Evidence map›Paper›PMID 41652571›Full record

ArticleBMC public health2026

Prevalence and associated factors of inappropriate analgesic drug use among community-dwelling older adults with chronic musculoskeletal pain: a cross-sectional study.

Natagarn Ampornpiriyakul, Narucha Komolsuradej, Siwaluk Srikrajang

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Article in BMC public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Natagarn AmpornpiriyakulDepartment of Family and Preventive Medicine, Faculty of Medicine, Prince of Songkla University, 15 Kanchanavanich Road, Songkhla, 90110, Thailand.
Narucha KomolsuradejDepartment of Family and Preventive Medicine, Faculty of Medicine, Prince of Songkla University, 15 Kanchanavanich Road, Songkhla, 90110, Thailand. narucha.ko@psu.ac.th.
Siwaluk SrikrajangDepartment of Physical Therapy, Faculty of Medicine, Prince of Songkla University, 15 Kanchanavanich Road, Songkhla, 90110, Thailand.

Funding

Faculty of Medicine, Prince of Songkla University 66-034-1
6 · The paper itself

Abstract

backgroundMusculoskeletal disorders are frequently associated with pain in older adults, and the use of inappropriate analgesics drugs is common. Understanding the patterns and factors of inappropriate analgesic use may help reduce its prevalence among older adults with chronic musculoskeletal pain.

methodsThis cross-sectional study evaluated 215 older adults aged ≥ 60 years who experienced chronic musculoskeletal pain and used oral medication to relieve pain within the previous 3 months. Participants were recruited through home visits using the community health register in Ban Phru, Hat Yai District, Songkhla Province (Southern Thailand) between July and December 2023. Analgesic use was determined by directly inspecting the drugs that participants were taking within the previous 3 months, regardless of whether they were prescribed or self-purchased. The name, dose, and source of each medication were recorded and cross-checked with the 2023 American Geriatrics Society Beers Criteria to identify potentially inappropriate drugs. This approach enabled differentiation into three patterns of inappropriate analgesic drug use: potentially inappropriate medication use, overtreatment, and undertreatment. Factors associated with the inappropriate use of analgesic drugs were analysed using multivariate logistic regression analysis.

resultsInappropriate analgesic drug use was prevalent in 66.5%. Regarding the prevalence rates by pattern, potentially inappropriate, overtreatment, and undertreatment were prevalent in 71.3%, 24.5%, and 33.6%, respectively. Non-prescribed polypharmaceutical packs (adjusted odds ratio [aOR] [95% confidence interval {CI}] = 11.45 [3.32, 72.15], P < 0.001) and pain interfering with enjoyment of life (aOR [95% CI] = 1.16 [1.04, 1.30], P = 0.007) were significantly associated with inappropriate analgesic drug use.

conclusionsInappropriate analgesic use was common, affecting 66.5% of community-dwelling older adults with chronic musculoskeletal pain. Non-prescribed polypharmaceutical packs and pain interference were significant predictors of inappropriate use. These findings underscore the influence of inappropriate self-medication, suggesting the need for greater attention from healthcare providers to promote safe and rational analgesic use in this population.

Indexed as

AnalgesicsChronic PainInappropriate PrescribingIndependent LivingMusculoskeletal PainAgedAged, 80 and overCross-Sectional StudiesFemaleHumansMaleMiddle AgedOvertreatmentPrevalenceThailandUndertreatmentAnalgesicsAnalgesicCommunity-dwelling older adultsInappropriate drug useMusculoskeletalPain

Identifiers

PMID41652571
PMCPMC12973537

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LicenceCC BY-NC-ND
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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.