Article:An overview of osteoporosis and frailty in the elderly. (5270357)

From ScienceSource
Jump to: navigation, search

This page is the ScienceSource HTML version of the scholarly article described at Its title is An overview of osteoporosis and frailty in the elderly. and the publication date was 2017-01-26. The initial author is Guowei Li.

Fuller metadata can be found in the Wikidata link, which lists all authors, and may have detailed items for some or all of them. There is further information on the article in the footer below. This page is a reference version, and is protected against editing.

Converted JATS paper:

Journal Information

Title: BMC Musculoskeletal Disorders

An overview of osteoporosis and frailty in the elderly

  • Guowei Li
  • Lehana Thabane
  • Alexandra Papaioannou
  • George Ioannidis
  • Mitchell A. H. Levine
  • Jonathan D. Adachi

Publication date (epub): 1/2017

Publication date (pmc-release): 1/2017

Publication date (collection): /2017


Osteoporosis and osteoporotic fractures remain significant public health challenges worldwide. Recently the concept of frailty in relation to osteoporosis in the elderly has been increasingly accepted, with emerging studies measuring frailty as a predictor of osteoporotic fractures. In this overview, we reviewed the relationship between frailty and osteoporosis, described the approaches to measuring the grades of frailty, and presented current studies and future research directions investigating osteoporosis and frailty in the elderly. It is concluded that measuring the grades of frailty in the elderly could assist in the assessment, management and decision-making for osteoporosis and osteoporotic fractures at a clinical research level and at a health care policy level.



Osteoporosis is defined as a systemic skeletal disease with the characteristics of low bone mass and microarchitectural deterioration of bone tissues [[1]]. In clinical practice, osteoporosis is usually diagnosed by the bone mineral density (BMD) criteria or the occurrence of a fragility fracture. Based on the BMD criteria, osteoporosis is diagnosed by a BMD of 2.5 standard deviations or more below the mean of a young healthy adult women reference population (T-score ≤ −2.5) [[2]]. Osteoporosis results in increased bone fragility and subsequent accumulated fracture risk. With decreased BMD as people age, osteoporosis becomes more prevalent among older individuals [[3]]. As the population ages worldwide, the number of osteoporotic fractures is growing substantially. In western countries, the lifetime risk of any osteoporotic fracture remains very high, lying within the range of 40–50% for women and 13–22% for men [[4]]. For the year 2000, it was estimated that 9 million new osteoporotic fractures occurred globally, of which 1.6 million were hip fractures and 1.4 million were clinical vertebral fractures [[5]]. In the US, there are more than 2 million fractures annually attributed to osteoporosis, including 550,000 vertebral fractures and 300,000 hip fractures [[6], [7]]. Osteoporotic fractures in the elderly are usually followed by hospitalization, long-term care, impaired quality of life, disability and death [[8]]. Therefore osteoporosis and osteoporotic fractures remain significant public health challenges worldwide.

Recently, the concept of frailty in relation to osteoporosis in the elderly has been increasingly accepted, with emerging studies measuring frailty as a predictor of osteoporotic fractures [[9]]. Frailty is defined as a dynamic clinical condition with increased vulnerability which results from aging-related degeneration across psychological, physical and social functioning [[10], [11]]. Frailty is accelerating in the aging population, with an overall prevalence of 10.7% in community-dwellers aged ≥ 65 years worldwide [[12]]. Moreover, it is estimated that 25–50% of older adults aged ≥ 85 years are frail [[9]]. Frailty is mainly caused by the complex aging mechanisms that are determined by underlying genetic, epigenetic and environmental factors [[9]]. However, other multifactorial elements such as sarcopenia, inflammation, malnutrition, co-morbidities, hormonal insufficiency, etc., can also result in frailty in the elderly [[13][15]]. The fundamental of the relationship between frailty and osteoporosis relies on the fact that, the frailer an individual is, the greater the likelihood that the individual will have a prevalent osteoporotic fracture and the higher the risk of a fracture in the future [[16], [17]]. Quantifying the degree of frailty could aid in the assessment, management and decision-making for the elderly at a clinical research level and at a health care policy level [[9]].

Measuring grades of frailty in assessing risk of osteoporotic fractures

A frailty instrument should be multidimensional, able to capture the grades of frailty, and qualified to serve as a screening or evaluation tool [[18]]. At present, two predominant approaches are being widely used in measuring the degree of frailty in the elderly: the phenotype model [[19]] and the frailty index of deficit accumulation [[20]]. Table 1 lists the respective components of the phenotype model and the frailty index of deficit accumulation. The phenotype model is calculated from five physical indicators (exhaustion, low physical activity, weakness, slow walking and unintentional weight loss) [[19]]. Each indicator is scored as either 0 or 1 and therefore the total score ranges from 0 to 5 points. The phenotype model categorizes the elderly into robust, pre-frail or frail groups by the cut-points of the total score of 0, 1–2 and ≥ 3 points respectively [[19]]. By contrast, the frailty index chooses a variety of individual health deficits to measure the cumulative effect and quantify the degree of frailty [[20]]. Generally, the deficits cover the domains of symptoms and signs, comorbidities, activities of daily living, and social relations and social support [[21], [22]]. Though each individual deficit may not carry an imminent threat of adverse health outcomes, the deficit accumulation contributes to the increased risk [[23]]. The frailty index approach does not require the same deficits or the same number of variables to build a frailty index [[24]]. Previous studies have selected 30 to 70 health deficits in creating a frailty index [[25]]. However it has been recommended to include at least 30 to 40 deficits in total to construct a frailty index [[22]]. Each deficit is dichotomized or polychotomized and mapped on an interval scale between 0 and 1, in order to reflect the frequency or severity of the deficit [[22]]. Subsequently, the frailty index is calculated by summing up all the deficit values and dividing by the whole number of the deficits included. For example, if a frailty index includes 35 deficits, and an individual has 6 deficits with each scored as 1 point (6 point total), 2 deficits with each scored as 0.5 (1 point total), and the remaining 27 deficits with each scored of 0, then the frailty index would be 7 divided by 35 giving an index of 0.2.Table 1

Components of the phenotype model and the frailty index of deficit accumulation

Approach to measuring grades of frailty Components
The phenotype modela Exhaustion
Low physical activity
Slow walking
Unintentional weight loss
The frailty index of deficit accumulationb Deficits of symptoms and signs
Deficits of activities of daily living
Deficits of social relations and social support

ahe phenotype model is based on five physical indicators

bThe frailty index of deficit accumulation is calculated from a variety of individual health deficits

Evidence has shown that both the phenotype model and the frailty index are predictive of osteoporotic fractures independent of chronological age in the elderly [[26][29]]. For instance, the Study of Osteoporotic Fractures (SOF) assessed the relationship between a phenotype model and risk of fractures in 6724 women aged ≥ 69 years with a mean follow-up of 9 years [[26]]. They reported higher hip fracture risk (hazard ratio (HR) = 1.40, 95% confidence interval (CI): 1.03–1.90) and non-spine fracture risk (HR = 1.25, 95% CI: 1.05–1.49) in frail women, compared with their robust peers. In addition, one study using data from the Canadian Multicentre Osteoporosis Study (CaMos) constructed a 30-item frailty index in 9423 adults with a mean age of 62 years and a 10-year follow-up [[29]]. Results indicated a significant HR of 1.18 for hip fractures and 1.30 for clinical vertebral fractures for every 0.10 increase in the frailty index.

In quantifying the risk of adverse health outcomes, even with statistical overlap and convergence, some studies argued that the continuous frailty index of deficit accumulation showed higher discriminatory ability than the categorical phenotype model [[9], [30][32]]. However, other comparative studies have found that the phenotype model was comparable with the frailty index in predicting risk of adverse outcomes [[33][35]]. For instance, results from a Chinese study presented similar predictive accuracy of the frailty index and the phenotype model for risk of mortality and physical limitation [[33]]. Likewise, our study using data from the Global Longitudinal Study of Osteoporosis in Women (GLOW) 3-year Hamilton Cohort did not find a significant difference in predictive accuracy for risk of osteoporotic fractures, even though the frailty index approach tended to yield more precise estimates as compared with the phenotype model [[35]]. These findings may imply the flexibility in the choice of frailty models in population-based settings for the elderly. However, the frailty index is usually considered as a research tool because of the amount of information it requires to complete the assessment, while the phenotype model can be pragmatically applied in geriatric clinical practice [[33], [35]]. Indeed, it has been suggested that the combined or sequential use of the two approaches should be implemented for the elderly, given that the frailty index and the phenotype model provide complementary and distinct clinical information on the risk profiles [[36]].

Current research investigating osteoporosis and frailty in the elderly

There are some studies using derivations of the phenotype model or other categorical frailty models to measure the degree of frailty. Results from the comparisons between them and the original phenotype model have been published, with comparable model performances reported in different populations [[3], [34], [37][40]]. In addition, evidence indicates that the phenotype model may require model calibration or redevelopment. Some studies have raised concerns about the scoring algorithm for the phenotype model, with emerging reports showing that not all the components contributed equally to the prediction of adverse health outcomes [[7], [41][43]]. Previous findings have suggested that slow walking appears to be the most important risk factor for adverse outcomes among the five indicators included in the phenotype model [[41], [42]]. Moreover, low predictive accuracy of the phenotype model in the prediction of adverse outcomes has been reported [[35], [37], [44]]. For instance, one study found the phenotype model could not differentiate the healthy elderly from those with unplanned hospital admission and falls, with an area under the receiver operating characteristic curve (AUC) value of 0.50 and 0.52 respectively [[44]]. Similarly, another study reported an AUC value of 0.55 for non-spine fractures and 0.63 for hip fractures in 6701 women using the phenotype model [[37]].

Regarding the frailty index approach, much of the literature focuses on the comparison between the frailty index and the phenotype model in predicting risk of adverse outcomes [[33][35], [38], [45][47]]. Of note, it may be methodologically challenging to directly compare the continuous frailty index and the categorical phenotype model. One study based on the GLOW 3-year Hamilton Cohort used three strategies to perform direct comparisons between the frailty index and the phenotype model by (1) investigating the associations between the adverse outcomes and respective per one-fifth (20%) increase of the frailty index and the phenotype model; (2) trichotomizing the frailty index according to the overlap in the density distribution of the frailty index by the robust, pre-frail and frail groups defined by the phenotype model; and (3) trichotomizing the participants based on a predicted probability function of outcomes predicted by the frailty index [[35]]. All the three strategies yielded comparable predictive accuracy of the frailty index and the phenotype model in predicting risk of adverse outcomes. Additionally, some studies compare the frailty index with other existing tools for predictions of risk of osteoporotic fractures. For instance, there was one study comparing the frailty index with the fracture risk assessment tool (FRAX) in prediction of risk of major osteoporotic fracture (spine, hip, upper arm or shoulder, or wrist) and hip fracture in 3985 elderly women [[48]]. The frailty index was found to be comparable with FRAX in predicting risk of major osteoporotic fractures and hip fracture, indicating that measuring grades of frailty may aid in fracture risk evaluation and fracture prevention for the elderly. Of note, we observed similar results in the women stratified by taking or not taking anti-osteoporotic treatments and/or supplementation, which indicated that the prediction of frailty index and FRAX in major osteoporotic fractures was not significantly influenced by the effect of anti-osteoporotic treatments and/or supplementation [[48]]. However, further studies are needed to evaluate whether the assessment of frailty would be a useful addition to FRAX to improve predictive accuracy for risk of fractures in the elderly. Furthermore, despite abundant studies investigating the trajectory nature of the frailty index in the elderly, limited evidence is available for the change of frailty before and after an osteoporotic fracture. In our study, we aimed to assess the change of the frailty index before and after onset of a major osteoporotic fracture during follow-up in the elderly women [[46]]. We found that the increase of the frailty index was significantly larger in the women who experienced a major osteoporotic fracture than their controls, indicating their greater deficit accumulation and accelerating frailty after a major osteoporotic fracture [[46]]. Investigating the transition nature by the change of frailty index before and after a major osteoporotic fracture may be useful to serve as an indicator for the effect of treatments or interventions [[16]]. For example, the change of frailty may be used to identify the minimally important differences (MIDs) in a fracture intervention study, taking into account the frailty transition nature [[46]]. Though results of the prediction of frailty status in risk of osteoporotic fractures are consistent in the literature, it still remains largely unknown whether frailty is a cause or a consequence of osteoporosis. For instance, some studies have reported no significant cross-sectional relationship between frailty and osteoporosis [[49], [50]], though frailty and osteoporosis share similar biological pathways and common risk factors such as advanced age, low physical activity, weight loss and cognitive decline [[51]]. More high-quality evidence is required to further clarify the association between frailty and osteoporosis dependently or independently of the aging process.

Future research directions

The phenotype model and the frailty index have been shown to be useful tools in predicting risk of osteoporotic fractures in the elderly. Future research may need to justify the validity and reliability of the frailty instruments in clinical settings and research studies, before they can be fully used to guide clinical decision-making [[16]]. Moreover, measures of frailty need to be tested against the effect of treatments or interventions in studies aiming to prevent or treat frailty. Likewise, the effect of frailty on recovery after a fracture or prevention of a secondary fracture in the elderly warrants further investigation. Besides, given that there is lack of an operational definition for frailty and sarcopenia, it would be a worthwhile endeavor to investigate the combined or sequential use of the instruments (or risk assessment tools) for frailty and sarcopenia in the elderly. Information on assessing frailty and sarcopenia may, together or in parallel of an osteoporosis assessment tool, provide more comprehensive vision of the risks to develop hard clinical outcomes for osteoporotic patients. Other research areas needed to be examined in depth include: 1) the relationship between frailty and osteoporotic fractures in different populations; 2) integration of elements of frailty to FRAX to determine whether higher predictive accuracy can be achieved; and 3) whether interventions in the pre-frail older adults can prevent osteoporotic fractures.

In addition, more studies are warranted to evaluate the role of the frailty instruments as an outcome measure, rather than just a risk assessment tool. As the frailer an elderly is, the greater the risk of osteoporotic fractures, quantifying the degree of frailty may be also helpful as an outcome measure, especially for some short-term fracture intervention studies. Furthermore, understanding the complexity of aging and frailty in the elderly necessitates more exploration of the aging nature per se.


In summary, we have presented an overview of the relationship between osteoporosis and frailty in the elderly. Measuring the degree of frailty in older adults by the frailty index and/or the phenotype model could assist in the assessment, management and decision-making for osteoporosis and osteoporotic fractures at a clinical research level and at a health care policy level. More evidence is needed to examine whether interventions in the pre-frail older adults can prevent osteoporotic fractures and to further support its usefulness and application of the frailty assessment in the elderly with osteoporosis in different populations.





This study received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

Availability of data and materials

The data appeared in this review are already publicly available in the literature.

Authors’ contributions

All the authors contributed to the study conception. GL was responsible for the draft of manuscript. LT, AP, GI, MAHL and JDA provided comments and made critical revision of the manuscript. All authors approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Not applicable.

Not applicable.


  1. NIH Consensus Development Panel on Osteoporosis Prevention, Diagnosis, and TherapyOsteoporosis prevention, diagnosis, and therapyJAMA2001285678579510.1001/jama.285.6.78511176917
  2. Assessment of fracture risk and its application to screening for postmenopausal osteoporosis. Report of a WHO Study Group. World Health Orga Tech Rep Ser. 1994: 843:1–129.
  3. DA HanleyRG JossePrevention and management of osteoporosis: consensus statements from the scientific advisory board of the osteoporosis society of Canada. 1. IntroductionCMAJ199615579219238837540
  4. O JohnellJ KanisEpidemiology of osteoporotic fracturesOsteoporos Int200516Suppl 2S3710.1007/s00198-004-1702-615365697
  5. O JohnellJA KanisAn estimate of the worldwide prevalence and disability associated with osteoporotic fracturesOsteoporos Int200617121726173310.1007/s00198-006-0172-416983459
  6. PR EbelingClinical practice. Osteoporosis in menN Engl J Med2008358141474148210.1056/NEJMcp070721718385499
  7. F CosmanSJ de BeurMS LeBoffEM LewieckiB TannerS RandallR LindsayClinician’s guide to prevention and treatment of osteoporosisOsteoporos Int201425102359238110.1007/s00198-014-2794-225182228
  8. LA BeaupreCA JonesLD SaundersDW JohnstonJ BuckinghamSR MajumdarBest practices for elderly hip fracture patients. A systematic overview of the evidenceJ Gen Intern Med200520111019102510.1111/j.1525-1497.2005.00219.x16307627
  9. A CleggJ YoungS IliffeMO RikkertK RockwoodFrailty in elderly peopleLancet (London, England)2013381986875276210.1016/S0140-6736(12)62167-9
  10. RJ GobbensKG LuijkxMT Wijnen-SponseleeJM ScholsToward a conceptual definition of frail community dwelling older peopleNurs Outlook2010582768610.1016/j.outlook.2009.09.00520362776
  11. QL XueThe frailty syndrome: definition and natural historyClin Geriatr Med201127111510.1016/j.cger.2010.08.00921093718
  12. RM CollardH BoterRA SchoeversRC Oude VoshaarPrevalence of frailty in community-dwelling older persons: a systematic reviewJ Am Geriatr Soc20126081487149210.1111/j.1532-5415.2012.04054.x22881367
  13. N AhmedR MandelMJ FainFrailty: an emerging geriatric syndromeAm J Med2007120974875310.1016/j.amjmed.2006.10.01817765039
  14. JE MorleyMT HarenY RollandMJ KimFrailtyMed Clin N Am200690583784710.1016/j.mcna.2006.05.01916962845
  15. R RoubenoffSarcopenia: a major modifiable cause of frailty in the elderlyJ Nutr Health Aging199943140142
  16. K RockwoodO TheouA MitnitskiWhat are frailty instruments for?Age Ageing201544454554710.1093/ageing/afv04325824236
  17. JP van den BerghTA van GeelPP GeusensOsteoporosis, frailty and fracture: implications for case finding and therapyNat Rev Rheumatol20128316317210.1038/nrrheum.2011.21722249162
  18. K RockwoodWhat would make a definition of frailty successful?Age Ageing200534543243410.1093/ageing/afi14616107450
  19. LP FriedCM TangenJ WalstonAB NewmanC HirschJ GottdienerT SeemanR TracyWJ KopG BurkeFrailty in older adults: evidence for a phenotypeJ Gerontol A Biol Sci Med Sci2001563M14615610.1093/gerona/56.3.M14611253156
  20. K RockwoodX SongC MacKnightH BergmanDB HoganI McDowellA MitnitskiA global clinical measure of fitness and frailty in elderly peopleCMAJ2005173548949510.1503/cmaj.05005116129869
  21. N De VriesJ StaalC Van RavensbergJ HobbelenM Olde RikkertM Nijhuis-Van der SandenOutcome instruments to measure frailty: a systematic reviewAgeing Res Rev201110110411410.1016/j.arr.2010.09.00120850567
  22. SD SearleA MitnitskiEA GahbauerTM GillK RockwoodA standard procedure for creating a frailty indexBMC Geriatr200882410.1186/1471-2318-8-2418826625
  23. K RockwoodA MitnitskiHow might deficit accumulation give rise to frailtyJ Frailty Aging2012181227092931
  24. A MitnitskiX SongI SkoogGA BroeJL CoxE GrunfeldK RockwoodRelative fitness and frailty of elderly men and women in developed countries and their relationship with mortalityJ Am Geriatr Soc200553122184218910.1111/j.1532-5415.2005.00506.x16398907
  25. K RockwoodA MitnitskiFrailty in relation to the accumulation of deficitsJ Gerontol A Biol Sci Med Sci200762772272710.1093/gerona/62.7.72217634318
  26. KE EnsrudSK EwingBC TaylorHA FinkKL StoneJA CauleyJK TracyMC HochbergN RodondiPM CawthonFrailty and risk of falls, fracture, and mortality in older women: the study of osteoporotic fracturesJ Gerontol A Biol Sci Med Sci200762774475110.1093/gerona/62.7.74417634322
  27. SE TomJD AdachiFA Anderson JrS BoonenRD ChapurlatJE CompstonC CooperSH GehlbachSL GreenspanFH HoovenFrailty and fracture, disability, and falls: a multiple country study from the global longitudinal study of osteoporosis in womenJ Am Geriatr Soc201361332733410.1111/jgs.1214623351064
  28. X FangJ ShiX SongA MitnitskiZ TangC WangP YuK RockwoodFrailty in relation to the risk of falls, fractures, and mortality in older Chinese adults: results from the Beijing Longitudinal Study of AgingJ Nutr Health Aging2012161090390710.1007/s12603-012-0368-623208030
  29. C KennedyG IoannidisK RockwoodL ThabaneJ AdachiS KirklandL PickardA PapaioannouA frailty index predicts 10-year fracture risk in adults age 25 years and older: results from the Canadian multicentre osteoporosis study (CaMos)Osteoporos Int201425122825283210.1007/s00198-014-2828-925103215
  30. AM KulminskiSV UkraintsevaIV KulminskayaKG ArbeevK LandAI YashinCumulative deficits better characterize susceptibility to death in elderly people than phenotypic frailty: lessons from the cardiovascular health studyJ Am Geriatr Soc200856589890310.1111/j.1532-5415.2008.01656.x18363679
  31. K RockwoodM AndrewA MitnitskiA comparison of two approaches to measuring frailty in elderly peopleJ Gerontol A Biol Sci Med Sci200762773874310.1093/gerona/62.7.73817634321
  32. HW JungSW KimS AhnJY LimJW HanTH KimKW KimKI KimCH KimPrevalence and outcomes of frailty in Korean elderly population: comparisons of a multidimensional frailty index with two phenotype modelsPLoS One201492e8795810.1371/journal.pone.008795824505338
  33. J WooJ LeungJE MorleyComparison of frailty indicators based on clinical phenotype and the multiple deficit approach in predicting mortality and physical limitationJ Am Geriatr Soc20126081478148610.1111/j.1532-5415.2012.04074.x22861118
  34. R RavindrarajahDM LeeSR PyeE GielenS BoonenD VanderschuerenN PendletonJD FinnA TajarMD O’ConnellThe ability of three different models of frailty to predict all-cause mortality: results from the European Male Aging Study (EMAS)Arch Gerontol Geriatr201357336036810.1016/j.archger.2013.06.01023871598
  35. G LiL ThabaneG IoannidisC KennedyA PapaioannouJD AdachiComparison between frailty index of deficit accumulation and phenotypic model to predict risk of falls: data from the global longitudinal study of osteoporosis in women (GLOW) Hamilton cohortPLoS One2015103e012014410.1371/journal.pone.012014425764521
  36. M CesariG GambassiGA van KanB VellasThe frailty phenotype and the frailty index: different instruments for different purposesAge Ageing2014431101210.1093/ageing/aft16024132852
  37. KE EnsrudSK EwingBC TaylorHA FinkPM CawthonKL StoneTA HillierJA CauleyMC HochbergN RodondiComparison of 2 frailty indexes for prediction of falls, disability, fractures, and death in older womenArch Intern Med2008168438238910.1001/archinternmed.2007.11318299493
  38. TK MalmstromDK MillerJE MorleyA comparison of four frailty modelsJ Am Geriatr Soc201462472172610.1111/jgs.1273524635726
  39. K Bandeen-RocheQ-L XueL FerrucciJ WalstonJM GuralnikP ChavesSL ZegerLP FriedPhenotype of frailty: characterization in the women’s health and aging studiesJ Gerontol A Biol Sci Med Sci200661326226610.1093/gerona/61.3.26216567375
  40. CM BoydQL XueCF SimpsonJM GuralnikLP FriedFrailty, hospitalization, and progression of disability in a cohort of disabled older womenAm J Med2005118111225123110.1016/j.amjmed.2005.01.06216271906
  41. TM GillEA GahbauerHG AlloreL HanTransitions between frailty states among community-living older personsArch Intern Med2006166441842310.1001/archinte.166.4.41816505261
  42. DK KielyLA CupplesLA LipsitzValidation and comparison of two frailty indexes: The MOBILIZE Boston StudyJ Am Geriatr Soc20095791532153910.1111/j.1532-5415.2009.02394.x19682112
  43. MD RothmanL Leo-SummersTM GillPrognostic significance of potential frailty criteriaJ Am Geriatr Soc200856122211211610.1111/j.1532-5415.2008.02008.x19093920
  44. HH AtkinsonC RosanoEM SimonsickJD WilliamsonC DavisWT AmbrosiusSR RappM CesariAB NewmanTB HarrisCognitive function, gait speed decline, and comorbidities: the health, aging and body composition studyJ Gerontol A Biol Sci Med Sci200762884485010.1093/gerona/62.8.84417702875
  45. M RittC SchwarzV KronawitterA DelinicLC BollheimerKG GassmannCC SieberAnalysis of Rockwood et Al’s clinical frailty scale and fried et Al’s frailty phenotype as predictors of mortality and other clinical outcomes in older patients Who were admitted to a geriatric wardJ Nutr Health Aging201519101043104810.1007/s12603-015-0667-926624218
  46. E DentI ChapmanS HowellC PiantadosiR VisvanathanFrailty and functional decline indices predict poor outcomes in hospitalised older peopleAge Ageing201443447748410.1093/ageing/aft18124257468
  47. FJ van DeudekomM van de RuitenbeekW Te WaterJM SmitBC van MunsterFrailty index and frailty phenotype in elderly patients with cancerActa oncologica (Stockholm, Sweden)201655564464610.3109/0284186X.2015.1096022
  48. G LiL ThabaneA PapaioannouJD AdachiComparison between frailty index of deficit accumulation and fracture risk assessment tool (FRAX) in prediction of risk of fracturesBone20157710711410.1016/j.bone.2015.04.02825916552
  49. P GerdhemKA RingsbergH MagnussonKJ ObrantK AkessonBone mass cannot be predicted by estimations of frailty in elderly ambulatory womenGerontology200349316817210.1159/00006916912679607
  50. SA SternbergR LevinS DkaidekS EdelmanT ResnickJ MenczelFrailty and osteoporosis in older women--a prospective studyOsteoporos Int201425276376810.1007/s00198-013-2471-x24002542
  51. Y RollandG Abellan Van KanA BenetosH BlainM BonnefoyP ChassagneC JeandelM LarocheF NourhashemiP OrcelFrailty, osteoporosis and hip fracture: causes, consequences and therapeutic perspectivesJ Nutr Health Aging200812533534610.1007/BF0298266518443717
The underlying source XML for this text is taken from The license for the article is Creative Commons Attribution 4.0 International. The main subject has been identified as osteoporosis.