Skip to content

Advertisement

You're viewing the new version of our site. Please leave us feedback.

Learn more

BMC Geriatrics

Open Access
Open Peer Review

This article has Open Peer Review reports available.

How does Open Peer Review work?

Anticholinergic medication use and falls in postmenopausal women: findings from the women’s health initiative cohort study

  • Zachary A. Marcum1Email author,
  • Heidi S. Wirtz2,
  • Mary Pettinger3,
  • Andrea Z. LaCroix4,
  • Ryan Carnahan5,
  • Jane A. Cauley6,
  • Jennifer W. Bea7 and
  • Shelly L. Gray1
BMC GeriatricsBMC series – open, inclusive and trusted201616:76

https://doi.org/10.1186/s12877-016-0251-0

Received: 4 December 2015

Accepted: 24 March 2016

Published: 2 April 2016

Abstract

Background

Results from studies assessing the association between anticholinergic use and falls are mixed, and prior studies are limited in their ability to control for important potential confounders. Thus, we sought to examine the association between anticholinergic medication use, including over-the-counter medications, and recurrent falls in community-dwelling older women.

Methods

We analyzed data from a prospective cohort study of women aged 65 to 79 years from the Women’s Health Initiative Observational Study and Clinical Trials. Women were recruited between 1993 and 1998, and analyses included 61,451 women with complete information. Medications with moderate or strong anticholinergic effects were ascertained directly from drug containers during face-to-face interviews. The main outcome measure was recurrent falls (≥2 falls in previous year), which was determined from self-report within 1.5 years subsequent to the medication assessment.

Results

At baseline, 11.3 % were using an anticholinergic medication, of which antihistamines (commonly available over-the-counter) were the most common medication class (received by 45.2 % of individuals on anticholinergic medication). Using multivariable GEE models and controlling for potential confounders, the adjusted odds ratio for anticholinergic medication use was 1.51 (95 % CI, 1.43–1.60) for recurrent falls. Participants using multiple anticholinergic medications had a 100 % increase in likelihood of recurrent falls (adjusted odds ratio 2.00, 95 % CI 1.73–2.32). Results were robust to sensitivity analysis.

Conclusions

Anticholinergic medication use was associated with increased risk for recurrent falls. Our findings reinforce judicious use of anticholinergic medications in older women. Public health efforts should emphasize educating older women regarding the risk of using over-the-counter anticholinergics, such as first-generation antihistamines.

Keywords

AnticholinergicFallsCommunity dwellingOlder adults

Background

Falls in older adults are significant public health concerns [1]. Approximately one-third of community-dwelling older adults fall at least once each year, of whom nearly 50 % have recurrent falls [2, 3]. Recurrent falls (as opposed to single falls) may be more clinically important as they may increase the risk of physician visits, functional status decline, nursing home admission, and death [2]. Moreover, the etiology of falls is multifactorial, including both extrinsic (e.g., environmental) and intrinsic (e.g., muscle weakness) risk factors. Importantly, identifying potentially modifiable risk factors for falls is vital in order to reduce the risk of falls in older adults.

Several medication classes, many of which have central nervous system effects, have been associated with increased risk for falls and fractures [4]. Medications with anticholinergic effects have many adverse effects that could contribute to falls risk, including blurred vision, sedation, and cognitive impairment [5, 6]. The prevalence of anticholinergic medication use is common with 13–25 % of community-dwelling older adults taking at least one agent [79]. Highly anticholinergic medications are considered as potentially inappropriate for use in older adults [10]. Moreover, nonpharmacological strategies or alternative medications without anticholinergic effects are often available to treat these specific conditions (e.g., sleep disturbances, urinary incontinence); therefore, reducing anticholinergic polypharmacy is feasible.

The prospective cohort studies assessing the association between anticholinergic use and falls in community residing older adults have found mixed results [1114]. One possible explanation for these mixed results may be due to differences in study designs and in the measurement of falls (e.g., self-reported vs. claims measurement, single vs. recurrent falls). Moreover, anticholinergic use has been reported to be associated with falls in high-risk populations of psychiatric inpatients, patients after traumatic brain injury, and residential care facility residents [1517]. However, much of the research on anticholinergic use and fall risk among older adults has been limited by use of a cross-sectional design [18] and use of highly select samples that may not be representative to the majority of older adults [1517]. In addition, most prior research on this topic has been conducted in non-US populations. This is important because in the US over-the-counter medication data are not available in administrative pharmacy claims, resulting in limited prior literature taking this type of medication exposure into account. Thus, additional studies are warranted in large samples to understand potential risks of these medications. The objective of this study was to examine the association between anticholinergic medication use, including over-the-counter medications, and recurrent falls in community-dwelling women.

Methods

Study population

The Women’s Health Initiative (WHI) studies included three Clinical Trials (CT) and an Observational Study (OS) that enrolled participants between 1993 and 1998 from 40 clinical centers across the United States. Study methods have been described in detail elsewhere [19]. This analysis included postmenopausal women aged 65–79 years upon study entry; 43,612 women from the Observational Study and 24,427 from the Clinical Trials. We excluded women without a falls assessment within 1.5 years of their baseline medication inventory (n = 4033) to ensure the timeliness of the falls relative to medication use, leaving a total sample of 67,006. Informed consent was obtained, and all protocols were approved by the respective institutional review boards at participating institutions.

Outcome ascertainment: recurrent falls

Fall history was obtained by asking participants to report the number of times they fell and landed on the floor or ground in the past 12 months. Self-reported falls were ascertained annually for women in the OS and every 6 months for women in the CT by use of standardized questionnaires. We defined a participant as having recurrent falls if she reported falling two or more times during the previous 12-month period [20, 21]. This method of fall recall (in the previous 12 months) has been shown to be highly specific (91–95 %) in comparison with that reported using more frequent assessments [22]. All participants (n = 67,006) had a baseline falls history collected.

Anticholinergic medication use

Women were asked about current prescription and over-the-counter medications that were taken in the past 2 weeks at the baseline and year 3 clinic visits. The medication information was obtained directly from the medication containers and entered into the WHI database. Each medication was assigned a drug code using Medispan software (First DataBank, Inc., San Bruno, California). Women were also asked how long they had used each medication. No information on dose was collected.

We adapted the Anticholinergic Drug Scale and focused on medications with moderate to strong anticholinergic activity (see Table 1) [23, 24]. This list was updated by consensus process by study investigators with expertise in pharmacology (co-authors H.W., S.G., R.C.) by using new information (serum anticholinergic activity, receptor binding affinity) and reviewing additional anticholinergic scales [25, 26].
Table 1

Frequency of Anticholinergic Medications at Baseline according to Therapeutic Class

Drug Class

Medicationa

N

Antihistamines

  
 

Diphenhydramine

5411

 

Chlorpheniramine

1408

 

Hydroxyzine

742

 

Doxylamine

219

 

Clemastine

153

 

Dexchlorpheniramine

81

 

Promethazine

80

 

Cyproheptadine

57

Antidepressants

  
 

Amitriptyline

2585

 

Paroxetine

1352

 

Nortriptyline

760

 

Imipramine

667

 

Doxepin

505

 

Desipramine

173

Gastrointestinal antispasmodics

  
 

Anticholinergic combinations

 
 

Hyoscyamine

1066

 

Dicyclomine

516

Urinary antimuscarinics

  
 

Oxybutynin

983

 

Flavoxate

47

Antivertigo/antiemetics

  
 

Meclizine

924

 

Dimenhydrinate

69

 

Scopolamine

248

Skeletal Muscle Relaxants

  
 

Cyclobenzaprine

772

 

Orphenadrine

118

Antipsychotics

  
 

Perphenazine

53

 

Trifluoperazine

40

 

Thioridazine

38

Antiparkinson agents

  
 

Benztropine

36

Other

  
 

Disopyramide

139

aOnly medications with a frequency of 0.2 % or higher were listed

Measurement of other covariates

Questionnaires were used to collect information on age, race and ethnicity, history of falls, self-reported health, smoking status, and physical activity from walking outside the home for more than 10 min without stopping (minutes per week). Alcohol consumption was estimated from the responses on the food-frequency questionnaire. Body mass index was calculated from measured height and weight (weight, kg/height, m2). Physical function was measured from the 10-item Rand Physical Function scale (>90 indicating higher function) [27].

Anticholinergics can be used for a variety of conditions. Therefore, to control for potential confounding by indication we measured self-reported of physician-diagnosed medical conditions for which anticholinergics may be used – urinary incontinence and Parkinson’s disease. Other medical conditions measured to address potential confounding by indication included insomnia and depressive symptoms. The 5-item WHI Insomnia Rating Scale was used for perceived insomnia symptoms, including sleep latency, sleep maintenance insomnia, early morning awakening, and sleep quality [28]. For each question, the score ranges from 0 to 4, and the summary score ranges from 0 to 20, with higher scores indicate greater insomnia. We classified the score for insomnia into four categories (0–3, 4–6, 7–10, and ≥11) consistent with a previous study [28]. The Centers for Epidemiologic Studies-Depression 6-item questionnaire was used to assess depressive symptoms (Burnham score >0.06) [29, 30].

In addition, diabetes was defined as presence of oral hypoglycemic medication or insulin, and Alzheimer Disease was measured via self-report of physician-diagnosed disease and/or use of an anti-dementia medication (i.e., acetylcholinesterase inhibitors or NMDA receptor antagonist). Arthritis was measured via self-report of a physician diagnosis. Baseline medication covariates included non-anticholinergic antiepileptics and psychoactive medications (benzodiazepine receptor agonists, antidepressants, and antipsychotics). Self-reported moderate/severe dizziness, back pain (moderate severe), and uncorrected vision problems were also assessed.

Statistical analysis

We used appropriate descriptive statistics for summarization and generalized estimating equations (GEE) for eliciting the main findings, allowing for multiple observations per participant. Odds ratios and 95 % confidence intervals were estimated from the GEE models that included baseline and year 3 medication exposure information, and recurrent falls in the following year as the outcome. Covariate data were from baseline. We included only women without missing covariate data for the primary analysis (N = 61,451). The primary analysis examined any use of anticholinergics as the main independent variable of interest and the risk of recurrent falls reported in 1.5 years subsequent to the assessment as the outcome. Since the focus of the analysis was on falls most proximal to medication use, only the most recent fall assessment (within 1.5 years) was used. Baseline and year 3 anticholinergic use was used to define the exposure in the primary analyses. All models were adjusted by age using 5-year age intervals and study component (clinical trial vs. observational study). We examined three models: Model 1 was adjusted for linear age at screening, diet modification (DM) trial, and Calcium/vitamin D (CaD) trial randomization arms; Model 2 was adjusted as Model 1, with additional adjustment for race/ethnicity, body mass index, poor vision, arthritis, treated diabetes, low back pain, Alzheimer Disease and/or use of anti-dementia medication, Parkinson’s Disease, urinary incontinence, depression, insomnia, self-reported health, alcohol intake, use of antiepileptics, and number of psychoactive medications. Most prior studies have been limited in their ability to adjust for physical function or physical activity, which are potential confounders. Because of a prevalent user design, these factors could also be influenced by anticholinergic use (or in the causal pathway). In addition, dizziness could be a confounder or a side effect from anticholinergic use. To examine this issue, we assessed a separate model (Model 3) that included all variables from Model 2, with additional adjustment for physical function, current physical activity from walking, and dizziness.

In addition, we assessed the association between the number of concurrent anticholinergic medications (0, 1 or ≥2), and duration of anticholinergic use at baseline (<1 year, 1–3 years, >3 years) and the risk of recurrent falls. We conducted trend tests for the number and duration of anticholinergic medication variables in order to assess associations across categories. Given the heterogeneity in medication use patterns (i.e., chronic vs. intermittent use as seen with many antihistamines) across anticholinergic agents, we grouped anticholinergic sub-classes into similar therapeutic groups (i.e., antihistamines, antidepressants/antipsychotics, gastrointestinal antispasmodics, urinary antimuscarinics, antivertigo/antiemetic, and miscellaneous) and assessed the association between each group and recurrent falls controlling for use of anticholinergics in other sub-classes. In addition to the primary associations of interest, we developed an interaction model to evaluate effect modification for recurrent falls based on history of a fall.

A sensitivity analysis was conducted to evaluate the robustness of our study results. Because the clinical trial arms of the WHI did not update many of the covariates at year 3, we ran the primary analyses only on those participants in the observational study sample, and updated the covariates at the year 3 exposure. All analyses were conducted using SAS statistical software, version 9.2 (SAS Institute Inc, Cary, North Carolina) with the GENMOD procedure to run the GEE models.

Results

Among the baseline sample of 61,451 postmenopausal women with complete data, the majority was white and overweight or obese (Table 2). At baseline, 11.3 % older women were using an anticholinergic medication (Table 3). Of users at baseline, 25.6 % had reported using the medication for less than 1 year, 36.2 % had used from 1 to 3 years, and 38.2 % had used for more than 3 years. Use of multiple anticholinergic medications was reported by 8.8 % of users. Compared to nonusers, individuals on anticholinergic medication were more likely to be obese, have a history of falls, have several health conditions (e.g., urinary incontinence, arthritis, low back pain), have higher psychoactive medication use including use certain medications (e.g., benzodiazepines, antidepressants), and have poorer physical function and poor/fair self-reported health.
Table 2

Baseline Characteristics of Sample: Overall and by Anticholinergic Usea (n = 61,451)

 

Overall

User of AC

Non-use of AC

(n = 61,451)

(n = 6940)

(n = 54,511)

 

N

%

N

%

N

%

Age group at screening

      

 65–69

31,008

50.5

3427

49.4

27,581

50.6

 70–74

21,491

35.0

2486

35.8

19,005

34.9

 75+

8952

14.6

1027

14.8

7925

14.5

Race/ethnicity

      

 White

54,015

87.9

6264

90.3

47,751

87.6

 Black

3572

5.8

314

4.5

3258

6.0

 Hispanic

1241

2.0

160

2.3

1081

2.0

 American Indian

200

0.3

34

0.5

166

0.3

 Asian/Pacific Islander

1594

2.6

82

1.2

1512

2.8

 Unknown

829

1.4

86

1.2

743

1.4

Number of falls in last 12 months (missing = 1658)

      

 None

40,419

67.6

4194

61.8

36,225

68.3

 1

12,200

20.4

1442

21.3

10,758

20.3

 2

4946

8.3

734

10.8

4212

8.0

 3 or more

2228

3.7

415

6.1

1813

3.4

Fair or poor self-reported health

5426

8.8

1049

15.1

4377

8.0

Smoking status (missing = 698)

      

 Never

32,298

53.2

3486

51.0

28,812

53.4

 Past

25,459

41.9

3017

44.1

22,442

41.6

 Current

2996

4.9

337

4.9

2659

4.9

Minutes per week spent walking (missing = 137)

      

 0 min

19,045

31.1

2494

36.0

16,551

30.4

  >0–150 min

32,225

52.6

3529

51.0

28,696

52.8

  >150 min

10,044

16.4

903

13.0

9141

16.8

Alcohol intake

      

 Non drinker

7375

12.0

852

12.3

6523

12.0

 Past drinker

11,657

19.0

1615

23.3

10,042

18.4

  <7 drinks per week

34,646

56.4

3665

52.8

30,981

56.8

 7+ drinks per week

7773

12.7

808

11.6

6965

12.8

BMI (kg/m2)

      

 Underweight (<18.5)

619

1.0

58

0.8

561

1.0

 Normal (18.5–24.9)

21,919

35.7

2184

31.5

19,735

36.2

 Overweight (25.0–29.9)

22,341

36.4

2601

37.5

19,740

36.2

 Obese (≥30.0)

16,572

27.0

2097

30.2

14,475

26.6

Rand Physical Function score >90 (missing = 731)

16,870

27.8

1191

17.4

15,679

29.1

Urinary incontinence

19,244

31.3

2754

39.7

16,490

30.3

History of Parkinson’s disease

228

0.4

64

0.9

164

0.3

Insomnia Rating Scale

      

 0–3

15,317

24.9

1296

18.7

14,021

25.7

 4–6

17,171

27.9

1698

24.5

15,473

28.4

 7–10

16,493

26.8

2034

29.3

14,459

26.5

  ≥11

12,470

20.3

1912

27.6

10,558

19.4

Depression (Burnham score >0.06)

5230

8.5

941

13.6

4289

7.9

Treated diabetes (oral or insulin)

2962

4.8

454

6.5

2508

4.6

Alzheimer Disease

35

0.1

2

0.03

33

0.1

Arthritis

34,728

56.5

4746

68.4

29,982

55.0

Anti-epileptic use

605

1.0

152

2.2

453

0.8

Benzodiazepine receptor agonist use

2563

4.2

860

12.4

1703

3.1

Antidepressant use

1710

2.8

409

5.9

1301

2.4

Antipsychotic use

54

0.1

27

0.4

27

0.1

Number of psychoactive meds

      

 0

57,378

93.4

5723

82.5

51,655

94.8

 1

3666

6.0

1072

15.5

2594

4.8

 2+

407

0.7

145

2.1

262

0.5

Dizziness (moderate/severe) (missing = 156)

1829

3.0

412

6.0

1417

2.6

Low back pain (moderate/severe)

12,719

20.7

2160

31.1

10,559

19.4

Vision problem uncorrected (moderate/severe)

3560

5.8

550

7.9

3010

5.5

WHI Participation

      

 Hormone therapy trial

10,986

17.9

1180

17.0

9806

18.0

 Diet modification trial

16,497

26.9

1754

25.3

14,743

27.1

 Calcium vitamin D trial

12,706

20.7

1272

18.3

11,434

21.0

 Observational study

36,723

59.8

4288

61.8

32,435

59.5

Abbreviation: AC anticholinergic

aMissing value is 0 unless otherwise specified

Table 3

Descriptives of Anticholinergic Medication Use Prevalence at Baseline and Year 3

 

Baseline

Year 3

 

N

%

N

%

Any Use

6940

100.00

6985

100.00

Number of Agents

    

 1

6332

91.24

6333

90.67

 2+

608

8.76

652

9.33

Duration

    

  <1 year

1775

25.58

1786

25.57

 1–3 years

2514

36.22

3306

47.33

  >3 years

2651

38.20

1893

27.10

Specific Anticholinergic Class

    

 Antihistamines

3136

45.19

2355

33.72

 Antidepressants/Antipsychotics

2252

32.45

2381

34.09

 Gastrointestinal antispasmodics

670

9.65

499

7.14

 Urinary antimuscarinics

582

8.39

1653

23.66

 Antivertigo/antiemetics

521

7.51

429

6.14

 Miscellaneousa

344

4.96

301

4.31

aMiscellaneous: antiparkinson agents and disopyramide

Using multivariable GEE models and controlling for potential confounders, the adjusted odds ratio for any anticholinergic medication use was 1.51 (95 % CI, 1.43–1.60) for recurrent falls (Table 4). Adjustment for physical function, physical activity, and dizziness had negligible impact on the odds ratio (Model 2 versus Model 3, Table 4). Participants using ≥ 2 anticholinergic medications had a 100 % increase in likelihood of recurrent falls (adjusted odds ratio [AOR] 2.00, 95 % CI 1.73–2.32). A significant trend for increasing likelihood of recurrent falls was detected with increasing duration of anticholinergic medication use (trend test p-value <0.0001). Moreover, use of each anticholinergic sub-class was associated with a statistically significant increase in likelihood of recurrent falls, with antidepressants/antipsychotics having the largest adjusted odds ratio (AOR 1.81, 95 % CI, 1.66–1.97) among the sub-classes.
Table 4

Adjusted Odds Ratios Relating Anticholinergic Use to Incident Recurrent Falls over the next 12 monthsa

  

Model 1

 

Model 2

 

Model 3

 

Number With falls

OR (95 % CI)

Number With falls

OR (95 % CI)

Number With falls

OR (95 % CI)

Any Anticholinergic use

      

 No use

7883

1.0

7883

1.0

7743

1.0

 Any use

1938

1.86 (1.76, 1.97)

1938

1.53 (1.45, 1.62)

1903

1.51 (1.43, 1.60)

Number of Agents*

      

 No use

7883

1.0

7883

1.0

7743

1.0

 1

1688

1.78 (1.67, 1.88)

1688

1.48 (1.40, 1.57)

1657

1.47 (1.38, 1.56)

 2+

250

2.84 (2.45, 3.28)

250

2.04 (1.76, 2.36)

246

2.00 (1.73, 2.32)

Duration*

      

 No use

7883

1.0

7883

1.0

7743

1.0

  <1 year

495

1.82 (1.64, 2.01)

495

1.52 (1.37, 1.68)

485

1.50 (1.36, 1.66)

 1–3 years

760

1.73 (1.59, 1.88)

760

1.42 (1.31, 1.55)

745

1.41 (1.29, 1.53)

  >3 years

683

2.10 (1.92, 2.29)

683

1.70 (1.55, 1.86)

673

1.68 (1.53, 1.84)

Specific Anticholinergic Classb

      

 Antihistamine/Antiemetic/Antivertigo

742

1.39 (1.28, 1.51)

742

1.22 (1.12, 1.32)

734

1.21 (1.11, 1.32)

 Antidepressant/Antipsychotic

811

2.26 (2.07, 2.46)

811

1.83 (1.67, 1.99)

796

1.81 (1.66, 1.97)

 Gastrointestinal/Urinary Antimuscarinics/Miscellaneous

607

1.81 (1.64, 1.99)

607

1.49 (1.35, 1.64)

591

1.47 (1.33, 1.62)

Abbreviations: CI confidence intervals, OR odds ratio

*Trend test p-values all <0.0001

aOR and CI are estimated from GEE models using an unstructured correlation matrix, including baseline and year 3 medication exposure information, and recurrent falls in the following year. All models are adjusted by age using 5-year age intervals, and study component (clinical trial vs. observational study). Model 1 adjusted for linear age, diet modification and CaD trial randomization arms. Model 2 was further adjusted for race/ethnicity, body mass index, poor vision, arthritis, treated diabetes, low back pain, Alzheimer’s Disease diagnosis and/or use of medication, indications for use (Parkinson’s disease, urinary incontinence, depression, insomnia scale), self-reported health, alcohol intake, use of antiepileptics, and number of psychoactive medications. Model 3 was further adjusted for physical function, dizziness, current physical activity from walking. All adjustment variables are from baseline

bOdds ratios for type of anticholinergic medication are adjusted for simultaneous use of a different type

Our sensitivity analysis did not reveal a statistically significant effect modification for recurrent falls based on history of a fall (falls in prior year: none/<2, AOR 1.47, 95 % CI, 1.37–1.58; falls in prior year: ≥2, AOR 1.38, 95 % CI, 1.25–1.53; interaction p value, 0.32). In addition, the sensitivity analysis including updated covariates at year 3 revealed similar findings to the primary analysis.

Discussion

We found that anticholinergic medication use was associated with recurrent falls among older postmenopausal women. The association with recurrent falls was even greater among those using multiple anticholinergic medications. In addition, we found a significant association between longer duration of anticholinergic use and recurrent falls. Each of the anticholinergic sub-classes was associated with recurrent falls; thus even anticholinergics likely to be used intermittently (e.g. antihistamines) were associated with recurrent falls. These findings were robust to sensitivity analysis.

A number of authoritative geriatric medicine sources report that anticholinergic use may increase fall risk [10, 31], despite some inconsistencies in the data that support these recommendations. Thus, our study addresses an important gap in the literature by evaluating the association between anticholinergic medication use and risk for falls among a large sample of community-dwelling women. The most comparable study to the current one was conducted in 2948 community-dwelling older men and women as part of the Health, Aging and Body Composition (ABC) study [13]. These authors also found an increased risk of recurrent falls in individuals on anticholinergic medication, but the results were not statistically significant perhaps because of the smaller sample size.

Conversely, a study by Berdot et al. on 6343 community-dwelling men and women aged ≥65 years found that the risk of falls was not significantly increased among individuals on anticholinergic medication in adjusted analysis [11]. However, when stratifying the analysis by type of anticholinergic use, Berdot et al. reported a statistically significant increase in likelihood of falls for regular but not occasional users compared to non users [11]. Of note, the authors were not able to determine if anticholinergic use had occurred before or after the fall based on their operational definition of regular use. Richardson et al. assessed the association between anticholinergic use and self-reported injurious falls in community-dwelling men and women aged ≥65 years in Ireland and found a statistically significant association between regular use and subsequent self-reported injurious falls in men, but not women [14]. In addition, Nisthala et al. examined the impact of anticholinergic and sedative medications (as measured by the Drug Burden Index [DBI]) in people aged ≥65 years in New Zealand and found that exposure to DBI drugs was independently associated with fall-related hospitalizations, primary care visits, and mortality [12]. However, it was not possible to disentangle the independent effect of anticholinergic use from the overall DBI drug exposure. While the literature regarding anticholinergic use and falls in older adults remains somewhat mixed, mounting evidence – including the results from our current study – suggests a significant association.

Given that many anticholinergic medications are over-the-counter, they may be used only intermittently (e.g., antihistamines). Medications with anticholinergic properties may increase falls risk by several mechanisms, including blurred vision, sedation, and cognitive impairment, therefore it is plausible that even intermittent use could increase risk via these adverse events [5, 6]. We explored this issue by performing our sub-class analysis where we found that even antihistamines were significantly associated with falls. It is also important to note that since antihistamines were the most commonly used therapeutic class of anticholinergics, studies relying on claims data to measure medication exposure would not capture antihistamines purchased over-the-counter and used intermittently. Future research would be strengthened by examining the association between patterns of anticholinergic use (including sporadic use) and falls.

Strengths of this study include the large sample of diverse women and extensive covariate information. In particular, we were able to adjust for important potential confounders not available in most administrative claims datasets, including physical function, physical activity, and dizziness. However, there are several limitations that warrant discussion. First, multiple scales exist for measuring anticholinergic exposure, with no true gold standard [32]. A study by Naples et al. found only low to moderate concordance among five commonly used anticholinergic scales [33]. To address this potential limitation, we included medications with moderate and strong anticholinergic activity and avoided medications with more questionable anticholinergic activity, potentially leading to a lower prevalence of anticholinergic medication use and thus a conservative estimate of the association between anticholinergic use and recurrent falls. Furthermore, our list is very similar to the medications identified as highly anticholinergic on the 2012 updated Beers criteria [10]. Medication information was only collected at baseline and year 3. As a result, anticholinergics users were likely to be those who tolerated the early adverse effects, and women experiencing adverse events may have discontinued the anticholinergics prior to their capture in our periodic assessment of medication use. This would be expected to bias our results towards the null and, therefore, our results are likely conservative. Finally, we did our best to adjust for baseline differences, but like all observational studies, residual or unmeasured confounding could explain our findings.

Conclusions

In conclusion, use of medications with strong or moderate anticholinergic effects in older women is associated with a slightly higher risk of recurrent falls, especially in those taking multiple agents or for 3 or more years. Anticholinergic medications have several potential adverse events (e.g., memory impairment, constipation, urinary retention), yet they continue to be widely used. Health care providers are encouraged to use anticholinergic medications judiciously and resort to alternative therapies when available. Since many medications with anticholinergic effects are available without a prescription, an effort to increase awareness among older adults of the potential for increased falling risk is an important public health priority.

Ethics, consent and permissions

All procedures performed in studies were approved by the respective institutional review boards at participating institutions and were in accordance with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. Specifically, the study protocol for the Women’s Health Initiative was reviewed and approved by each clinical center’s institutional review board (see Additional file 1). Informed consent was obtained from all individual participants included in the study.

Availability of data and materials

The datasets supporting the conclusions of this article are available at: https://www.whi.org/SitePages/WHI%20Home.aspx.

Abbreviations

ABC: 

aging, and body composition

ADS: 

anticholinergic drug scale

AOR: 

adjusted odds ration

CaD: 

calicum/vitamin D

CT: 

clinical trials

DBI: 

drug burden index

DM: 

diet modification

GEE: 

generalized estimating equations

OS: 

observational study

WHI: 

women’s health initiative

Declarations

Funding

The WHI program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through contracts HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, and HHSN271201100004C.

The authors thank the WHI investigators and staff for their dedication, and the study participants for making the program possible. A full listing of WHI investigators can be found at: https://www.whi.org/researchers/Documents%20%20Write%20a%20Paper/WHI%20Investigator%20Long%20List.pdf. The authors would also like to thank Joseph Hanlon, PharmD, MS, who commented on an earlier draft of this manuscript.

The funding organization had no role in the design and conduct of the study; the collection, management, analysis, and interpretation of the data; or the preparation, review, or approval of the manuscript.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
School of Pharmacy, University of Washington
(2)
Amgen Inc.
(3)
WHI Clinical Coordinating Center, Fred Hutchinson Cancer Research Center
(4)
Division of Epidemiology, UC San Diego
(5)
College of Public Health, Department of Epidemiology, University of Iowa
(6)
Department of Epidemiology, University of Pittsburgh
(7)
Departments of Medicine and Nutritional Sciences, University of Arizona Cancer Center

References

  1. Centers for Disease Control and Prevention. Falls among older adults: an overview. Retrieved 15 March, 2013, from http://www.cdc.gov/homeandrecreationalsafety/falls/adultfalls.html.
  2. King MB. Falls. In: Halter J, Ouslander J, Tinetti M, Studenski S, High K, Asthana S, editors. Hazzard’s geriatric medicine and gerontology. 6th ed. New York: McGraw-Hill; 2009. p. 659–70.Google Scholar
  3. Hanlon JT, Boudreau RM, Roumani YF, et al. Number and dosage of central nervous system medications on recurrent falls in community elders: the Health, Aging and Body Composition study. J Gerontol Med Sci. 2009;64:492–8.View ArticleGoogle Scholar
  4. Woolcott JC, Richardson KJ, Wiens MO, et al. Meta-analysis of the impact of 9 medication classes on falls in elderly persons. Arch Intern Med. 2009;169:1952–60.View ArticlePubMedGoogle Scholar
  5. Ancelin ML, Artero S, Portet F, et al. Non-degenerative mild cognitive impairment in elderly people and use of anticholinergic drugs: longitudinal cohort study. BMJ. 2006;332:455–9.View ArticlePubMedPubMed CentralGoogle Scholar
  6. Campbell NL, Boustani MA, Lane KA, et al. Use of anticholinergics and the risk of cognitive impairment in an African American population. Neurology. 2010;75:152–9.View ArticlePubMedPubMed CentralGoogle Scholar
  7. Ness J, Hoth A, Barnett MJ, et al. Anticholinergic medications in community-dwelling older veterans: prevalence of anticholinergic symptoms, symptom burden, and adverse drug events. Am J Geriatr Pharmacother. 2006;4:42–51.View ArticlePubMedGoogle Scholar
  8. Hilmer SN, Mager DE, Simonsick EM, et al. A drug burden index to define the functional burden of medications in older people. Arch Intern Med. 2007;167:781–7.View ArticlePubMedGoogle Scholar
  9. Boudreau RM, Hanlon JT, Roumani YF, et al. Central nervous system medication use and incident mobility limitation in community elders: the Health, Aging, and Body Composition study. Pharmacoepidemiol Drug Saf. 2009;18:916–22.View ArticlePubMedPubMed CentralGoogle Scholar
  10. American Geriatrics Society 2012 Beers Criteria Update Expert Panel. American Geriatrics Society updated Beers Criteria for potentially inappropriate medication use in older adults. J Am Geriatr Soc. 2012;60:616–31.View ArticleGoogle Scholar
  11. Berdot S, Bertrand M, Dartigues JF, et al. Inappropriate medication use and risk of falls--a prospective study in a large community-dwelling elderly cohort. BMC Geriatr. 2009;9:30.View ArticlePubMedPubMed CentralGoogle Scholar
  12. Nishtala PS, Narayan SW, Wang T, et al. Associations of drug burden index with falls, general practitioner visits, and mortality in older adults. Pharmacoepidemiol Drug Saf. 2014;23:753–8.View ArticlePubMedGoogle Scholar
  13. Marcum ZA, Perera S, Thorpe JM, et al. Anticholinergic use and recurrent falls in community-dwelling older adults: findings from the Health ABC study. Ann Pharmacother. 2015;49:1214–21.View ArticlePubMedPubMed CentralGoogle Scholar
  14. Richardson K, Bennett K, Maidment ID, et al. Use of medications with anticholinergic activity and self-reported injurious falls in older community-dwelling adults. J Am Geriatr Soc. 2015;63:1561–9.View ArticlePubMedGoogle Scholar
  15. Aizenberg D, Sigler M, Weizman A, et al. Anticholinergic burden and the risk of falls among elderly psychiatric inpatients: a 4-year case–control study. Int Psychogeriatr. 2002;14:307–10.View ArticlePubMedGoogle Scholar
  16. Murphy MP, Carmine H, Kolakowsky-Hayner S. Modifiable and nonmodifiable risk factors for falls after traumatic brain injury: an exploratory investigation with implications for medication use. Rehabil Nurs. 2014;39:113–22.View ArticlePubMedGoogle Scholar
  17. Wilson NM, Hilmer SN, March LM, et al. Associations between drug burden index and falls in older people in residential aged care. J Am Geriatr Soc. 2011;59:875–80.View ArticlePubMedGoogle Scholar
  18. Fraser LA, Adachi JD, Leslie WD, et al. Effect of anticholinergic medications on falls, fracture risk, and bone mineral density over a 10-year period. Ann Pharmacother. 2014;48:954–61.View ArticlePubMedGoogle Scholar
  19. Women’s Health Initiative Study Group. Design of the Women’s Health Initiative clinical trial and observational study. Control Clin Trials. 1998;19:61–109.View ArticleGoogle Scholar
  20. Carbone LD, Johnson KC, Bush AJ, et al. Loop diuretic use and fracture in postmenopausal women: findings from the Women’s Health Initiative. Arch Intern Med. 2009;169:132–40.View ArticlePubMedGoogle Scholar
  21. Masud T, Morris RO. Epidemiology of falls. Age Ageing. 2001;30:3–7.View ArticlePubMedGoogle Scholar
  22. Ganz DA, Higashi T, Rubenstein LZ. Monitoring falls in cohort studies of community-dwelling older people: effect of the recall interval. J Am Geriatr Soc. 2005;53:2190–4.View ArticlePubMedGoogle Scholar
  23. Carnahan RM, Lund BC, Perry PJ, et al. The Anticholinergic Drug Scale as a measure of drug-related anticholinergic burden: associations with serum anticholinergic activity. J Clin Pharmacol. 2006;46:1481–6.View ArticlePubMedGoogle Scholar
  24. Chew ML, Mulsant BH, Pollock BG, et al. Anticholinergic activity of 107 medications commonly used by older adults. J Am Geriatr Soc. 2008;56:1333–41.View ArticlePubMedGoogle Scholar
  25. Boustani M, Campbell N, Munger S, et al. Impact of anticholinergics on the aging brain: a review and practical application. Aging Health. 2008;4:311–20.View ArticleGoogle Scholar
  26. Rudolph JL, Salow MJ, Angelini MC, et al. The anticholinergic risk scale and anticholinergic adverse effects in older persons. Arch Intern Med. 2008;168:508–13.View ArticlePubMedGoogle Scholar
  27. Ware Jr JE, Sherbourne CD. The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care. 1992;30:473–83.View ArticlePubMedGoogle Scholar
  28. Luo J, Sands M, Wactawski-Wende J, et al. Sleep disturbance and incidence of thyroid cancer in postmenopausal women the Women’s Health Initiative. Am J Epidem. 2013;177:42–9.View ArticleGoogle Scholar
  29. Burnam MA, Wells KB, Leake B, et al. Development of a brief screening instrument for detecting depressive disorders. Med Care. 1988;26:775–89.View ArticlePubMedGoogle Scholar
  30. Tuunainen A, Langer RD, Klauber MR, et al. Short version of the CES-D (Burnam screen) for depression in reference to the structured psychiatric interview. Psychiatry Res. 2001;103:261–70.View ArticlePubMedGoogle Scholar
  31. Hanlon JT, Handler S, Maher R, et al. Geriatric Pharmacotherapy and Polypharmacy. In: Fillit H, Rockwood K, Woodhouse K, editors. Brocklehurst’s Textbook of Geriatric Medicine. 7th ed. London: Churchill Livingstone; 2010. p. 880–5.View ArticleGoogle Scholar
  32. Rudd KM, Raehl CL, Bond CA, et al. Methods for assessing drug-related anticholinergic activity. Pharmacotherapy. 2005;25:1592–601.View ArticlePubMedGoogle Scholar
  33. Naples JG, Marcum ZA, Perera S, et al. Concordance among anticholinergic burden scales. J Am Geriatr Soc. 2015;63:2120–4.View ArticlePubMedPubMed CentralGoogle Scholar

Copyright

© Marcum et al. 2016

Advertisement