Evidence map›Paper›PMID 39954222›Full record

ArticleInternational journal of clinical pharmacy2025

Defining polypharmacy in older adults: a cross-sectional comparison of prevalence estimates calculated according to active ingredient and unique product counts.

Georgie B Lee, Sarah M Hosking, Christopher Etherton-Beer, Julie A Pasco, Lana J Williams, Kara L Holloway-Kew, Amy T Page

Abstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of clinical pharmacy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Georgie B LeeSchool of Medicine, IMPACT - Institute for Mental and Physical Health and Clinical Translation, Deakin University, Geelong, VIC, Australia. georgie.lee@research.uwa.edu.au.ORCID http://orcid.org/0000-0002-4343-3020
Sarah M HoskingSchool of Medicine, IMPACT - Institute for Mental and Physical Health and Clinical Translation, Deakin University, Geelong, VIC, Australia.
Christopher Etherton-BeerWA Centre for Health and Ageing, University of Western Australia, Crawley, WA, Australia.
Julie A PascoSchool of Medicine, IMPACT - Institute for Mental and Physical Health and Clinical Translation, Deakin University, Geelong, VIC, Australia.
Lana J WilliamsSchool of Medicine, IMPACT - Institute for Mental and Physical Health and Clinical Translation, Deakin University, Geelong, VIC, Australia.
Kara L Holloway-KewSchool of Medicine, IMPACT - Institute for Mental and Physical Health and Clinical Translation, Deakin University, Geelong, VIC, Australia.
Amy T PageWA Centre for Health and Ageing, University of Western Australia, Crawley, WA, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPolypharmacy is common in older adults and may be associated with poor outcomes. However, methods used to define polypharmacy are rarely reported precisely, with potential implications for polypharmacy exposure estimates.

aimThe aim was to investigate prevalence estimates according to different methods in an Australian population-based sample of older adults.

methodThis cross-sectional study included 735 adults aged ≥ 60 years participating in the Geelong Osteoporosis Study. Current prescription, non-prescription and complementary and alternative medicines were self-reported. Counting methods included the number of active ingredients and unique products. Polypharmacy and hyperpolypharmacy were determined using ≥ 5 and ≥ 10 medicine cut points respectively. Prevalence was estimated using ingredient- and product-level counts according to criteria defined by medicine schedule and type (i.e. scheduled prescription, non-prescription). Non-parametric testing measured differences between counting methods, univariate logistic regressions investigated disagreement between total counts and polypharmacy exposure.

resultsPolypharmacy prevalence (scheduled prescription medicines) was 30.3% and 35.9% (products versus ingredients). Prevalence increased to 52.8% and 57.3% when counts considered any medicine. Adults aged ≥ 80 years were most likely to use prescription combination products (OR 2.22 [95% CI 1.46, 3.35] p < 0.01), however, age was not associated with disagreement between product and ingredient polypharmacy exposure. Being male was associated with both prescription combination product use (OR 1.79 [95% CI 1.29, 2.47] p < 0.001) and disagreement between polypharmacy exposures (OR 2.29 [95% CI 1.15, 4.47] p=0.02).

conclusionPolypharmacy prevalence estimates varied substantially depending on the method applied. These data indicate the need for standardised reporting specific to medicines data and polypharmacy measures.

Indexed as

PolypharmacyPrescription DrugsAgedAged, 80 and overAustraliaCross-Sectional StudiesFemaleHumansMaleMiddle AgedPrevalencePrescription DrugsAgingEpidemiologic methodsInappropriate prescribingPolypharmacyPrevalence

Identifiers

PMID39954222
PMCPMC12125127

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.