, Edwin C K Tan, J Simon Bell

Research output: Contribution to journalArticleResearchpeer-review

5 Citations (Scopus)


Background: There is increasing awareness that medications can contribute to cognitive decline. Prospective cohort studies are rich sources of clinical data. However, investigating the contribution of medications to cognitive decline is challenging because both medication exposure and cognitive impairment can be associated with attrition of study participants, and medication exposure status may change over time. The objective of this review was to investigate the statistical methods in prospective cohort studies assessing the effect of medications on cognition in older people.
Methods: A systematic literature search was conducted to identify prospective cohort studies of at least 12 months duration that investigated the effect of common medications or medication classes (anticholinergics, antihistamines, hypnotics, sedatives, opioids, statins, estrogens, testosterone, antipsychotics, anticonvulsants, antidepressants, anxiolytics, antiparkinson agents and bronchodilators) on cognition in people aged 65 years and older. Data extraction was performed independently by two investigators. A descriptive analysis of the statistical methods was performed.
Results: A total of 44 articles were included in the review. The most common statistical methods were logistic regression (24.6% of all reported methods), Cox proportional hazards regression (22.8%), linear mixed-effects models (21.1%) and multiple linear regression (14.0%). The use of advanced techniques, most notably linear mixed-effects models, increased over time. Only 6 articles (13.6%) reported methods for addressing missing data.
Conclusions: A variety of statistical methods have been used for investigating the effect of medications on cognition in older people. While advanced techniques that are appropriate for the analysis of longitudinal data, most notably linear mixed-effects models, have increasingly been employed in recent years, there is an opportunity to implement alternative techniques in future studies that could address key research questions.
Original languageEnglish
Pages (from-to)20-28
Number of pages9
JournalResearch in Social and Administrative Pharmacy
Issue number1
Publication statusPublished - 2016


  • Aged
  • Cognitive impairment
  • Cohort studies
  • Data interpretation
  • Drug utilization
  • Review
  • Statistical

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