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. 2023 May 9;14(3):455–463. doi: 10.1007/s41999-023-00786-x

Psychotropic medication use and future unexplained and injurious falls and fracture amongst community-dwelling older people: data from TILDA

Eleanor Gallagher 1, Mustafa Mehmood 4, Amanda Lavan 1,2,3, Rose Anne Kenny 1,2,3, Robert Briggs 1,2,3,
PMCID: PMC10261192  PMID: 37157012

Key Summary Points

Aim

To examine the association of psychotropic medication use with future unexplained and injurious falls and fracture in a large cohort of community-dwelling older people.

Findings

Psychotropic medication use was independently associated with falls, unexplained falls and fracture. Antidepressants and anticholinergics were independently associated with future unexplained falls. Benzodiazepines and Z-drugs were not independently associated with falls.

Message

Regular review of ongoing need for these medications should therefore be central to the comprehensive geriatric assessment.

Keywords: Psychotropic, Falls, Older, Antidepressant, Fractures, Antidepressants

Abstract

Purpose

Psychotropic medications (antidepressants, anticholinergics, benzodiazepines, ‘Z’-drugs and antipsychotics) are frequently identified as Falls Risk Increasing Drugs. The aim of this study is to clarify the association of psychotropic medication use with future falls/fracture amongst community-dwelling older people.

Methods

Participants ≥ 65 years from TILDA were included and followed from Waves 1 to 5 (8-year follow-up). Incidence of falls (total falls/unexplained/injurious) and fracture was by self-report; unexplained falls were falls not caused by a slip/trip, with no apparent cause. Poisson regression models reporting incidence rate ratios (IRR) assessed the association between medications and future falls/fracture, adjusted for relevant covariates.

Results

Of 2809 participants (mean age 73 years), 15% were taking ≥ 1 psychotropic medication. During follow-up, over half of participants fell, with 1/3 reporting injurious falls, over 1/5 reporting unexplained falls and almost 1/5 reporting fracture. Psychotropic medications were independently associated with falls [IRR 1.15 (95% CI 1.00–1.31)] and unexplained falls [IRR 1.46 (95% CI 1.20–1.78)]. Taking ≥ 2 psychotropic medications was further associated with future fracture (IRR 1.47 (95% CI 1.06–2.05)]. Antidepressants were independently associated with falls [IRR 1.20 (1.00–1.42)] and unexplained falls [IRR 2.12 (95% CI 1.69–2.65)]. Anticholinergics were associated with unexplained falls [IRR 1.53 (95% CI 1.14–2.05)]. ‘Z’-drug and benzodiazepine use were not associated with falls or fractures.

Conclusion

Psychotropic medications, particularly antidepressants and anticholinergic medications, are independently associated with falls and fractures. Regular review of ongoing need for these medications should therefore be central to the comprehensive geriatric assessment.

Introduction

Falls can have a profound impact on the health and general well-being of older people, increasing the risk of significant injury, hospitalisation and early mortality [1, 2]. Importantly falls can also lead to a decline in functional status and loss of independence and can therefore represent a tipping point in terms of admission to a nursing home [3].

Identification of modifiable risk factors for falls is therefore important to inform preventative strategies. One such important modifiable factor is medication use, particularly psychotropic medications. Antidepressants, benzodiazepines, ‘Z’ drugs, anticholinergic medications and antipsychotics are often essential for the management of psychiatric illness and symptoms including mood disturbance, anxiety, psychosis and insomnia amongst older people [47]. Exposure to centrally acting medications can impair cognitive function, level of alertness and neuromuscular function however and have been implicated in falls in later life [8, 9]. Many psychotropic medications also impair cardiovascular autonomic reflexes, leading to orthostatic hypotension, an important cause of falls amongst older people [10].

Age-related changes in drug metabolism can lead to higher bioavailability, increasing the potential for drug–drug interactions and for adverse effects of medication use [11]. Despite this, use of psychotropic medication amongst older people in the community [12] and in hospital settings [13] is relatively high, including older people with cognitive impairment [14].

Explained falls are those due to slips or trips [15]. About one-third of falls seen in the emergency department are unexplained [16] with no readily apparent cause, conferring a higher likelihood of admission to hospital [17]. Frequent underlying causes of unexplained falls are orthostatic hypotension [18] and cardiac arrhythmia [19].

Whilst the association between psychotropic medication use and falls is well established, [20, 21] studies to date have not yet examined the link with specific fall types longitudinally and/or robustly adjusted for competing covariates, such as heart disease and chronic disease burden.

The aim of this study therefore is to clarify the longitudinal association between psychotropic medication use and incident falls, injurious falls, unexplained falls and fracture in a large well-described cohort of community-dwelling older people at 8-year follow-up.

Methods

Study design

This is a longitudinal cohort study utilising data from The Irish Longitudinal Study on Ageing (TILDA), a large population-based nationally representative sample of community-dwelling older adults aged ≥ 50 years. This study establishes the longitudinal relationship between classes of psychotropic medication use and incident falls and fractures from baseline (Wave 1) to Wave 5 (8-year follow-up).

The TILDA study was designed to investigate how the health, social and economic circumstances of the older Irish population interact in the determination of ‘healthy’ ageing. The TILDA study design has been outlined previously [22]. Briefly, there are three components to data collection: a computer-assisted personal interview carried out by social interviewers in the participants’ own home; a self-completion questionnaire completed and returned by the participant; and a comprehensive centre-based health assessment or a modified home-based health assessment carried out by trained research nurses. Waves of data collection are conducted at 2-yearly intervals, and we used data from Waves 1 to 5, collected between 2009 and 2018.

Participants were included in this study if they were aged ≥ 65 years at Wave 1 and had a medication list examined for medications of interest at baseline and were followed up for at least 2 years, i.e. to Wave 2 of TILDA. Participants were excluded from participation in TILDA at Wave 1 if they had a pre-existing diagnosis of dementia. Subsequent waves were conducted at 2-yearly intervals.

Psychotropic medications

Medication use was recorded and cross-checked with medication labels at baseline assessment. The Anatomical Therapeutic Chemical (ATC) Classification System was used to identify specific medications. Antidepressants were identified with an ATC code of N06A. Benzodiazepines were identified with an ATC code of N05BA, N05CD and N03AE. ‘Z’ drugs were coded as N05CF and antipsychotics were coded as N05A.

Anticholinergic medications were defined as those classified as having ‘definite’ anticholinergic effects according to the Anticholinergic Cognitive Burden scale [23]. This comprises antidepressants (N06AA, N06AB05), medications acting on the bladder (G04BD), antipsychotics (N05AA01, N05AA03, N05AB03, N05AB06, N05AC02, N05AH03, N05AH04), medications acting on the gastrointestinal system (A03), medications for Parkinson’s Disease (N04A), antihistamines (R06A) and others (M03BA03, M03BC01, N05CM05, N05BB01). Changes to medication use during the follow-up period were not captured.

Falls and fractures

At Waves 2–5, participants were asked ‘Have you had any falls since the last interview?’ This was used to derive the ‘Falls’ variable.

If they answered yes to this, participants were then asked, ‘Were any of these falls non-accidental, i.e. with no apparent or obvious reason?’ This was used to inform the ‘Unexplained Falls’ variable. Explained falls were therefore accidental falls, due to slips or trips.

Participants were further asked at each wave regarding falls causing injury with ‘Did you injure yourself seriously enough to need medical treatment?’ and this was used to inform the ‘Injurious Falls’ variable.

Participants were also asked about a history of fracture since the last interview (hip, wrist, vertebral and other fractures) at waves 2–5 and this was used to derive the ‘Fractures’ variable.

Other measures

Highest level of educational attainment was collected by self-report (primary, secondary or tertiary). The Cut Down, Angry, Guilty, Eye Opener (CAGE) scale was used to assess for excess alcohol intake [24]. Heart disease was defined as a self-reported history of heart attack, angina, congestive cardiac failure and/or arrhythmia. Antihypertensive use was defined as being prescribed at least one medication with ATC codes CO2, C03, C07, C08 or C09 after examination of medication list. Chronic disease burden was assessed by self-report of the following conditions: lung disease, eye problems, cancer, osteoporosis, liver disease, arthritis, incontinence, Parkinson’s disease and diabetes. Depressive symptoms were assessed with the Centre for Epidemiological Studies Depression Scale, with a score ≥ 16 indicating clinically significant symptoms [25]. Poor sleep was defined as responding “all the time” when asked how often a participant’s sleep was restless in the last week. Chronic pain was defined as answering ‘severe’ when asked about severity of persistent pain. Self-rated memory problems were defined as answering ‘fair’ or ‘poor’ when asked ‘how would you rate your day-to-day memory at the present time?’

Statistical analysis

Data were analysed using Stata version 14.1 (Statacorp, Texas).

Baseline characteristics by psychotropic medication use were reported descriptively with differences between groups analysed with chi-square tests and t tests.

Poisson regression models, reporting incidence rate ratios (IRR) with 95% confidence intervals, with future falls, unexplained falls, injurious falls and fractures as dependent variables, were used to assess the longitudinal association with psychotropic medications. Two models were used: Model 1 was adjusted only for follow-up time, whilst model 2 was adjusted for age, sex, educational attainment, alcohol excess, heart disease, antihypertensive medication use, chronic disease burden, depressive symptoms, poor sleep, chronic pain and memory problems. These covariates were chosen a priori based on their likelihood of modifying an association with future falls based on prior research studies [2631].

Ethics

The TILDA study was approved by the Faculty of Health Sciences Research Ethics Committee at Trinity College Dublin, and all participants gave informed written consent. All experimental procedures adhered to the Declaration of Helsinki. All assessments were carried out by trained research nurses.

Results

Over 2800 participants were included, and the median follow-up time was 8 years. Baseline characteristics of the study sample by psychotropic medication use are shown in Table 1. Only 18 participants were prescribed antipsychotics, so this cohort was not analysed separately.

Table 1.

Baseline characteristics by psychotropic medication use

Total sample
n = 2809
Antidepressants
n = 201
Benzodiazepines
n = 146
‘Z’ drugs
n = 109
Anticholinergic
n = 129
Mean age, years (95% CI) 72.9 (72.7–73.1) 73.4 (72.5–74.2) 74.2 (73.2–75.3) 74.1 (72.8–75.4) 73.5 (72.4–74.6)
Age bands
 65–75 years, n (%) 1,810 (64) 121 (60) 75 (51) 65 (60) 80 (62)
 75–85 years, n (%) 848 (30) 69 (34) 62 (42) 31 (28) 41 (32)
 ≥ 85 years, n (%) 151 (5) 11 (5) 9 (6) 13 (12) 8 (5)
Female sex, n (%) 1475 (53)* 125 (62)* 101 (69)** 72 (66)* 75 (58)
Educational attainment
 Primary/none, n (%) 1166 (42) 92 (46) 73 (50) 51 (47) 55 (43)
 Secondary, n (%) 947 (34) 66 (33) 46 (34) 28 (26) 46 (36)
 Tertiary, n (%) 696 (25) 43 (21) 24 (16) 30 (28) 28 (22)
CAGE score
 < 2, n (%) 2,257 (80) 148 (74) 111 (76) 86 (79) 98 (76)
 ≥ 2, n (%) 179 (6) 25 (12) 7 (5) 12 (11) 16 (12)
 Did not answer, n (%) 373 (13) 28 (14) 28 (19) 11 (10) 15 (12)
Heart disease, n (%)A 629 (22) 62 (31)* 51 (35)** 39 (36)* 41 (32)*
Antihypertensive, n (%)B 1,558 (55) 127 (63)* 79 (54) 76 (70)* 81 (63)
No. of chronic diseasesC
 None, n (%) 918 (33) 37 (18)** 27 (18)** 22 (20)** 18 (14)**
 1, n (%) 896 (32) 49 (24) 41 (28) 24 (22) 29 (22)
 2–3, n (%) 837 (30) 87 (43) 55 (38) 47 (43) 54 (42)
 ≥ 4, n (%) 158 (6) 28 (14) 23 (16) 16 (15) 28 (22)
Depressive symptomsD 226 (8) 34 (17)** 43 (29)** 21 (19)** 20 (16)*
Poor sleepE 196 (7) 26 (13)* 24 (17)** 16 (15)* 17 (13)*
Chronic painF 251 (9) 29 (14)* 33 (23)** 19 (17)* 20 (16)*
Memory problemsG 551 (20) 73 (36)** 51 (35)** 33 (30)* 41 (32)**

Chi-square tests used for categorical variables, t tests used for continuous variables

Antidepressants were identified with an ATC code of N06A; Benzodiazepines were identified with an ATC code of N05BA, N05CD and N03AE; Anticholinergics comprised antidepressants with anticholinergic effects (N06AA, N06AB05), medications acting on the bladder (G04BD), antipsychotics with anticholinergic effects (N05AA01, N05AA03, N05AB03, N05AB06, N05AC02, N05AH03, N05AH04), medications acting on the gastrointestinal system (A03), medications for Parkinson’s Disease (N04A), antihistamines (R06A) and others (M03BA03, M03BC01, N05CM05, N05BB01) and ‘Z’ drugs were coded as N05C

CAGE cut down, angry, guilty, eye opener scale, No. number

ADefined as self-report of heart attack, angina, congestive cardiac failure and/or arrhythmia

BPrescribed an antihypertensive medication with ATC code of CO2, C03, C07, C08 or C09

CChronic disease burden was assessed by self-report of the following conditions: lung disease, eye problems, cancer, osteoporosis, liver disease, arthritis, incontinence, Parkinson’s disease, and diabetes

DDefined as Centre for Epidemiological Studies Depression Scale ≥ 16

EPoor sleep defined as reporting restless sleep at least 5 of the last 7 days

FChronic pain defined as reporting severe chronic pain; G memory problems defined a self-report of memory as fair or poor

‘*’ denotes p < 0.05; ‘**’ denotes p < 0.001

The mean age of the sample at baseline was almost 73 years and 15% (423/2809) were taking at least one psychotropic medication. Participants prescribed psychotropic medication were more likely to be female and had a higher burden of heart disease, chronic illness and depressive symptoms.

Over half (1548/2809, 55%) of participants had a fall during follow-up, with one-third (904/2809, 32%) reporting an injurious fall, over one-fifth (614/2809, 22%) reporting an unexplained fall and almost one-fifth (520/2809, 19%) reporting a fracture. Incidence of falls and fracture at each Wave is shown in Fig. 1.

Fig. 1.

Fig. 1

Incidence of falls (total, injurious and unexplained) and fracture during follow-up. At Waves 2–5, participants were asked ‘Have you had any falls since the last interview?’ This was used to derive ‘Total Falls’; Injurious falls were those causing an injury significant enough to require medical attention; Unexplained falls were those not due to a slip or trip and with no apparent cause, collected by self-report; Fracture is hip, wrist, vertebral or other fracture, by self-report

Psychotropic medication and falls

Over 10% (286/2809) of the study sample was taking one psychotropic medication, i.e. either an antidepressant, benzodiazepine, ‘Z’ drug, anticholinergic or antipsychotic, whilst 5% (137/2809) was taking more than one agent.

Psychotropic medication use was independently associated with falls [IRR 1.15 (95% CI 1.00–1.31); p = 0.047], unexplained falls [IRR 1.46 (95% CI 1.20–1.78); p < 0.001] longitudinally.

As shown in Table 2 and Fig. 2, taking more than one psychotropic medication was more closely associated with injurious and unexplained falls, as well as future fracture (IRR 1.47 (95% CI 1.06–2.05); p 0.021) during follow-up. There was a graded relationship between psychotropic medication use and unexplained and injurious falls, as well as fracture.

Table 2.

Poisson regression models reporting incidence rate ratios with falls/fracture as dependent variables

Falls Injurious falls Unexplained falls Fracture
Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted
Any Psych

IRR 1.30 (1.14, 1.48)

p < 0.001

IRR 1.15 (1.00, 1.31)

p = 0.047

IRR 1.34 (1.13, 1.58)

p 0.001

IRR 1.10 (0.92, 1.31)

p 0.288

IRR 1.85 (1.54, 2.23)

p < 0.001

IRR 1.46 (1.20, 1.78)

p < 0.001

IRR 1.53 (1.24, 1.90)

p < 0.001

IRR 1.25 (0.99, 1.56)

p 0.056

≥ 2 Psych

IRR 1.38 (1.13, 1.70)

p 0.002

IRR 1.21 (0.98, 1.50)

p 0.070

IRR 1.59 (1.24, 2.05)

p < 0.001

IRR 1.30 (1.00, 1.68)

p 0.049

IRR 2.13 (1.62, 2.80)

p < 0.001

IRR 1.64 (1.23, 2.19)

p 0.001

IRR 1.80 (1.31, 2.48)

p < 0.001

IRR 1.47 (1.06, 2.05)

p 0.021

Benzo

IRR 1.21 (0.98, 1.49)

p 0.082

IRR 1.05 (0.84, 1.30)

p 0.694

IRR 1.30 (0.99, 1.70)

p 0.059

IRR 1.04 (0.79, 1.38)

p 0.775

IRR 1.60 (1.18, 2.15)

p 0.002

IRR 1.19 (0.86, 1.62)

p 0.284

IRR 1.43 (1.01, 2.02)

p 0.041

IRR 1.08 (0.75, 1.55)

p 0.680

Antidep

IRR 1.34 (1.13, 1.59)

p 0.001

IRR 1.20 (1.00, 1.42)

p = 0.044

IRR 1.44 (1.16, 1.79)

p < 0.001

IRR 1.22 (0.98, 1.53)

p 0.079

IRR 2.12 (1.69, 2.65)

p < 0.001

IRR 1.71 (1.35, 2.16)

p < 0.001

IRR 1.54 (1.16, 2.03)

p 0.003

IRR 1.31 (0.98, 1.75)

p 0.067

‘Z’ drugs

IRR 1.31 (1.04, 1.65)

p 0.022

IRR 1.15 (0.91, 1.45)

p 0.251

IRR 1.33 (0.98, 1.80)

p 0.064

IRR 1.09 (0.80,1.48)

p 0.576

IRR 1.27 (0.88, 1.85)

p 0.208

IRR 0.99 (0.68, 1.45)

p 0.967

IRR 1.48 (1.01, 2.17)

p 0.043

IRR 1.20 (0.81, 1.76)

p 0.367

Antichol

IRR 1.26 (1.02, 1.56)

p 0.032

IRR 1.14 (0.91, 1.41)

p 0.255

IRR 1.31 (1.00, 1.72)

p 0.054

IRR 1.13 (0.85, 1.49)

p 0.402

IRR 1.90 (1.43, 2.52)

p < 0.001

IRR 1.53 (1.14, 2.05)

p 0.004

IRR 1.50 (1.07, 2.12)

p 0.020

IRR 1.31 (0.92, 1.87)

p 0.128

Antidepressants were identified with an ATC code of N06A; Benzodiazepines were identified with an ATC code of N05BA, N05CD and N03AE; Anticholinergics comprised antidepressants with anticholinergic effects (N06AA, N06AB05), medications acting on the bladder (G04BD), antipsychotics with anticholinergic effects (N05AA01, N05AA03, N05AB03, N05AB06, N05AC02, N05AH03, N05AH04), medications acting on the gastrointestinal system (A03), medications for Parkinson’s Disease (N04A), antihistamines (R06A) and others (M03BA03, M03BC01, N05CM05, N05BB01) and ‘Z’ drugs were coded as N05C

Fracture comprises hip, wrist, vertebral and other fractures

Poisson regression models, reporting incidence rate ratios and 95% confidence intervals, with falls, unexplained falls, injurious falls, and fractures during follow-up as dependent variables, were used to assess the longitudinal association with psychotropic medications. Two models were used: Model 1 was adjusted only for follow-up time, whilst model 2 was adjusted for age, sex, educational attainment, alcohol excess, heart disease, chronic disease burden, depressive symptoms, poor sleep, chronic pain and self-rated memory problems

Psych psychotropic medication, Benzo benzodiazepine, Antidep antidepressant, Antichol anticholinergic medication, IRR incidence rate ratio

Fig. 2.

Fig. 2

Incidence rate ratios with 95% confidence intervals for association between psychotropic medication use and future falls (total/unexplained) and fracture. Data presented are incidence rate ratios with 95% confidence intervals from fully adjusted models with Injurious and Unexplained falls and Fractures as dependant variables. Models were adjusted for age, sex, educational attainment, alcohol excess, heart disease, chronic disease burden, depressive symptoms, poor sleep, chronic pain, and self-rated memory problems. Fracture comprises hip, wrist, vertebral and other fractures. Antidepressants were identified with an ATC code of N06A; benzodiazepines were identified with an ATC code of N05BA, N05CD and N03AE; anticholinergics comprised antidepressants with anticholinergic effects (N06AA, N06AB05), medications acting on the bladder (G04BD), antipsychotics with anticholinergic effects (N05AA01, N05AA03, N05AB03, N05AB06, N05AC02, N05AH03, N05AH04), medications acting on the gastrointestinal system (A03), medications for Parkinson’s Disease (N04A), antihistamines (R06A) and others (M03BA03, M03BC01, N05CM05, N05BB01) and ‘Z’ drugs were coded as N05C

Antidepressants

Antidepressant use was independently associated with future falls [IRR 1.20 (95% CI 1.00–1.42); p = 0.044] and unexplained falls [IRR 1.64 (95% CI 1.23–2.19); p = 0.001]. See Table 2 and Fig. 1.

Benzodiazepines

Benzodiazepine use was not associated with falls, injurious falls, unexplained falls or fracture in fully adjusted models. See Table 2 and Fig. 2.

‘Z’ drugs

The use of ‘Z’ drugs was not associated with falls, injurious falls, unexplained falls or fracture in fully adjusted models. See Table 2 and Fig. 2.

Anticholinergics

Anticholinergic use was associated with an increased likelihood of unexplained falls [IRR 1.50 (95% CI 1.14–2.05); p = 0.004] in fully adjusted models. The association with injurious falls was non-significant, as was the association with future fracture.

Discussion

This study examines the association between psychotropic medication use and future falls and fracture in a cohort of community-dwelling people aged ≥ 65 years at 8-year follow-up. We have shown that taking a single psychotropic medication is independently associated with an almost 50% higher likelihood of unexplained falls, whilst taking more than one psychotropic medication is associated with a 64% increased risk of unexplained falls in fully adjusted models. Psychotropic medication use was associated with falls, unexplained falls and incident fracture, with a closer association with taking more than one psychotropic medication for each of these outcomes.

Prior studies have shown that psychotropic medications increase the risk of falls [20, 21] and fracture [32]. This study adds to the existing evidence base however by robustly controlling for covariates including heart disease and chronic disease burden, over a prolonged follow-up period of 8 years. Further, we also examine the risk associated specifically with unexplained falls, which are more often underpinned by orthostatic blood pressure changes and heart rhythm disturbance, both of which exacerbated by psychotropic medications.

When examined by classes of psychotropic medication, we found that in fully adjusted models, antidepressants and anticholinergic medication were associated with unexplained falls. Perhaps surprisingly benzodiazepine and z-drug use was not associated with falls or fracture in fully adjusted models.

Whilst depression has been shown to increase falls risk amongst older people [28], the strong association between antidepressant use and unexplained falls persisted after adjustment for depressive symptoms burden in this study. TILDA data have previously shown the link between antidepressant use and falls at 4-year follow-up—yet did not examine the longitudinal relationship with fracture [33]. Further, data from TILDA have also demonstrated that antidepressant users had doubled the risk of orthostatic hypotension compared to non-users [34] whilst delayed postural BP stabilisation related to antidepressant use has also been delineated in a cohort of patients with Alzheimer’s disease [35]. Antidepressant use may also accelerate post-menopausal bone loss, contributing to risk of fracture [36].

Our findings regarding ‘Z’ drug are in line with a recent meta-analysis of 14 studies which showed a trend towards increased falls only [37]. Consistent with our findings, anticholinergic medications have been consistently linked with incident falls in later life [38, 39], and we have also demonstrated a strong relationship with unexplained falls in this study, likely also related to effects on cognition, cardiovascular reflexes and gait.

Whilst cross-sectionally benzodiazepines are associated with falls amongst the TILDA cohort [40], we found no significant longitudinal relationship with falls, including injurious and unexplained falls, and fracture in this study. This contrasts with findings from systemic reviews and meta-analyses, which have shown an increased falls risk related to benzodiazepine use [20, 41], but it is important to note that many studies to date have not adjusted for the full spectrum of competing covariates, especially when we consider that benzodiazepines are more often prescribed for people with pre-existing risk factors for fall [42].

There are some limitations of this study which should be noted. Falls outcomes and several covariates (including cardiovascular disease, educational attainment, chronic disease burden, etc.) were by self-report only and could therefore be subject to recall bias, which could impact findings. Further, neuroleptic medication use was captured at baseline, but changes in medication use over time were not captured in the analysis. We could not perform any meaningful analysis on participants taking antipsychotic medications due to the small numbers involved. We also did not have any information on compliance with medications, but data was collected by manually checking participant medication lists. Whilst we have adjusted for a wide range of covariates in this study, the complex and often multifactorial nature of falls amongst older people is such that there remains a possibility of residual confounding that we have not adjusted for. The strengths of this study include the large, well-described population-representative sample of older people, with robust 8-year follow-up. To our knowledge, this is the first study to examine the relationship between psychotropic medication use and unexplained falls amongst older people.

Our study suggests that withdrawal of psychotropic medication use may reduce the risk of falls. This is supported by intervention studies involving small participant numbers [43, 44]. Tool such as STOPPFall, developed to aid de-prescribing of medications that increase falls risk, may help as it involves mostly psychotropic medications [45]. However, de-prescribing psychotropic medications can be challenging in practice even when supported by tools such as this [46]. For example, there is lack of consensus as to when antidepressants should be discontinued in patients with stable late-life depression [47]. Additionally, even though withdrawing of benzodiazepines in older people does not generally lead to significant sleep disturbance [48], it can also be complex and is considered arduous and time-intensive by physicians [49, 50].

In conclusion, we have shown that psychotropic medication use amongst community-dwelling older people significantly increases the likelihood of unexplained falls, including those causing fracture. As part of a comprehensive multifactorial falls assessment, described in recently published World Falls Guidelines [51], de-prescribing of psychotropic medications to reduce falls risk, particularly amongst older people taking more than one agent, should be considered where appropriate and feasible and can be supported by structured de-prescribing tools. If psychotropic medications cannot be discontinued, close attention should be paid to orthostatic BP and ECG monitoring, as well as review of other co-prescribed culprit medications. Further work is required however, in establishing how and when psychotropic medications can be dose-reduced or discontinued.

Funding

Open Access funding provided by the IReL Consortium.

Declarations

Conflict of interest

The authors have no conflicts of interest to declare.

Ethical approval

Each wave of the TILDA study was approved by the Faculty of Health Sciences Research Ethics Committee at Trinity College Dublin. All experimental procedures adhered to the Declaration of Helsinki.

Informed consent

All participants gave informed written consent.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  • 1.Jónsdóttir HL, Ruthig JC. A longitudinal study of the negative impact of falls on health, well-being, and survival in later life: the protective role of perceived control. Aging Ment Health. 2021;25(4):742–748. doi: 10.1080/13607863.2020.1725736. [DOI] [PubMed] [Google Scholar]
  • 2.Newgard CD, Lin A, Caughey AB, McConnell KJ, Bulger E, Malveau S, Staudenmayer K, Griffiths D, Eckstrom E. Falls in older adults requiring emergency services: mortality, use of healthcare resources, and prognostication to one year. West J Emerg Med. 2022;23(3):375–385. doi: 10.5811/westjem.2021.11.54327. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Tinetti ME, Williams CS. Falls, injuries due to falls, and the risk of admission to a nursing home. N Engl J Med. 1997;337(18):1279–1284. doi: 10.1056/NEJM199710303371806. [DOI] [PubMed] [Google Scholar]
  • 4.Lindblad AJ, Clarke JA, Lu S. Antidepressants in the elderly. Can Fam Physician. 2019;65(5):340. [PMC free article] [PubMed] [Google Scholar]
  • 5.Johnson CF, Frei C, Downes N, McTaggart SA, Akram G. Benzodiazepine and z-hypnotic prescribing for older people in primary care: a cross-sectional population-based study. Br J Gen Pract. 2016;66(647):e410–e415. doi: 10.3399/bjgp16X685213. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Rhee TG, Choi YC, Ouellet GM, Ross JS. National prescribing trends for high-risk anticholinergic medications in older adults. J Am Geriatr Soc. 2018;66(7):1382–1387. doi: 10.1111/jgs.15357. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Alexopoulos GS, Streim J, Carpenter D, Docherty JP, Expert Consensus Panel for Using Antipsychotic Drugs in Older Patients (2004) Using antipsychotic agents in older patients. J Clin Psychiatry 65(Suppl 2):5–99 (discussion 100–102; quiz 103–4) [PubMed]
  • 8.Dealberto MJ, Mcavay GJ, Seeman T, Berkman L. Psychotropic drug use and cognitive decline among older men and women. Int J Geriatr Psychiatry. 1997;12(5):567–574. doi: 10.1002/(SICI)1099-1166(199705)12:5<567::AID-GPS552>3.0.CO;2-V. [DOI] [PubMed] [Google Scholar]
  • 9.Brooks JO, Hoblyn JC. Neurocognitive costs and benefits of psychotropic medications in older adults. J Geriatr Psychiatry Neurol. 2007;20(4):199–214. doi: 10.1177/0891988707308803. [DOI] [PubMed] [Google Scholar]
  • 10.Rivasi G, Rafanelli M, Mossello E, Brignole M, Ungar A. Drug-Related Orthostatic Hypotension: Beyond Anti-Hypertensive Medications. Drugs Aging. 2020;37(10):725–738. doi: 10.1007/s40266-020-00796-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Klotz U. Pharmacokinetics and drug metabolism in the elderly. Drug Metab Rev. 2009;41(2):67–76. doi: 10.1080/03602530902722679. [DOI] [PubMed] [Google Scholar]
  • 12.Prudent M, Dramé M, Jolly D, Trenque T, Parjoie R, Mahmoudi R, Lang PO, Somme D, Boyer F, Lanièce I, Gauvain JB, Blanchard F, Novella JL. Potentially inappropriate use of psychotropic medications in hospitalized elderly patients in France: cross-sectional analysis of the prospective, multicentre SAFEs cohort. Drugs Aging. 2008;25(11):933–946. doi: 10.2165/0002512-200825110-00004. [DOI] [PubMed] [Google Scholar]
  • 13.Arnold I, Straube K, Himmel W, Heinemann S, Weiss V, Heyden L, Hummers-Pradier E, Nau R. High prevalence of prescription of psychotropic drugs for older patients in a general hospital. BMC Pharmacol Toxicol. 2017;18(1):76. doi: 10.1186/s40360-017-0183-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Walsh KA, O'Regan NA, Byrne S, Browne J, Meagher DJ, Timmons S. Patterns of psychotropic prescribing and polypharmacy in older hospitalized patients in Ireland: the influence of dementia on prescribing. Int Psychogeriatr. 2016;28(11):1807–1820. doi: 10.1017/S1041610216001307. [DOI] [PubMed] [Google Scholar]
  • 15.Rafanelli M, Mossello E, Testa GD, Ungar A. Unexplained falls in the elderly. Minerva Med. 2022;113(2):263–272. doi: 10.23736/S0026-4806.21.07749-1. [DOI] [PubMed] [Google Scholar]
  • 16.Jusmanova K, Rice C, Bourke R, Lavan A, McMahon CG, Cunningham C, Kenny RA, Briggs R. Impact of a specialist service in the Emergency Department on admission, length of stay and readmission of patients presenting with falls, syncope and dizziness. QJM. 2021;114(1):32–38. doi: 10.1093/qjmed/hcaa261. [DOI] [PubMed] [Google Scholar]
  • 17.Bhangu J, Hall P, Devaney N, Bennett K, Carroll L, Kenny RA, McMahon CG. The prevalence of unexplained falls and syncope in older adults presenting to an Irish urban emergency department. Eur J Emerg Med. 2019;26(2):100–104. doi: 10.1097/MEJ.0000000000000548. [DOI] [PubMed] [Google Scholar]
  • 18.Ungar A, Mussi C, Ceccofiglio A, Bellelli G, Nicosia F, Bo M, Riccio D, Martone AM, Guadagno L, Noro G, Ghidoni G, Rafanelli M, Marchionni N, Abete P. Etiology of syncope and unexplained falls in elderly adults with dementia: syncope and dementia (SYD) study. J Am Geriatr Soc. 2016;64(8):1567–1573. doi: 10.1111/jgs.14225. [DOI] [PubMed] [Google Scholar]
  • 19.Bhangu J, McMahon CG, Hall P, Bennett K, Rice C, Crean P, Sutton R, Kenny RA. Long-term cardiac monitoring in older adults with unexplained falls and syncope. Heart. 2016;102(9):681–686. doi: 10.1136/heartjnl-2015-308706. [DOI] [PubMed] [Google Scholar]
  • 20.Bloch F, Thibaud M, Dugué B, Brèque C, Rigaud AS, Kemoun G. Psychotropic drugs and falls in the elderly people: updated literature review and meta-analysis. J Aging Health. 2011;23(2):329–346. doi: 10.1177/0898264310381277. [DOI] [PubMed] [Google Scholar]
  • 21.Seppala LJ, Wermelink AMAT, de Vries M, Ploegmakers KJ, van de Glind EMM, Daams JG, van der Velde N; EUGMS task and Finish group on fall-risk-increasing drugs (2018) Fall-risk-increasing drugs: a systematic review and meta-analysis: II. Psychotropics. J Am Med Dir Assoc 19(4):371.e11–371.e17 [DOI] [PubMed]
  • 22.Donoghue OA, McGarrigle CA, Foley M, Fagan A, Meaney J, Kenny RA. Cohort profile update: The Irish Longitudinal Study on Ageing (TILDA) Int J Epidemiol. 2018;47(5):1398–1398l. doi: 10.1093/ije/dyy163. [DOI] [PubMed] [Google Scholar]
  • 23.Malaz B, Campbell N, Munger S, Maidment I, Fox C. Impact of anticholinergics on the aging brain: a review and practical application. Aging Health. 2008;4(3):311–320. doi: 10.2217/1745509X.4.3.311. [DOI] [Google Scholar]
  • 24.Bush B, Shaw S, Cleary P, Delbanco TL, Aronson MD. Screening for alcohol abuse using the CAGE questionnaire. Am J Med. 1987;82(2):231–235. doi: 10.1016/0002-9343(87)90061-1. [DOI] [PubMed] [Google Scholar]
  • 25.Lewinsohn PM, Seeley JR, Roberts RE, Allen NB. Center for Epidemiologic Studies Depression Scale (CES-D) as a screening instrument for depression among community-residing older adults. Psychol Aging. 1997;12(2):277–287. doi: 10.1037/0882-7974.12.2.277. [DOI] [PubMed] [Google Scholar]
  • 26.Mukamal KJ, Mittleman MA, Longstreth WT, Jr, Newman AB, Fried LP, Siscovick DS. Self-reported alcohol consumption and falls in older adults: cross-sectional and longitudinal analyses of the cardiovascular health study. J Am Geriatr Soc. 2004;52(7):1174–1179. doi: 10.1111/j.1532-5415.2004.52318.x. [DOI] [PubMed] [Google Scholar]
  • 27.Immonen M, Haapea M, Similä H, Enwald H, Keränen N, Kangas M, Jämsä T, Korpelainen R. Association between chronic diseases and falls among a sample of older people in Finland. BMC Geriatr. 2020;20(1):225. doi: 10.1186/s12877-020-01621-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Briggs R, Kennelly SP, Kenny RA. Does baseline depression increase the risk of unexplained and accidental falls in a cohort of community-dwelling older people? Data from The Irish Longitudinal Study on Ageing (TILDA) Int J Geriatr Psychiatry. 2018;33(2):e205–e211. doi: 10.1002/gps.4770. [DOI] [PubMed] [Google Scholar]
  • 29.Honda H, Ashizawa R, Take K, Hirase T, Arizono S, Yoshimoto Y (2022) Effect of chronic pain on the occurrence of falls in older adults with disabilities: a prospective cohort study. Physiother Theory Pract 1–9 [DOI] [PubMed]
  • 30.Latimer Hill E, Cumming RG, Lewis R, Carrington S, Le Couteur DG. Sleep disturbances and falls in older people. J Gerontol A Biol Sci Med Sci. 2007;62(1):62–66. doi: 10.1093/gerona/62.1.62. [DOI] [PubMed] [Google Scholar]
  • 31.Donnell DO, Romero-Ortuno R, Kennelly SP, O'Neill D, Donoghue PO, Lavan A, Cunningham C, McElwaine P, Kenny RA, Briggs R (2023) The 'Bermuda Triangle' of orthostatic hypotension, cognitive impairment and reduced mobility: prospective associations with falls and fractures in The Irish Longitudinal Study on Ageing. Age Ageing 52(2):afad005 [DOI] [PMC free article] [PubMed]
  • 32.Takkouche B, Montes-Martínez A, Gill SS, Etminan M. Psychotropic medications and the risk of fracture: a meta-analysis. Drug Saf. 2007;30(2):171–184. doi: 10.2165/00002018-200730020-00006. [DOI] [PubMed] [Google Scholar]
  • 33.Donoghue OA, Briggs R, Moriarty F, Kenny RA. Association of antidepressants with recurrent, injurious and unexplained falls is not explained by reduced gait speed. Am J Geriatr Psychiatry. 2020;28(3):274–284. doi: 10.1016/j.jagp.2019.10.004. [DOI] [PubMed] [Google Scholar]
  • 34.Briggs R, Carey D, McNicholas T, Claffey P, Nolan H, Kennelly SP, Kenny RA. The association between antidepressant use and orthostatic hypotension in older people: a matched cohort study. J Am Soc Hypertens. 2018;12(8):597–604.e1. doi: 10.1016/j.jash.2018.06.002. [DOI] [PubMed] [Google Scholar]
  • 35.Dyer AH, Murphy C, Briggs R, Lawlor B, Kennelly SP, NILVAD Study Group (2020) Antidepressant use and orthostatic hypotension in older adults living with mild-to-moderate Alzheimer disease. Int J Geriatr Psychiatry 35(11):1367–1375 [DOI] [PubMed]
  • 36.Rauma PH, Honkanen RJ, Williams LJ, Tuppurainen MT, Kröger HP, Koivumaa-Honkanen H. Effects of antidepressants on postmenopausal bone loss—a 5-year longitudinal study from the OSTPRE cohort. Bone. 2016;89:25–31. doi: 10.1016/j.bone.2016.05.003. [DOI] [PubMed] [Google Scholar]
  • 37.Treves N, Perlman A, Kolenberg Geron L, Asaly A, Matok I. Z-drugs and risk for falls and fractures in older adults—a systematic review and meta-analysis. Age Ageing. 2018;47(2):201–208. doi: 10.1093/ageing/afx167. [DOI] [PubMed] [Google Scholar]
  • 38.Stewart C, Taylor-Rowan M, Soiza RL, Quinn TJ, Loke YK, Myint PK. Anticholinergic burden measures and older people's falls risk: a systematic prognostic review. Ther Adv Drug Saf. 2021;12:20420986211016645. doi: 10.1177/20420986211016645. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Green AR, Reifler LM, Bayliss EA, Weffald LA, Boyd CM. Drugs contributing to anticholinergic burden and risk of fall or fall-related injury among older adults with mild cognitive impairment, dementia and multiple chronic conditions: a retrospective cohort study. Drugs Aging. 2019;36(3):289–297. doi: 10.1007/s40266-018-00630-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Marron L, Segurado R, Kenny RA, McNicholas T. The association between benzodiazepine use and falls, and the impact of sleep quality on this association: data from the TILDA study. QJM. 2020;113(1):31–36. doi: 10.1093/qjmed/hcz217. [DOI] [PubMed] [Google Scholar]
  • 41.Díaz-Gutiérrez MJ, Martínez-Cengotitabengoa M, Sáez de Adana E, Cano AI, Martínez-Cengotitabengoa MT, Besga A, Segarra R, González-Pinto A (2017) Relationship between the use of benzodiazepines and falls in older adults: a systematic review. Maturitas 101:17–22 [DOI] [PubMed]
  • 42.Bartlett G, Abrahamowicz M, Grad R, Sylvestre MP, Tamblyn R. Association between risk factors for injurious falls and new benzodiazepine prescribing in elderly persons. BMC Fam Pract. 2009;10:1. doi: 10.1186/1471-2296-10-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Campbell AJ, Robertson MC, Gardner MM, Norton RN, Buchner DM. Psychotropic medication withdrawal and a home-based exercise program to prevent falls: a randomized, controlled trial. J Am Geriatr Soc. 1999;47(7):850–853. doi: 10.1111/j.1532-5415.1999.tb03843.x. [DOI] [PubMed] [Google Scholar]
  • 44.van der Velde N, Stricker BH, Pols HA, van der Cammen TJ. Risk of falls after withdrawal of fall-risk-increasing drugs: a prospective cohort study. Br J Clin Pharmacol. 2007;63(2):232–237. doi: 10.1111/j.1365-2125.2006.02736.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Seppala LJ, Petrovic M, Ryg J, Bahat G, Topinkova E, Szczerbińska K, van der Cammen TJM, Hartikainen S, Ilhan B, Landi F, Morrissey Y, Mair A, Gutiérrez-Valencia M, Emmelot-Vonk MH, Mora MÁC, Denkinger M, Crome P, Jackson SHD, Correa-Pérez A, Knol W, Soulis G, Gudmundsson A, Ziere G, Wehling M, O'Mahony D, Cherubini A, van der Velde N. STOPPFall (Screening Tool of Older Persons Prescriptions in older adults with high fall risk): a Delphi study by the EuGMS Task and Finish Group on Fall-Risk-Increasing Drugs. Age Ageing. 2021;50(4):1189–1199. doi: 10.1093/ageing/afaa249. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.van Poelgeest EP, Pronk AC, Rhebergen D, van der Velde N. Depression, antidepressants and fall risk: therapeutic dilemmas-a clinical review. Eur Geriatr Med. 2021;12(3):585–596. doi: 10.1007/s41999-021-00475-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Andreescu C, Reynolds CF., III Late-life depression: evidence-based treatment and promising new directions for research and clinical practice. Psychiatr Clin N Am. 2011;34(2):335–355. doi: 10.1016/j.psc.2011.02.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Furukawa TA. Withdrawal of benzodiazepines in elderly long term users does not produce significant adverse effects in the short term. Evid Based Ment Health. 2004;7(2):46. doi: 10.1136/ebmh.7.2.46. [DOI] [PubMed] [Google Scholar]
  • 49.Iliffe S, Curran HV, Collins R, Yuen Kee SC, Fletcher S, Woods B. Attitudes to long-term use of benzodiazepine hypnotics by older people in general practice: findings from interviews with service users and providers. Aging Ment Health. 2004;8(3):242–248. doi: 10.1080/13607860410001669778. [DOI] [PubMed] [Google Scholar]
  • 50.Cook JM, Biyanova T, Thompson R, Coyne JC. Older primary care patients' willingness to consider discontinuation of chronic benzodiazepines. Gen Hosp Psychiatry. 2007;29(5):396–401. doi: 10.1016/j.genhosppsych.2007.07.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Montero-Odasso M, van der Velde N, Martin FC, Petrovic M, Tan MP, Ryg J, Aguilar-Navarro S, Alexander NB, Becker C, Blain H, Bourke R, Cameron ID, Camicioli R, Clemson L, Close J, Delbaere K, Duan L, Duque G, Dyer SM, Freiberger E, Ganz DA, Gómez F, Hausdorff JM, Hogan DB, Hunter SMW, Jauregui JR, Kamkar N, Kenny RA, Lamb SE, Latham NK, Lipsitz LA, Liu-Ambrose T, Logan P, Lord SR, Mallet L, Marsh D, Milisen K, Moctezuma-Gallegos R, Morris ME, Nieuwboer A, Perracini MR, Pieruccini-Faria F, Pighills A, Said C, Sejdic E, Sherrington C, Skelton DA, Dsouza S, Speechley M, Stark S, Todd C, Troen BR, van der Cammen T, Verghese J, Vlaeyen E, Watt JA, Masud T (2022) Task force on global guidelines for falls in older adults. World guidelines for falls prevention and management for older adults: a global initiative. Age Ageing 51(9):afac205

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