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Original Investigation |

Comparison of 2 Frailty Indexes for Prediction of Falls, Disability, Fractures, and Death in Older Women FREE

Kristine E. Ensrud, MD, MPH; Susan K. Ewing, MS; Brent C. Taylor, PhD; Howard A. Fink, MD, MPH; Peggy M. Cawthon, PhD; Katie L. Stone, PhD; Teresa A. Hillier, MD, MS; Jane A. Cauley, DrPH; Marc C. Hochberg, MD; Nicolas Rodondi, MD, MAS; J. Kathleen Tracy, PhD; Steven R. Cummings, MD; Study of Osteoporotic Fractures Research Group
[+] Author Affiliations

Author Affiliations: Center for Chronic Disease Outcomes Research, Veterans Affairs Medical Center, and Department of Medicine and Division of Epidemiology and Community Health, University of Minnesota, Minneapolis (Drs Ensrud, Taylor, and Fink); Department of Epidemiology and Biostatistics, University of California, San Francisco (Ms Ewing), and Research Institute, California Pacific Medical Center (Drs Cawthon, Stone, and Cummings), San Francisco; Center for Health Research, Kaiser Permanente Northwest/Hawaii, Portland, Oregon (Dr Hillier); Department of Epidemiology, University of Pittsburgh, Pittsburgh, Pennsylvania (Dr Cauley); Departments of Medicine (Dr Hochberg) and Epidemiology (Dr Tracy), University of Maryland, Baltimore; and University Outpatient Clinic, Department of Community Medicine and Public Health, University of Lausanne, Lausanne, Switzerland (Dr Rodondi).Group Information: A list of the Study of Osteoporotic Fractures Research Group was published in Arch Intern Med. 2007;167(2):138.


Arch Intern Med. 2008;168(4):382-389. doi:10.1001/archinternmed.2007.113.
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Published online

Background  Frailty, as defined by the index derived from the Cardiovascular Health Study (CHS index), predicts risk of adverse outcomes in older adults. Use of this index, however, is impractical in clinical practice.

Methods  We conducted a prospective cohort study in 6701 women 69 years or older to compare the predictive validity of a simple frailty index with the components of weight loss, inability to rise from a chair 5 times without using arms, and reduced energy level (Study of Osteoporotic Fractures [SOF index]) with that of the CHS index with the components of unintentional weight loss, poor grip strength, reduced energy level, slow walking speed, and low level of physical activity. Women were classified as robust, of intermediate status, or frail using each index. Falls were reported every 4 months for 1 year. Disability (≥1 new impairment in performing instrumental activities of daily living) was ascertained at 4½ years, and fractures and deaths were ascertained during 9 years of follow-up. Area under the curve (AUC) statistics from receiver operating characteristic curve analysis and −2 log likelihood statistics were compared for models containing the CHS index vs the SOF index.

Results  Increasing evidence of frailty as defined by either the CHS index or the SOF index was similarly associated with an increased risk of adverse outcomes. Frail women had a higher age-adjusted risk of recurrent falls (odds ratio, 2.4), disability (odds ratio, 2.2-2.8), nonspine fracture (hazard ratio, 1.4-1.5), hip fracture (hazard ratio, 1.7-1.8), and death (hazard ratio, 2.4-2.7) (P < .001 for all models). The AUC comparisons revealed no differences between models with the CHS index vs the SOF index in discriminating falls (AUC = 0.61 for both models; P = .66), disability (AUC = 0.64; P = .23), nonspine fracture (AUC = 0.55; P = .80), hip fracture (AUC = 0.63; P = .64), or death (AUC = 0.72; P = .10). Results were similar when −2 log likelihood statistics were compared.

Conclusion  The simple SOF index predicts risk of falls, disability, fracture, and death as well as the more complex CHS index and may provide a useful definition of frailty to identify older women at risk of adverse health outcomes in clinical practice.

Figures in this Article

Frailty is defined variably because many factors have been reported to reflect frailty in older adults1 and it has not yet emerged as a discrete clinical syndrome.2,3 Despite these limitations, it is recognized that older persons characterized as frail have a higher risk of adverse health outcomes that is not entirely explained by advanced age, poorer functional status, or greater prevalence of comorbidities.4

In an attempt to operationalize and standardize the definition of frailty, Fried et al,5 using data from the Cardiovascular Health Study (CHS), proposed a phenotype of frailty (CHS index) in which 3 or more of the following 5 components were present: unintentional weight loss, self-reported reduced energy level, reduced grip strength, slow walking speed, and low level of physical activity. Frailty as defined by the CHS index was associated with an increased risk of falls, hospitalization, disability, and death. Subsequently, the predictive validity of the CHS index has been confirmed in other cohorts.610 It has been suggested that the CHS index be used to screen older persons for frailty.5

However, assessment of frailty using the CHS index is impractical in the clinical setting. Ascertainment of 3 of its components (grip strength, walking speed, and physical activity) requires knowledge of the underlying distribution of the measure in a given population and identification of these components also depends on sex and body size. Components including physical activity and timed walks are often infeasible to evaluate in the clinic because of tight schedules and space constraints. Unintentional weight loss is a component of the CHS frailty phenotype; however, reporting of intent to lose weight is not straightforward because knowledge of the direction of weight change may bias patient responses to a question about intent. In addition, both intentional and unintentional weight loss have been associated with an increased risk of disease in older persons.1114

Based on the physiologic domains most frequently cited in the frailty literature,15,16 findings from previous studies that evaluated the predictive validity of individual components,11,12,1721 and suitability of assessment of components in a busy clinical practice setting, we proposed a simple frailty index using 3 components: weight loss, the subject's inability to rise from a chair 5 times without using her arms, and reduced energy level (Study of Osteoporotic Fractures [SOF] index). We used data collected in the SOF to compare the value of the SOF index with that of the more complex CHS index for prediction of falls, disability, fractures, and death in a cohort of 6701 community-dwelling women 69 years or older.

PARTICIPANTS

From September 1986 to October 1988, a total of 9704 women aged at least 65 years were recruited for participation in the baseline examination of the prospective SOF. Women were recruited from population-based listings in 4 areas of the United States (Baltimore County, Maryland; Minneapolis, Minnesota; Portland, Oregon; and the Monongahela Valley, Pennsylvania).22 Black women were originally excluded from the SOF because they have a low incidence of hip fracture. In addition, women were excluded if they were unable to walk without assistance or had a history of bilateral hip replacement.

All surviving participants were invited to undergo a fourth examination between August 1992 and July 1994. A total of 8412 women (97% of the survivors as of July 31, 1994) completed at least the questionnaire component of this examination. Of these, 6701 women provided data for at least 2 components of the 3 frailty criteria in the SOF index and for at least 3 components of the 5 frailty criteria in the CHS index and are the subject of this analysis. The institutional review board at each center approved the study protocol, and written informed consent was obtained from all participants.

MEASUREMENTS

Participants completed a questionnaire and were interviewed at the fourth examination and asked about health status, educational achievement, smoking history, intent to lose weight, and falls during the previous year. A selected medical history was obtained that included a history of physician diagnosis of fracture since the age of 50 years, stroke, cancer excluding skin cancer, dementia, hypertension, parkinsonism, diabetes mellitus, coronary heart disease, and chronic obstructive lung disease. Participants were asked to bring all prescription and nonprescription medications, including estrogen preparations, to the clinic for verification of use. Physical activity was assessed using a modified version of the Harvard Alumni Questionnaire23,24 and was expressed as a weighted score of kilocalories expended per week. Depressive symptoms were evaluated using the 15-item Geriatric Depression Scale (which includes the question “Do you feel full of energy?”).25 Cognitive function was assessed with a modified version of the Mini-Mental State Examination26 with a maximum score of 26. To assess functional disability, women were asked whether they had any difficulty performing any of 5 instrumental activities of daily living (IADL).27 Tests of physical function included grip strength using a handheld dynamometer (Jamar; Sammons Preston Rolyan, Bolingbrook, Illinois), walking speed (time in seconds to walk 6 m at usual pace), and the subject's ability to rise from a chair 5 times without using her arms. Body weight was recorded using a balance beam scale at the third and fourth examinations. Height was measured using a standard held-expiration technique with a wall-mounted stadiometer (Harpenden; Holtain Ltd, Crymych, Wales). Height and weight were used to calculate a standard body mass index (calculated as weight in kilograms divided by height in meters squared). Bone mineral density of the proximal femur was measured using dual-energy x-ray absorptiometry (QDR 1000 densitometer; Hologic Inc, Waltham, Massachusetts).

SOF FRAILTY INDEX

Frailty defined by the SOF index was identified by the presence of 2 or more of the following 3 components at the fourth examination: (1) weight loss (irrespective of intent to lose weight) of 5% or more between the third and fourth examinations (mean [SD] years between examinations, 2.0 [0.3]); (2) the subject's inability to rise from a chair 5 times without using her arms; and (3) reduced energy level, as identified by an answer of “no” to the question “Do you feel full of energy?” on the Geriatric Depression Scale.25 Women having none of these components were considered to be robust, and those having 1 component were considered to be in an intermediate or prefrail stage.

CHS FRAILTY INDEX

Frailty defined by the CHS index as proposed by Fried et al5 was identified by the presence of 3 or more of the following 5 components at the fourth examination: (1) unintentional weight loss of 5% or more between the third and fourth examinations (mean [SD] years between examinations, 2.0 [0.3]); (2) weakness, as identified by grip strength in the lowest quintile stratified by body mass index quartile; (3) reduced energy level, as identified by an answer of “no” to the question “Do you feel full of energy?” on the Geriatric Depression Scale25 (4) slowness, as identified by a walking speed in the lowest quintile stratified by median standing height; and (5) low physical activity level, as identified by a weighted score of kilocalories expended per week in the lowest quintile. Women having none of these components were considered to be robust, and those having 1 or 2 components were considered to be in an intermediate or prefrail stage.

ASCERTAINMENT OF FALLS, DISABILITY, FRACTURES, AND DEATH

After the fourth examination, we contacted participants about falls and fractures every 4 months by postcard or telephone. All falls reported on the first 3 postcards were included in the falls analysis (mean [SD] 11.9 [0.9] months) after the fourth examination (covering approximately 1 year). More than 98% of these follow-up contacts were completed. Functional status was assessed at the fourth examination and, on average, 4½ years later at the sixth examination; incident disability was defined as 1 or more new impairment(s) in IADL. Fractures were confirmed by review of radiographic reports. All first hip fractures occurring after the fourth examination and before January 31, 2006, were included in analyses examining the association between frailty and risk of hip fracture. Any nonspine fractures during this period were included in the analyses examining the relationship between frailty and risk of any nonspine fracture. Mean (SD) follow-up was 9.3 (3.5) years for hip fracture and 7.9 (4.0) years for any nonspine fracture. We were able to complete more than 95% of the triannual follow-up contacts about fracture status in surviving women. Deaths were identified by contacts every 4 months and confirmed with death certificates. Follow-up for vital status was 99% complete. Mean (SD) follow-up for death was 9.6 (3.3) years.

STATISTICAL ANALYSIS

We used χ2 tests of homogeneity, analyses of variance, and Kruskal-Wallis tests to compare characteristics of participants at the fourth examination by category of frailty according to the SOF index. Logistic regression was used to analyze the association between frailty status as defined by SOF and CHS indexes and the odds of recurrent falls (≥2 falls vs ≤1 fall) in the subsequent year and odds of disability after 4½ years of follow-up. Cox proportional hazards models were used to analyze the associations between frailty status as defined by SOF and CHS indexes and subsequent outcomes including any incident nonspine fracture, first hip fracture, and death. The relative risk (approximated as hazard ratios or odds ratios) of each outcome with 95% confidence intervals was estimated in women categorized as having intermediate frailty status and those categorized as frail, using women who were categorized as robust as the referent group. We also used logistic regression to examine receiver operating characteristic curves for each model and calculated the area under the curve (AUC). All primary analyses were adjusted for age alone because the objective was to assess the utility of each frailty index as it might be used in clinical practice to predict outcomes. Secondary analyses were adjusted for additional factors previously identified in the cohort to predict the outcomes.

A bootstrap procedure28,29 was used to compare −2 log likelihood (−2LL) model fit statistics for proportional hazards or logistic regression models containing CHS index vs SOF index and to compare AUC statistics from logistic regression receiver operating characteristic curve analysis. The full study population was sampled (with replacement) 1000 times. Each bootstrap sample was fit to the 2 models being compared, and the difference between the −2LL statistics and between AUC statistics was calculated. The distribution of these observed differences was used to make statistical inference about the likelihood that the −2LL statistics or AUC statistics from the 2 models were significantly different (P < .05). Using the 10-fold cross-validation procedure,30 results for the comparison of observed AUC statistics between models with the CHS index and models with the SOF index were cross-validated (results not shown).

CHARACTERISTICS OF THE STUDY POPULATION

Characteristics of the cohort of 6701 women (mean age, 76.7 years) are given in Table 1. With the CHS index, 16% were classified as frail (≥3 components), 47% as having intermediate status (1-2 components), and 37% as robust (no components). With the SOF index, 17% of women were classified as frail (≥2 components), 36% as having intermediate status (1 component), and 47% as robust (no components). Classification of frailty status using the indexes was concordant in 4965 women (74%). The κ statistic was 0.59. The Spearman correlation between indexes was 0.75 (P < .001). Characteristics of participants by category of frailty status as defined by the SOF index are given in Table 2.

Table Graphic Jump LocationTable 1. Characteristics of 6701 Participants
Table Graphic Jump LocationTable 2. Characteristics of Participants by Category of Frailty Status as Defined by the SOF Index

During a mean follow-up of 11.9 months, 734 women (11%) experienced 2 (recurrent) falls or more. At a mean of 4½ years later, 1912 women (35%) reported 1 or more new IADL impairment(s) among the 5386 women with IADL data at both examinations. During a mean follow-up ranging from 7.9 years (any nonspine fracture) to 9.3 years (hip fracture) to 9.6 years (death), 2200 women (33%) experienced 1 or more nonspine fracture(s), including 707 women (11%) who sustained a first hip fracture, and 2751 women (41%) who died. Compared with the 6701 women included in this analysis who provided sufficient data on frailty components for calculation of the frailty indexes, the 1711 women excluded from the analyses because of insufficient data were more likely to have died during follow-up (55% vs 41%; P < .001).

SOF INDEX VS CHS INDEX FOR PREDICTION OF FALLS, DISABILITY, FRACTURES, AND DEATH

Increasing evidence of frailty as identified using the SOF or CHS index was similarly associated with an increased odds of 2 or more (recurrent) falls in the subsequent year (Table 3). Compared with robust women, women in the intermediate group had a 1.2- to 1.4-fold age-adjusted increase in risk (P < .04 for both models) and frail women had a 2.4-fold increase in risk (P < .001 for both models). There was no difference in −2LL statistics between models (P = .89). Across a range of sensitivities and specificities, the receiver operating characteristic curves were essentially superimposed for the model containing the SOF index vs the model containing the CHS index (Figure, A). Using either index, AUC statistics were essentially identical (P = .66 for comparison of AUC statistics).

Table Graphic Jump LocationTable 3. Comparison of CHS vs SOF Indexes for Prediction of Recurrent Falls
Place holder to copy figure label and caption
Figure.

Age-adjusted receiver operating characteristic curves for prediction of recurrent falls (A), disability (B), hip fracture (C), and death (D) with the Study of Osteoporotic Fractures (SOF) and Cardiovascular Health Study (CHS) frailty indexes. The black diagonal line indicates a reference area under the curve (AUC) of 0.50 (no better than chance alone).

Graphic Jump Location

The odds of incident disability (≥1 new IADL impairment) were greater with increasing evidence of frailty using either the SOF or CHS index (Table 4). Compared with robust women, women in the intermediate group had an age-adjusted 1.8- to 1.9-fold increase in risk (P < .001 for both models) and frail women had a 2.2- to 2.9-fold increase in risk (P < .001 for both models). Although the point estimates of the association were higher in magnitude for the model with the CHS index, the comparison between −2LL statistics did not reach significance (P = .17) and there was no difference between AUC statistics (P = .23) (Figure, B).

Table Graphic Jump LocationTable 4. Comparison of CHS vs SOF Indexes for Prediction of Disability

Frailty as identified using either the SOF or CHS index was also similarly related to an increased risk of incident nonspine fracture (results not shown), including hip fracture (Table 5). After adjustment for age, women in the intermediate group had a 1.3- to 1.4-fold increased risk of hip fracture (P < .002 for both models) and a 1.2-fold increased risk of any nonspine fracture (P < .002 for both models), whereas frail women had a 1.7- to 1.8-fold increased risk of hip fracture (P < .001 for both models) and a 1.5-fold increased risk of any nonspine fracture (P < .001 for both models). There was no difference in −2LL statistics between hip fracture models (P = .34) or nonspine fracture models (P = .95). In receiver operating characteristic analyses, hip fracture models containing the SOF index performed similarly to those containing the CHS index (Figure, C) (P = .64 for comparison of AUC statistics). The AUC statistics were lower, but similar using either index, for nonspine fracture models (AUC, 0.55 for both models; P = .80).

Table Graphic Jump LocationTable 5. Comparison of CHS vs SOF Indexes for Prediction of Hip Fracture

All-cause mortality rates were higher with increasing evidence of frailty as identified using either the SOF or CHS index (Table 6). Compared with robust women, women in the intermediate group had an age-adjusted 1.4- to 1.5-fold increased risk of death (P < .001 for both models) and frail women had a 2.4- to 2.7-fold increased risk of death (P < .001 for both models). Although the point estimates of the association were slightly greater for the model with the CHS index, the comparison between −2LL statistics did not reach significance (P = .20). Similarly, there was no difference between AUC statistics (P = .10) for the 2 models (Figure, D).

Table Graphic Jump LocationTable 6. Comparison of CHS vs SOF Indexes for Prediction of Death

For each outcome, the addition of multiple covariates (including health status; smoking history; educational achievement; estrogen use; history of fracture; history of selected medical conditions including stroke, cancer (excluding skin cancer), dementia, hypertension, parkinsonism, diabetes mellitus, coronary heart disease, and chronic obstructive lung disease; history of falls (models for fracture and death); depressive symptoms; cognitive function; functional disability; body mass index; and femoral neck bone mineral density to the age-adjusted model resulted in a small to moderate improvement in the predictive accuracy of the model. However, there was still no difference in −2LL statistics from multivariate models with the SOF index and those containing the CHS index. P values for −2LL comparisons were 0.38 (falls), 0.34 (disability), 0.62 (nonspine fracture), 0.92 (hip fracture), and 0.28 (death). Using either index, AUC statistics were almost identical for falls (AUC, 0.67 using the SOF index vs 0.68 using the CHS index; P = .054), and there was no difference between multivariate models in discriminating disability (AUC, 0.68 using the SOF index vs 0.69 using the CHS index;  = .42), nonspine fracture (AUC, 0.65 for both models; P = .86), hip fracture (AUC, 0.73 for both models; P = .96), or death (AUC, 0.74 for both models; P = .17).

In this large cohort of community-dwelling older women, assessment of frailty using the simple SOF index based on 3 components (weight loss, the subject's inability to rise from a chair 5 times without using her arms, and reduced energy level) and evaluation of frailty using the more complex CHS index performed similarly in the prediction of risk of falls, disability, fracture, and death. These findings suggest that the parsimonious SOF index provides a useful definition of frailty to identify high-risk older women seen in clinical practice.

There is a pervasive belief that clinicians can easily discern whether an older patient is frail.31 However, there is no uniformly accepted definition or official International Classification of Diseases (ICD) diagnosis for frailty. The use of the term frailty in clinical geriatric medicine typically describes the presence of multisystem impairment and increasing vulnerability. Several instruments have been developed to operationalize the construct of frailty,15 including recent indexes based on clinical judgment,32 deficit accumulation,33 and comprehensive geriatric assessment.34 The CHS index5 has been most extensively studied. The validity of the CHS index in predicting risk of adverse outcomes including functional impairment, falls, hospitalization, fracture, and death has been corroborated in several cohorts of older adults.610 In addition, the CHS index has been linked to specific alterations in physiologic factors providing evidence of multisystem impairment and biological and molecular pathways that may underlie the development of the clinical frailty syndrome.3537 It has been suggested that the CHS index might serve as the basis for screening older persons for frailty and risk of frailty,5 be used to identify a target population for entry into randomized trials evaluating interventions with the goal of preventing or delaying functional decline and disability,15 and be integrated into the comprehensive care for older women.38

We found that classification of frailty status using the CHS and SOF indexes was concordant in 74% of participants. Thus, the SOF and CHS indexes similarly discriminate between groups of older women in identification of frailty status. In addition, our results confirm the value of the CHS index in screening older women for risk of falls, disability, fracture, and death, with an AUC as high as 0.72 for death in age-adjusted models. However, we did not find evidence that the prediction of these outcomes was better using the more complicated CHS index as compared with the straightforward SOF index, which was parsimonious without substantial losses in its discriminative ability. Like the CHS index, the 3 components of the SOF index (weight loss, the subject's inability to rise from a chair 5 times without using her arms, and reduced energy level) reflect impairment in 1 or more physiologic domains most frequently cited in the frailty literature15,16: mobility, such as lower-extremity performance and gait abnormalities; muscle weakness; poor exercise tolerance including feelings of fatigue and exhaustion; unstable balance; and factors related to body composition such as weight loss, malnutrition, and sarcopenia. However, unlike for the CHS index, the SOF criteria are not dependent on sex, body size, underlying distribution of the measure in a population, or ability to assess intent to lose weight, and are easily assessed and inexpensively obtained in a few minutes in the clinical setting.

This study has many strengths, including its prospective design, comprehensive set of measurements, and duration and completeness of follow-up. To our knowledge, this is the first study to evaluate and compare the overall predictive value of 2 frailty instruments. However, this study has several limitations. Participants were older white women living in the community, and our findings may not be applicable to other population groups. Additional prospective studies are needed to confirm the predictive validity of the SOF index in other populations. While prediction of all-cause mortality is of essential prognostic importance in aged populations and disability, falls and fractures are a common cause of morbidity in older adults39,40; future studies should evaluate the ability of the SOF index to predict other outcomes including hospitalization and institutionalization. Our findings indicate that both the CHS and SOF indexes are limited in their ability to discriminate falls, disability, and fracture. Neither index should be used as the sole tool for screening for risk of these outcomes. However, the validity of these frailty indexes in predicting hip and nonspine fractures was similar to that reported for other tools based on the use of clinical risk factors alone.41 These results may underestimate the ability of the CHS and SOF indexes to predict death because women excluded from the analyses owing to insufficient data on frailty components were more likely to die during follow-up. The objective of this analysis was to compare the ability of the SOF index with that of the CHS index to predict adverse outcomes, and future studies are needed to examine whether the SOF index is useful in the longitudinal characterization of change in frailty status across time. We compared the predictive ability of the SOF index with that of the widely used CHS index; however, several indexes of frailty have been proposed15,3234 and our findings are not generalizable across different frailty definitions.

The simple SOF index provides an operational definition of frailty that predicts risk of falls, disability, fracture, and death as well as the more complicated CHS index. Thus, the SOF index provides a useful phenotype of frailty to identify high-risk older women in clinical practice.

Corresponding Author: Kristine E. Ensrud, MD, MPH; Center for Chronic Disease Outcomes Research, Veterans Affairs Medical Center, 1 Veterans Dr, General Internal Medicine (Mail Stop 111-0), Minneapolis, MN 55417 (ensru001@umn.edu).

Accepted for Publication: September 17, 2007.

Author Contributions: Ms Ewing had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analyses. Study concept and design: Ensrud and Cauley. Acquisition of data: Ensrud, Hochberg, and Cummings. Analysis and interpretation of data: Ensrud, Ewing, Taylor, Fink, Cawthon, Stone, Hillier, Cauley, Rodondi, and Tracy. Drafting of the manuscript: Ensrud and Cauley. Critical revision of the manuscript for important intellectual content: Ewing, Taylor, Fink, Cawthon, Stone, Hillier, Cauley, Hochberg, Rodondi, Tracy, and Cummings. Statistical analysis: Ewing, Taylor, Fink, Stone, Rodondi, and Tracy. Obtained funding: Ensrud, Stone, and Cummings. Administrative, technical, and material support: Cawthon. Study supervision: Ensrud and Stone.

Financial Disclosure: None reported.

Funding/Support: This study was supported in part by Public Health Service research grants AG05407, AR35582, AG05394 (Dr Ensrud), AR35584, AR35583 and AG08415 from the National Institutes of Health.

Role of the Sponsor: The National Insitutes of Health had no role in the design and conduct of the study; in the collection, analysis, and interpretation of the data; or in the preparation, review, or approval of the manuscript.

Additional Contributions: Kyle A. Moen assisted with the manuscript and with the preparation and formatting of the tables and figure.

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Whooley  MAKip  KECauley  JA  et al. Study of Osteoporotic Fractures Research Group, Depression, falls, and risk of fracture in older women. Arch Intern Med 1999;159 (5) 484- 490
PubMed Link to Article
Ensrud  KFullman  RMarshall  L  et al.  Neuromuscular function and risk of fractures in older men. J Bone Miner Res 2005;20 ((suppl 1)) S159
Cummings  SRBlack  DMNevitt  MC  et al. Study of Osteoporotic Fractures Research Group, Appendicular bone density and age predict hip fracture in women. JAMA 1990;263 (5) 665- 668
PubMed Link to Article
Paffenbarger  RS  JrWing  ALHyde  RT Physical activity as an index of heart attack risk in college alumni. Am J Epidemiol 1978;108 (3) 161- 175
PubMed
Gregg  EWCauley  JAStone  K  et al.  Relationship of changes in physical activity and mortality among older women. JAMA 2003;289 (18) 2379- 2386
PubMed Link to Article
Sheikh  JIYesavage  JA Geriatric Depression Scale (GDS): recent evidence and development of a shorter version. Clin Gerontol 1986;5 (1/2) 165- 173
Link to Article
Folstein  MFRobins  LNHelzer  JE The Mini-Mental State Examination. Arch Gen Psychiatry 1983;40 (7) 812
PubMed Link to Article
Ensrud  KENevitt  MCYunis  C  et al.  Correlates of impaired function in older women. J Am Geriatr Soc 1994;42 (5) 481- 489
PubMed
Efron  BTibshirani  RJ An Introduction to the Bootstrap.  New York, NY Chapman & Hall1993;
Hui  SLSlemenda  CWCarey  MAJohnston  CC  Jr Choosing between predictors of fractures. J Bone Miner Res 1995;10 (11) 1816- 1822
PubMed Link to Article
Breiman  LFriedman  JStone  CJOlshen  RA Classification and Regression Trees.  New York, NY Chapman & Hall1984;
Wilson  JF Frailty—and its dangerous effects—might be preventable. Ann Intern Med 2004;141 (6) 489- 492
PubMed Link to Article
Studenski  SHayes  RPLeibowitz  RQ  et al.  Clinical Global Impression of Change in Physical Frailty: development of a measure based on clinical judgment. J Am Geriatr Soc 2004;52 (9) 1560- 1566
PubMed Link to Article
Mitnitski  ASong  XSkoog  I  et al.  Relative fitness and frailty of elderly men and women in developed countries and their relationship with mortality. J Am Geriatr Soc 2005;53 (12) 2184- 2189
PubMed Link to Article
Jones  DMSong  XRockwood  K Operationalizing a frailty index from a standardized comprehensive geriatric assessment. J Am Geriatr Soc 2004;52 (11) 1929- 1933
PubMed Link to Article
Leng  SChaves  PKoenig  KWalston  J Serum interleukin-6 and hemoglobin as physiological correlates in the geriatric syndrome of frailty: a pilot study. J Am Geriatr Soc 2002;50 (7) 1268- 1271
PubMed Link to Article
Shlipak  MGStehman-Breen  CFried  LF  et al.  The presence of frailty in elderly persons with chronic renal insufficiency. Am J Kidney Dis 2004;43 (5) 861- 867
PubMed Link to Article
Walston  JMcBurnie  MANewman  A  et al.  Frailty and activation of the inflammation and coagulation systems with and without clinical comorbidities: results from the Cardiovascular Health Study. Arch Intern Med 2002;162 (20) 2333- 2341
PubMed Link to Article
Correa-de-Araujo  R An operational definition of frailty predicted death, hip fracture, and hospitalization in older women. ACP J Club 2006;144 (1) 23
PubMed
Kannus  PSievänen  HPalvanen  MJärvinen  TParkkari  J Prevention of falls and consequent injuries in elderly people. Lancet 2005;366 (9500) 1885- 1893
PubMed Link to Article
US Department of Health and Human Services, Bone Health and Osteoporosis: A Report of the Surgeon General.  Rockville, MD US Dept of Health and Human Services, Office of the Surgeon General2004;
Kanis  JAOden  AJohnell  O  et al.  The use of clinical risk factors enhances the performance of BMD in the prediction of hip and osteoporotic fractures in men and women. Osteoporos Int 2007;18 (8) 1033- 1046
PubMed Link to Article

Figures

Place holder to copy figure label and caption
Figure.

Age-adjusted receiver operating characteristic curves for prediction of recurrent falls (A), disability (B), hip fracture (C), and death (D) with the Study of Osteoporotic Fractures (SOF) and Cardiovascular Health Study (CHS) frailty indexes. The black diagonal line indicates a reference area under the curve (AUC) of 0.50 (no better than chance alone).

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1. Characteristics of 6701 Participants
Table Graphic Jump LocationTable 2. Characteristics of Participants by Category of Frailty Status as Defined by the SOF Index
Table Graphic Jump LocationTable 3. Comparison of CHS vs SOF Indexes for Prediction of Recurrent Falls
Table Graphic Jump LocationTable 4. Comparison of CHS vs SOF Indexes for Prediction of Disability
Table Graphic Jump LocationTable 5. Comparison of CHS vs SOF Indexes for Prediction of Hip Fracture
Table Graphic Jump LocationTable 6. Comparison of CHS vs SOF Indexes for Prediction of Death

References

Hamerman  D Toward an understanding of frailty. Ann Intern Med 1999;130 (11) 945- 950
PubMed Link to Article
Morley  JEPerry  HM  IIIMiller  DK Editorial: something about frailty. J Gerontol A Biol Sci Med Sci 2002;57 (11) M698- M704
PubMed Link to Article
Rockwood  K Frailty and its definition: a worthy challenge. J Am Geriatr Soc 2005;53 (6) 1069- 1070
PubMed Link to Article
Fried  LPFerrucci  LDarer  JWilliamson  JDAnderson  G Untangling the concepts of disability, frailty, and comorbidity: implications for improved targeting and care. J Gerontol A Biol Sci Med Sci 2004;59 (3) 255- 263
PubMed Link to Article
Fried  LPTangen  CMWalston  J  et al.  Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001;56 (3) M146- M156
PubMed Link to Article
Woods  NFLaCroix  AZGray  SL  et al.  Frailty: emergence and consequences in women aged 65 and older in the Women's Health Initiative Observational Study. J Am Geriatr Soc 2005;53 (8) 1321- 1330
PubMed Link to Article
Bandeen-Roche  KXue  QLFerrucci  L  et al.  Phenotype of frailty: characterization in the Women's Health and Aging Studies. J Gerontol A Biol Sci Med Sci 2006;61 (3) 262- 266
PubMed Link to Article
Boyd  CMXue  QLSimpson  CFGuralnik  JMFried  LP Frailty, hospitalization, and progression of disability in a cohort of disabled older women. Am J Med 2005;118 (11) 1225- 1231
PubMed Link to Article
Ensrud  KEEwing  SKTaylor  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 (7) 744- 751
PubMed Link to Article
Cawthon  PMMarshall  LMMichael  Y  et al.  Frailty in older men: prevalence, progression, and relationship with mortality. J Am Geriatr Soc 2007;55 (8) 1216- 1223
PubMed Link to Article
Ensrud  KEEwing  SKStone  KL  et al.  Intentional and unintentional weight loss increase bone loss and hip fracture risk in older women. J Am Geriatr Soc 2003;51 (12) 1740- 1747
PubMed Link to Article
Newman  ABYanez  DHarris  T  et al.  Weight change in old age and its association with mortality. J Am Geriatr Soc 2001;49 (10) 1309- 1318
PubMed Link to Article
Wannamethee  SGShaper  AGWhincup  PHWalker  M Characteristics of older men who lose weight intentionally or unintentionally. Am J Epidemiol 2000;151 (7) 667- 675
PubMed Link to Article
Ensrud  KEFullman  RLBarrett-Connor  E  et al.  Voluntary weight reduction in older men increases hip bone loss: the Osteoporotic Fractures in Men Study. J Clin Endocrinol Metab 2005;90 (4) 1998- 2004
PubMed Link to Article
Ferrucci  LGuralnik  JMStudenski  S  et al.  Designing randomized, controlled trials aimed at preventing or delaying functional decline and disability in frail, older persons: a consensus report. J Am Geriatr Soc 2004;52 (4) 625- 634
PubMed Link to Article
Walston  JHadley  ECFerrucci  L  et al.  Research agenda for frailty in older adults: toward a better understanding of physiology and etiology. Summary from the American Geriatrics Society/National Institute on Aging Research Conference on Frailty in Older Adults. J Am Geriatr Soc 2006;54 (6) 991- 1001
PubMed Link to Article
Cummings  SRNevitt  MCBrowner  WS  et al. Study of Osteoporotic Fractures Research Group, Risk factors for hip fracture in white women. N Engl J Med 1995;332 (12) 767- 773
PubMed Link to Article
Ensrud  KECauley  JLipschutz  RCummings  SRStudy of Osteoporotic Fractures Research Group, Weight change and fractures in older women. Arch Intern Med 1997;157 (8) 857- 863
PubMed Link to Article
Whooley  MABrowner  WSStudy of Osteoporotic Fractures Research Group, Association between depressive symptoms and mortality in older women. Arch Intern Med 1998;158 (19) 2129- 2135
PubMed Link to Article
Whooley  MAKip  KECauley  JA  et al. Study of Osteoporotic Fractures Research Group, Depression, falls, and risk of fracture in older women. Arch Intern Med 1999;159 (5) 484- 490
PubMed Link to Article
Ensrud  KFullman  RMarshall  L  et al.  Neuromuscular function and risk of fractures in older men. J Bone Miner Res 2005;20 ((suppl 1)) S159
Cummings  SRBlack  DMNevitt  MC  et al. Study of Osteoporotic Fractures Research Group, Appendicular bone density and age predict hip fracture in women. JAMA 1990;263 (5) 665- 668
PubMed Link to Article
Paffenbarger  RS  JrWing  ALHyde  RT Physical activity as an index of heart attack risk in college alumni. Am J Epidemiol 1978;108 (3) 161- 175
PubMed
Gregg  EWCauley  JAStone  K  et al.  Relationship of changes in physical activity and mortality among older women. JAMA 2003;289 (18) 2379- 2386
PubMed Link to Article
Sheikh  JIYesavage  JA Geriatric Depression Scale (GDS): recent evidence and development of a shorter version. Clin Gerontol 1986;5 (1/2) 165- 173
Link to Article
Folstein  MFRobins  LNHelzer  JE The Mini-Mental State Examination. Arch Gen Psychiatry 1983;40 (7) 812
PubMed Link to Article
Ensrud  KENevitt  MCYunis  C  et al.  Correlates of impaired function in older women. J Am Geriatr Soc 1994;42 (5) 481- 489
PubMed
Efron  BTibshirani  RJ An Introduction to the Bootstrap.  New York, NY Chapman & Hall1993;
Hui  SLSlemenda  CWCarey  MAJohnston  CC  Jr Choosing between predictors of fractures. J Bone Miner Res 1995;10 (11) 1816- 1822
PubMed Link to Article
Breiman  LFriedman  JStone  CJOlshen  RA Classification and Regression Trees.  New York, NY Chapman & Hall1984;
Wilson  JF Frailty—and its dangerous effects—might be preventable. Ann Intern Med 2004;141 (6) 489- 492
PubMed Link to Article
Studenski  SHayes  RPLeibowitz  RQ  et al.  Clinical Global Impression of Change in Physical Frailty: development of a measure based on clinical judgment. J Am Geriatr Soc 2004;52 (9) 1560- 1566
PubMed Link to Article
Mitnitski  ASong  XSkoog  I  et al.  Relative fitness and frailty of elderly men and women in developed countries and their relationship with mortality. J Am Geriatr Soc 2005;53 (12) 2184- 2189
PubMed Link to Article
Jones  DMSong  XRockwood  K Operationalizing a frailty index from a standardized comprehensive geriatric assessment. J Am Geriatr Soc 2004;52 (11) 1929- 1933
PubMed Link to Article
Leng  SChaves  PKoenig  KWalston  J Serum interleukin-6 and hemoglobin as physiological correlates in the geriatric syndrome of frailty: a pilot study. J Am Geriatr Soc 2002;50 (7) 1268- 1271
PubMed Link to Article
Shlipak  MGStehman-Breen  CFried  LF  et al.  The presence of frailty in elderly persons with chronic renal insufficiency. Am J Kidney Dis 2004;43 (5) 861- 867
PubMed Link to Article
Walston  JMcBurnie  MANewman  A  et al.  Frailty and activation of the inflammation and coagulation systems with and without clinical comorbidities: results from the Cardiovascular Health Study. Arch Intern Med 2002;162 (20) 2333- 2341
PubMed Link to Article
Correa-de-Araujo  R An operational definition of frailty predicted death, hip fracture, and hospitalization in older women. ACP J Club 2006;144 (1) 23
PubMed
Kannus  PSievänen  HPalvanen  MJärvinen  TParkkari  J Prevention of falls and consequent injuries in elderly people. Lancet 2005;366 (9500) 1885- 1893
PubMed Link to Article
US Department of Health and Human Services, Bone Health and Osteoporosis: A Report of the Surgeon General.  Rockville, MD US Dept of Health and Human Services, Office of the Surgeon General2004;
Kanis  JAOden  AJohnell  O  et al.  The use of clinical risk factors enhances the performance of BMD in the prediction of hip and osteoporotic fractures in men and women. Osteoporos Int 2007;18 (8) 1033- 1046
PubMed Link to Article

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