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Canadian Geriatrics Journal logoLink to Canadian Geriatrics Journal
. 2022 Dec 1;25(4):347–367. doi: 10.5770/cgj.25.569

Medication Prescribed Within One Year Preceding Fall-Related Injuries in Ontario Older Adults

Yu Ming 1,✉, Aleksandra A Zecevic 1, Richard G Booth 2, Susan W Hunter 3, Rommel G Tirona 4, Andrew M Johnson 1
PMCID: PMC9684022  PMID: 36505916

Abstract

Background

Serious injuries secondary to falls are becoming more prevalent due to the worldwide ageing of societies. Several medication classes have been associated with falls and fall-related injuries. The purpose of this study was to describe medication classes and the number of medication classes prescribed to older adults prior to the fall-related injury.

Methods

This population-based descriptive study used secondary administrative health-care data in Ontario, Canada for 2010–2014. Descriptive statistics were reported for Anatomic Therapeutic Chemical 4th level medication classes. Frequency of medications prescribed to older adults was calculated on different sex, age groups, types of medications, and injures.

Results

Over five years (2010–2014), 288,251 older adults (63.2% females) were admitted to an emergency department for a fall-related injury (40.0% fractures, 12.1% brain injury). In the year before the injury, 48.5% were prescribed statins, 27.2% antidepressants, 25.0% opioids, and 16.6% anxiolytics. Females were prescribed more diuretics, antidepressants, and anxiolytics than males; and people aged 85 years and older had a higher percentage of diuretics, antidepressants, and antipsychotics. There were 36.4% of older adults prescribed 5–9 different medication classes and 41.2% were prescribed 10 or more medication classes.

Discussion

Older adults experiencing fall-related injuries were prescribed more opioids, benzodiazepines, and antidepressants than previously reported for the general population of older adults in Ontario. Higher percentage of females and more 85+ older adults were prescribed with psychotropic drugs, and they were also found to be at higher risk of fall-related injuries. Further associations between medications and fall-related injuries need to be explored in well-defined cohort studies.

Keywords: medication prescription, fall-related injuries, fall-related fractures, older adults

INTRODUCTION

Falls are the leading cause of both fatal and non-fatal injury in older adults.(1) Nearly one-third of older adults fall every year.(2–3) Minor injuries, such as bruises or lacerations, occur in 30–50% of falls, while 5–10% of falls lead to serious injuries such as hip fractures or traumatic brain injury.(4–9) Fall-related injuries can also result in adverse consequences such as reduced quality of life,(10) higher possibility of admission to long-term care facilities,(10) and increased risk of death.(11)

Numerous fall-related risk factors in older adults have been identified through past research. Specific use of certain medications and concurrent use of more than four medications have consistently been reported to be associated with both increased risk of falls and fall-related injury in this population.(12–17) Widely acknowledged fall risk-increasing drugs (FRIDs) include antihypertensive agents, diuretics, antidepressants, analgesics, anti-epileptics, and sedative/hypnotics.(18–22)

While previous research has commonly investigated the association between specific and known FRIDs and fall-related injuries (e.g., benzodiazepines,(23–24) anti-hypertensive medications,(25–26) and antidepressants(27–28)), limited evidence currently exists regarding medication classes of other than FRIDs that were prescribed to older adults prior to a fall-related injury. Providing a more comprehensive picture of medication classes prescribed to older adults before the occurrence of a fall-related injury is necessary to expand our knowledge on medications that may induce any fall-related injury. Therefore, the purpose of this study was: 1) to describe medication classes and numbers of medication classes prescribed to older adults within one year prior to the fall-related injury; and 2) to describe medication classes prescribed to older adults within one year prior to fall-related fractures and fall-related brain injury, as these two types of injury are of high prevalence and can cause serious consequences.(29–31)

METHODS

Study Design and Setting

We conducted a population-based, descriptive study of medication classes prescribed to older adults who experienced at least one fall-related injury from 1 January 2010 to 31 December 2014, using Ontario health-care administrative data held by the provincial data steward ICES. Ontario is the largest province in Canada, with a population of over 13 million and 2.2 million older adults over the age of 65,(32) all of whom have access to universal health-care services. ICES is an independent, non-profit research institute whose legal status under Ontario’s health information privacy law allows it to collect and analyze health-care and demographic data, without consent, for health system evaluation and improvement. ICES is a prescribed entity under section 45 of Ontario’s Personal Health Information Protection Act. Section 45 authorizes ICES to collect personal health information, without consent, for the purpose of analysis or compiling statistical information with respect to the management of, evaluation or monitoring of, the allocation of resources to or planning for all or part of the health system. Projects conducted under section 45, by definition, do not require review by a Research Ethics Board. This project was conducted under section 45, and was approved by ICES’ Privacy and Legal Office.

Population

Older adults aged 66 years and older who experienced a fall-related injury over the study period and resided in Ontario were included in this study. We chose the study period to be between 2010 and 2014 because it aligns well with the first of ‘baby boomers’ reaching the age of 65. The result of this study can serve as a baseline characteristics description for comparison with our future fall-related injuries research results. A fall-related injury was defined by combining at least one ICD-10 code for falls (W00-W19) with at least one code for injury (S00-S99, T00-T14) (Appendix A). The Emergency Department visit date for a fall-related injury was defined as the index date. Fall-related injuries of interest in this study were: 1) any fall-related injury; 2) fall-related fracture; and 3) fall-related traumatic brain injury (TBI). Fall-related fracture was identified through presence of at least one specific fracture S code (S02, S12, S22, S32, S42, S52, S62, S72, S82, S92, T02, T08, T10, T12, T142) and one W code (W00-W19). Fall-related traumatic brain injury was identified by presence of at least one specific concussion and brain injury code (S06, S099) and one W code (W00-W19). If a patient had multiple falls during the time period, only the first fall was included.

Data Sources

We used records arising from several databases held by ICES, including: 1) the Ontario Drug Benefit (ODB) database, which provides prescription drug coverage data for residents over the age of 65, including individuals in long-term care homes;(33) 2) the Discharge Abstract Database (DAD), which records information on all hospital admissions and discharge diagnosis; 3) the National Ambulatory Care Reporting System (NACRS), which captures information on visits to emergency departments and community-based ambulatory care facilities; and 4) the Ontario Registered Persons Database (RPDB), which contains demographic information for Ontario residents. ICES also applied validated case definition, including diabetes, chronic obstructive pulmonary diseases (COPD), asthma, hypertension, and dementia to each older adult and produced flags for these comorbidities. These datasets were linked using a unique encoded identifier, which ensured the confidentiality of personal and health information. In this study, socio-demographic data were extracted from the RPDB, primary diagnosis data arose from both NACRS and DAD, and medication prescriptions were drawn from ODB.

Medication Information

Medication information extracted from the ODB database used the Drug Identification Number (DIN) assigned by Health Canada.(34) Each DIN uniquely identifies the manufacturer, trade name, active ingredients, strength of active ingredients, pharmaceutical form, and route of administration.(34) For better understanding and comparability with the results of other studies, DIN codes were converted into Anatomical Therapeutic Chemical (ATC) level 5 codes, which represent the chemical substance.(35) Medication prescription information was reported on the 4th level of ATC codes in this study. ATC 4th level is the level used to count number of different medications as it is the level which aggregates medications just above their descriptive chemical substance.(36,37)

Outcomes

The primary outcome of this study was medication classes prescribed to older adults within one year prior to any fall-related injury, fall-related fractures, and fall-related traumatic brain injuries. Canadian Institute of Health Information reported medication use in general older adult population during the whole year of 2016.(37) To allow contextualization and comparison of our results with their findings,(37) we chose one year look-back window for medication use in older adults who have experienced fall-related injuries. We also explored medication prescription patterns in both fall-related fractures and fall-related brain injuries and medications taken in the year prior to these specific injuries. Finally, the number of ATC 4th level medication classes prescribed to each older adult within a year was calculated and summarized into four categories: 0–4 medication classes, 5–9 medication classes, 10–14 medication classes, and 15 or more medication classes.(37)

Statistical Analysis

Descriptive analysis summarized the cohort baseline characteristics such as age, sex, age group, and income quintile. Income quintile is a measure of socioeconomic status that divides the population living in the same dissemination area into five income groups (1 represents the lowest income) with approximately 20% of the population in each group.(38) The dissemination area was determined from the older adults’ residential postal code and statistics Canada Census data.(39) Prevalence of diabetes, COPD, asthma, hypertension, and dementia was also calculated using descriptive statistics. The fall-related injury (any injury type) was reported for each year and as a five-year total (2010–2014).

The percentage of people prescribed each ATC 4th level medication class was calculated by dividing the number of people who were prescribed a certain class within a year prior to a fall-related injury (numerator) by the total number of people who experienced a fall-related injury (denominator). The top 20 medication classes with the highest number of users were summarized as the percentage of female and male users, and percentage of different age-group users (i.e., 66–74, 75–84, 85+). The same analysis was repeated for subgroups of older adults who experienced fall-related fractures and fall-related TBIs. The difference between percentages of female and male older adults prescribed certain medication classes was determined by Wilcoxon rank-sum test and the comparison among different age groups was determined by Kruskal-Wallis test. All analyses were conducted with SAS 9.4 (SAS Institute Inc., Cary, NC).

RESULTS

A total of 288,251 older adults experienced any fall-related injury during the time frame of interest. Fall-related fractures made up 40.0% of all fall-related injuries, superficial injuries were 23.2%, open wound were 16.3%, traumatic brain injury were 12.1%, sprains and strains were 5.0%, and other injuries were 3.5%. The mean age was 78.3 ± 7.8 years old and 63.2% of the older adults were female. Over three quarters (76.9%) were diagnosed with hypertension, 30.5% with diabetes, 26.9% with COPD, 15.8% with dementia, and 15.0% with asthma (Table 1). Of the study population, 3.5% were not prescribed any medication classes within one year before the injury, while 18.9% were prescribed 1–4 different medication classes, 36.4% were prescribed 5–9 different medication classes, 26.0% were prescribed 10–14 different medication classes, and 15.2% were prescribed more than 15 different medication classes. Complete medication classes prescribed are provided in Appendix B, Table B1.

TABLE 1.

Characteristics of older adults who experienced fall-related injuries in 2010–2014.

2010 2011 2012 2013 2014 2010–2014
Age (Mean ± SD) 78.7 ± 7.6 78.5 ± 7.7 78.5 ± 7.8 78.1 ± 7.9 77.8 ± 8.0 78.3 ± 7.8
Age Median 79 79 79 78 78 78
Total Number 56,203 56,230 55,945 58,950 60,923 288,251
Age 66–74 (n, %) 18,673 (33.2) 19,296 (34.3) 19,842 (34.8) 22,160 (37.6) 23,813 (39.1) 103,424 (35.9)
Age 75–84 (n, %) 22,429 (39.9) 22,014 (39.2) 21,551 (38.5) 21,644 (36.7) 21,752 (35.7) 109,400 (38.0)
Age 85+ (n, %) 15,091 (26.9) 14,920 (26.5) 14,912 (26.7) 15,146 (25.7) 15,358 (25.2) 75,427 (26.2)
Sex Female (n, %) 36,562 (65.1) 35,976 (64.0) 35,315 (63.4) 36,492 (61.9) 37,656 (61.8) 182,136 (63.2)
Income Quintile
 1 (lowest) 11,687 (20.88%) 11,325 (20.22%) 11,169 (20.04%) 11,668 (19.87%) 13,868 (22.80%) 59,717 (20.79%)
 2 11,525 (20.59%) 11,455 (20.46%) 11,521 (20.68%) 11,953 (20.35%) 13,486 (22.17%) 59,940 (20.87%)
 3 11,134 (19.89%) 10,922 (19.50%) 10,921 (19.60%) 11,480 (19.55%) 11,816 (19.43%) 56,273 (19.59%)
 4 10,887 (19.45%) 11,146 (19.90%) 11,208 (20.11%) 11,920 (20.30%) 10,581 (17.40%) 55,742 (19.41%)
 5 10,737 (19.18%) 11,151 (19.91%) 10,902 (19.57%) 11,712 (19.94%) 11,069 (18.20%) 55,571 (19.35%)
Comorbidities
 Diabetes (n, %) 16,639 (29.6) 16,926 (30.1) 17,036 (30.5) 18,200 (30.9) 19,161 (31.5) 87,962 (30.5)
 COPD (n, %) 15,388 (27.4) 15,207 (27.0) 15,223 (27.2) 15,781 (26.8) 15,963 (26.2) 77,572 (26.9)
 Asthma (n, %) 8379 (14.9) 8,374 (14.9) 8,283 (14.8) 8,951 (15.2) 9,192 (15.1) 43,179 (15.0)
 Hypertension (n, %) 43,325 (77.1) 43,332 (77.1) 43,197 (77.2) 45,113 (76.5) 46,556 (76.4) 221,523 (76.9)
 Dementia (n, %) 9,329 (16.6) 9,175 (16.3) 8.934 (16.0) 9,130 (15.5) 9,007 (14.8) 45,575 (15.8)
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HMG-CoA reductase inhibitors (C10AA), commonly known as statins and used to treat high cholesterol, were the most commonly prescribed medication class, used by nearly half (48.5%) of the study population (Table 2). They were also the most frequently prescribed medication class in analyses stratified by sex and age subgroups (Figure 1). More than half (54.8%) of males were using statins before they experienced any fall-related injury. In the 75–84 age group, 53.4% used statins and the percentage dropped to 42.8% in the group of 85 years and older adults. The most prescribed statin (Appendix B, Table B2) was atorvastatin (24.3% in all older adults who experienced fall-related injuries), followed by rosuvastatin (17.2%) and pravastatin (1.9%).

TABLE 2.

Top 20 medication classes prescribed to older adults prior to a fall-related injury, percentage of users, 2010–2014

ATC Code Drug Class Common Use Percentage of Use p value
Total (%) Female (%) Male (%)
C10AA HMG CoA reductase inhibitors High cholesterol 48.5 44.7 54.8 <0.01
A02BC Proton pump inhibitors Gastroesophageal reflux, peptic ulcer disease 34.3 35.8 31.7 <0.01
C09AA ACE inhibitors, plain High blood pressure 29.0 26.1 33.9 <0.01
C07AB Beta blocking agents, selective High blood pressure, heart failure 25.9 24.8 27.8 <0.01
N02AA Natural opium alkaloids Management of moderate to severe pain 25.0 25.0 25.0 0.72
C08CA Dihydropyridine derivatives High blood pressure, heart failure, angina 23.7 24.8 21.8 <0.01
M05BA Biphosphates Prevent bone density loss, treat osteoporosis 20.4 28.2 7.1 <0.01
H03AA Thyroid hormones Hypothyroidism 18.3 23.1 10.0 <0.01
H02AB Glucocorticoids Autoimmune and inflammatory disorders, cancer, asthma, COPD 17.0 16.6 17.7 <0.01
N05BA Benzodiazepine derivatives Agitation, anxiety, insomnia, seizures 16.6 19.0 12.4 <0.01
C03CA Sulfonamides, plain High blood pressure, heart failure 16.5 16.0 17.5 <0.01
C09CA Agents acting on the renin-angiotensin system High blood pressure, heart or kidney disease 16.3 17.7 13.8 <0.01
C03AA Thiazides, plain High blood pressure, heart or kidney disease 15.2 17.0 12.1 <0.01
J01MA Fluoroquinolones Respiratory and urinary tract infections 15.2 15.2 15.1 0.56
N06AB Selective serotonin reuptake inhibitors Depression 14.7 16.4 11.9 <0.01
A10BA Biguanides Type 2 diabetes 14.3 12.9 16.8 <0.01
J01CA Penicillins with extended spectrum Bacterial infection 13.6 13.6 13.7 0.58
R03CC Selective beta-2-adrenoreceptor agonists COPD, asthma 13.1 13.3 12.8 <0.01
A06AA Softeners, emollients constipation 12.9 12.8 13.1 0.04
N06AX Other antidepressant (TCAs) Depression 12.5 13.5 10.7 <0.01
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FIGURE 1.

FIGURE 1

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Top 10 medicationsa prescribed to older adults of different age group before they experienced a fall-related injury

aC10AA, HMG CoA reductase inhibitors; A02BC, proton pump inhibitors; C09AA, ACEIs; C07AB, beta blocking agents; N02AA, Natural opium alkaloids; C08CA, dihydropyridine derivatives; M05BA, bisphosphonates; H03AA, thyroid hormones; H02AB, glucocorticoids for systematic use; N05BA, benzodiazepine derivatives

Proton pump inhibitors (PPIs, A02BC) were the second most prescribed drug class, with 34.3% of all older adults. For age groups 75–84 and 85 years and older, a slightly greater percentage of PPI use was found (36.2% and 36.5%, respectively), while the age group 66–74 years old had somewhat lower prevalence (30.6%, Figure 1). Commonly prescribed medications included pantoprazole (14.2%), rabeprazole (13.2%), lansoprazole (5.1%), and omeprazole (4.7%).

Four drug classes for the management of hypertension were noted among the top 10 drug classes. Angiotensin-converting enzyme inhibitors (ACEIs, C09AA) were prescribed to 33.9% of male and 26.1% females. Most common ACEIs were ramipril (14.8%), perindopril (7.0%), enalapril (2.4%), and lisinopril (2.0%). A higher percentage of males (27.8%) were prescribed beta-blocking agents (BBs) than females (24.8%). BBs included metoprolol (11.5%), bisoprolol (7.6%), and atenolol (6.7%). Agents acting on the renin-angiotensin system (ARBs, C09CA) included candesartan, valsartan, irbesartan, losartan, and telmisartan. Thiazides (C03AA) included hydrochlorothiazide (15.2%) and indapamide (2.2%). ARBs and thiazides were prescribed in higher percentage to females than males. The prescription of agents for treatment of high blood pressure increased with age (Figure 1). The percentage of the 85 years and older age group prescribed ACEIs, beta-blocking agents and dihydropyridine derivatives were the highest among the three age groups.

Biphosphates (M05BA) and thyroid hormones (H03AA) were prescribed to 28.3% and 23.1% of females, but only to 7.1% and 10.0% males, respectively. These two medication classes emerged as the most gender-specific among the older adults who experienced any fall-related injury. The percentage of older adults prescribed these two drug classes also increased with age (Figure 1), with the age group 85 years and older having the highest percentage.

Natural opium alkaloids (N02AA) were prescribed to a quarter of female and male older adults. For example, codeine and oxycodone were prescribed to 17.3% and 6.6%, respectively, of older adults who had fall-related injuries one year prior to the injury. The highest percentage of opioids prescription was noted for the age group 75–84 years. Older adults 85 years and older were prescribed fewer opioids than the other two age groups (Figure 1). Benzodiazepine derivatives were prescribed to 19.0% females and 12.4% males, with an increase with age to 18.5% in 85 years and older people. Lorazepam was prescribed to 12.2%, oxazepam to 2.7%, and clonazepam to 2.7% of older adults. For antidepressants, such as selective serotonin reuptake inhibitors (SSRIs, including citalopram, escitalopram, fluoxetine, etc.) and tricyclic antidepressants (TCAs, including amitriptyline, clomipramine, and doxepin), there was a higher percentage of female users than male users, namely 16.4% female, 11.9% male for SSRIs and 13.5% female, 10.7% male for TCAs.

Fall-related fractures were diagnosed in 115,230 older adults (40.0% of all older adults with any fall-related injury). More women (70.7%) than men (29.3%) experienced fall-related factures. For 85 years and older age group, the number of females (22,231) was almost three times as many as males (7,742). Statins and PPIs were still the top two most commonly prescribed medication classes. A higher percentage of males were prescribed statins, ACEIs, and BBs than females, while a higher percentage of females were prescribed bisphosphonates, dihydropyridine derivatives, and thyroid hormones. As for age differences, adults 85 years and older had the highest percentage of prescribed ACEIs, BBs, bisphosphonates, dihydropyridine derivatives, thyroid hormones, benzodiazepine derivatives, agents acting on the renin-angiotensin system, SSRIs, fluoroquinolones, and emollients (Table 3).

TABLE 3.

Top 20 medication classes prescribed to older adults with fall-related fracture, usage rate by sex and age group, 2010–2014

ATC Codes Drug Class Age Group p value b
Total (%) Female (%) Male (%) p value a 66–74 (%) 75–84 (%) 85+ (%)
C10AA HMG CoA reductase inhibitors 45.4 42.5 52.4 <0.01 44.6 50.4 39.6 <0.01
A02BC Proton pump inhibitors 33.1 33.9 31.0 <0.01 29.2 35.1 35.4 <0.01
C09AA ACE inhibitors, plain 27.6 25.5 32.8 <0.01 23.1 29.5 31.0 <0.01
N02AA Natural opium alkaloids 24.5 24.2 25.2 <0.01 23.7 26.0 23.5 <0.01
C07AB Beta blocking agents, selective 24.5 23.7 26.2 <0.01 18.4 26.8 29.3 <0.01
M05BA Biphosphates 23.6 30.0 8.1 <0.01 18.9 26.1 26.5 <0.01
C08CA Dihydropyridine derivatives 23.6 24.3 21.8 <0.01 17.7 25.2 29.2 <0.01
H03AA Thyroid hormones 18.6 22.3 9.7 <0.01 15.1 18.9 22.7 <0.01
N05BA Benzodiazepine derivatives 16.6 18.5 12.1 <0.01 13.9 17.8 18.7 <0.01
H02AB Glucocorticoids 16.1 15.5 17.4 <0.01 15.3 17.0 15.8 <0.01
C09CA agents acting on the renin-angiotensin system 15.7 16.7 13.3 <0.01 14.1 17.0 16.0 <0.01
C03CA Sulfonamides, plain 15.5 14.9 16.9 <0.01 8.3 15.3 25.2 <0.01
C03AA Thiazides, plain 14.7 16.1 11.3 <0.01 12.8 15.7 15.7 <0.01
N06AB Selective serotonin reuptake inhibitors 14.6 15.7 11.9 <0.01 13.0 14.9 16.4 <0.01
J01MA Fluoroquinolones 14.3 14.2 14.6 0.14 11.6 14.8 17.3 <0.01
J01CA Penicillins with extended spectrum 13.0 13.0 13.1 0.51 13.7 13.3 11.7 <0.01
A10BA Biguanides 12.7 11.7 15.3 <0.01 14.1 14.0 9.2 <0.01
R03CC Selective beta-2-adrenoreceptor agonists 12.4 12.3 12.4 0.62 12.6 12.9 11.4 <0.01
A06AA Softeners, emollients 12.2 11.9 13.0 <0.01 7.8 13.3 16.5 <0.01
N06AX Other antidepressants 12.1 12.8 10.3 <0.01 10.9 12.1 13.5 <0.01
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a

Wilcoxon rank-sum test.

b

Kruskal-Wallis test.

Fall-related TBIs was observed in 34,810 older adults (12.1% of all older adults with any fall-related injury), 20,246 occurred in females (58.7%) and 14,364 in males (41.3%). Nearly a third (31.7%) of older adults who experienced fall-related TBIs were in the 66–74 age group, with 39.9% in the 75–84 and 28.4% in the 85+ age groups, respectively. A higher percentage of males diagnosed with fall-related traumatic brain injury were prescribed statins, ACEIs, and BBs than females, while higher percentage of females were prescribed opioids, benzodiazepine derivatives, bisphosphonates, and thyroid hormones. As for age groups, adults 85 years and older had the highest prescriptions of ACEIs, BBs, dihydropyridine derivatives, bisphosphonates, thyroid hormones, sulfonamides, benzodiazepine derivatives, SSRIs, fluoroquinolones, emollients, TCAs, and contact laxatives (Table 4).

TABLE 4.

Top 20 medication classes prescribed to older adults with fall-related traumatic brain injury, by sex and age group

ATC Codes Drug Class Age Group p value b
Total (%) Female (%) Male (%) p value a 66–74 (%) 75–84 (%) 85+ (%)
C10AA HMG CoA reductase inhibitors 52.0 48.2 57.4 <0.01 49.5 57.3 47.3 <0.01
A02BC Proton pump inhibitors 35.5 37.5 32.5 <0.01 31.8 37.3 36.9 <0.01
C09AA ACE inhibitors, plain 30.3 27.3 34.6 <0.01 26.1 31.9 32.7 <0.01
C07AB Beta blocking agents, selective 28.7 27.7 30.2 <0.01 22.1 30.8 33.2 <0.01
C08CA Dihydropyridine derivatives 25.1 26.5 23.1 <0.01 19.3 26.9 29.2 <0.01
N02AA Natural opium alkaloids 24.9 25.4 24.1 <0.01 25.0 25.7 23.5 <0.01
M05BA Biphosphates 19.4 28.1 7.0 <0.01 13.9 20.9 23.3 <0.01
H03AA Thyroid hormones 19.1 24.8 11.0 <0.01 15.7 19.0 23.1 <0.01
C03CA Sulfonamides, plain 18.1 17.5 19.0 <0.01 10.3 17.5 27.6 <0.01
C09CA agents acting on the renin-angiotensin system 17.4 19.3 14.8 <0.01 15.8 19.0 17.0 <0.01
H02AB Glucocorticoids 17.3 17.2 17.5 0.34 16.1 18.3 17.4 <0.01
N05BA Benzodiazepine derivatives 17.2 20.0 13.2 <0.01 15.7 17.8 18.0 <0.01
A10BA Biguanides 16.6 15.2 18.6 <0.01 18.2 18.1 12.6 <0.01
N06AB Selective serotonin reuptake inhibitors 16.5 18.6 13.6 <0.01 15.2 16.9 17.4 <0.01
J01MA Fluoroquinolones 16.1 16.2 16.0 0.64 13.0 16.5 18.9 <0.01
C03AA Thiazides, plain 15.3 17.6 12.1 <0.01 13.4 16.7 15.5 <0.01
J01CA Penicillins with extended spectrum 14.4 14.7 14.0 0.06 15.5 14.2 13.7 <0.01
A06AA Softeners, emollients 14.4 14.2 14.6 0.30 10.1 15.2 18.1 <0.01
N06AX Other antidepressants 13.4 14.8 11.5 <0.01 13.1 13.0 14.4 <0.01
R03CC Selective beta-2-adrenoreceptor agonists 12.8 13.3 12.0 <0.01 13.0 12.9 12.2 0.14
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a

Wilcoxon rank-sum test.

b

Kruskal-Wallis test.

DISCUSSION

Using health-care administrative data, this study has described the medication classes prescribed to older adults in one year prior to a fall-related injury and two specific fall-injury types (i.e., fracture and traumatic brain injury). The results showed that among older adults sustaining any fall-related injury, 48.5% were prescribed statins, 34.3% PPIs, 25.0% opioids, and 16.6% anxiolytics. Similar patterns of medication prescription were also found for fall-related fractures and traumatic brain injury. Notably, 36.4% of older adults were prescribed 5–9 different medication classes and 41.2% were prescribed 10 or more medication classes within one year prior to fall-related injuries.

The findings of this study also indicate that medications prescribed to older adults who had any fall-related injury were similar—but not the same—to medications prescribed to the general population of older adults in Ontario.(37) CIHI reported that, in the whole year of 2016, there were 51.7% and 17.3% of Ontario general population of older adults (OGP-OAs) who were prescribed statins and agents acting on RAS,(37) while in our study, 48.5% and 16.3% of older adults who had fall related injury (FRI-OAs) were prescribed statins and ARBs within the year before the injury. However, compared to prescription in OGP-OAs, higher percentage of FRI-OAs were prescribed with ACEIs, BBs, opioids, bisphosphonates, benzodiazepine derivatives, thiazides, and SSRI. For example, CIHI reported there were 15.4% of OGP-OAs prescribed opioids, while in our study, 25.0% of FRI-OAs were prescribed opioids the year before their fall-related injury. The percentage of being prescribed SSRI in FRI-OAs and OGP-OAs were 14.6% and 10.5% respectively, bisphosphonates were 20.4% and 9.4% respectively, and benzodiazepine derivatives were 15.2% and 10.8% respectively.

From the above comparison, a finding is that all medication classes (except for bisphosphonates) with a higher percentage of prescription in older adults who had any fall-related injury were recognized as FRIDs. These classes of medications have been repeatedly identified to be related to falls and fall-related injury.(40–43) In this aspect, findings from our studies were supportive to previous studies on FRIDs and their association with falls and fall-related injury.

In this study, a number of medication classes were prescribed to a high percentage of older adults the year before they had fall-related injury, such as statins (48.5%), PPIs (34.3%), bisphosphonates (20.4%), thyroid hormones (18.3%), glucocorticoids (17.0%), and fluoroquinolones (15.2%). Unfortunately, research regarding the association between these medication classes and fall-related injuries has not been well-established.(26,44) The role of these commonly prescribed medication classes on fall-related injury in older adults needs to be disclosed as well.

Medications can be seen as a surrogate for a person’s health status and the number of medications was a valid proxy for multi-comorbidities.(45) Using multiple medications concurrently is common in older adults with multi-comorbidities and is associated with adverse outcomes such as mortality, falls, injuries, adverse drug reactions, and prolonged length of stay in hospital.(46–48) The risk of having adverse consequences and experiencing harm increased with each additional medication because of complicated drug-drug and drug-disease interactions.(49) Our study showed that 77.9% of older adults who had any fall-related injury were prescribed five or more different classes of medication within one year before the injury and 41.2% were prescribed 10 or more different classes of medication. CIHI reported that 65.7% general population of older adults in Canada were prescribed five or more medication classes and 26.5% were prescribed 10 or more medication classes in the year of 2016.(37) Compared with the general population of older adults, a higher percentage of older adults who experienced fall-related injuries were prescribed multiple medication classes before the injury. Untangling multiple medications prescribed to older adults by enhancing communication between patients and health-care providers, and improving cooperation of pharmacists, family doctors, and specialists in prescribing practices will be important in future research.

Strengths and Limitations

The strengths of this study are the large number of observations and provincial representativeness. This study included data for over a quarter million older adults and provided detailed information on demographics, comorbidities, and strictly defined fall-related injury using ICD-10-CA codes. All the data were obtained from ICES databases which were reported to have excellent data completeness(50) and high quality as per previous studies.(51–53)

Several limitations are associated with this study. First is the inherent limitation of administrative data that may lead to underreporting of some diagnoses,(54) which might have been omitted during the coding process. Second, only dispensed drugs were recorded in the ODB database, and the information collected through the ODB database could be an underestimation of prescriptions. Additionally, prescription (and even dispensing) cannot be equated with actual use. If older adults forgot to take medications as they were instructed, the registry data could be an overestimation of drug use; while on the other hand, if older adults get medications with multiple pharmacies, the registry data could underestimate the actual medication use.

CONCLUSION

This study described the medications classes and numbers of medication classes prescribed to older adults prior to a fall-related injury. Gender difference in medication prescribed was noted, specifically more females were prescribed antidepressants (SSRIs and TCAs) and anxiolytics (short-acting benzodiazepines such as lorazepam and long-acting such as clonazepam). A higher percentage of people 85 years and older were prescribed antihypertensive agents (ACEIs, BBs and dihydropyridine derivatives) and anxiolytics (benzodiazepines). There were 77.6% older adults were prescribed five or more different medication classes prior to any fall-related injury. Well-designed cohort studies are needed to determine the association between medication classes and different types of fall-related injuries.

ACKNOWLEDGEMENTS

This study was supported by ICES, which is funded by an annual grant from the Ontario Ministry of Health and Long-Term Care (MOHLTC). The opinions, results, and conclusions reported in this paper are those of the authors and are independent from the funding sources. No endorsement by ICES or the Ontario MOHLTC is intended or should be inferred.

APPENDIX A. ICD-10 codes forinjuries and falls

Falls
W00 Fall on same level involving ice and snow
W01 Fall on same level from slipping, tripping and stumbling
W02 Fall involving skates, skis, sport boards and in-line skates
W03 Other fall on same level due to collision with, or pushing by, another person
W04 Fall while being carried or supported by other persons
W05 Fall involving wheelchair
W06 Fall involving bed
W07 Fall involving chair
W08 Fall involving other furniture
W09 Fall involving swing
W10 Fall on and from stairs and steps
W11 Fall on and from ladder
W12 Fall on and from scaffolding
W13 Fall from, out of or through building or structure
W14 Fall from tree
W15 Fall from cliff
W16 Diving or jumping into water causing injury other than drowning or submersion
W17 Other fall from one level to another
W18 Fall on same level in or from bathtub
W19 Unspecified fall
Injury
S00–S09 Injuries to the head
S10–S19 Injuries to the neck
S20–S29 Injuries to the thorax
S30–S39 Injuries to the abdomen, lower back, lumbar spine and pelvis
S40–S49 Injuries to the shoulder and upper arm
S50–S59 Injuries to the elbow and forearm
S60–S69 Injuries to the wrist and hand
S70–S79 Injuries to the hip and thigh
S80–S89 Injuries to the knee and lower leg
S90–S99 Injuries to the ankle and foot
T00–T07 Injuries involving multiple body regions
T08–T14 Injuries to unspecified parts of trunk, limb or body region
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APPENDIX B.

TABLE B1.

Numbers of older adults being prescribed with different medication classes within one year prior to fall-related injurya

APPENDIX B.

APPENDIX B.

APPENDIX B.

APPENDIX B.

APPENDIX B.

APPENDIX B.

APPENDIX B.

ATC Codes Drug Class Female Male Total
66–74 75–84 85+ Total % 66–74 75–84 85+ Total % # %
A02BA H2-receptor antagonists 3180 4049 3088 10317 5.7 1762 2309 1380 5451 5.1 15768 5.5
A02BB Prostaglandins 149 129 73 351 0.2 30 41 24 95 0.1 446 0.2
A02BC Proton pump inhibitors 20449 25546 19100 65095 35.7 11144 14059 8441 33644 31.7 98739 34.3
A02BX Other drugs for peptic ulcer and (GORD) 313 344 180 837 0.5 143 166 92 401 0.4 1238 0.4
A03AB Synthetic anticholinergics, quaternary ammonium compounds 43 34 73 150 0.1 33 38 24 95 0.1 245 0.1
A03FA Propulsives 2578 3302 2390 8270 4.5 1151 1443 823 3417 3.2 11687 4.1
A04AA Serotonin (5HT3) antagonists 556 378 124 1058 0.6 375 333 77 785 0.7 1843 0.6
A05AA Bile acids and derivatives 101 96 48 245 0.1 38 39 9 86 0.1 331 0.1
A06AA Softeners, emollients 5198 9364 8785 23347 12.8 3480 5960 4444 13884 13.1 37231 12.9
A06AB Contact laxatives 4250 7242 6522 18014 9.9 2811 4592 3556 10959 10.3 28973 10.1
A06AC Bulk-forming laxatives 795 1512 1414 3721 2.0 447 953 816 2216 2.1 5937 2.1
A06AD Osmotically acting laxatives 4405 6337 6058 16800 9.2 3201 4336 3049 10586 10.0 27386 9.5
A07AA Antibiotics 1212 1346 850 3408 1.9 559 659 352 1570 1.5 4978 1.7
A07DA Antipropulsives 654 1082 1198 2934 1.6 391 541 401 1333 1.3 4267 1.5
A07EA Corticosteroids acting locally 3577 3842 2360 9779 5.4 2007 2473 1338 5818 5.5 15597 5.4
A07EC Aminosalicylic acid and similar agents 210 185 80 475 0.3 115 85 37 237 0.2 712 0.2
A09AA Enzyme preparations 119 147 103 369 0.2 87 112 41 240 0.2 609 0.2
A10AB Insulins and analogues for injection, fast-acting 1503 1126 482 3111 1.7 1494 1112 295 2901 2.7 6012 2.1
A10AC Insulins and analogues for injection, intermediate-acting 615 583 298 1496 0.8 503 505 155 1163 1.1 2659 0.9
A10AE Insulins and analogues for injection, long-acting 1979 1558 627 4164 2.3 1999 1430 426 3855 3.6 8019 2.8
A10BA Biguanides 8771 9660 5014 23445 12.9 7615 7466 2771 17852 16.8 41297 14.3
A10BB Sulfonylureas 4130 4924 2829 11883 6.5 3924 4141 1762 9827 9.3 21710 7.5
A10BD Combinations of oral blood glucose lowering drugs 418 304 97 819 0.4 398 232 72 702 0.7 1521 0.5
A10BF Alpha glucosidase inhibitors 172 191 90 453 0.2 142 145 47 334 0.3 787 0.3
A10BG Thiazolidinediones 651 624 200 1475 0.8 564 495 134 1193 1.1 2668 0.9
A10BH Dipeptidyl peptidase 4 (DPP-4) inhibitors 1779 1697 695 4171 2.3 1650 1339 511 3500 3.3 7671 2.7
A10BX Other blood glucose lowering drugs, excl. insulins 43 79 37 159 0.1 28 51 16 95 0.1 254 0.1
A11CC Vitamin D and analogues 499 837 629 1965 1.1 458 668 395 1521 1.4 3486 1.2
B01AA Vitamin K antagonists 2280 5597 5833 13710 7.5 2643 5344 3576 11563 10.9 25273 8.8
B01AB Heparin group 505 537 323 1365 0.7 371 476 206 1053 1.0 2418 0.8
B01AC Platelet aggregation inhibitors excl. heparin 2830 5263 5008 13101 7.2 3413 4923 3042 11378 10.7 24479 8.5
B01AE Direct thrombin inhibitors 317 884 809 2010 1.1 381 793 560 1734 1.6 3744 1.3
B01AF Direct factor Xa inhibitors 758 1037 714 2509 1.4 526 785 486 1797 1.7 4306 1.5
B01AX Other antithrombotic agents 20 26 16 62 0.0 18 23 13 54 0.1 116 0.0
B03AD Iron in combination with folic acid 3393 5997 5509 14899 8.2 2075 3733 2846 8654 8.2 23553 8.2
B03BA Vitamin B12 (cyanocobalamin and analogues) 2196 3648 3523 9367 5.1 1119 1986 1559 4664 4.4 14031 4.9
B03BB Folic acid and derivatives 1303 1610 1091 4004 2.2 737 890 559 2186 2.1 6190 2.1
B03XA Other antianemic preparations 75 141 83 299 0.2 43 106 63 212 0.2 511 0.2
B05AA Blood substitutes and plasma protein fractions 177 348 296 821 0.5 69 128 107 304 0.3 1125 0.4
B05BB Solutions affecting the electrolyte balance 426 484 245 1155 0.6 318 379 174 871 0.8 2026 0.7
B05XA Electrolyte solutions 15 25 16 56 0.0 7 9 9 25 0.0 81 0.0
C01AA Digitalis glycosides 779 2358 3301 6438 3.5 892 1812 1525 4229 4.0 10667 3.7
C01BC Antiarrhythmics, class Ic 185 245 131 561 0.3 90 128 64 282 0.3 843 0.3
C01CA Adrenergic and dopaminergic agents 36 83 32 151 0.1 50 108 51 209 0.2 360 0.1
C01DA Organic nitrates 3102 5853 6997 15952 8.8 2937 4645 3545 11127 10.5 27079 9.4
C02AB Methyldopa 60 105 118 283 0.2 25 41 25 91 0.1 374 0.1
C02AC Imidazoline receptor agonists 309 217 118 644 0.4 82 71 33 186 0.2 830 0.3
C02CA Alpha-adrenoreceptor antagonists 221 333 282 836 0.5 451 761 429 1641 1.5 2477 0.9
C02DB Hydrazinophthalazine derivatives 171 324 277 772 0.4 155 270 129 554 0.5 1326 0.5
C03AA Thiazides, plain 9338 12533 9169 31040 17.0 4603 5321 2940 12864 12.1 43904 15.2
C03BA Sulfonamides, plain 1769 2527 1806 6102 3.4 1148 1518 781 3447 3.2 9549 3.3
C03CA Sulfonamides, plain 5460 10254 13402 29116 16.0 4101 7758 6709 18568 17.5 47684 16.5
C03DA Aldosterone antagonists 1204 1821 1921 4946 2.7 1055 1478 957 3490 3.3 8436 2.9
C03DB Other potassium-sparing agents 629 832 632 2093 1.1 219 251 191 661 0.6 2754 1.0
C03EA Low-ceiling diuretics and potassium-sparing agents 1189 1600 1349 4138 2.3 342 468 331 1141 1.1 5279 1.8
C04AD Purine derivatives 114 221 240 575 0.3 142 237 136 515 0.5 1090 0.4
C07AA Beta blocking agents, non-selective 857 1126 884 2867 1.6 545 681 418 1644 1.5 4511 1.6
C07AB Beta blocking agents, selective 11055 18228 15896 45179 24.8 9634 12649 7206 29489 27.8 74668 25.9
C07AG Alpha and beta blocking agents 400 641 521 1562 0.9 541 821 444 1806 1.7 3368 1.2
C07BB Beta blocking agents, selective, and thiazides 180 234 128 542 0.3 80 67 35 182 0.2 724 0.3
C07CA Beta blocking agents, non-selective, and other diuretics 21 38 29 88 0.0 10 14 9 33 0.0 121 0.0
C08CA Dihydropyridine derivatives 11153 17993 15951 45097 24.8 7725 9698 5722 23145 21.8 68242 23.7
C08DA Phenylalkylamine derivatives 240 357 298 895 0.5 144 162 96 402 0.4 1297 0.4
C08DB Benzothiazepine derivatives 2993 4920 4251 12164 6.7 1870 2522 1499 5891 5.6 18055 6.3
C09AA ACE inhibitors, plain 13192 18661 15763 47616 26.1 12529 15070 8356 35955 33.9 83571 29.0
C09BA ACE inhibitors and diuretics 1985 2166 1370 5521 3.0 1604 1344 581 3529 3.3 9050 3.1
C09CA agents acting on the renin-angiotensin system 9578 13183 9416 32177 17.7 5568 6204 2923 14695 13.8 46872 16.3
C09DA Angiotensin II receptor blockers (ARBs) and diuretics 3124 3452 2029 8605 4.7 1747 1451 508 3706 3.5 12311 4.3
C09DB ARBs and calcium channel blockers 832 832 451 2115 1.2 471 391 144 1006 0.9 3121 1.1
C10AA HMG CoA reductase inhibitors 27117 33976 20398 81491 44.7 21800 24490 11904 58194 54.8 139685 48.5
C10AB Fibrates 972 1162 467 2601 1.4 852 703 236 1791 1.7 4392 1.5
C10AC Bile acid sequestrants 437 532 460 1429 0.8 189 246 157 592 0.6 2021 0.7
C10AD Nicotinic acid and derivatives 74 65 14 153 0.1 132 90 28 250 0.2 403 0.1
C10AX Other lipid modifying agents 2878 3148 1170 7196 4.0 2601 2442 707 5750 5.4 12946 4.5
C10BX HMG CoA reductase inhibitors, other combinations 481 681 442 1604 0.9 442 508 206 1156 1.1 2760 1.0
D01AA Antibiotics 305 404 393 1102 0.6 150 180 117 447 0.4 1549 0.5
D01AC Imidazole and triazole derivatives 3499 4741 4472 12712 7.0 1862 2453 1767 6082 5.7 18794 6.5
D01AE Other antifungals for topical use 1257 1299 969 3525 1.9 1091 1116 676 2883 2.7 6408 2.2
D05AX Other antipsoriatics for topical use 509 391 198 1098 0.6 444 353 140 937 0.9 2035 0.7
D06AX Other antibiotics for topical use 3713 5171 5205 14089 7.7 2433 3659 2758 8850 8.3 22939 8.0
D06BX Other chemotherapeutics 645 620 341 1606 0.9 245 275 119 639 0.6 2245 0.8
D07AA Corticosteroids, weak (group I) 3848 5128 4542 13518 7.4 2120 3029 2199 7348 6.9 20866 7.2
D07AB Corticosteroids, moderately potent (group II) 971 1099 773 2843 1.6 474 616 378 1468 1.4 4311 1.5
D07AC Corticosteroids, potent (group III) 2290 2734 2014 7038 3.9 1525 2063 1242 4830 4.6 11868 4.1
D07AD Corticosteroids, very potent (group IV) 1366 1317 789 3472 1.9 612 754 393 1759 1.7 5231 1.8
D07XC Corticosteroids, potent, other combinations 200 198 177 575 0.3 121 146 97 364 0.3 939 0.3
D10AF Antiinfectives for treatment of acne 58 31 8 97 0.1 43 48 14 105 0.1 202 0.1
D10AH 79 78 66 223 0.1 49 47 20 116 0.1 339 0.1
G01AG Triazole derivatives 195 157 83 435 0.2 N/A N/A N/A N/A 0.0 440 0.2
G03BA 3-oxoandrosten (4) derivatives 6 4 3 13 0.0 541 370 118 1029 1.0 1042 0.4
G03CA Natural and semisynthetic estrogens, plain 2917 2596 1530 7043 3.9 N/A N/A N/A 7 0.0 7050 2.4
G03HA Antiandrogens, plain 2 1 0 3 0.0 31 96 82 209 0.2 212 0.1
G03XA Antigonadotropins and similar agents 482 585 390 1457 0.8 12 10 6 28 0.0 1485 0.5
G04BD Drugs for urinary frequency and incontinence 2922 4248 3447 10617 5.8 1134 1898 1187 4219 4.0 14836 5.1
G04CA Alpha-adrenoreceptor antagonists 841 1051 767 2659 1.5 6362 9975 6452 22789 21.5 25448 8.8
G04CB Testosterone-5-alpha reductase inhibitors N/A N/A N/A N/A 0.0 3031 4997 3357 11385 10.7 11389 4.0
H02AB Glucocorticoids 10186 11888 8114 30188 16.6 6354 7872 4605 18831 17.7 49019 17.0
H03AA Thyroid hormones 12594 16233 13300 42127 23.1 2769 4286 3574 10629 10.0 52756 18.3
H03BA Thiouracils 60 72 58 190 0.1 14 26 8 48 0.0 238 0.1
H04AA Glycogenolytic hormones 80 98 85 263 0.1 72 84 36 192 0.2 455 0.2
J01AA Tetracyclines 309 288 190 787 0.4 226 240 104 570 0.5 1357 0.5
J01CA Penicillins with extended spectrum 9185 9310 6284 24779 13.6 5536 5849 3128 14513 13.7 39292 13.6
J01CF Beta-lactamase resistant penicillins 571 669 691 1931 1.1 439 583 379 1401 1.3 3332 1.2
J01CR Combinations of penicillins, incl. beta-lactamase inhibitors 1500 1419 1137 4056 2.2 1024 1038 570 2632 2.5 6688 2.3
J01DB First-generation cephalosporins 18 31 21 70 0.0 15 15 13 43 0.0 113 0.0
J01DC 2nd-generation cephalosporins 1764 2008 1704 5476 3.0 1037 1343 815 3195 3.0 8671 3.0
J01DD 3rd-generation cephalosporins 297 445 379 1121 0.6 207 253 197 657 0.6 1778 0.6
J01EA Trimethoprim and derivatives 116 213 193 522 0.3 57 101 65 223 0.2 745 0.3
J01EE Intermediate-acting sulfonamides 2985 4057 3695 10737 5.9 1350 1864 1217 4431 4.2 15168 5.3
J01FA Macrolides 8142 7044 4229 19415 10.7 4178 4042 2096 10316 9.7 29731 10.3
J01FF Lincosamides 1726 1740 976 4442 2.4 973 970 497 2440 2.3 6882 2.4
J01GB Other aminoglycosides 14 21 11 46 0.0 9 18 N/A 31 0.0 77 0.0
J01MA Fluoroquinolones 7489 9948 8864 26301 14.4 4765 6388 4268 15421 14.5 41722 14.5
J01XA Glycopeptide antibacterials 20 34 21 75 0.0 9 22 12 43 0.0 118 0.0
J01XD Imidazole derivatives 1515 1550 866 3931 2.2 872 860 423 2155 2.0 6086 2.1
J01XE Nitrofuran derivatives 5186 7225 5696 18107 9.9 751 1310 1047 3108 2.9 21215 7.4
J01XX Other antibacterials N/A N/A N/A 14 0.0 8 N/A N/A 13 0.0 27 0.0
J02AB Imidazole derivatives 25 23 16 64 0.0 42 39 26 107 0.1 171 0.1
J02AC Triazole derivatives 159 144 78 381 0.2 81 99 41 221 0.2 602 0.2
J04AK Other drugs for tuberculosis 16 17 12 45 0.0 6 12 N/A 22 0.0 67 0.0
J04AM Combinations of drugs for treatment of tuberculosis 33 43 39 115 0.1 22 36 16 74 0.1 189 0.1
J05AB Nucleosides and nucleotides 887 1001 714 2602 1.4 466 556 272 1294 1.2 3896 1.4
J05AF Nucleoside and nucleotide reverse transcriptase inhibitors 36 12 N/A 52 0.0 64 18 N/A 87 0.1 139 0.0
J05AH Neuraminidase inhibitors 262 1017 2450 3729 2.0 219 535 778 1532 1.4 5261 1.8
L01AA Nitrogen mustard analogues 46 111 56 213 0.1 49 89 41 179 0.2 392 0.1
L01AB Alkyl sulfonates 108 90 28 226 0.1 33 23 N/A 56 0.1 282 0.1
L01BA Folic acid analogues 1047 1046 431 2524 1.4 366 339 149 854 0.8 3378 1.2
L01BC Pyrimidine analogues 63 83 14 160 0.1 31 46 20 97 0.1 257 0.1
L01XE Protein kinase inhibitors 43 48 12 103 0.1 37 39 14 90 0.1 193 0.1
L01XX Other antineoplastic agents 75 156 147 378 0.2 52 91 64 207 0.2 585 0.2
L02AB Progestogens 52 100 107 259 0.1 60 110 68 238 0.2 497 0.2
L02AE Gonadotropin releasing hormone analogues N/A N/A N/A N/A 0.0 487 1269 1087 2843 2.7 2844 1.0
L02BA Anti-estrogens 243 291 230 764 0.4 10 30 30 70 0.1 834 0.3
L02BB Anti-androgens N/A N/A N/A N/A 0.0 225 684 675 1584 1.5 1586 0.6
L02BG Aromatase inhibitors 978 971 514 2463 1.4 N/A N/A N/A 10 0.0 2473 0.9
L03AA Colony stimulating factors 98 45 15 158 0.1 31 26 6 63 0.1 221 0.1
L04AA Selective immunosuppressants 240 175 46 461 0.3 202 105 15 322 0.3 783 0.3
L04AB Tumor necrosis factor alpha (TNF-α) inhibitors 108 90 28 226 0.1 33 23 N/A 56 0.1 282 0.1
L04AD Calcineurin inhibitors 270 169 97 536 0.3 203 160 62 425 0.4 961 0.3
L04AX Other immunosuppressants 189 139 62 390 0.2 101 91 24 216 0.2 606 0.2
M01AE Propionic acid derivatives 4491 3622 1766 9879 5.4 2570 1973 748 5291 5.0 15170 5.3
M01AH Coxibs 3717 3891 2288 9896 5.4 1698 1729 778 4205 4.0 14101 4.9
M03BX Other centrally acting agents 1119 850 306 2275 1.2 566 412 135 1113 1.0 3388 1.2
M04AA Preparations inhibiting uric acid production 1240 2250 1920 5410 3.0 2683 3815 2010 8508 8.0 13918 4.8
M05BA Biphosphates 14187 21354 15912 51453 28.2 1867 3299 2316 7482 7.1 58935 20.4
M05BX Other drugs affecting bone structure and mineralization 446 896 679 2021 1.1 14 35 28 77 0.1 2098 0.7
N02AA Natural opium alkaloids 15408 17873 12311 45592 25.0 10350 10711 5437 26498 25.0 72090 25.0
N02AB Phenylpiperidine derivatives 608 922 877 2407 1.3 334 407 237 978 0.9 3385 1.2
N02AJ Opioids in combination with non-opioid analgesics 13685 15531 10035 39251 21.6 9283 9555 4712 23550 22.2 62801 21.8
N02BA Salicylic acid and derivatives 1351 2294 1931 5576 3.1 1239 1785 1078 4102 3.9 9678 3.4
N03AA Barbiturates and derivatives 164 172 89 425 0.2 134 133 58 325 0.3 750 0.3
N03AB Hydantoin derivatives 716 710 437 1863 1.0 713 666 311 1690 1.6 3553 1.2
N03AE Benzodiazepine derivatives 2372 1967 1049 5388 3.0 1060 916 369 2345 2.2 7733 2.7
N03AF Carboxamide derivatives 538 491 284 1313 0.7 377 308 130 815 0.8 2128 0.7
N03AG Fatty acid derivatives 603 340 153 1096 0.6 432 278 90 800 0.8 1896 0.7
N03AX Other antiepileptics 3036 3026 1889 7951 4.4 1638 1656 757 4051 3.8 12002 4.2
N04AA Tertiary amines 64 47 21 132 0.1 65 49 6 120 0.1 252 0.1
N04BA Dopa and dopa derivatives 924 1653 1001 3578 2.0 1023 1971 860 3854 3.6 7432 2.6
N04BB Adamantane derivatives 102 74 16 192 0.1 97 103 13 213 0.2 405 0.1
N04BC Dopamine agonists 742 719 400 1861 1.0 455 514 189 1158 1.1 3019 1.0
N04BD Monoamine oxidaseB inhibitors 24 29 14 67 0.0 38 37 11 86 0.1 153 0.1
N04BX Other dopaminergic agents 91 119 39 249 0.1 117 176 48 341 0.3 590 0.2
N05AA Phenothiazines-aliphatic sidechain 168 111 75 354 0.2 124 102 56 282 0.3 636 0.2
N05AB Phenothiazines piperazine structure 899 855 373 2127 1.2 537 487 160 1184 1.1 3311 1.1
N05AC Phenothiazines piperidine structure 79 98 52 229 0.1 24 15 7 46 0.0 275 0.1
N05AD Butyrophenone derivatives 182 349 416 947 0.5 179 319 222 720 0.7 1667 0.6
N05AH Diazepines, oxazepines, thiazepines and oxepines 2178 3160 3404 8742 4.8 1431 1993 1413 4837 4.6 13579 4.7
N05AN Lithium 295 194 78 567 0.3 187 97 18 302 0.3 869 0.3
N05AX Other antipsychotics 778 1585 2049 4412 2.4 562 958 789 2309 2.2 6721 2.3
N05BA Benzodiazepine derivatives 10302 13766 10602 34670 19.0 4420 5446 3334 13200 12.4 47870 16.6
N05CD Benzodiazepine derivatives 1207 1537 1184 3928 2.2 656 808 515 1979 1.9 5907 2.0
N06AA Non-selective monoamine reuptake inhibitors 4182 4347 2208 10737 5.9 1452 1437 695 3584 3.4 14321 5.0
N06AB Selective serotonin reuptake inhibitors 9510 11206 9084 29800 16.4 4198 5191 3221 12610 11.9 42410 14.7
N06AG Monoamine oxidase A inhibitors 50 41 12 103 0.1 28 24 7 59 0.1 162 0.1
N06AX Other antidepressants 7940 8789 7339 24068 13.2 3806 4399 2873 11078 10.4 35146 12.2
N06BA Centrally acting sympathomimetics 145 99 72 316 0.2 104 88 32 224 0.2 540 0.2
N06DA Anticholinesterases 1295 6300 7831 15426 8.5 997 3746 3319 8062 7.6 23488 8.1
N07AA Anticholinesterases 47 47 29 123 0.1 30 50 25 105 0.1 228 0.1
N07AB Choline esters 48 57 46 151 0.1 28 53 44 125 0.1 276 0.1
N07BA Drugs used in nicotine dependence 237 48 N/A 288 0.2 196 43 N/A 240 0.2 528 0.2
P03AC Pyrethrines 90 141 217 448 0.2 63 82 77 222 0.2 670 0.2
R01AD Corticosteroids (nasal preparations) 3002 2786 1547 7335 4.0 1577 1726 876 4179 3.9 11514 4.0
R02AX Other nasal preparations 32 33 21 86 0.0 21 19 7 47 0.0 133 0.0
R03BA Glucocorticoids (drugs for COPD) 4821 4940 3189 12950 7.1 2184 2743 1522 6449 6.1 19399 6.7
R03BB Anticholinergics 4553 6158 4246 14957 8.2 3341 5164 3197 11702 11.0 26659 9.2
R03CB Non-selective beta-adrenoreceptor agonists 77 84 79 240 0.1 44 40 34 118 0.1 358 0.1
R03CC Selective beta-2-adrenoreceptor agonists 9090 9039 6065 24194 13.3 4754 5607 3227 13588 12.8 37782 13.1
S01AA Antibiotics-ophthalmologicals 2063 2660 2028 6751 3.7 1127 1658 1080 3865 3.6 10616 3.7
S01AD Antivirals-ophthalmologicals 68 61 45 174 0.1 45 53 36 134 0.1 308 0.1
S01AE Fluoroquinolones 76 100 96 272 0.1 43 63 63 169 0.2 441 0.2
S01BA Corticosteroids, plain 3520 4958 2405 10883 6.0 1919 2855 1334 6108 5.8 16991 5.9
S01BC Antiinflammatory agents, 1240 1800 811 3851 2.1 694 1121 460 2275 2.1 6126 2.1
S01EA Sympathomimetics in glaucoma 707 1336 1315 3358 1.8 496 945 669 2110 2.0 5468 1.9
S01EB Parasympathomimetics 71 152 251 474 0.3 46 83 98 227 0.2 701 0.2
S01EC Carbonic anhydrase inhibitors 1022 1975 2204 5201 2.9 677 1377 1031 3085 2.9 8286 2.9
S01ED Beta blocking agents 909 1681 1946 4536 2.5 503 1002 820 2325 2.2 6861 2.4
S01EE Prostaglandin analogues 2491 4673 5003 12167 6.7 1475 2805 2221 6501 6.1 18668 6.5
S01FA Anticholinergics 162 198 177 537 0.3 172 214 126 512 0.5 1049 0.4
S01GX Other antiallergics 792 988 591 2371 1.3 321 404 235 960 0.9 3331 1.2
S01HA Local anesthetics 139 98 58 295 0.2 110 89 27 226 0.2 521 0.2
S01LA Antineovascularisation agents 318 1107 1530 2955 1.6 241 620 638 1499 1.4 4454 1.5
S02CA Corticosteroids and anti-infectives (otologicals) 421 487 266 1174 0.6 253 308 171 732 0.7 1906 0.7
V06DC Carbohydrates 9727 11013 5692 26432 14.5 7991 8510 3329 19830 18.7 46262 16.0
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a

Medication classes that were prescribed to fewer than 6 persons were reported as N/A to protect the patients’ privacy.

TABLE B2.

Numbers of older adults being prescribed with different generic names within one year prior to fall-related injury

APPENDIX B.

APPENDIX B.

Generic Medication Names Female Male Total
66–74 75–84 85+ Total % 66–74 75–84 85+ Total % # %
Atorvastatin 12491 17122 11208 40821 14.2 10462 13107 6765 30334 10.5 71155 24.7
Amlodipine 8728 14064 12598 35390 12.3 6187 7730 4590 18507 6.4 53897 18.7
Codeine 10500 12465 8376 31341 10.9 6921 7715 3993 18629 6.5 49970 17.3
Levothyroxine 12594 16233 13300 42127 14.6 2769 4286 3574 10629 3.7 52756 18.3
Ramipril 6254 9119 7921 23294 8.1 6632 8165 4599 19396 6.7 42690 14.8
Hydrochlorothiazide 9338 12533 9169 31040 10.8 4603 5321 2940 12864 4.5 43904 15.2
Rosuvastatin 11920 11644 5293 28857 10.0 9431 8156 3024 20611 7.2 49468 17.2
Glucose 9727 11013 5692 26432 9.2 7991 8510 3329 19830 6.9 46262 16.0
Metformin 8771 9660 5014 23445 8.1 7615 7466 2771 17852 6.2 41297 14.3
Furosemide 5460 10254 13402 29116 10.1 4101 7758 6709 18568 6.4 47684 16.5
Amoxicillin 9135 9232 6211 24578 8.5 5506 5811 3110 14427 5.0 39005 13.5
Rabeprazole 7840 10255 7578 25673 8.9 4053 5249 3038 12340 4.3 38013 13.2
Lorazepam 7637 10196 7826 25659 8.9 3076 3948 2426 9450 3.3 35109 12.2
Pantoprazole 8507 10347 7956 26810 9.3 4914 6138 3819 14871 5.2 41681 14.5
Metoprolol 4392 7695 7342 19429 6.7 4426 5911 3520 13857 4.8 33286 11.5
Docusate 5198 9364 8785 23347 8.1 3480 5960 4444 13884 4.8 37231 12.9
Acetaminophen 4428 8708 9740 22876 7.9 2129 3943 3635 9707 3.4 32583 11.3
Nitroglycerin 3016 5646 6716 15378 5.3 2859 4488 3412 10759 3.7 26137 9.1
Salbutamol 8769 8690 5819 23278 8.1 4616 5417 3138 13171 4.6 36449 12.6
Risedronate 7908 11776 8987 28671 9.9 1044 1826 1302 4172 1.4 32843 11.4
Betamethasone 4120 5230 4157 13507 4.7 2922 3764 2551 9237 3.2 22744 7.9
Warfarin 2280 5597 5833 13710 4.8 2643 5344 3576 11563 4.0 25273 8.8
Atenolol 3441 5168 4030 12639 4.4 2254 2844 1497 6595 2.3 19234 6.7
Ciprofloxacin 4595 6190 5434 16219 5.6 2950 3798 2456 9204 3.2 25423 8.8
Hydrocortisone 3916 5183 4561 13660 4.7 2174 3103 2241 7518 2.6 21178 7.3
Cephalexin 4198 5317 4870 14385 5.0 3241 3968 2478 9687 3.4 24072 8.4
Alendronate 5743 8498 6053 20294 7.0 739 1300 921 2960 1.0 23254 8.1
Ferrous 3393 5997 5509 14899 5.2 2075 3733 2846 8654 3.0 23553 8.2
Sennosides 3206 6243 6004 15453 5.4 2133 3928 3249 9310 3.2 24763 8.6
Tiotropium 3850 5095 3371 12316 4.3 2904 4326 2531 9761 3.4 22077 7.7
Azithromycin 4835 4412 2762 12009 4.2 2483 2508 1334 6325 2.2 18334 6.4
Prednisolone 4465 5113 3166 12744 4.4 2667 3350 1830 7847 2.7 20591 7.1
Bisoprolol 3171 5245 4414 12830 4.5 2965 3870 2154 8989 3.1 21819 7.6
Oxycodone 4697 4549 2352 11598 4.0 3432 2819 1055 7306 2.5 18904 6.6
Perindopril 3538 4598 3559 11695 4.1 3239 3497 1812 8548 3.0 20243 7.0
Ranitidine 2961 3715 2821 9497 3.3 1634 2156 1284 5074 1.8 14571 5.1
Nitrofurantoin 5186 7225 5696 18107 6.3 751 1310 1047 3108 1.1 21215 7.4
Lactulose 2277 4695 5696 12668 4.4 1784 3194 2776 7754 2.7 20422 7.1
Omeprazole 2887 3670 2638 9195 3.2 1380 1799 1074 4253 1.5 13448 4.7
Salmeterol 4105 4893 3105 12103 4.2 2332 3236 1891 7459 2.6 19562 6.8
Diltiazem 2993 4920 4251 12164 4.2 1870 2522 1499 5891 2.0 18055 6.3
Clopidogrel 2469 4495 4213 11177 3.9 3041 4206 2582 9829 3.4 21006 7.3
Clarithromycin 3654 2864 1584 8102 2.8 1849 1678 847 4374 1.5 12476 4.3
Meloxicam 3633 3970 2125 9728 3.4 1545 1531 786 3862 1.3 13590 4.7
Nifedipine 2234 3551 3060 8845 3.1 1397 1774 1016 4187 1.5 13032 4.5
Fluticasone 3186 3136 2075 8397 2.9 1422 1712 965 4099 1.4 12496 4.3
Allopurinol 1258 2278 1935 5471 1.9 2768 3887 2032 8687 3.0 14158 4.9
Tamsulosin 58 44 22 124 0.0 4451 7019 4622 16092 5.6 16216 5.6
Clotrimazole 2564 3723 3672 9959 3.5 1236 1741 1296 4273 1.5 14232 4.9
Sulfamethoxazole 2985 4057 3695 10737 3.7 1350 1864 1217 4431 1.5 15168 5.3
Lansoprazole 3180 3751 2770 9701 3.4 1758 2130 1228 5116 1.8 14817 5.1
Celecoxib 3717 3891 2288 9896 3.4 1698 1729 778 4205 1.5 14101 4.9
Citalopram 3529 4848 4348 12725 4.4 1589 2337 1554 5480 1.9 18205 6.3
Trazodone 3032 4269 4476 11777 4.1 1573 2340 1843 5756 2.0 17533 6.1
Ezetimibe 2878 3148 1170 7196 2.5 2601 2442 707 5750 2.0 12946 4.5
Cyanocobalamin 2196 3648 3523 9367 3.2 1119 1986 1559 4664 1.6 14031 4.9
Amitriptyline 3535 3525 1681 8741 3.0 1205 1143 530 2878 1.0 11619 4.0
Candesartan 2242 3071 2346 7659 2.7 1378 1499 741 3618 1.3 11277 3.9
Valsartan 2192 3205 2371 7768 2.7 1230 1457 707 3394 1.2 11162 3.9
Latanoprost 1455 2837 3232 7524 2.6 844 1665 1390 3899 1.4 11423 4.0
Gliclazide 2737 3091 1796 7624 2.6 2618 2552 1140 6310 2.2 13934 4.8
Naproxen 3124 2305 912 6341 2.2 1756 1274 426 3456 1.2 9797 3.4
Donepezil 809 4044 5057 9910 3.4 621 2337 2079 5037 1.7 14947 5.2
Levofloxacin 1645 2155 1864 5664 2.0 1013 1579 1117 3709 1.3 9373 3.3
Dexamethasone 2181 2411 1054 5646 2.0 1315 1658 621 3594 1.2 9240 3.2
Enalapril 1098 1683 1673 4454 1.5 811 1117 673 2601 0.9 7055 2.4
Irbesartan 1759 2362 1597 5718 2.0 1063 1148 508 2719 0.9 8437 2.9
Hydromorphone 2349 3167 2681 8197 2.8 1539 1658 935 4132 1.4 12329 4.3
Domperidone 2317 3003 2220 7540 2.6 986 1278 754 3018 1.0 10558 3.7
Budesonide 2456 2320 1348 6124 2.1 1362 1489 801 3652 1.3 9776 3.4
Oxazepam 1281 2099 2022 5402 1.9 623 947 678 2248 0.8 7650 2.7
Spironolactone 1204 1821 1921 4946 1.7 1055 1476 957 3488 1.2 8434 2.9
Losartan 1329 2061 1555 4945 1.7 669 874 448 1991 0.7 6936 2.4
Metronidazole 2124 2146 1195 5465 1.9 1110 1131 538 2779 1.0 8244 2.9
Telmisartan 1715 2170 1375 5260 1.8 999 1081 465 2545 0.9 7805 2.7
Indapamide 1283 1850 1246 4379 1.5 684 901 428 2013 0.7 6392 2.2
Lisinopril 905 1441 1174 3520 1.2 762 1011 556 2329 0.8 5849 2.0
Beclomethasone 1399 1779 1165 4343 1.5 761 1099 621 2481 0.9 6824 2.4
Quetiapine 1546 2260 2544 6350 2.2 1003 1478 1118 3599 1.2 9949 3.5
Hydrocodone 1683 1562 700 3945 1.4 885 836 350 2071 0.7 6016 2.1
Digoxin 779 2358 3301 6438 2.2 892 1812 1525 4229 1.5 10667 3.7
Tolterodine 1694 2561 1998 6253 2.2 645 1173 735 2553 0.9 8806 3.1
Risperidone 702 1540 2039 4281 1.5 517 937 783 2237 0.8 6518 2.3
Pravastatin 889 1546 1137 3572 1.2 587 885 551 2023 0.7 5595 1.9
Terazosin 305 473 339 1117 0.4 1162 2042 1257 4461 1.5 5578 1.9
Clonazepam 2372 1967 1049 5388 1.9 1060 916 369 2345 0.8 7733 2.7
Dorzolamide 624 1324 1625 3573 1.2 406 922 747 2075 0.7 5648 2.0
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Footnotes

CONFLICT OF INTEREST DISCLOSURES

We have read and understood the Canadian Geriatrics Journal’s policy on conflicts of interest disclosure and declare there are not conflicts of interest.

FUNDING

This research did not receive external funding.

REFERENCES

  • 1.Bergen G, Stevens MR, Burns ER. Falls and fall injuries among adults aged ≥65 years—United States, 2014. Morb Mortal Wkly Rep. 2016 Sep 23;65(37):993–98. doi: 10.15585/mmwr.mm6537a2. [DOI] [PubMed] [Google Scholar]
  • 2.Chang HJ, Lynm C, Glass RM. JAMA Patient Page [website] Falls and older adults. Published January 20, 2010. Available from: https://jamanetwork.com/journals/jama/fullarticle/1852363. [DOI] [PubMed]
  • 3.Tinetti ME, Gordon C, Sogolow E, Lapin P, Bradley EH. Fall-risk evaluation and management: challenges in adopting geriatric care practices. Gerontologist. 2006 Dec 1;46(6):717–25. doi: 10.1093/geront/46.6.717. [DOI] [PubMed] [Google Scholar]
  • 4.Cameron ID, Gillespie LD, Robertson MC, et al. Interventions for preventing falls in older people in care facilities and hospitals. Cochrane Database Syst Rev. 2012 2012 Dec 12;(12) doi: 10.1002/14651858.CD005465.pub3. [DOI] [PubMed] [Google Scholar]
  • 5.Gillespie LD, Robertson MC, Gillespie WJ, et al. Interventions for preventing falls in older people living in the community. Cochrane Database Syst Rev. 2012;9 doi: 10.1002/14651858.CD007146.pub3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Goldacre MJ, Roberts SE, Yeates D. Mortality after admission to hospital with fractured neck of femur: database study. Br Med J. 2002 Oct 19;325(7369):868–69. doi: 10.1136/bmj.325.7369.868. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Medical Advisory Secretariat. Prevention of falls and fall-related injuries in community-dwelling seniors: an evidence-based analysis. Ont Health Technol Assess Ser. 2008;8(2):1–78. [PMC free article] [PubMed] [Google Scholar]
  • 8.Masud T, Morris RO. Epidemiology of falls. Age Ageing. 2001 Nov 1;30(Suppl 4):3–7. doi: 10.1093/ageing/30.suppl_4.3. [DOI] [PubMed] [Google Scholar]
  • 9.Rubenstein LZ, Josephson KR. The epidemiology of falls and syncope. Clin Geriatr Med. 2002 May 1;18(2):141–58. doi: 10.1016/S0749-0690(02)00002-2. [DOI] [PubMed] [Google Scholar]
  • 10.Gill TM, Murphy TE, Gahbauer EA, Allore HG. Association of injurious falls with disability outcomes and nursing home admissions in community-living older persons. Am J Epidemiol. 2013 Aug 1;178(3):418–25. doi: 10.1093/aje/kws554. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Todd C, Skelton D. What are the main risk factors for falls amongst older people and what are the most effective interventions to prevent these falls? Copenhagen: World Health Organization Europe, Health Evidence Network report; Available from: http://www.euro.who.int/__data/assets/pdf_file/0018/74700/E82552.pdf. [Google Scholar]
  • 12.Ambrose AF, Paul G, Hausdorff JM. Risk factors for falls among older adults: a review of the literature. Maturitas. 2013 May 1;75(1):51–61. doi: 10.1016/j.maturitas.2013.02.009. [DOI] [PubMed] [Google Scholar]
  • 13.Huang AR. Future directions. In: Huang AR, Mallet L, editors. Medication-Related Falls in Older People: Causative Factors and Management Strategies Division of Geriatric Medicine, University of Ottawa, The Ottawa Hospital. Chap. 21. Ottawa, ON, Canada: Springer International Publishing; 2016. pp. 253–63. [DOI] [Google Scholar]
  • 14.Hartikainen S, Lönnroos E, Louhivuori K. Medication as a risk factor for falls: critical systematic review. Journals Gerontol Ser A. 2007 Oct 1;62(10):1172–81. doi: 10.1093/gerona/62.10.1172. [DOI] [PubMed] [Google Scholar]
  • 15.Leipzig RM, Cumming RG, Tinetti ME. Drugs and falls in older people: a systematic review and meta-analysis: I. Psychotropic drugs. J Am Geriatr Soc. 1999 Jan;47(1):30–39. doi: 10.1111/j.1532-5415.1999.tb01898.x. [DOI] [PubMed] [Google Scholar]
  • 16.Park H, Satoh H, Miki A, Urushihara H, Sawada Y. Medications associated with falls in older people: systematic review of publications from a recent 5-year period. Eur J Clin Pharmacol. 2015 Dec;71(12):1429–40. doi: 10.1007/s00228-015-1955-3. [DOI] [PubMed] [Google Scholar]
  • 17.Woolcott Meta-analysis of the impact of 9 medication classes on falls in elderly persons. Arch Intern Med. 2009 Nov 23;169(21):1952–60. doi: 10.1001/archinternmed.2009.357. [DOI] [PubMed] [Google Scholar]
  • 18.Van Der Velde N, Stricker BHC, Pols HAP, Van Der Cammen TJ. Withdrawal of fall-risk-increasing drugs in older persons: effect on mobility test outcomes. Drugs Aging. 2007 Aug;24(8):691–99. doi: 10.2165/00002512-200724080-00006. [DOI] [PubMed] [Google Scholar]
  • 19.The Swedish National board of Health and Welfare. Indikatorer för god läkemedelsterapi hos äldre. 2017. Available from https://www.socialstyrelsen.se/globalassets/sharepoint-dokument/artikelkatalog/ovrigt/2017-6-7.pdf.
  • 20.Bauer TK, Lindenbaum K, Stroka MA, Engel S, Linder R, Verheyen F. Fall risk increasing drugs and injuries of the frail elderly—evidence from administrative data. Pharmacoepidemiol Drug Saf. 2012 Dec;21(12):1321–27. doi: 10.1002/pds.3357. [DOI] [PubMed] [Google Scholar]
  • 21.De Winter S, Vanwynsberghe S, Foulon V, et al. Exploring the relationship between fall risk-increasing drugs and fall-related fractures. Int J Clin Pharm. 2016 Apr;38(2):243–51. doi: 10.1007/s11096-015-0230-0. Epub 2016 Jan 9. [DOI] [PubMed] [Google Scholar]
  • 22.Zia A, Kamaruzzaman SB, Tan MP. The consumption of two or more fall risk-increasing drugs rather than polypharmacy is associated with falls. Geriatr Gerontol Int. 2017 Mar;17(3):463–70. doi: 10.1111/ggi.12741. [DOI] [PubMed] [Google Scholar]
  • 23.Davies SJC, Jacob B, Rudoler D, Zaheer J, de Oliveira C, Kurdyak P. Benzodiazepine prescription in Ontario residents aged 65 and over: a population-based study from 1998 to 2013. Ther Adv Psychopharmacol. 2018 Mar;8(3):99–114. doi: 10.1177/2045125317743651. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Donnelly K, Bracchi R, Hewitt J, Routledge PA, Carter B. Benzodiazepines, Z-drugs and the risk of hip fracture: a systematic review and meta-analysis. PLoS One. 2017 Apr 27;12(4):e0174730. doi: 10.1371/journal.pone.0174730. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Verma AA, Khuu W, Tadrous M, Gomes T, Mamdani MM. Fixed-dose combination antihypertensive medications, adherence, and clinical outcomes: a population-based retrospective cohort study. PLoS Med. 2018 Jan 11;15(6):e1002584. doi: 10.1371/journal.pmed.1002584. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.de Vries M, Seppala LJ, Daams JG, et al. Fall-risk-increasing drugs: a systematic review and meta-analysis: I. Cardiovascular drugs. J Am Med Dir Assoc. 2018 Apr 1;19(4):371e1. doi: 10.1016/j.jamda.2017.12.013. [DOI] [PubMed] [Google Scholar]
  • 27.Kurdyak PA, Juurlink DN, Mamdani MM. The effect of antidepressant warnings on prescribing trends in Ontario, Canada. Am J Public Health. 2007 Apr;97(4):750–54. doi: 10.2105/AJPH.2006.087262. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Axmon A, Sandberg M, Ahlstrom G, Midlov P. Fall-risk-increasing drugs and falls requiring health care among older people with intellectual disability in comparison with the general population: a register study. PLoS One. 2018 Jun 19;13(6):e0199218. doi: 10.1371/journal.pone.0199218. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Peterson AB, Kegler SR. Deaths from fall-related traumatic brain injury—United States, 2008–2017. Morb Mortal Wkly Rep. 2020 Mar 3;69(9):225–30. doi: 10.15585/mmwr.mm6909a2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Teo DB, Wong HC, Yeo AW, Lai YW, Choo EL, Merchant RA. Characteristics of fall-related traumatic brain injury in older adults. Intern Med J. 2018 Sept;48(9):1048–55. doi: 10.1111/imj.13794. [DOI] [PubMed] [Google Scholar]
  • 31.Court-Brown CM, Clement ND, Duckworth AD, Biant LC, McQueen MM. The changing epidemiology of fall-related fractures in adults. Injury. 2017 Apr 1;48(4):819–24. doi: 10.1016/j.injury.2017.02.021. [DOI] [PubMed] [Google Scholar]
  • 32.Government of Canada. Age and sex, and type of dwelling data: key results from the 2016 Census. Ottawa, ON: Government of Canada; 2016. Available from: https://www150.statcan.gc.ca/n1/daily-quotidien/170503/dq170503a-eng.htm. [Google Scholar]
  • 33.Government of Ontario. Get coverage for prescription drugs. Get help paying for prescription drugs when you qualify for the Ontario Drug Benefit program. Toronto: Ontario: Government of Ontario; 2019. Available from: https://www.ontario.ca/page/get-coverage-prescription-drugs. [Google Scholar]
  • 34.Health Canada. Drug Identification Number (DIN) Ottawa ON: Health Canada; 2018. Available from: https://www.canada.ca/en/health-canada/services/drugs-health-products/drug-products/fact-sheets/drug-identification-number.html. [Google Scholar]
  • 35.World Health Organization. SHO Collaborating Centre for Drug Statistics Methodology. International language for drug utilization research. Oslo, Norway: World Health Organization; 2019. Available from: https://www.whocc.no/atc/structure_and_principles/ [Google Scholar]
  • 36.Krause W. Database of drugs. In: Krause W, editor. Drugs compromising male sexual health. Berlin: Springer; 2008. [Google Scholar]
  • 37.Canadian Institute for Health Information. Drug use among seniors in Canada, 2016. Ottawa, ON: Canadian Institute for Health Information; 2018. Available from: https://www.cihi.ca/sites/default/files/document/drug-use-among-seniors-2016-en-web.pdf. [Google Scholar]
  • 38.Canadian Institute for Health Information. Health system indicators. Statistics Canada; 2019. Publication No 82-221-X. Available from: https://www150.statcan.gc.ca/n1/pub/82-221-x/2013001/quality-qualite/qua8-eng.htm. [Google Scholar]
  • 39.Wilkins R. PCCF + Version 5F user’s guide: automated geographic coding based on the Statistics Canada postal code conversion files. Statistics Canada Health Statistics Division; 2010. Catalogue # 82F0086-XDB. Available from: http://odesi1.scholarsportal.info/documentation/PCCF+/V5F/MSWORD.PCCF5F.pdf. [Google Scholar]
  • 40.Lee JY, Holbrook A. The efficacy of fall-risk-increasing drug (FRID) withdrawal for the prevention of falls and fall-related complications: protocol for a systematic review and meta-analysis. Syst Rev. 2017 Dec;6(1):33. doi: 10.1186/s13643-017-0426-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Machado-Duque ME, Castano-Montoya JP, Medina-Morales DA, Castro-Rodriguez A, Gonzalez-Montoya A, Machado-Alba JE. Association between the use of benzodiazepines and opioids with the risk of falls and hip fractures in older adults. Int Psychogeriatr. 2018 Jul;30(7):941–46. doi: 10.1017/S1041610217002745. [DOI] [PubMed] [Google Scholar]
  • 42.Richardson K, Bennett K, Kenny RA. Polypharmacy including falls risk-increasing medications and subsequent falls in community-dwelling middle-aged and older adults. Age Ageing. 2015 Oct 12;44(1):90–96. doi: 10.1093/ageing/afu141. [DOI] [PubMed] [Google Scholar]
  • 43.Seppala LJ, Wermelink AM, de Vries M, et al. Fall-risk-increasing drugs: a systematic review and meta-analysis: II. Psychotropics. J Am Med Dir Assoc. 2018 Apr 1;19(4):371e11. doi: 10.1016/j.jamda.2017.12.098. [DOI] [PubMed] [Google Scholar]
  • 44.Seppala LJ, van de Glind EM, Daams JG, et al. Fall-risk-increasing drugs: a systematic review and meta-analysis: III. Others. J Am Med Dir Assoc. 2018 Apr 1;19(4):372e1. doi: 10.1016/j.jamda.2017.12.099. [DOI] [PubMed] [Google Scholar]
  • 45.Schneeweiss S, Seeger JD, Maclure M, Wang PS, Avorn J, Glynn RJ. Performance of comorbidity scores to control for confounding in epidemiologic studies using claims data. Am J Epidemiol. 2001 Nov 1;154(9):854–64. doi: 10.1093/aje/154.9.854. [DOI] [PubMed] [Google Scholar]
  • 46.Caughey GE, Roughead EE, Vitry AI, McDermott RA, Shakib S, Gilbert AL. Comorbidity in the elderly with diabetes: identification of areas of potential treatment conflicts. Diabetes Res Clin Pract. 2010 Mar 1;87(3):385–93. doi: 10.1016/j.diabres.2009.10.019. [DOI] [PubMed] [Google Scholar]
  • 47.Correa-Pérez A, Delgado-Silveira E, Martín-Aragón S, Rojo-Sanchís AM, Cruz-Jentoft AJ. Fall-risk increasing drugs and prevalence of polypharmacy in older patients discharged from an orthogeriatric unit after a hip fracture. Aging Clin Exp Res. 2019 Jul;31(7):969–75. doi: 10.1007/s40520-018-1046-2. [DOI] [PubMed] [Google Scholar]
  • 48.Milton JC, Hill-Smith I, Jackson SHD. Prescribing for older people. BMJ. 2008 Mar 13;336(7644):606–09. doi: 10.1136/bmj.39503.424653.80. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Maher RL, Hanlon J, Hajjar ER. Clinical consequences of polypharmacy in elderly. Expert Opin Drug Saf. 2014 Jan 1;13(1):57–65. doi: 10.1517/14740338.2013.827660. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Levy AR, O’Brien BJ, Sellors C, Grootendorst P, Willison D. Coding accuracy of administrative drug claims in the Ontario Drug Benefit database. Can J Clin Pharmacol. 2003 Jan 1;10(2):67–71. [PubMed] [Google Scholar]
  • 51.Aiken AB, Mahar AL, Kurdyak P, Whitehead M, Groome PA. A descriptive analysis of medical health services utilization of Veterans living in Ontario: a retrospective cohort study using administrative healthcare data. BMC Health Serv Res. 2016 Dec;16(1):351. doi: 10.1186/s12913-016-1596-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52.Liu AR, Hildebrand AM, Dixon S, et al. A matched case-control study to assess the association between non-steroidal anti-inflammatory drug use and thrombotic microangiopathy. PLoS One. 2018 Aug 24;13(8):1–10. doi: 10.1371/journal.pone.0202801. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Macri JC, Iaboni A, Kirkham JG, et al. Association between antidepressants and fall-related injuries among long-term care residents. Am J Geriatr Psychiatry. 2017 Dec 1;25(12):1326–36. doi: 10.1016/j.jagp.2017.08.014. [DOI] [PubMed] [Google Scholar]
  • 54.Sarrazin MSV, Rosenthal GE. Finding pure and simple truths with administrative data. JAMA. 2012 Apr 4;307(13):1433–35. doi: 10.1001/jama.2012.404. [DOI] [PubMed] [Google Scholar]

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