BACKGROUND: To describe covariates and patterns of late-life analgesic use in the rural, population-based MoVIES cohort from 1989 to 2002. METHODS: Secondary analysis of epidemiologic survey of elderly people conducted over six biennial assessment waves. Potential covariates of analgesic use included age, gender, depression, sleep, arthritis, smoking, alcohol, and general health status. Of the original cohort of 1,681, this sample comprised 1,109 individuals with complete data on all assessments. Using trajectory analysis, participants were characterized as chronic or non-chronic users of opioid and non-opioid analgesics. Multivariable regression was used to model predictors of chronic analgesic use. RESULTS: The cohort was followed for mean (SD) 7.3 (2.7) years. Chronic use of opioid analgesics was reported by 7.2%, while non-opioid use was reported by 46.1%. In the multivariable model, predictors of chronic use of both opioid and non-opioid analgesics included female sex, taking ≥2 prescription medications, and "arthritis" diagnoses. Chronic opioid use was also associated with age 75-84 years; chronic non-opioid use was also associated with sleep continuity disturbance. CONCLUSIONS: These epidemiological data confirm clinical observations and generate hypotheses for further testing. Future studies should investigate whether addressing sleep problems might lead to decreased use of non-opioid analgesics and possibly enhanced pain management.
BACKGROUND: To describe covariates and patterns of late-life analgesic use in the rural, population-based MoVIES cohort from 1989 to 2002. METHODS: Secondary analysis of epidemiologic survey of elderly people conducted over six biennial assessment waves. Potential covariates of analgesic use included age, gender, depression, sleep, arthritis, smoking, alcohol, and general health status. Of the original cohort of 1,681, this sample comprised 1,109 individuals with complete data on all assessments. Using trajectory analysis, participants were characterized as chronic or non-chronic users of opioid and non-opioid analgesics. Multivariable regression was used to model predictors of chronic analgesic use. RESULTS: The cohort was followed for mean (SD) 7.3 (2.7) years. Chronic use of opioid analgesics was reported by 7.2%, while non-opioid use was reported by 46.1%. In the multivariable model, predictors of chronic use of both opioid and non-opioid analgesics included female sex, taking ≥2 prescription medications, and "arthritis" diagnoses. Chronic opioid use was also associated with age 75-84 years; chronic non-opioid use was also associated with sleep continuity disturbance. CONCLUSIONS: These epidemiological data confirm clinical observations and generate hypotheses for further testing. Future studies should investigate whether addressing sleep problems might lead to decreased use of non-opioid analgesics and possibly enhanced pain management.
Authors: Maiju K Marttinen; Hannu Kautiainen; Maija Haanpää; Heini Pohjankoski; Jukka Hintikka; Markku J Kauppi Journal: BMC Public Health Date: 2021-01-31 Impact factor: 3.295