Prescription Opioids and Longitudinal Changes in Cognitive Function in Older Adults

A Population-based Observational Study

Nafisseh S. Warner MD; Andrew C. Hanson MS; Phillip J. Schulte PhD; Elizabeth B. Habermann PhD; David O. Warner MD; Michelle M. Mielke PhD

Disclosures

J Am Geriatr Soc. 2022;70(12):3526-3537.

Abstract and Introduction

Abstract

Background: Opioids are frequently prescribed to alleviate pain in older adults, yet the relationships between prescription opioids and long-term cognitive function are unclear.

Methods: In this analysis of the Mayo Clinic Study of Aging, a longitudinal population-based cohort study of older adults with formal neuropsychological testing and cognitive evaluations performed every 15 months, the associations between prescription opioids, global and domain-specific cognitive function, and mild cognitive impairment were evaluated through time-dependent linear mixed effects and Cox proportional hazards models.

Results: Four thousand two hundred eighteen participants (51% male) were included with enrollment between 11/1/2004 and 4/1/2019 and median age of 76 (interquartile range 72, 82) years. Two thousand nine hundred seventy-seven subjects (71%) received at least 1 opioid prescription during a median follow-up of 7.5 (5.0, 10.7) years. Overall, there was an estimated 0.096 reduction in the global cognitive Z-score per year, including decreases of 0.050 in memory, 0.080 in language, 0.044 in visual–spatial cognition, and 0.112 in attention. In multivariable analyses, each receipt of an opioid prescription resulted in an additional −0.007 (95% CI −0.009, −0.005) change in global cognitive Z-score (p < 0.001), with significant effects seen in the domains of memory (−0.005, 95% CI −0.007, −0.003; p < 0.001), language (−0.002, 95% CI −0.003, 0.000; p = 0.024) and attention (−0.004, 95% CI −0.006, −0.002; p < 0.001) but not visual–spatial function (0.000, 95% CI −0.001, 0.001; p = 0.897). Opioid prescriptions were associated with incident mild cognitive impairment (MCI) in adjusted analysis (hazard ratio 1.21, 95% CI 1.04, 1.42; p = 0.014).

Conclusion: Prescription opioids are associated with small but statistically significant declines in long-term cognitive function in older adults, which may represent effects of opioids or other related factors.

Introduction

Chronic pain is common in older adults, with a prevalence of bothersome pain for those ≥65 years exceeding 50%.^[1–3] Pain in this population is associated with decreased quality of life,^[4–6] inferior perception of health,^[7] and increased healthcare resource utilization.^[5] Persistent pain symptoms may also be associated with accelerated cognitive decline.^[8–11] Thus, it is critically important to optimize analgesic outcomes for older adults.

Opioids are frequently prescribed in older adults to treat pain symptoms. Approximately 10% of US adults >60 years of age are using opioids at any given time.^[12] Despite it being known that a single therapeutic dose of opioid causes transient declines in attention, working memory, and verbal memory in older adults,^[13] the long-term effects of opioids on cognitive performance, including the development of mild cognitive impairment (MCI) or dementia, is unclear. The limited evidence suggests that opioid use may be a risk factor for long-term cognitive impairment in older adults.^[14–16] However, most data are based on the utilization of cognitive screening tools rather than longitudinal assessment of global and domain-specific cognitive function and with limited adjustment for important covariates that may influence propensity for opioid use and/or cognitive function.

In this study, we determined the associations between prescription opioid availability, longitudinal changes in global and domain-specific cognitive function, and incident MCI utilizing data from a longitudinal population-based cohort study, the Mayo Clinic Study of Aging (MCSA). We hypothesized that opioid availability in older adults would be associated with accelerated cognitive decline and an increased risk of incident MCI. In addition, we describe patterns of opioid prescribing in this population-based cohort to provide insights into current prescribing practices in older adults.

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Abstract and Introduction
Methods
Results
Discussion
References
Sidebar

Table 1. Participant demographics at time of enrollment ( N = 4218) ^a
	Overall (N = 4218)	No opioid Rx during follow-up (N = 1241)	One or more opioid Rx during follow-up (N = 2977)	Absolute standardized differences
Age, years	76 (72, 82)	76 (71, 81)	77 (72, 82)	0.171
Gender
Male	2140 (51%)	658 (53%)	1482 (50%)	0.065
Female	2078 (49%)	583 (47%)	1495 (50%)	0.065
Education (n = 4211)
<12 years	305 (7%)	58 (5%)	247 (8%)	0.147
12 years	1374 (33%)	362 (29%)	1012 (34%)	0.103
13–15 years	1101 (26%)	324 (26%)	777 (26%)	0.002
16+ years	1431 (34%)	493 (40%)	938 (32%)	0.174
Marital status (n = 4212)
Married/living together	2835 (67%)	856 (69%)	1979 (67%)	0.052
Widowed	934 (22%)	236 (19%)	698 (23%)	0.109
Separated/divorced	273 (6%)	98 (8%)	175 (6%)	0.080
Single, never married	170 (4%)	50 (4%)	120 (4%)	0.000
Smoking status (n = 4209)
Never	2141 (51%)	667 (54%)	1474 (50%)	0.085
Former	1893 (45%)	531 (43%)	1362 (46%)	0.059
Current	175 (4%)	40 (3%)	135 (5%)	0.068
Charlson index	3 (1, 5)	2 (1, 5)	3 (1, 5)	0.150
APOE-E4 positive (n = 4069)	1070 (26%)	304 (26%)	766 (26%)	0.009
Mild cognitive impairment	635 (15%)	177 (14%)	458 (15%)	0.032
Chronic pain diagnosis in prior year	1238 (29%)	227 (18%)	1011 (34%)	0.362
Antidepressants	749 (18%)	192 (15%)	557 (19%)	0.086
Benzodiazepines	148 (4%)	37 (3%)	111 (4%)	0.041
Opioid Rx in prior 6 months	536 (13%)	70 (6%)	466 (16%)	0.329
Opioid Rx in prior 12 months	901 (21%)	156 (13%)	745 (25%)	0.323
BDI-II grand total (n = 4106)	4 (1, 7)	3 (1, 7)	4 (1, 8)	0.143
BAI total (n = 4193)	1 (0, 4)	1 (0, 4)	2 (0, 5)	0.157

Abbreviations: BAI, Beck Anxiety Inventory; BDI-II, Beck Depression Inventory; Rx, prescription.
^aData are summarized as number (percentage) for categorical variables and median (25th, 75th percentile) for continuous variables. When not all data are available, number of observations with complete data is reported. Groups are compared using absolute standardized differences.

Table 2. Prescriptions occurring during follow-up ^a
	Summary of all prescriptions (N = 21,949)	Per-participant summary (N = 2977)^b
Medication
Oxycodone	6686 (30%)	1886 (63%)
Tramadol	6660 (30%)	1486 (50%)
Hydrocodone	2830 (13%)	992 (33%)
Codeine	857 (4%)	378 (13%)
Propoxyphene	383 (2%)	183 (6%)
Fentanyl	946 (4%)	147 (5%)
Hydromorphone	1155 (5%)	326 (11%)
Morphine	1102 (5%)	507 (17%)
Oxycodone and tramadol	631 (3%)	440 (15%)
Other/other combination	699 (3%)	338 (11%)
Medication form
Tablet	19,357 (88%)	2828 (95%)
Patch	949 (4%)	149 (5%)
Solution	1595 (7%)	731 (25%)
Other	48 (<1%)	13 (<1%)
Hospitalization	5096 (23%)	1741 (58%)
Surgical episode	2299 (10%)	1045 (35%)
ICU admission	863 (4%)	495 (17%)
Dose (MME, n = 21,887)^c	5 (5, 9)	10 (8, 15)
Daily dose (MME, n = 21,887)	30 (15, 45)	60 (45, 90)
Total MME, (n = 21,887)	300 (150, 600)	475 (225, 950)
Prescription length (days)	13 (5, 30)	15 (7, 40)
New prescription obtained with meds remaining^d	6315 (29%)	1301 (44%)

Abbreviation: MME, oral morphine milligram equivalents.
^aData are from 21,949 prescriptions in 2977 participants written between enrollment and end of follow-up. Median (25th, 75th) number of prescriptions 3 (2, 8). Values are number (percent) for categorical variables and median (25th, 75th) for continuous variables. Prescriptions for the same medication and form were combined (n = 279).
^bIn the per-participant summary, categorical variables reflect meeting the definition for the characteristic at any time during follow-up. For example, out of 2977 participants receiving any opioid prescription during follow-up, 1886 (63%) participants had at least one prescription for oxycodone. Percentages will no longer sum to 100. Values summarized for continuous variables are the maximum observed for each participant during follow-up.
^cWhen multiple prescriptions were written on the same date, the dose OME was summed regardless of whether it was intended for the medications to be taken at the same time or not.
^dBased on usage of maximum frequency and dosage, was there a new prescription obtained prior to the estimated date at which subject would exhaust the supply from this prescription.

Table 3. Associations between opioid prescriptions and changes in cognitive Z-scores from linear mixed effects models ^a
	Slope prior estimate	Change in slope following each Rx estimate (95% CI)	p-value
Global	−0.096	−0.007 (−0.009, −0.005)	<0.001
Memory	−0.050	−0.005 (−0.007, −0.003)	<0.001
Language	−0.080	−0.002 (−0.003, 0.000)	0.024
Visual–spatial	−0.044	0.000 (−0.001, 0.001)	0.897
Attention	−0.112	−0.004 (−0.006, −0.002)	<0.001

^aModels adjusted for baseline age, gender, prescription in the prior 6 and 12 months, baseline Charlson index, education, marital status, smoking status, APOE-ε4 allele, Beck depression, Beck anxiety, pain diagnosis, antidepression medication, benzodiazepine medication, test naïvety, and current opioid availability.

Table 4. Summary of estimated association between receipt of opioid prescription and change in cognitive decline measured on raw scales of cognitive tests ^a
Test (valid range)	Opioid unexposed			Opioid exposed			Estimated slope prior to Rx	Estimated change in slope following each Rx estimate (95% CI)	p-value
Test (valid range)	Baseline mean (SD)	Following visit mean (SD)	Difference mean (SD)	Baseline mean (SD)	Following visit mean (SD)	Difference mean (SD)	Estimated slope prior to Rx		p-value
Memory
WMSR Log Mem II Total (0–43)	17.7 (8.1)	17.9 (8.6)	0.1 (5.2)	19.1 (8.3)	18.2 (9.8)	−1.0 (6.0)	−0.126	−0.027 (−0.039, −0.014)	<0.001
WMSR Vis Rep II Total (0–41)	21.5 (9.0)	21.8 (9.6)	0.3 (6.5)	23.7 (8.6)	20.1 (9.5)	−3.7 (7.4)	−0.396	−0.020 (−0.032, −0.007)	0.002
ALVT half hour delay (0–15)	7.3 (3.8)	7.3 (3.8)	0.0 (2.4)	7.8 (3.6)	6.4 (4.1)	−1.4 (2.9)	−0.175	−0.007 (−0.013, −0.001)	0.015
Language
Boston naming score (0–60)	54.6 (5.0)	54.5 (5.4)	−0.1 (2.8)	54.9 (5.0)	53.9 (6.2)	−1.0 (4.0)	−0.238	−0.009 (−0.016, −0.001)	0.029
Category fluency (0–74)	42.9 (10.1)	42.1 (10.4)	−0.8 (6.7)	42.2 (9.6)	37.9 (11.0)	−4.3 (7.6)	−0.824	−0.011 (−0.024, 0.003)	0.127
Visual–spatial
WAISR PIC Comp Total (0–20)	13.5 (3.3)	13.5 (3.4)	0.1 (2.6)	13.9 (3.2)	13.7 (3.6)	−0.2 (2.4)	−0.013	−0.001 (−0.005, 0.004)	0.745
WAISR Block Des Total (0–51)	24.0 (8.6)	23.3 (8.8)	−0.7 (5.8)	24.3 (8.4)	20.9 (8.6)	−3.4 (5.8)	−0.597	0.000 (−0.009, 0.009)	0.933
Attention
WAISR Digit Sym Total (0–93)	43.8 (11.2)	43.0 (11.6)	−0.9 (5.9)	44.3 (10.4)	38.4 (11.4)	−5.9 (7.5)	−0.969	−0.021 (−0.035, −0.007)	0.004
TMTB total (0–300)^b	104.9 (54.0)	110.3 (60.1)	5.4 (38.5)	102.3 (49.3)	139.4 (78.7)	37.1 (58.4)	6.24	0.25 (0.12, 0.38)	<0.001

Abbreviations: ALVT, Auditory Verbal Learning Test; Block Des, Block Design; CI, confidence interval; Digit Sym, Digit Symbol; Log Mem II, Logical Memory-II; PIC Comp, Picture Completion; Rx, prescription; SD, standard deviation; TMTB, Trailmaking Test B; Vis Rep II, Visual Reproduction II; WAISR, Wechsler Adult Intelligence Scale-Revised; WMSR, Wechsler Memory Scale-Revised.
^aBaseline and following visit test scores are presented as mean (SD) for patients prior to any opioid exposure (unexposed) and following exposure (exposed). Baseline values for exposed are from the last visit prior to exposure.
^bHigher scores on TMBT represent worse performance.