Frailty as a predictor of future falls among community dwelling older people a systematic review and meta analysis

Review ArticleFrailty as a Predictor of Future Falls Among Community-Dwelling Older People: A Systematic Review and Meta-Analysis Japan Green Medical Centre, London, United Kingdom Keywo

Review Article

Frailty as a Predictor of Future Falls Among Community-Dwelling

Older People: A Systematic Review and Meta-Analysis

Japan Green Medical Centre, London, United Kingdom

Keywords:

Frailty

falls

community-dwelling older people

a b s t r a c t

Background: Although multiple longitudinal studies have investigated frailty as a predictor of future falls, the results were mixed Thus far, no systematic review or meta-analysis on this topic has been conducted Objective: To review the evidence of frailty as a predictor of future falls among community-dwelling older people

Methods: Systematic review of literature and meta-analysis were performed using 6 electronic databases (Embase, Scopus, MEDLINE, CINAHL Plus, PsycINFO, and the Cochrane Library) searching for studies that prospectively examined risk of future fall risk according to frailty among community-dwelling older people published from 2010 to April 2015 with no language restrictions

Results: Of 2245 studies identified through the systematic review, 11 studies incorporating 68,723 individuals were included in the meta-analysis Among 7 studies reporting odds ratios (ORs), frailty and prefrailty were significantly associated with higher risk of future falls (pooled OR ¼ 1.84, 95% confidence interval [95% CI]¼ 1.43e2.38, P < 001; pooled OR ¼ 1.25, 95% CI ¼ 1.01e1.53, P ¼ 005, respectively) Among 4 studies reporting hazard ratios (HRs), whereas frailty was significantly associated with higher risk of future falls (pooled HR¼ 1.24, 95% CI ¼ 1.10e1.41, P < 001), future fall risk according to prefrailty did not reach statistical significance (pooled HR ¼ 1.14, 95% CI ¼ 0.95e1$36, P ¼ 15) High heterogeneity was noted among 7 studies reporting ORs and seemed attributed to difference in gender proportion of cohorts according to subgroup and meta-regression analyses

Conclusions: Frailty is demonstrated to be a significant predictor of future falls among community-dwelling older people despite various criteria used to define frailty The future fall risk according to frailty seemed to be higher in men than in women

Ó 2015 AMDA e The Society for Post-Acute and Long-Term Care Medicine

Older people are a highly heterogeneous population Although

people generally develop diseases and disabilities as they age, the

trajectory and rate of change in health and functional status vary

widely in each individual and persons with the same chronological

age can have very different biological ages.1 Therefore, it is

chal-lenging to measure the heterogeneity of the aging process in the

elderly

One of the potential concepts to quantify the overall health

diversity of older people is frailty Frailty is a biological syndrome

characterized by reduced reserve capacity in multiple physiologic

systems and increased vulnerability to stressors due to age-related

cumulative deficits.2 In general, people are more likely to develop

frailty as they get older.2,3Prevalence of frailty among community-dwelling people aged 65 years and older is widely variable depend-ing on settdepend-ings, rangdepend-ing from 4.0% to 59.1%.3Frailty has been shown to

be associated with multiple adverse health outcomes, including disability, falls, hospitalization, institutionalization, and death.2 Among these, fall is a leading cause of mortality in older people.4 Fall is not only associated with a wide range of negative conse-quences, such as disabilities, fear of falling, and impaired quality of life,4,5 but also associated with increased health care burden and costs.6 Incidence of fall is high among older people; one-third of elderly aged 65 and older fall every year, and the incidence of falling increases up to 50% among those 80 years and older.7Given the ex-panding elderly population worldwide, preventing falls has been a major public concern of authorities in many countries.4,8,9One of the important key issues for preventing falls is identification of risk fac-tors for falling

Weakness, impaired balance, and abnormal gait are major com-ponents of physical frailty2,10and are likely to increase the risk of

The author declares no conflicts of interest.

* Address correspondence to Gotaro Kojima, MD, Japan Green Medical Centre, 10

Throgmorton Avenue, London EC2N 2DL, UK.

E-mail address: gotarokojima@yahoo.co.jp.

JAMDA

j o u r n a l h o m e p a g e : w w w j a m d a c o m

http://dx.doi.org/10.1016/j.jamda.2015.06.018

1525-8610/Ó 2015 AMDA e The Society for Post-Acute and Long-Term Care Medicine.

falling in older people Furthermore, frail older people may be at high

risk of falling because of decreased functional reserve capacity in

maintaining position, balance, and coordination, and increased

vulnerability to such stressors as accidents, disease symptoms, or

adverse drug reactions The evidence of frailty as a predictor of falls in

community-dwelling older people comes from prospective cohort

studies with mixed results Most of the studies demonstrated that the

frail elderly were more likely to fall than the nonfrail,10e17but a few

showed nonsignificant results.18e20Thus far, no systematic review or

meta-analysis studies on this topic have been conducted in the

literature Therefore, the objectives of this systematic review were (1)

to identify and compare prospective cohort studies examining frailty

as a predictor of future falls among community-dwelling older

peo-ple, and (2) to combine those data to synthesize pooled risk estimates

of frailty for future falls

Methods

This study was conducted according to a protocol developed with

adherence to Meta-analysis of Observational Studies in Epidemiology

(MOOSE)21statements by a clinician researcher who was trained for

internal medicine and geriatric medicine and is currently working as

a general practitioner

Data Sources and Search Strategy

A systematic search of the literature was performed in April 2015

using Embase, Scopus, MEDLINE, CINAHL Plus, PsycINFO, and the

Cochrane Library for studies written in any languages and published

from 2000 through present The search terms used included

(Acci-dental falls (Medical Subject Heading (MeSH))) OR (Falling (MeSH))

OR (Falls (MeSH)) OR (Fall*) AND (Frailty) using an explosion function

if available PubMed and reference lists of relevant studies were also

hand searched

Study Selection

Prospective cohort studies examining frailty as a risk factor for

future falls were selected using the following inclusion criteria:

1 Prospective study design

2 Community-dwelling individuals

3 Sample size at least 100 individuals

4 Individuals aged 60 years or older or mean age of 70 years or

older

5 Frailty was defined by criteria originally designed to measure

frailty and validated in population-based studies or its

modi-fied versions

6 Adjusted or unadjusted odds ratio (OR), risk ratio (RR), or

hazard ratio (HR) as a risk measure reported or able to be

calculated from available data

Studies were excluded if they substituted other measures, such as

disability or walking speed, to define frailty or used selected samples

with certain conditions or diseases If multiple studies used the same

data or cohort, a study with the largest number of individuals was

selected

Data Extraction

A standardized data collection tool was used to collect data from

the eligible studies The data extracted included the following:first

author, year of publication, location, sample size, proportion of male

individuals, age, frailty criteria, outcome, follow-up period, frequency

of fall monitoring, and effect measure When single fallers and

recurrent fallers were used as separate outcomes and data of any fallers (single fallersþ recurrent fallers) were not available, calcula-tion of an OR of any fallers compared with nonfallers was attempted,

or the data of only recurrent fallers were used Some frailty criteria

define “prefrail” or similar terminology, which is an intermediate frailty status between frail and nonfrail/robust, and these data were also collected and used for meta-analyses if available When 2 or more frailty criteria were used in a study, the most commonly used Fried phenotype criteria or its modified versions were selected if available or criteria less modified from the original were selected Methodological Quality Assessment

Eligible studies were further examined for methodological quality using the Newcastle-Ottawa scale for cohort studies This scale has 9 criteria to examine the methodological quality of cohort studies Each

of the included studies was assessed using this scale and considered

to have adequate quality to be included for meta-analysis if it met 5

or more items out of 9

Statistical Analysis

OR, RR, and HR along with 95% confidence interval (95% CI) of future fall risk for frailty or prefrailty compared with nonfrailty/ robust were extracted directly from the articles or calculated based

on raw numbers shown in the articles All analyses were performed using StataIC 13 (Stata Corp, College Station, TX), Review Manager 5 (Computer program, Version 5.2; The Nordic Cochrane Centre, The Cochrane Collaboration, Copenhagen, Denmark), and Comprehensive Meta-Analysis version 3.3 (Biostat, Englewood, NJ)

OR, RR, and HR were log-transformed SEs of the log-transformed

OR, RR, and HR were calculated by dividing the difference between log-transformed upper and lower limits of 95% CI by 3.92 These data

of each study were entered into the Review Manager and Compre-hensive Meta-Analysis to perform meta-analysis and meta-regression analysis The c2 test was used to assess heterogeneity across the studies, and heterogeneity was considered present when P value was less than 0.10 I2statistic was used to quantify the degree of hetero-geneity and I2values of 25%, 50%, and 75% were considered as low, moderate, and high heterogeneity, respectively.22 When high het-erogeneity was observed, subgroup analyses and random-effects meta-regression were performed to identify possible causes of het-erogeneity Publication bias was assessed by visually inspecting the funnel plots

Results Selection Processes

Figure 1 shows a flow chart of the literature search and study selection with numbers of studies at each stage Of 2245 citations identified by the systematic review of the literature using 6 electronic databases, 1306 duplicated articles were excluded and 920 articles were excluded through review of titles and abstracts One additional article18was found by manual search and added, leaving 20 articles for full-text review Of these, 9 articles were excluded because they were review articles (n¼ 2), did not classify frailty and nonfrailty status (n¼ 2),23,24

included nonecommunity-dwelling populations (n¼ 2), and used the same cohort (n ¼ 1) Neither abstracts nor full texts were able to be obtained for 2 studies Eleven articles were left and confirmed that they met the inclusion criteria.10e20Eleven arti-cles provided data for 68,723 community-dwelling older people and these were included in this systematic review These studies were then assessed for methodological quality using the Newcastle-Ottawa

quality assessment scale for cohort studies All of the 11 studies met

at least 5 criteria of 9 and were included for the meta-analyses

(Table 1)

Study Characteristics

Characteristics of the 11 studies included in this study are

sum-marized inTable 1.10e20More than half of the included studies were

from the United States,10,12e15,18 3 were from Europe,11,19,20 1 was

from Taiwan,17and 1 included cohorts from multiple countries.16The

largest study used a cohort of the Global Longitudinal Study of

Osteoporosis in Women, consisting of 48,636 women from multiple countries in Europe, North America, and Australia,16and 6 studies involved fewer than 1000 individuals.14,15,17e20Three studies had all-female cohorts,13,16,181 had an all-male cohort,12and the rest had cohorts including 30.3% to 53.5% male individuals.10,11,14,15,17,19,20The mean age of the included studies with available data ranged from 72.1

to 82.0 years old Original or modified Fried phenotype criteria were most commonly used by 8 of the 11 studies.10,12e16,18,20 The other criteria used were Study of Osteoporotic Fractures frailty index,12,14,19 Longitudinal Aging Study Amsterdam frailty instrument,11 and Chinese-Canadian Study of Health and Aging Clinical Frailty Scale.17

Three studies used 2 different kinds of frailty criteria.12,14,19 Recur-rent falls was most frequently used as an outcome11e14,16,17,19,20and first fall or any falls were used by 4 studies.10,15,17,18Follow-up periods ranged from 1 year to 4 years Although 6 studies monitored falls every 1 to 18 months,10e14,18 the other studies identified falls by asking individuals if they had 1 or more falls at the end of the

follow-up period.15e17,19,20 Cox proportional hazard models were used in 4 studies10,11,14,18 presenting HRs Seven studies presented ORs calculated using logis-tic regression models or from raw numbers of 2  2

table-s.12,13,15e17,19,20No study used RR

Frailty as a Predictor of Future Falls Meta-analysis of studies presenting OR ORs from 7 studies, including a total of 60,577 individuals, were combined to calculate a pooled OR and 95% CI using a random-effects model due to high heterogeneity Frailty was significantly associated with higher future fall risk (pooled OR¼ 1.84, 95% CI ¼ 1.43e2.38,

P< 001,c2¼ 26.41, df ¼ 6, I2¼ 77%) Prefrailty was examined by 4 of these 7 studies and was also found to be associated with significantly higher future fall risk (pooled OR¼ 1.25, 95% CI ¼ 1.01e1.53, P ¼ 04,

c2¼ 12.83, df ¼ 3, I2¼ 77%) (Figure 2A)

Meta-analysis of studies presenting HR Four studies with 8146 individuals presented HRs for frailty, among which 3 studies presented HRs for prefrailty Fixed-effects models were used to calculate pooled HR and 95% CI, as heteroge-neity was low for frailty and prefrailty Although frailty was signi fi-cantly associated with higher future fall risk (pooled HR¼ 1.24, 95%

CI¼ 1.10e1.41, P < 001,c2¼ 5.11, df ¼ 3, I2¼ 41%), an association between prefrailty and fall risk did not reach a statistical significance Fig 1 Flow chart of study selection.

Table 1

Summary of Included Studies on Future Fall Risk Associated With Frailty Among Community-Dwelling Older People

Period, y

Frequency of Monitoring

Effect Measure Qualityz

Tom et al 16 2013 USA, Europe,

Australia

aOR, adjusted OR; aHR, adjusted HR; CSHA-CFS, Chinese-Canadian Study of Health and Aging Clinical Frailty Scale; CSBA index, Conselice Study of Brain Aging index; LASA, Longitudinal Aging Study Amsterdam frailty instrument; Recurrent falls, 2 or more falls; SOF, Study of Osteoporotic Fractures frailty index.

*Sample size of cohort actually used for frailty and fall analysis, or of entire cohort if not available.

y Mean age of analytic sample if available, otherwise mean age of entire sample or age criterion for inclusion.

z Number of methodological quality criteria met using the Newcastle-Ottawa scale for cohort studies (range: 0e9).

(pooled HR¼ 1.14, 95% CI ¼ 0.95e1.36, P ¼ 15,c2¼ 2.16, df ¼ 2,

I2¼ 7%) (Figure 2B)

Subgroup analysis and meta-regression analysis

High heterogeneity was noted among the 7 studies presenting

ORs.12,13,15e17,19,20 Subgroup analyses were attempted based on age

and gender, 2 well-known factors associated with frailty,2,3as well as

other factors including location (United States versus others), sample

size (n 1000 versus <1000), frailty criteria (original or modified Fried phenotype versus others), outcome (any falls versus recurrent falls), follow-up period (1 year versus more than 1 year), and fre-quency of fall monitoring (1 year or more versus less than 1 year) Mean age, however, of the 7 studies was in a relatively narrow range from 67.7 to 76.7 years old and not all studies presented mean age,16 thus subgroup analysis according to age was not performed When 1 study12consisting of all men was excluded, a meta-analysis Fig 2 Forest plots presenting effect of frailty and prefrailty on future fall risk according to OR (A: 6 studies, C: 5 studies including women) and HR (B: 4 studies) df, degrees of freedom; fixed, fixed-effects model; IV, inverse variance; Random, random-effects model.

incorporating the rest of the 6 studies including women (female

proportion 46.5%e100%)10,13e17 showed that I2 statistic reduced

considerably from 77% down to 17% Pooled OR combining these 6

studies using a fixed-effects model was slightly decreased but was

statistically significant (pooled OR ¼ 1.65, 95% CI ¼ 1.53e1.79,

P < 001,c2 ¼ 6.00, df ¼ 5, I2¼ 17%) (Figure 2C) Other subgroup

analyses showed any subgroups including this all-men study12had

high heterogeneity and any subgroups without had low

heteroge-neity (data not shown) Disparity in gender proportion was

specu-lated to be an important moderator influencing future fall risk

according to frailty based on the results of the subgroup analyses as

well as the fact that gender disparity has been shown to be associated

with both falls and frailty.3,25 This possibility was further explored

using meta-regression analysis A random-effects meta-regression

model with the proportion of male individuals in each study as a

covariate demonstrated that higher male proportion was significantly

associated with higher future fall risk according to frailty

(coefficient ¼ 0.0079 per 1% increase in male proportion, SE ¼ 0.0027,

P ¼ 003, goodness of fit P ¼ 08) The male proportion of cohorts

explained 63% of the between-study variance (R2 analog ¼ 0.63)

Figure 3 shows a bubble plot with a meta-regression line, which

suggests that higher male proportion is associated with higher future

fall risk according to frailty

Publication bias assessment

Funnel plots were illustrated for 2 study groups presenting ORs

and HRs separately Although difficult to interpret because of the

small number of studies, especially for studies providing HRs or

prefrailty outcomes, visual inspection of the funnel plots suggests the

presence of publication bias; asymmetry was noted in both plots with

more studies with results favoring higher future fall risk by frailty

(Figures 4A and 4B)

Discussion This is, to the best of my knowledge, thefirst study to perform systematic review and meta-analyses on future fall risk associated with frailty among community-dwelling older people Eleven studies with a total of 68,723 individuals presenting ORs and HRs as fall risk measures for frailty status were identified by this systematic review

A meta-analysis combining theirfindings consistently showed frailty was associated with higher future fall risk despite different frailty criteria and effect measures used Substantial heterogeneity was observed across the studies presenting ORs and difference in gender proportion of each study was considered to be a possible moderator causing the heterogeneity based on the findings of the subgroup analysis and meta-regression analysis

Two studies23,24could not be included in the meta-analyses because, instead of comparing frailty versus nonfrailty, they evalu-ated frailty status in a grade manner using the frailty index The frailty index, a continuous score ranging from 0 to 1, is another well-validated approach to operationalize frailty based on a cumulative

deficit model and has been shown to have a better discriminative ability to identify mortality risk than Fried phenotype criteria.26

A Canadian study with 3985 women aged 55 years and older showed that the frailty index at baseline was significantly associated with increased risk of future falls during the third year (adjusted

OR¼ 1.02 per 0.01 increase in the frailty index, P < 001) and the area under the receiver operating characteristic curve was 0.69 (95%

CI¼ 0.67e0.71).24Another study including 3257 Chinese community-dwellers aged 55 years and older from the Beijing Longitudinal Study

of Aging divided the cohort into 5 groups based on the frailty index (0.03, 0.03e0.10, 0.10e0.20, 0.21e0.5, and >0.5) and showed that a higher level of frailty was significantly associated with future fall risk (adjusted OR¼ 1.54 per increase in frailty level, 95% CI ¼ 1.34e1.76).23

Thefindings of these studies using a different approach of the frailty

fitted meta-regression line for the association between OR of future fall risk for frailty and proportion of male individuals.

index further support the association between frailty and higher

future fall risk shown in this meta-analysis

Higher fall risk associated with frailty was observed in studies

including more men in this systematic review Although women are

reported as more likely to be frail3and more likely to fall27than men,

mechanisms underlying thisfinding are not clear Gender disparity in

frailty-associated fall risk could be related to differences in health

conditions, physical components, lifestyle factors, behavioral

pat-terns, or mixed Among these, gender difference in physical activity

may explain the higher fall risk in frail men Compared with women,

men are more physically active28and therefore may be more likely to

encounter situations in which frailty is influential to their

maintain-ing balance, stability, and coordination In such situations, men’s

relatively higher center of gravity and heavier weight may predispose

them further to higher risk of falling associated with frailty

Falling as a research outcome is difficult to investigate among

older people because it mostly relies on self-report information and

therefore its accuracy may be compromised by memory disorders,

especially when a fall monitoring covers a long period of time

Therefore, it is important to recognize how falls are identified

Various methodologies were used across the studies to obtain fall

information from participants Three studies interviewed participants

for incident falls,15,19,20and other methods included post card,12,13

calendar,11,14and telephone.13,17Three studies did not provide clear

explanation of how falls were reported.10,16,18

Among the studies using original or modified Fried phenotype

criteria, all but the original study modified 1 or more of the original 5

criteria components according to data availability or study designs

However, it is not the case only with these included studies in this

review but also with most other published studies.29The modi

fica-tion of the original criteria can potentially result in biasing the study

findings.28

Four studies examined any falls or incidentfirst fall10,15,17,18and

7 studies examined recurrent falls or incident second

fall-s.11e14,16,19,20 They are theoretically different outcomes although

these outcomes were treated as the same fall outcome when

meta-analyzed in this review because of the relatively small number of

studies if stratified Especially results based on recurrent falls may

be affected by nature and consequences of thefirst fall For example,

a serious or injurious first fall may cause disabilities or fear of

falling, which can lead to less mobility or physical activities,

even-tually limiting chances of second falls Pooled risk estimates among

studies examining any or incident first fall and those examining

recurrent or incident second falls were calculated in the

meta-analysis; pooled OR¼ 2.05 (95% CI ¼ 1.46e2.89, P < 0001, from 2

studies15,17 usingfixed-effects model) and pooled OR ¼ 1.77 (95%

CI¼ 1.28e2.43, P ¼ 0005, from 5 studies12,13,16,19,20using

random-effects model), respectively

This study has some limitations First, a few of the included studies15,17,19did not present adjusted OR but only crude ORs, which were incorporated into the meta-analyses However, because of possible confounding effects on frailty and falls, especially by age and gender as well as other factors, adjusted ORs would better describe the true associations Excluding these studies in the meta-analysis did not change pooled OR or I2statistics substantially (pooled OR¼ 1.80, 95% CI¼ 1.27e2.57, P ¼ 001, df ¼ 3, I2¼ 88%) Second, publication bias favoring studies with positive results was suggested by visual inspection of funnel plots and therefore pooled estimates may be overestimated

One of this study’s strengths is that it is the first systematic review and meta-analysis on associations between frailty and future fall risk among community-dwelling older people Another strength is its robust methodology, including extensive and reproducible systematic reviews using 6 databases and assessments of methodological quality, publication bias, and heterogeneity across the included studies In addition, subgroup analyses and meta-regression analyses were performed to investigate possible causes of the heterogeneity Despite different frailty criteria and methodology used by the included studies, the meta-analyses consistently demonstrated frailty

as a significant predictor of future falling

In summary, this study provides the first evidence of the association between frailty and higher future fall risk among community-dwelling older people based on the comprehensive sys-tematic review and meta-analyses Subgroup and meta-regression analyses suggest a gender disparity in future fall risk associated with frailty

Given the detrimental effects of falls in older people, it is impor-tant for health care providers, especially geriatricians and those who treat elderly individuals, to recognize frailty as a risk factor for future falling Future research should be directed to whether treating or reversing frailty should prevent falling among frail elderly and also to investigation of mechanisms underlying the gender disparity in the future fall risk according to frailty, which may lead to further un-derstanding frailty in relation to falls and developing more effective interventions for both frailty and falls

References

1 Mitnitski AB, Graham JE, Mogilner AJ, et al Frailty, fitness and late-life mortality in relation to chronological and biological age BMC Geriatr 2002;2:1.

2 Clegg A, Young J, Iliffe S, et al Frailty in elderly people Lancet 2013;381: 752e762.

3 Collard RM, Boter H, Schoevers RA, et al Prevalence of frailty in community-dwelling older persons: A systematic review J Am Geriatr Soc 2012;60: 1487e1492.

Fig 4 Funnel plots for future fall risk according to frailty (A: studies presenting ORs, B: studies presenting HRs).

4 Centers for Disease Control and Prevention Falls among older adults: An

overview 2013 Available at: http://www.cdc.gov/homeandrecreationalsafety/

falls/adultfalls.html Accessed April 29, 2015.

5 Parry SW, Deary V, Finch T, et al The STRIDE (Strategies to Increase

con-fidence, InDependence and Energy) study: Cognitive behavioural

therapy-based intervention to reduce fear of falling in older fallers living in the

communitydstudy protocol for a randomised controlled trial Trials 2014;

15:210.

6 Centers for Disease Control and Prevention Costs of falls among older adults.

2015 Available at: http://www.cdc.gov/HomeandRecreationalSafety/Falls/

fallcost.html Accessed April 29, 2015.

7 Tinetti ME, Speechley M, Ginter SF Risk factors for falls among elderly persons

living in the community N Engl J Med 1988;319:1701e1707.

8 National Institute for Health and Care Excellence (UK) NICE clinical guideline,

falls: Assessment and prevention of falls in older people 2013 Available at:

https://www.nice.org.uk/guidance/cg161 Accessed April 29, 2015.

9 Public Health Agency of Canada (Canada) You CAN Prevent Falls! 2011.

Available at: http://www.phac-aspc.gc.ca/seniors-aines/publications/public/

injury-blessure/prevent-eviter/index-eng.php Accessed April 29, 2015.

10 Fried LP, Tangen CM, Walston J, et al Frailty in older adults: Evidence for a

phenotype J Gerontol A Biol Sci Med Sci 2001;56:M146eM156.

11 de Vries OJ, Peeters GM, Lips P, et al Does frailty predict increased risk of falls

and fractures? A prospective population-based study Osteoporos Int 2013;24:

2397e2403.

12 Ensrud KE, Ewing SK, Cawthon PM, et al A comparison of frailty indexes for the

prediction of falls, disability, fractures, and mortality in older men J Am Geriatr

Soc 2009;57:492e498.

13 Ensrud KE, Ewing SK, Taylor BC, et al Frailty and risk of falls, fracture, and

mortality in older women: The study of osteoporotic fractures J Gerontol A Biol

Sci Med Sci 2007;62:744e751.

14 Kiely DK, Cupples LA, Lipsitz LA Validation and comparison of two

frailty indexes: The MOBILIZE Boston Study J Am Geriatr Soc 2009;57:

1532e1539.

15 Samper-Ternent R, Karmarkar A, Graham J, et al Frailty as a predictor of falls in

older Mexican Americans J Aging Health 2012;24:641e653.

16 Tom SE, Adachi JD, Anderson FA Jr, et al Frailty and fracture, disability, and

falls: A multiple country study from the global longitudinal study of

osteopo-rosis in women J Am Geriatr Soc 2013;61:327e334.

17 Wu TY, Chie WC, Yang RS, et al Risk factors for single and recurrent falls: A prospective study of falls in community dwelling seniors without cognitive impairment Prev Med 2013;57:511e517.

18 Bandeen-Roche K, Xue QL, Ferrucci L, et al Phenotype of frailty: Character-ization in the women’s health and aging studies J Gerontol A Biol Sci Med Sci 2006;61:262e266.

19 Forti P, Rietti E, Pisacane N, et al A comparison of frailty indexes for prediction

of adverse health outcomes in an elderly cohort Arch Gerontol Geriatr 2012; 54:16e20.

20 Sheehan KJ, O’Connell MD, Cunningham C, et al The relationship between increased body mass index and frailty on falls in community dwelling older adults BMC Geriatr 2013;13:132.

21 Stroup DF, Berlin JA, Morton SC, et al Meta-analysis of observational studies in epidemiology: A proposal for reporting Meta-analysis of observational studies

in epidemiology (MOOSE) group JAMA 2000;283:2008e2012.

22 Higgins JP, Thompson SG, Deeks JJ, et al Measuring inconsistency in meta-analyses BMJ 2003;327:557e560.

23 Fang X, Shi J, Song X, et al Frailty in relation to the risk of falls, fractures, and mortality in older Chinese adults: Results from the Beijing Longitudinal Study

of Aging J Nutr Health Aging 2012;16:903e907.

24 Li G, Ioannidis G, Pickard L, et al Frailty index of deficit accumulation and falls: Data from the Global Longitudinal Study of Osteoporosis in Women (GLOW) Hamilton cohort BMC Musculoskelet Disord 2014;15:185.

25 Stevens JA, Sogolow ED Gender differences for non-fatal unintentional fall related injuries among older adults Inj Prev 2005;11:115e119.

26 Rockwood K, Andrew M, Mitnitski A A comparison of two approaches to measuring frailty in elderly people J Gerontol A Biol Sci Med Sci 2007;62: 738e743.

27 Deandrea S, Lucenteforte E, Bravi F, et al Risk factors for falls in community-dwelling older people: A systematic review and meta-analysis Epidemiology 2010;21:658e668.

28 Centers for Disease Control and Prevention Facts about physical activity 2014 Available at: http://www.cdc.gov/physicalactivity/data/facts.html Accessed April 29, 2015.

29 Theou O, Cann L, Blodgett J, et al Modifications to the frailty phenotype criteria: Systematic review of the current literature and investigation of 262 frailty phenotypes in the Survey of Health, Ageing, and Retirement in Europe Ageing Res Rev 2015;21:78e94.