Final published version
Licence: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Article number | e054584 |
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<mark>Journal publication date</mark> | 24/05/2022 |
<mark>Journal</mark> | BMJ Open |
Issue number | 5 |
Volume | 12 |
Number of pages | 9 |
Publication Status | Published |
<mark>Original language</mark> | English |
Objectives To examine the socioeconomic and demographic drivers associated with polypharmacy (5–9 medicines), extreme polypharmacy (9–20 medicines) and increased medication count.
Design, setting and participants A total of 5509 participants, from two waves of the English North West Coast, Household Health Survey were analysed
Outcome measures Logistic regression modelling was used to find associations with polypharmacy and extreme polypharmacy. A negative binomial regression identified associations with increased medication count. Descriptive statistics explored associations with medication management.
Results Age and number of health conditions account for the greatest odds of polypharmacy. ORs (95% CI) were greatest for those aged 65+ (3.87, 2.45 to 6.13) and for those with ≥5 health conditions (10.87, 5.94 to 19.88). Smaller odds were seen, for example, in those prescribed cardiovascular medications (3.08, 2.36 to 4.03), or reporting >3 emergency attendances (1.97, 1.23 to 3.17). Extreme polypharmacy was associated with living in a deprived neighbourhood (1.54, 1.06 to 2.26). The greatest risk of increased medication count was associated with age, number of health conditions and use of primary care services. Relative risks (95% CI) were greatest for those aged 65+ (2.51, 2.23 to 2.82), those with ≥5 conditions (10.26, 8.86 to 11.88) or those reporting >18 primary care visits (2.53, 2.18 to 2.93). Smaller risks were seen in, for example, respondents with higher levels of income deprivation (1.35, 1.03 to 1.77). Polypharmic respondents were more likely to report medication management difficulties associated with taking more than one medicine at a time (p<0.001). Furthermore, individuals reporting a mental health condition, were significantly more likely to consistently report difficulties managing their medication (p<0.001).
Conclusion Age and number of health conditions are most associated with polypharmacy. Thus, delaying or preventing the onset of long-term conditions may help to reduce polypharmacy. Interventions to reduce income inequalities and health inequalities generally could support a reduction in polypharmacy, however, more research is needed in this area. Furthermore, increased prevention and support, particularly with medication management, for those with mental health conditions may reduce adverse medication effects.