Analyzing Analgesic Medications in Community-Dwelling Older Adults.

OBJECTIVES

Analyzing medication data for research purposes is complex, and methods are rarely described in the literature. Our objective was to describe methods of quantifying opioid and nonopioid analgesics and to compare the utility of five different analgesic coding methods when analyzing relationships between pain, analgesic use, and clinical outcomes. In this study, we used physical function as the outcome variable for its clinical relevance and its relationship to pain in older adults.

DESIGN

Secondary analyses of baseline cross-sectional data from the Advanced Cognitive Training Interventions for Vital Elders (ACTIVE) study.

SETTING

Community settings in six regions of the United States.

SUBJECTS

A total of 2,802 community-residing adults older than age 65 years.

METHODS

A medication audit was conducted. Analgesics were coded as any pain medication, counts (total analgesics, number of opioids and nonopioids), equianalgesics (oral morphine equivalents, oral acetaminophen equivalents), and dose categories. Adjuvant medications used to treat pain (e.g., tricyclic antidepressants and anticonvulsants) and low-dose aspirin typically used for cardiovascular conditions were excluded from these analyses. To examine the utility of these various approaches, a series of hierarchical regression models were conducted with pain and analgesics as predictors and physical functioning as the dependent variable.

RESULTS

Eighty-one point nine percent of participants reported experiencing recent pain, but 26% reported analgesic use. Nonopioids were the most common drug class used. Models revealed that pain was significantly associated with worse physical function (β = -0.45, P = 0.001), after controlling for demographic and analgesic variables. Two basic drug coding methods (e.g., any pain medication, number of pain medications) were equivalent in their explanatory power (β = -0.12, P = 0.001) and were slightly stronger predictors of function than the more complex coding procedures.

CONCLUSIONS

Analgesic medications are important variables to consider in community-based studies of older adults. We illustrate several methods of quantifying analgesic medications for research purposes. In this community-based sample, we found no advantage of complex equianalgesic coding methods over simple counts in predicting physical functioning. The results may differ depending on the research question or clinical outcome studied. Thus, methods of analyzing analgesic drug data warrant further research.