‘This is the peer reviewed version of the following article: Denk, K., Lennon, S., Gordon, S., & Jaarsma, R. L.
(2018). The association between decreased hand grip strength and hip fracture in older people: A systematic review. Experimental Gerontology, 111, 1–9. https://
doi.org/10.1016/j.exger.2018.06.022 which has been published in final form at https://doi.org/10.1016/j.exger.2018.06.022
© 2018 Elsevier inc. This manuscript version is made available under the CC-BY-NC-ND 4.0 license:
http://creativecommons.org/licenses/by-nc-nd/4.0/
The association between decreased hand grip strength and hip fracture in older people: A systematic review
Katharina Denk, Sheila Lennon, Susan Gordon, Ruurd Lucas Jaarsma
PII: S0531-5565(18)30322-X
DOI: doi:10.1016/j.exger.2018.06.022
Reference: EXG 10394
To appear in:
Experimental GerontologyReceived date: 10 May 2018
Revised date: 19 June 2018
Accepted date: 22 June 2018
Please cite this article as: Katharina Denk, Sheila Lennon, Susan Gordon, Ruurd Lucas Jaarsma , The association between decreased hand grip strength and hip fracture in older people: A systematic review. Exg (2018), doi:10.1016/j.exger.2018.06.022
This is a PDF file of an unedited manuscript that has been accepted for publication. As
a service to our customers we are providing this early version of the manuscript. The
manuscript will undergo copyediting, typesetting, and review of the resulting proof before
it is published in its final form. Please note that during the production process errors may
be discovered which could affect the content, and all legal disclaimers that apply to the
journal pertain.
ACCEPTED MANUSCRIPT
1 Title:
The association between decreased hand grip strength and hip fracture in older people: a systematic review
Corresponding author:
Katharina Denka,b,c, PT, MAppSc Postal address:
Flinders Medical Centre, Department of Orthopaedic Surgery & Trauma, Room 5A155, Flinders Drive, Bedford Park, South Australia 5042, AUSTRALIA
Email:
[email protected]; [email protected] Phone:
+61 8 82044673 Co- authors:
Professor Sheila Lennona, PT, PhD Professor Susan Gordona, BAppSc, PhD
Professor Ruurd Lucas Jaarsmab,c, MD, PhD, FRACS, FAOrthA
aFlinders University, College of Nursing and Health Sciences
Sturt Road, Bedford Park, South Australia 5042, AUSTRALIA [email protected]
bFlinders University, College of Medicine and Public Health
Sturt Road, Bedford Park, South Australia 5042, AUSTRALIA [email protected]
cFlinders Medical Centre, Department of Orthopaedic Surgery & Trauma Flinders Drive, Bedford Park, South Australia 5042, AUSTRALIA [email protected]
Disclosure of potential conflicts of interest:
The above listed authors have nothing to disclose.
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
ACCEPTED MANUSCRIPT
2
ACCEPTED MANUSCRIPT
3 The association between decreased hand grip strength and hip fracture in older people: a systematic review
ABSTRACT
Hip fractures are a global concern, resulting in poor outcomes and high health care costs.
They mostly affect people >80 years. Hip fractures are influenced by various (modifiable) risk factors. Emerging evidence suggests hand grip strength (HGS) to be one of several useful tools to identify hip fracture risk. This is the first systematic review that aims to assess the evidence underlying the relationship between hip fracture incidence and HGS.
Eleven studies were selected for this review (six case-control and five cohort studies), comprising 21197 participants. Where reported, HGS was significantly decreased in individuals with a hip fracture near the time of injury as compared to controls (p<0.001);
HGS was associated with increased hip fracture risk in all included studies. Meta-analysis was not possible.
All studies included in this systematic review confirmed a relationship between decreased HGS and hip fracture incidence. We were not able to quantify the strength of this
relationship, due to the heterogeneity of the included studies. HGS merits further investigation as a useful tool for identifying individuals that might be at elevated risk for sustaining a hip fracture.
Key words: Hand grip strength, hip fracture, proximal femur fracture, frailty, risk factor 1. Introduction
Low impact fractures of the proximal femur (hip fractures) are a major worldwide public health concern (Hernlund et al., 2013; Kanis et al., 2012; The World Bank, 2015). They mostly occur in people older than 80 years (Kistler et al., 2015).
As the population ages, hip fractures are predicted to increase by 35% between 2012 and 2022; the annual cost will rise to $1.27 billion in Australia alone (Watts et al., 2013). The current annual hospital cost of hip fractures in the UK has been estimated at £1.1 billion (Leal et al., 2016).
Thus, it is vital to further improve fracture prevention strategies, not only to decrease health care costs, but also to reduce devastating outcomes such as morbidity, disability,
dependency, and poor quality of life (Griffin et al., 2015; Parker, 2016).
Many, often modifiable, risk factors need to be considered for hip fracture prevention.
Osteoporosis (Kanis, 1994) and falls (Jarvinen et al., 2008) are recognized risk factors for sustaining a hip fracture. Other factors include, but are not limited to, sarcopenia (Oliveira and Vaz, 2015), muscle weakness, physical inactivity, impaired cognition, impaired vision, and chronic health conditions (Marks, 2010).
The current gold standard screening tool to assist in identifying those most at risk of hip fracture is the Fracture Risk Assessment Tool (FRAX®). FRAX is based on 12 variables: age, sex, weight, height, previous fracture, parent fractured hip, current smoking,
glucocorticoids, rheumatoid arthritis, secondary osteoporosis, alcohol (three or more units/day), and femoral neck bone mineral density (BMD) (The University of Sheffield, 2011). Low BMD, the cardinal sign of osteoporosis, was established as the number one risk factor for sustaining a hip fracture more than two decades ago (Kanis, 1994). However, only between 10% and 44% of fractures occur in people with osteoporosis (Jarvinen et al., 2015;
Stone et al., 2003). Hence the value and benefit of FRAX have become a subject of debate.
General validity and reliability appear to be higher in women than in men (Sandhu et al.,
ACCEPTED MANUSCRIPT
4 2010). When used without BMD, FRAX does not perform any better than only screening for age and previous fracture incidence (Rubin et al., 2013; Sambrook et al., 2011). FRAX does not include variables like activity level, muscle strength and mass, or falls history, and does not differentiate between different types of previous fractures (number, site, severity) (Silverman and Calderon, 2010).
Investigating other aspects of hip fracture prevention seems therefore critical when striving for an inclusive evidence based approach.
This review focused on the relationship between hip fracture and hand grip strength (HGS), with the latter being an indicator for overall muscle strength (Hirschfeld et al., 2017;
Rantanen et al., 2003) and an important measure for frailty (Syddall et al., 2003),
sarcopenia (Chen et al., 2014; Cruz-Jentoft et al., 2010) and osteoporosis (Cheung et al., 2012; Kritz-Silverstein and Barrett-Connor, 1994).
1.1 Hip fracture, hand grip strength, and frailty
It is well recognised that hip fractures affect individuals aged 65 and over, with the majority being older than 80 years (Auais et al., 2013; Kistler et al., 2015). As people age, the likelihood of developing chronic diseases or geriatric syndromes increases. Two of those ageing related conditions are osteoporosis and sarcopenia. They have similar risk factors and often occur simultaneously, then referred to as osteosarcopenia (Hirschfeld et al., 2017).
Osteoporosis is an undisputed major risk factor for sustaining a hip fracture. Decreased BMD makes the proximal femur susceptible to breaking, with no or minimal impact involved (Kanis, 1994). There is somewhat conflicting but mostly positive evidence for a relationship between HGS and systemic BMD (Dixon et al., 2005).
Sarcopenia is a recognized factor in hip fracture risk (Ho et al., 2016; Oliveira and Vaz, 2015; Tarantino et al., 2015). Progressive, generalized loss of muscle strength and mass lead to an increased risk of falls (impaired neuromuscular function) and decreased bone strength (lack of mechanical forces) (Cederholm et al., 2013).
The clinical diagnosis of sarcopenia is based on three criteria: decreased muscle mass, poor physical performance (gait speed), and decreased muscle strength (HGS) (Chen et al., 2014;
Cruz-Jentoft et al., 2010).
Not surprisingly, Huo et al. (2015) demonstrated gait velocity and HGS to be reduced in patients with osteosarcopenia (p>0.001), and Yoo et al. (2018) found that 28.7% of their 324 hip fracture patients had osteosarcopenia.
Relationships between HGS and postoperative complications, length of hospital stay, discharge destination, disability, multi-morbidity, chronic disease, cognition, mortality, fractures, poor physical performance, and decreased mobility have also been demonstrated (Bohannon, 2008; Cheung et al., 2013; Cheung et al., 2012; Keevil et al., 2013; Lloyd et al., 2009; Rijk et al., 2016; Roberts et al., 2012).
A causal link between HGS and all the aforementioned conditions and outcomes is considered unlikely. Bohannon (2008) suggested the linking factor to be frailty.
An operational definition of frailty has not yet been established, (Rodriguez-Manas et al., 2013) but it is generally accepted that genetic and environmental factors of aging are potentially reducing the physiological reserve in several body systems. Together with decreased physical activity and poor nutrition, this leads to increased vulnerability to poor resolution of homeostasis after a stressor event, which causes increased risk of adverse
ACCEPTED MANUSCRIPT
5 outcomes (Clegg et al., 2013). Sarcopenia, osteoporosis, and osteosarcopenia can be
considered part of frailty (Hirschfeld et al., 2017). Frailty is associated with chronological age (Bassey and Harries, 1993), but Syddall et al. (2003) demonstrated an even stronger
association between frailty and (decreased) age and gender stratified HGS. They hence suggested that HGS could possibly be used as a single marker for frailty. Several instruments and scores for diagnosing and monitoring frailty have been developed, and many of them include HGS measures (Buta et al., 2016; de Vries et al., 2011). An example is the currently most cited score, Fried’s Phenotype (Fried et al., 2001). It includes HGS as one of two objective measures, together with gait speed, the same criteria as used for diagnosing sarcopenia (Chen et al., 2014; Cruz-Jentoft et al., 2010).
Frailty measures appear to aid in the prediction of: early complications post hip fracture surgery (Kistler et al., 2015; Kua et al., 2016), adverse outcomes in older inpatients (Hubbard et al., 2017), nursing home placement (Kojima, 2018), falls risk, fracture risk, mortality, length of hospital stay (Ensrud et al., 2007; Khandelwal et al., 2012; Kistler et al., 2015), disability (Vermeulen et al., 2011), and cognitive decline (Godin et al., 2017).
Evidence based cut-off points for identifying low HGS are available from current literature.
Dodds et al. (2014) published very well informed normative, age and gender stratified HGS data and suggested cut-off points at 32kg for men and 19kg for women (based on a T-score of -2 or below), measured with a dynamometer. They later conducted a systematic review and meta-analysis to investigate differences in grip strength by world region, which supported the use of their cut-off points across developed regions (Dodds et al., 2016).
The European Working Group on Sarcopenia in Older People (EWGSOP) recommended generic cut-off points at 30kg for men and 20kg for women; they then suggested
differentiating further depending on a person’s body mass index (BMI) (Cruz-Jentoft et al., 2010).
The Asian Working Group for Sarcopenia (AWGS) provided two sets of cut-off points. Base on Japanese data: 30.3kg for men and 19.3kg for women; base on the recommendations by the EWGSOP, adjusted according to Asian data: >22.4kg for men and >14.3kg for women (Chen et al., 2014).
Many epidemiological studies investigating HGS and its relationship to various parameters have been published over the past few decades. Several systematic reviews have been conducted to summarize this evidence:
Bohannon (2008) looked at HGS as a prognostic tool for negative health outcomes; Norman et al. (2011) established HGS as a marker for nutritional status; den Ouden et al. (2011) related HGS to disability in later life; and Rijk et al. (2016) looked more broadly at the prognostic value of HGS in older individuals.
To our knowledge, no previous review has looked specifically at the relationship between decreased HGS and hip fracture incidence. We believe that HGS is a simple, inexpensive measure that has potential to aid in the identification of individuals at risk of hip fracture. It may support hip fracture prevention strategies and thus help older people to maintain their independence.
1.2 Aim of this review
This paper systematically reviewed the literature about HGS in relation to individuals with hip fracture, pre-injury or at acute presentation, and assessed the strength of the evidence for a relationship between HGS and hip fracture.
ACCEPTED MANUSCRIPT
6 2 Methods
2.1 Search strategy
A systematic review of current literature was conducted. (PROSPERO Registration number:
CRD42014010080). The reporting of this paper conforms to the process outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement (Liberati et al., 2009; Moher et al., 2009). A comprehensive computerized database search was performed in Ovid MEDLINE(R), PubMed, Embase, CINAHL, Scopus, and Cochrane Library (both controlled trials and reviews) from each database’s earliest inception data to January 2018. The initial search was performed in Ovid MEDLINE(R), using Medical Subject Headings (MeSH terms), explode functions (brackets to break a string into an array), keyword searching, truncations (to retrieve all alternative terms), adjacency (to narrow search) and Boolean operators (connectors AND/OR). The key words of HGS and proximal femur fracture were combined to conduct the search. The full search strategy can be found in appendix 1. References of included papers were hand-searched for further relevant studies.
2.2 Inclusion criteria and study identification
The inclusion criteria comprised of: adults aged 50 years or older; that had their HGS measured at least once during the study period; with hip fracture as an outcome. Any study design was included. Publications written in a language other than English were excluded.
Studies focusing on recovery after hip fracture were not included. Populations with pathological hip fractures were excluded.
Eligible studies were identified by two reviewers independently (KD and RJ). Titles of all citations identified through database and reference searches were screened for relevance.
Selected studies underwent abstract screening, determining aptness based on inclusion criteria. Remaining papers were assessed in full text for confirmation of eligibility and subsequent critical appraisal.
2.3 Critical appraisal, grading of evidence and data analysis
The Joanna Briggs Institute (JBI) Critical Appraisal Checklists (Joanna Briggs Institute, 2016) were used to critically assess methodological quality. JBI checklists were chosen over all other available checklists because a) separate tailored checklists are available for each study type; and b) they are based on extensive research on evidence base health care.(Pearson et al., 2009) Two authors (KD and SL) independently marked all included studies. Each ‘yes’ scored one point; the maximum score was 100%. Where the two reviewers could not reach consensus at any item, a third reviewer (RJ) made the final decision.
Overall evidence was graded using previously published criteria (Brennan et al., 2011;
Lievense et al., 2002) with four levels of evidence (no evidence to strong evidence) based on quality, design and number of included studies (appendix 2).
In order to compare HGS measures, values provided in Newton were converted into
Kilograms (kg); values provided in Kilopascal (kPa) could not be converted (conversion only possible to Kilogram force per square meter).
3 Results
3.1 Selection of studies
The data base search returned 526 studies; two more studies were identified by hand searching reference lists. Following removal of duplicates using endnote X8, 271 studies
ACCEPTED MANUSCRIPT
7 were screened; 79 underwent full-text review. Eleven studies were included in the review (see figure 1). The most common reasons for excluding studies were: populations of children or adolescents; assessing HGS in relation to minimal trauma fractures of all sites combined (vertebra, wrist, hip etc.); exploring the association between HGS and outcomes post hip fracture; correlating HGS with BMD and other outcomes like falls. Only one study was excluded due to language.
[Figure 1 about here]
3.2 Study characteristics
The 11 papers included in this review comprised six case-control studies (Bean et al., 1995;
Coupland et al., 1993; Elliot et al., 1992; Lan et al., 2010; Lau et al., 1993; Meyer et al., 1995), and five cohort studies (Cawthon et al., 2008; Dargent-Molina et al., 1996;
Karkkainen et al., 2008; Kauppi et al., 2014; Robbins et al., 2005), published between 1992 and 2014.
Two publications - one by Dargent-Molina et al. (1996), the other by Robbins et al. (2005) - were based on the same data resulting from the EPIDOS study, with different aims.
Dargent-Molina et al. (1996) conducted their analyses at an earlier stage of the study with shorter follow up time and with a lower number of hip fractures. They also had a lower total number of participants (7575 versus 7598) which might be due to the exclusion of women that were unable to walk independently. We tried to contact the main author for clarification but did not receive a response. We decided to evaluate both studies independently, but for calculating the total number of participants included in our review, we only added the higher number once.
The cohorts had large sample sizes (average n=4682), but very low hip fracture incidence with an average of only 2.25% (ranging from 0.3% (Karkkainen et al., 2008) to 3.8%
(Dargent-Molina et al., 1996; Robbins et al., 2005)). Sample sizes of case- control studies were much smaller (average n=414), but at least 30% of the studied populations were hip fracture cases.
Included studies sought to determine key risk factors for hip fracture or relationships between hip fracture and selected variables. The 11 included studies reported on 74 different variables. None of the studies’ primary objective was to assess the relationship between HGS and hip fracture risk. An overview of all selected studies is presented in table 1.
[Table 1 about here]
3.3 Participant characteristics
The mean age of participants was 59 years in two studies (Karkkainen et al., 2008; Kauppi et al., 2014), and >70 years in the remaining nine papers. The proportion of female participants was considerably higher in nine studies; only one study looked solely at men (Cawthon et al., 2008). This reflects the demography of hip fracture (Dhanwal et al., 2011).
Seven studies specifically excluded individuals with cognitive impairments and/or the
inability to give written informed consent (Bean et al., 1995; Cawthon et al., 2008; Coupland et al., 1993; Dargent-Molina et al., 1996; Elliot et al., 1992; Meyer et al., 1995; Robbins et al., 2005); the remaining four studies did not mention the cognitive status of participants (Karkkainen et al., 2008; Kauppi et al., 2014; Lan et al., 2010; Lau et al., 1993).
In five case-control studies participants were age and sex matched (Bean et al., 1995;
Coupland et al., 1993; Elliot et al., 1992; Lan et al., 2010; Meyer et al., 1995), one used
ACCEPTED MANUSCRIPT
8 random samples (Lau et al., 1993). Controls were either drawn from community samples or from existing longitudinal studies which included aging individuals.
3.4 Methodological quality and strength of evidence
Two authors (KD; SL) independently assessed the quality of the included studies and reached 95% of agreement initially. Disagreement was resolved by discussion. The final overall quality scores for each study and reasons for lost points are shown in appendix 3. Six of the eleven studies scored 100% (Cawthon et al., 2008; Coupland et al., 1993; Karkkainen et al., 2008; Kauppi et al., 2014; Lan et al., 2010; Meyer et al., 1995) and one study scored below 50% (Lau et al., 1993). The issues for studies scoring low were: confounding factors not addressed, insufficient follow up time, poor reporting, and method for HGS measures not specified (appendix 3).
All studies were observational. Grading of the overall evidence based on Brennan et al.
(2011) confirmed strong evidence for a relationship between HGS and hip fracture incidence (“generally consistent findings in multiple high-quality cohort studies”).
It was however not possible to comment on the strength of that relationship, as studies were not comparable with regard to design, analyses, populations, primary objectives and dynamometer brands. Pooling data for meta-analysis was therefore also not possible.
3.5 HGS and in relation to hip fracture incidence
The total sample size across the selected studies was 21197, of which 1392 (6.56%) had sustained a hip fracture. All studies described some evidence for a relationship between HGS and hip fracture incidence.
3.6 Statistically significantly decreased HGS in individuals with hip fracture
HGS was significantly decreased in individuals with hip fracture at the time of injury as compared to controls, (p<0.001) (Bean et al., 1995; Elliot et al., 1992; Lau et al., 1993), and at baseline when assessing a cohort (p<0.001) (Kauppi et al., 2014; Robbins et al., 2005). The remaining studies did not report on the sole differences in HGS between study groups and controls/unaffected participants.
3.7 HGS as a risk factor for sustaining a hip fracture
HGS was associated with increased hip fracture risk in all 11 included studies (Bean et al., 1995; Cawthon et al., 2008; Coupland et al., 1993; Dargent-Molina et al., 1996; Elliot et al., 1992; Karkkainen et al., 2008; Kauppi et al., 2014; Lan et al., 2010; Lau et al., 1993; Meyer et al., 1995; Robbins et al., 2005). The study that looked solely at males found some
association between decreased HGS and fracture risk within the lowest HGS group, but did find a much stronger association between the inability to perform the HGS test and fracture risk (Cawthon et al., 2008).
In seven studies, authors aimed to determine if risk factors were independent (Bean et al., 1995; Cawthon et al., 2008; Coupland et al., 1993; Dargent-Molina et al., 1996; Kauppi et al., 2014; Lan et al., 2010; Lau et al., 1993). HGS remained as an independent risk factor for sustaining a hip fracture in three studies (Bean et al., 1995; Coupland et al., 1993; Lan et al., 2010).
Risks were established using multiple and logistic regressions in case control studies, and Cox regressions in cohort studies. Multivariate models were used to determine the
independence of risk factors. Risks were presented as odds ratios, hazard ratios and relative risks. Over all, the risk increase for sustaining a hip fracture based on decreased HGS varied
ACCEPTED MANUSCRIPT
9 greatly between the studies. Risk increased as little as 0.7 times in one study (Kauppi et al., 2014) to as much as 49.5 times in another (Coupland et al., 1993).
3.8 HGS values compared to stratified means and cut-off points HGS for hip fracture cases was provided in five studies:
In the female United Kingdom population examined by Bean et al. (1995) the mean HGS of controls was 2.46% below the age and gender stratified means established by Dodds et al.
(2014) (see table 1), and the HGS of cases was 39.1% below the stratified mean. The cases’
mean dominant HGS was well below the 20 kg cut-off point recommended for females by the EWGSOP (Cruz-Jentoft et al., 2010).
In the study by Lau et al. (1993) all Hong Kong participants were below the stratified mean (Dodds et al., 2014) (male controls 35.1%, male cases 60.6% , female controls 43.15%, and female cases 58.9%). Cases’ HGS was well below the 22.4 kg (males) and 14.3 kg (females) cut-off points recommended for Asian populations (Chen et al., 2014).
In the French study reported by Robbins et al. (2005), HGS was recorded in kPa. Cases were significantly weaker than the rest of the cohort but no comparisons with means or cut- off points were possible, as they are presented in kg.
Elliot et al. (1992) and Kauppi et al. (2014) combined males and females; no comparisons with means or cut-off points were possible, as they are gender specific. However, in both studies, cases’ HGS was well below the stratified mean for females, and well below the EWGSOP cut-off point for females.
In the remaining six studies (Cawthon et al., 2008; Coupland et al., 1993; Dargent-Molina et al., 1996; Karkkainen et al., 2008; Lan et al., 2010; Meyer et al., 1995), HGS of all
participants was divided into tertiles or quartiles and there was no distinction between HGS of cases and controls/participants without fracture; only the numbers of fractures within each tertile/quartile were stated.
3.9 Measurement of HGS
Baseline measures of HGS taken before the point of fracture were only available for the four cohorts, where recruitment had occurred prior to the hip fracture; the length of time from measurement to fracture was not provided. For the case-control populations, HGS had been measured either within 72 hours of the hip fracture or between 72 hours and two weeks post fracture. A variety of different dynamometer devices was used to measure HGS,
ranging from a custom-built strain gauge (Bean et al., 1995) to a Jamar device (Cawthon et al., 2008); three studies did not specify the brand (Coupland et al., 1993; Dargent-Molina et al., 1996; Lau et al., 1993; Robbins et al., 2005). Methods of HGS measurements also varied greatly between studies. In five studies both hands were measured (Bean et al., 1995;
Cawthon et al., 2008; Coupland et al., 1993; Dargent-Molina et al., 1996; Lau et al., 1993;
Robbins et al., 2005), in three studies the dominant (Elliot et al., 1992; Karkkainen et al., 2008; Lan et al., 2010), and in one study the non-dominant hand (Meyer et al., 1995). The number of measurements diverged widely from the best of two attempts (Cawthon et al., 2008; Kauppi et al., 2014), to best of six attempts (Bean et al., 1995). No information about the method of measurement was provided for publications resulting from the EPIDOS study (Dargent-Molina et al., 1996; Robbins et al., 2005).
4 Discussion
4.1 Summary of findings
ACCEPTED MANUSCRIPT
10 This systematic review aimed to assess the evidence for a relationship between HGS and hip fracture incidence. Our findings confirm an association between decreased HGS and hip fracture incidence. The retrieved evidence conclusively confirms: a) patients with hip fracture have decreased HGS at the time of hip fracture; b) decreased HGS is a risk factor for sustaining a hip fracture.
Previously published systematic reviews investigated HGS and frailty, and their prognostic value for several variables: HGS has predictive power for mortality, decreased mobility, and cognitive decline in older people (Rijk et al., 2016). HGS is an important factor of frailty (Chainani et al., 2016; Syddall et al., 2003), and frailty is a predictor/risk factor for falls in older people (Cheng and Chang, 2017; Kojima, 2015). This is the first systematic review to objectively confirm the relationship between decreased HGS and hip fracture in older people.
None of the studies included in this review exclusively assessed the relationship between HGS and hip fracture. The 11 included studies reported on 74 different variables. We had targeted our comprehensive data base search towards finding papers about HGS. Thus, only some variables were considered in more than one study. Amongst the most mentioned variables related to hip fracture were low BMD (considered in six studies (Cawthon et al., 2008; Dargent-Molina et al., 1996; Elliot et al., 1992; Lan et al., 2010; Lau et al., 1993;
Robbins et al., 2005) with significant results in four (Dargent-Molina et al., 1996; Lan et al., 2010; Lau et al., 1993; Robbins et al., 2005)) and falls (considered in five studies (Cawthon et al., 2008; Elliot et al., 1992; Lan et al., 2010; Meyer et al., 1995; Robbins et al., 2005) with significant results in two (Lan et al., 2010; Robbins et al., 2005)). Even though we did not aim to search for risk factors other than HGS, our review highlights the dominance of low BMD and falls as perceived main factors for hip fracture. On the other hand, the large number of other variables investigated in the 11 studies also shows that the pathogenesis of hip fractures is complex, far beyond just BMD and falls.
Frailty was briefly mentioned in the discussion of four papers (Cawthon et al., 2008;
Dargent-Molina et al., 1996; Karkkainen et al., 2008; Lan et al., 2010), but one of the included papers discussed the concept of frailty; this might be because most papers’
publication date predates the wider recognition of frailty as a concept, starting with Fried et al. (2001) and Rockwood (2005).
4.2 ‘Risk factor’, what does that mean?
All included studies talked about risk factors or correlations.
There is consensus in the literature that a risk factor is an exposure that pre-dates and is in some way related to an outcome. There is no certitude on how strong the association between exposure and outcome has to be for the former to become a risk factor, or if the exposure must be causal (Burt, 2001).
Five out of the 11 included studies were longitudinal and exposure clearly pre-dated outcome. The remaining six studies were case control studies, where it is impossible to prove that the exposure pre-dated that outcome; Burt (2001) suggested using the term ‘risk indicator’ rather than ‘risk factor’ if relationships are based on prevalence data.
HGS was reported as an independent risk factor in three out of seven studies included in this review. The clinical relevance of establishing the independence of a risk factor is debated:
Brotman et al. (2005) explained that independence is a statistical paradigm that depends on which variables are included in each model, and it does not inform about causality. They
ACCEPTED MANUSCRIPT
11 pointed out that the same variable may remain an independent factor in one study but not in another; this is due to differences in populations, choice of statistical methods, and selection of co-variables. An independent risk factor may thus be less clinically relevant then another factor that did not reach statistical independence.
Common sense does not suggest that decreased HGS would be a causal risk factor for sustaining a hip fracture; it is much more likely that they both are related to a third variable such as osteosarcopenia that might be causal.
4.3 The link between HGS and hip fracture
In the introduction, we explored the link between HGS and hip fracture incidence through the concept of frailty, including sarcopenia, osteoporosis and osteosarcopenia. Lan et al.
(2010) discussed the possibility of a chain reaction in muscle recruitment to be the link between HGS and fracture incidence: the activation of arm and shoulder muscles through strong grip might trigger stabilizing trunk muscle activity, which further triggers muscle contraction forces directly at the hip. Two other papers support this theory: Firstly, Martelli et al. (2014) concluded in a biomechanical paper that hip extensor contractions improve femoral neck bone strength (not density). Secondly, Sherrington and Henschke (2013) pointed out that in an older, falls prone population, the importance of exercise training lies with the stimulation of central and peripheral neurological factors, which are crucial for falls and fracture prevention; inter-muscular coordination, motor control, and cognition are the key. In a previous paper, Sherrington and Lord (2005) found HGS to be an indicator for hip muscle strength. Weakness due to neuro-degeneration, malnutrition, low physical activity, and falls are important factors of sarcopenia which is a core aspect of frailty (Martin, 2017).
4.4 Limitations
Only English language papers were finally included in this review, which might have led to bias. However, despite not limiting our data base searches to English language, we excluded only one study due to language (Chinese).
A further limitation was that pooling of data was not possible due to varied populations, objectives, methods, analyses, as well as different dynamometer brands and different measurement techniques to establish HGS.
In six of the 11 included studies, individuals with cognitive impairments were excluded; as delirium and dementia are very common in the hip fracture population, this might introduce bias to the sample.
A last limitation was that hip fracture rates were very low in all four cohort studies with an average of only 2.25% of participants having sustained a hip fracture during the study period.
4.5 Clinical implications
HGS is an accessible, cost effective, and simple measure that can be easily conducted in the community, a doctor’s office, aged care facility, or hospital.
In line with Rijk et al. (2016), we suggest using HGS measures more broadly in the
assessment of older individuals. Although HGS measures alone are unlikely to be sufficient to prevent hip fractures, our results suggest that HGS measures may be useful for
identifying individuals that might be at elevated risk of hip fracture. Normative age and gender stratified HGS data as well as cut-off points suggested in the literature (e.g. Dodds et al. (2014): 32kg for men and 19kg for women) can be used as reference values.
4.6 Conclusion
ACCEPTED MANUSCRIPT
12 This systematic review confirmed an association between decreased HGS and low impact hip fracture. We were not able to quantify the strength of this relationship, due to the
heterogeneity of the included studies. Nevertheless, our results suggest that HGS merits further investigation as a useful tool for identifying individuals that might be at elevated risk for sustaining a hip fracture.
REFERENCES:
Auais, M., Morin, S., Nadeau, L., Finch, L., Mayo, N., 2013. Changes in frailty-related characteristics of the hip fracture population and their implications for healthcare services: evidence from Quebec, Canada.
Osteoporos. Int. 24, 2713-2724.
Bassey, E.J., Harries, U.J., 1993. Normal values for handgrip strength in 920 men and women aged over 65 years, and longitudinal changes over 4 years in 620 survivors. Clin. Sci. (Lond) 84, 331-337.
Bean, N., Bennett, K.M., Lehmann, A.B., 1995. Habitus and hip fracture revisited: skeletal size, strength and cognition rather than thinness? Age Ageing 24, 481-484.
Bohannon, R.W., 2008. Hand-grip dynamometry predicts future outcomes in aging adults. J. Geriatr. Phys.
Ther. 31, 3-10.
Brennan, S.L., Pasco, J.A., Urquhart, D.M., Oldenburg, B., Wang, Y., Wluka, A.E., 2011. Association
between socioeconomic status and bone mineral density in adults: a systematic review. Osteoporos. Int.
22, 517-527.
Brotman, D.J., Walker, E., Lauer, M.S., O'Brien, R.G., 2005. In search of fewer independent risk factors. Arch.
Intern. Med. 165, 138-145.
Burt, B.A., 2001. Definitions of risk. J. Dent. Educ. 65, 1007-1008.
Buta, B.J., Walston, J.D., Godino, J.G., Park, M., Kalyani, R.R., Xue, Q.L., Bandeen-Roche, K., Varadhan, R., 2016. Frailty assessment instruments: Systematic characterization of the uses and contexts of highly-cited instruments. Ageing Res. Rev. 26, 53-61.
Cawthon, P.M., Fullman, R.L., Marshall, L., Mackey, D.C., Fink, H.A., Cauley, J.A., Cummings, S.R., Orwoll, E.S., Ensrud, K.E., Osteoporotic Fractures in Men Research, G., 2008. Physical performance and risk of hip fractures in older men. J. Bone Miner. Res. 23, 1037-1044.
Cederholm, T., Cruz-Jentoft, A.J., Maggi, S., 2013. Sarcopenia and fragility fractures. Eur. J. Phys. Rehabil.
Med. 49, 111-117.
Chainani, V., Shaharyar, S., Dave, K., Choksi, V., Ravindranathan, S., Hanno, R., Jamal, O., Abdo, A., Abi Rafeh, N., 2016. Objective measures of the frailty syndrome (hand grip strength and gait speed) and cardiovascular mortality: A systematic review. Int. J. Cardiol. 215, 487-493.
Chen, L.K., Liu, L.K., Woo, J., Assantachai, P., Auyeung, T.W., Bahyah, K.S., Chou, M.Y., Chen, L.Y., Hsu, P.S., Krairit, O., Lee, J.S., Lee, W.J., Lee, Y., Liang, C.K., Limpawattana, P., Lin, C.S., Peng, L.N., Satake, S., Suzuki, T., Won, C.W., Wu, C.H., Wu, S.N., Zhang, T., Zeng, P., Akishita, M., Arai, H., 2014. Sarcopenia in Asia: consensus report of the Asian Working Group for Sarcopenia. J. Am. Med.
Dir. Assoc. 15, 95-101.
Cheng, M.H., Chang, S.F., 2017. Frailty as a Risk Factor for Falls Among Community Dwelling People:
Evidence From a Meta-Analysis. J. Nurs. Scholarsh. 49, 529-536.
Cheung, C.L., Nguyen, U.S., Au, E., Tan, K.C., Kung, A.W., 2013. Association of handgrip strength with chronic diseases and multimorbidity : A cross-sectional study. Age 35, 929-41.
Cheung, C.L., Tan, K.C., Bow, C.H., Soong, C.S., Loong, C.H., Kung, A.W., 2012. Low handgrip strength is a predictor of osteoporotic fractures: cross-sectional and prospective evidence from the Hong Kong Osteoporosis Study. Age 34, 1239-1248.
Clegg, A., Young, J., Iliffe, S., Rikkert, M.O., Rockwood, K., 2013. Frailty in elderly people. Lancet 381, 752- 762.
Coupland, C., Wood, D., Cooper, C., 1993. Physical inactivity is an independent risk factor for hip fracture in the elderly. J. Epidemiol. Community Health 47, 441-443.
Cruz-Jentoft, A.J., Baeyens, J.P., Bauer, J.M., Boirie, Y., Cederholm, T., Landi, F., Martin, F.C., Michel, J.P., Rolland, Y., Schneider, S.M., Topinkova, E., Vandewoude, M., Zamboni, M., European Working Group on Sarcopenia in Older, P., 2010. Sarcopenia: European consensus on definition and
ACCEPTED MANUSCRIPT
13 diagnosis: Report of the European Working Group on Sarcopenia in Older People. Age Ageing 39, 412- 423.
Dargent-Molina, P., Favier, F., Grandjean, H., Baudoin, C., Schott, A.M., Hausherr, E., Meunier, P.J., Breart, G., 1996. Fall-related factors and risk of hip fracture: the EPIDOS prospective study. Lancet 348, 145-149.
de Vries, N.M., Staal, J.B., van Ravensberg, C.D., Hobbelen, J.S., Olde Rikkert, M.G., Nijhuis-van der Sanden, M.W., 2011. Outcome instruments to measure frailty: a systematic review. Ageing Res. Rev.
10, 104-114.
den Ouden, M.E., Schuurmans, M.J., Arts, I.E., van der Schouw, Y.T., 2011. Physical performance characteristics related to disability in older persons: a systematic review. Maturitas 69, 208-219.
Dhanwal, D.K., Dennison, E.M., Harvey, N.C., Cooper, C., 2011. Epidemiology of hip fracture: Worldwide geographic variation. Indian J. Orthop. 45, 15-22.
Dixon, W.G., Lunt, M., Pye, S.R., Reeve, J., Felsenberg, D., Silman, A.J., O'Neill, T.W., European Prospective Osteoporosis Study Group, 2005. Low grip strength is associated with bone mineral density and vertebral fracture in women. Rheumatology (Oxford) 44, 642-646.
Dodds, R.M., Syddall, H.E., Cooper, R., Benzeval, M., Deary, I.J., Dennison, E.M., Der, G., Gale, C.R., Inskip, H.M., Jagger, C., Kirkwood, T.B., Lawlor, D.A., Robinson, S.M., Starr, J.M., Steptoe, A., Tilling, K., Kuh, D., Cooper, C., Sayer, A.A., 2014. Grip strength across the life course: normative data from twelve British studies. PLoS One 9, e113637.
Dodds, R.M., Syddall, H.E., Cooper, R., Kuh, D., Cooper, C., Sayer, A.A., 2016. Global variation in grip strength: a systematic review and meta-analysis of normative data. Age Ageing 45, 209-216.
Elliot, J.R., Hanger, H.C., Gilchrist, N.L., Frampton, C., Turner, J.G., Sainsbury, R., Gillespie, W.J., 1992. A comparison of elderly patients with proximal femoral fractures and a normal elderly population: a case control study. N. Z. Med. J. 105, 420-422.
Ensrud, K.E., Ewing, S.K., Taylor, B.C., Fink, H.A., Stone, K.L., Cauley, J.A., Tracy, J.K., Hochberg, M.C., Rodondi, N., Cawthon, P.M., Study of Osteoporotic Fractures Research, G., 2007. Frailty and risk of falls, fracture, and mortality in older women: the study of osteoporotic fractures. J. Gerontol. A. Biol.
Sci. Med. Sci. 62, 744-751.
Fried, L.P., Tangen, C.M., Walston, J., Newman, A.B., Hirsch, C., Gottdiener, J., Seeman, T., Tracy, R., Kop, W.J., Burke, G., McBurnie, M.A., Cardiovascular Health Study Collaborative Research Group, 2001. Frailty in older adults: evidence for a phenotype. J. Gerontol. A. Biol. Sci. Med. Sci. 56, M146-156.
Godin, J., Armstrong, J.J., Rockwood, K., Andrew, M.K., 2017. Dynamics of Frailty and Cognition After Age 50: Why It Matters that Cognitive Decline is Mostly Seen in Old Age. J. Alzheimers Dis. 58, 231-242.
Griffin, X.L., Parsons, N., Achten, J., Fernandez, M., Costa, M.L., 2015. Recovery of health-related quality of life in a United Kingdom hip fracture population. The Warwick Hip Trauma Evaluation - a prospective cohort study. Bone Joint J. 97-B, 372-382.
Hernlund, E., Svedbom, A., Ivergard, M., Compston, J., Cooper, C., Stenmark, J., McCloskey, E.V., Jonsson, B., Kanis, J.A., 2013. Osteoporosis in the European Union: medical management, epidemiology and economic burden. A report prepared in collaboration with the International
Osteoporosis Foundation (IOF) and the European Federation of Pharmaceutical Industry Associations (EFPIA). Arch. Osteoporos. 8, 136.
Hirschfeld, H.P., Kinsella, R., Duque, G., 2017. Osteosarcopenia: where bone, muscle, and fat collide.
Osteoporos. Int. 28, 2781-2790.
Ho, A.W., Lee, M.M., Chan, E.W., Ng, H.M., Lee, C.W., Ng, W.S., Wong, S.H., 2016. Prevalence of pre- sarcopenia and sarcopenia in Hong Kong Chinese geriatric patients with hip fracture and its correlation with different factors. Hong Kong Med. J. 22, 23-29.
Hubbard, R.E., Peel, N.M., Samanta, M., Gray, L.C., Mitnitski, A., Rockwood, K., 2017. Frailty status at admission to hospital predicts multiple adverse outcomes. Age Ageing, 1-6.
Huo, Y.R., Suriyaarachchi, P., Gomez, F., Curcio, C.L., Boersma, D., Muir, S.W., Montero-Odasso, M., Gunawardene, P., Demontiero, O., Duque, G., 2015. Phenotype of osteosarcopenia in older individuals with a history of falling. J. Am. Med. Dir. Assoc. 16, 290-295.
Jarvinen, T.L., Michaelsson, K., Jokihaara, J., Collins, G.S., Perry, T.L., Mintzes, B., Musini, V., Erviti, J., Gorricho, J., Wright, J.M., Sievanen, H., 2015. Overdiagnosis of bone fragility in the quest to prevent hip fracture. BMJ 350, h2088.
ACCEPTED MANUSCRIPT
14 Jarvinen, T.L., Sievanen, H., Khan, K.M., Heinonen, A., Kannus, P., 2008. Shifting the focus in fracture
prevention from osteoporosis to falls. BMJ 336, 124-126.
Joanna Briggs Institute, 2016. Critical appraisal tools. http://joannabriggs.org/research/critical-appraisal- tools.html (accessed 20 October 2017).
Kanis, J.A., 1994. Assessment of fracture risk and its application to screening for postmenopausal osteoporosis:
synopsis of a WHO report. WHO Study Group. Osteoporos. Int. 4, 368-381.
Kanis, J.A., Oden, A., McCloskey, E.V., Johansson, H., Wahl, D.A., Cooper, C., 2012. A systematic review of hip fracture incidence and probability of fracture worldwide. Osteoporos. Int. 23, 2239-2256.
Karkkainen, M., Rikkonen, T., Kroger, H., Sirola, J., Tuppurainen, M., Salovaara, K., Arokoski, J., Jurvelin, J., Honkanen, R., Alhava, E., 2008. Association between functional capacity tests and fractures: an eight-year prospective population-based cohort study. Osteoporos. Int. 19, 1203-1210.
Kauppi, M., Stenholm, S., Impivaara, O., Maki, J., Heliovaara, M., Jula, A., 2014. Fall-related risk factors and heel quantitative ultrasound in the assessment of hip fracture risk: a 10-year follow-up of a nationally representative adult population sample. Osteoporos. Int. 25, 1685-1695.
Keevil, V., Mazzuin Razali, R., Chin, A.V., Jameson, K., Aihie Sayer, A., Roberts, H., 2013. Grip strength in a cohort of older medical inpatients in Malaysia: a pilot study to describe the range, determinants and association with length of hospital stay. Arch. Gerontol. Geriatr. 56, 155-159.
Khandelwal, D., Goel, A., Kumar, U., Gulati, V., Narang, R., Dey, A.B., 2012. Frailty is associated with longer hospital stay and increased mortality in hospitalized older patients. J. Nutr. Health Aging 16, 732-735.
Kistler, E.A., Nicholas, J.A., Kates, S.L., Friedman, S.M., 2015. Frailty and Short-Term Outcomes in Patients With Hip Fracture. Geriatr. Orthop. Surg. Rehabil. 6, 209-214.
Kojima, G., 2015. Frailty as a Predictor of Future Falls Among Community-Dwelling Older People: A Systematic Review and Meta-Analysis. J. Am. Med. Dir. Assoc. 16, 1027-1033.
Kojima, G., 2018. Frailty as a Predictor of Nursing Home Placement Among Community-Dwelling Older Adults:
A Systematic Review and Meta-analysis. J. Geriatr. Phys. Ther. 41, 42-48.
Kritz-Silverstein, D., Barrett-Connor, E., 1994. Grip strength and bone mineral density in older women. J. Bone Miner. Res. 9, 45-51.
Kua, J., Ramason, R., Rajamoney, G., Chong, M.S., 2016. Which frailty measure is a good predictor of early post-operative complications in elderly hip fracture patients? Arch. Orthop. Trauma Surg. 136, 639-647.
Lan, T.Y., Hou, S.M., Chen, C.Y., Chang, W.C., Lin, J., Lin, C.C., Liu, W.J., Shih, T.F., Tai, T.Y., 2010. Risk factors for hip fracture in older adults: a case-control study in Taiwan. Osteoporos. Int. 21, 773-784.
Lau, E.M., Woo, J., Leung, P.C., Swaminthan, R., 1993. Low bone mineral density, grip strength and skinfold thickness are important risk factors for hip fracture in Hong Kong Chinese. Osteoporos. Int. 3, 66-70.
Leal, J., Gray, A.M., Prieto-Alhambra, D., Arden, N.K., Cooper, C., Javaid, M.K., Judge, A., 2016. Impact of hip fracture on hospital care costs: a population-based study. Osteoporos. Int. 27, 549-558.
Liberati, A., Altman, D.G., Tetzlaff, J., Mulrow, C., Gotzsche, P.C., Ioannidis, J.P., Clarke, M., Devereaux, P.J., Kleijnen, J., Moher, D., 2009. The PRISMA statement for reporting systematic reviews and meta- analyses of studies that evaluate healthcare interventions: explanation and elaboration. BMJ 339, b2700.
Lievense, A.M., Bierma-Zeinstra, S.M., Verhagen, A.P., Verhaar, J.A., Koes, B.W., 2002. Prognostic factors of progress of hip osteoarthritis: a systematic review. Arthritis Rheum. 47, 556-562.
Lloyd, B.D., Williamson, D.A., Singh, N.A., Hansen, R.D., Diamond, T.H., Finnegan, T.P., Allen, B.J., Grady, J.N., Stavrinos, T.M., Smith, E.U., Diwan, A.D., Fiatarone Singh, M.A., 2009. Recurrent and injurious falls in the year following hip fracture: a prospective study of incidence and risk factors from the
Sarcopenia and Hip Fracture study. J. Gerontol. A. Biol. Sci. Med. Sc.i 64, 599-609.
Marks, R., 2010. Hip fracture epidemiological trends, outcomes, and risk factors, 1970-2009. Int. J. Gen. Med. 3, 1-17.
Martelli, S., Kersh, M.E., Schache, A.G., Pandy, M.G., 2014. Strain energy in the femoral neck during exercise.
J. Biomech. 47, 1784-1791.
Martin, F.C., 2017. Frailty, Sarcopenia, Falls and Fractures, in: Falaschi, P., Marsh, D.R. (Eds.), Orthogeriatrics.
Springer International Publishing, Switzerland, pp. 47-61.
Meyer, H.E., Henriksen, C., Falch, J.A., Pedersen, J.I., Tverdal, A., 1995. Risk factors for hip fracture in a high incidence area: a case-control study from Oslo, Norway. Osteoporos. Int. 5, 239-246.
Moher, D., Liberati, A., Tetzlaff, J., Altman, D.G., 2009. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ 339, b2535.
ACCEPTED MANUSCRIPT
15 Norman, K., Stobaus, N., Gonzalez, M.C., Schulzke, J.D., Pirlich, M., 2011. Hand grip strength: outcome
predictor and marker of nutritional status. Clin. Nutr. 30, 135-142.
Oliveira, A., Vaz, C., 2015. The role of sarcopenia in the risk of osteoporotic hip fracture. Clin. Rheumatol. 34, 1673-1680.
Parker, M.J., 2016. Reducing morbidity and mortality in the hip fracture patient group. Orthop. Trauma 30, 153- 158.
Pearson, A., Field, J., Jordan, Z., 2009. Evidence-Based Clinical Practice in Nursing and Health Care : Assimilating Research, Experience and Expertise. John Wiley & Sons, Incorporated.
Rantanen, T., Volpato, S., Ferrucci, L., Heikkinen, E., Fried, L.P., Guralnik, J.M., 2003. Handgrip strength and cause-specific and total mortality in older disabled women: exploring the mechanism. J. Am.
Geriatr. Soc. 51, 636-641.
Rijk, J.M., Roos, P.R., Deckx, L., van den Akker, M., Buntinx, F., 2016. Prognostic value of handgrip strength in people aged 60 years and older: A systematic review and meta-analysis. Geriatr. Gerontol. Int. 16, 5- 20.
Robbins, J.A., Schott, A.M., Garnero, P., Delmas, P.D., Hans, D., Meunier, P.J., 2005. Risk factors for hip fracture in women with high BMD: EPIDOS study. Osteoporos. Int. 16, 149-154.
Roberts, H.C., Syddall, H.E., Cooper, C., Aihie Sayer, A., 2012. Is grip strength associated with length of stay in hospitalised older patients admitted for rehabilitation? Findings from the Southampton grip strength study. Age Ageing 41, 641-646.
Rockwood, K., 2005. A global clinical measure of fitness and frailty in elderly people. CMAJ 173, 489-495.
Rodriguez-Manas, L., Feart, C., Mann, G., Vina, J., Chatterji, S., Chodzko-Zajko, W., Gonzalez-Colaco Harmand, M., Bergman, H., Carcaillon, L., Nicholson, C., Scuteri, A., Sinclair, A., Pelaez, M., Van der Cammen, T., Beland, F., Bickenbach, J., Delamarche, P., Ferrucci, L., Fried, L.P., Gutierrez- Robledo, L.M., Rockwood, K., Rodriguez Artalejo, F., Serviddio, G., Vega, E., 2013. Searching for an operational definition of frailty: a Delphi method based consensus statement: the frailty operative definition-consensus conference project. J. Gerontol. A. Biol. Sci. Med. Sci. 68, 62-67.
Rubin, K.H., Abrahamsen, B., Friis-Holmberg, T., Hjelmborg, J.V., Bech, M., Hermann, A.P., Barkmann, R., Gluer, C.C., Brixen, K., 2013. Comparison of different screening tools (FRAX(R), OST, ORAI, OSIRIS, SCORE and age alone) to identify women with increased risk of fracture. A population-based
prospective study. Bone 56, 16-22.
Sambrook, P.N., Flahive, J., Hooven, F.H., Boonen, S., Chapurlat, R., Lindsay, R., Nguyen, T.V., Diez- Perez, A., Pfeilschifter, J., Greenspan, S.L., Hosmer, D., Netelenbos, J.C., Adachi, J.D., Watts, N.B., Cooper, C., Roux, C., Rossini, M., Siris, E.S., Silverman, S., Saag, K.G., Compston, J.E., LaCroix, A., Gehlbach, S., 2011. Predicting fractures in an international cohort using risk factor algorithms without BMD. J. Bone Miner. Res. 26, 2770-2777.
Sandhu, S.K., Nguyen, N.D., Center, J.R., Pocock, N.A., Eisman, J.A., Nguyen, T.V., 2010. Prognosis of fracture: evaluation of predictive accuracy of the FRAX algorithm and Garvan nomogram. Osteoporos.
Int. 21, 863-871.
Sherrington, C., Henschke, N., 2013. Why does exercise reduce falls in older people? Unrecognised contributions to motor control and cognition? Br. J. Sports Med. 47, 730-731.
Sherrington, C., Lord, S.R., 2005. Reliability of simple portable tests of physical performance in older people after hip fracture. Clin. Rehabil. 19, 496-504.
Silverman, S.L., Calderon, A.D., 2010. The utility and limitations of FRAX: A US perspective. Curr. Osteoporos Rep. 8, 192-197.
Stone, K.L., Seeley, D.G., Lui, L.Y., Cauley, J.A., Ensrud, K., Browner, W.S., Nevitt, M.C., Cummings, S.R., Osteoporotic Fractures Research, G., 2003. BMD at multiple sites and risk of fracture of multiple types: long-term results from the Study of Osteoporotic Fractures. J. Bone Miner. Res. 18, 1947-1954.
Syddall, H., Cooper, C., Martin, F., Briggs, R., Aihie Sayer, A., 2003. Is grip strength a useful single marker of frailty? Age Ageing 32, 650-656.
Tarantino, U., Piccirilli, E., Fantini, M., Baldi, J., Gasbarra, E., Bei, R., 2015. Sarcopenia and fragility fractures: molecular and clinical evidence of the bone-muscle interaction. J. Bone Joint Surg. Am. 97, 429-437.
The University of Sheffield, 2011. FRAX Fracture Risk Assessment Tool. https://www.sheffield.ac.uk/FRAX/
(accessed 17 August 2017).
ACCEPTED MANUSCRIPT
16 The World Bank, 2015. Rapid Aging in East Asia and Pacific Will Shrink Workforce and Increase Public
Spending. http://www.worldbank.org/en/region/eap/brief/rapid-aging-in-east-asia-and-pacific-will-shrink- workforce-increase-public-spending (accessed 15 July 2017).
Vermeulen, J., Neyens, J.C., van Rossum, E., Spreeuwenberg, M.D., de Witte, L.P., 2011. Predicting ADL disability in community-dwelling elderly people using physical frailty indicators: a systematic review.
BMC geriatr. 11, 33.
Watts, J.J., Abimanyi-Ochom, J., Sanders, K.M. Osteoporosis Costing All Australians, 2012 - 2022: A new burden of disease analysis. Glebe, NSW: Osteoporosis Australia; 2013.
Yoo, J.I., Kim, H., Ha, Y.C., Kwon, H.B., Koo, K.H., 2018. Osteosarcopenia in Patients with Hip Fracture Is Related with High Mortality. J. Korean Med. Sci. 33, e27.
ACCEPTED MANUSCRIPT
17
Author (year)
/ location Study design/ numbers Mean age in years (SD) Gender
female% Relevant results – HGS HGS values in kg Normative HGS values
in kg for age and gender
(Dodds et al., 2014)
(Bean et al., 1995)
UK Case control
Age matched +/- 3 years, 1:1 Total: n=100
Cases: n=50 Controls: n=50
Cases 79.5 ( 8.4)
Controls 79.6 (7.7) 100 T-test:
HGS weaker in cases p<0.001 Stepwise multiple regression:
Multiple R=0.59 R2=0.35 p<0.0001
Females with # =11.63 (mean)
Females without #
=18.63 (mean)
Females: 19.1 (80)
(Cawthon et al., 2008)
USA Retrospective cohort
Total: n=5902 Hip fractures: n=77 Mean follow-up: 5.3 years
≥65
(71.9 to 77.2) 0 Cox regression:
HR (95% CI) of hip fracture (multiple adjusted):
worst quartile: HR 1.63(0.65- 4.14) unable: HR 4.50 (1.32-15.35) p for trend=0.184
Worst quartile:
Males
<36
Males: 39.1 (70)
(Coupland et al., 1993)
UK Case control
Age and sex matched, 1:2 Total: n=579
Cases: n=197 Controls: n=382
>50
(65% >75) 85.3 Multiple regression:
OR (95% CI) of hip fracture (multiple adjusted):
worst tertile:
OR male: 49.5(1.5-1618) p for trend <0.0001 OR female: 5.3(2.4-11.7) p for trend <0.0001
Worst tertile:
Males
<28.0 Females
<14.3
Males: 35.6 (75) Females: 21.4 (75)
(Elliot et al., 1992)
NZ Case control
Age and sex matched, 1:2 Total: n=108
Cases: n=36 Controls: n=72
Cases 79.1(1.0)
Controls 78.4(0.7) 78 T-test:
HGS weaker in cases p<0.001 Logistic regression:
p=0.003 (coefficient=0.14)
Females and males combined with #
=11.4 (mean) Females and males combined without # =19.2 (mean)
Males: 32.2 (80) Females: 19.1 (80)
(Karkkainen et al., 2008)
FI
Retrospective cohort Total: n=2928 Hip fractures: n=8 Mean follow-up: 8.3 years
59.1(2.9) 100 Cox regression:
HR (95% CI) of hip fracture (multiple adjusted):
HR: 1.046 (1.005-1.088);
p for trend=0.026
No values available
(Kauppi et al., 2014)
FI Retrospective cohort
Total: n=2300; hip Fractures:
n=96
Mean follow-up: 9.8 years
Cases 74.29(7.92)
Controls 66.08(8.11) 58.87 T-test:
HGS weaker in cases p<0.0001
HR (95% CI) of hip fracture (multiple adjusted):
HR 0.70 (0.45-1.08) p for trend=not provided
Females and males combined with # =25.0 (mean)
Females and males combined without # =32.4 (mean)
Males: 35.6 (75) Females: 21.4 (75)
(Lan et al., 2010)
TW Case control
Age and sex matched 1:1 or 1:2 Total: n=725
Cases: n=228
80.1(7.9) Cases: 71.5
Controls:
69.4
Logistic regression:
OR (95% CI) of hip fracture (adjusted):
best tertile:
OR males (group adjusted):
Worst tertile:
Males
≤15 Females
Males: 32.2 (80) Females: 19.1 (80)
ACCEPTED MANUSCRIPT
18
Controls: n=497 0.10(0.03-0.35)
p for trend<0.001
OR females (multiple adjusted): 0.29(0.10-0.55) p for trend<0.001
worst tertile:
OR males: 1.00, referent OR females: 1.00, referent
≤15
(Lau et al., 1993)
HK Case control
No matching Total: n=480 Cases: n=163 Controls: n=317
Cases males 76(8) Controls males 74(6) Cases females 79(8) Controls females 76(9)
80.4 T-test:
HGS weaker in cases p<0.01 Multiple regression:
RR (95% CI) of hip fracture (age adjusted):
worst quartile:
RR male: 4.9(1.3-17.6) P for trend <0.01 RR female: 2.0(1.1-3.9) P for trend<0.01
Males with #
=14.1 (mean) Males without #
=23.0 (mean) Females with #
=7.8 (mean) Females without #
=10.8 (mean)
Males: 35.6 (75) Females: 19.1 (80)
(Meyer et al., 1995)
NO Case control
Age matched +/- 4 years Total: n=492
Cases: n=246 Controls: n=246
Cases males 74(0) Controls males 74(9) Cases females 79(9) Controls females 79(8)
Not specified Logistic regression:
OR (95% CI) of hip fracture (multiple adjusted):
worst quartile:
OR: 3.27(1.54-6.97) p for trend=0.0005
Worst quartile:
Males
≤26.5 Females
≤14.0
Males: 35.6 (75) Females: 19.1 (80)
EPIDOS study (Dargent-Molina et al., 1996)
FR
Retrospective cohort Total: n=7575 Hip fractures: n=154 Mean follow-up: 1.9 years
Cases 82.6(4.7)
Rest of cohort 80.5(3.8) 100 Cox regression:
RR (95% CI) of hip fracture:
best quartile:
RR: 2.6 (1.9-3.4) p for trend=not provided worst quartile:
RR: 1.00, referent
Values in kPa Worst quartile:
<44
No reference values
(Robbins et al., 2005)
FR Retrospective cohort
Total: n=7598 Hip fractures: n=293
>3-yaers follow-up
Cases 82.4(4.5)
Rest of cohort 80.4(3.7) 100 T-test:
HGS weaker in cases p<0.001 Cox regression:
HR (95% CI) of hip fracture (age adjusted):
right: HR: 0.82(0.73-0.93); p=0.001 left: HR: 0.77(0.68-0.87); p<0.001
Values in kPa Females with #
=49 (mean) Females without #
=53 (mean)
No reference values
HGS= handgrip strength; HR=hazard ratio; OR=odds ratio; RR=relative risk; #=fracture
ACCEPTED MANUSCRIPT
19 Figure 1: Flowchart of inclusion
ACCEPTED MANUSCRIPT
20
1 Hand Strength/
2 "grip strength".mp.
3 (hand* adj3 (strength* or grip* or grasp*)).mp.
4 Muscle Strength Dynamometer/ or dynamom*.mp 5 1 or 2 or 3 or 4
6 hip fractures/ or femoral neck fractures/ or proximal femur fracture 7 Femoral Fractures/ and (Femur Head/ or Femur Neck/)
8 (("femoral neck" or "femoral head" or "femur neck" or "femur head" or trochant* or intertrochant* or "inter-trochant*" or subtrochant* or "sub- trochant*" or intratrochant* or "intra-trochant*" or peritrochant* or "peri-trochant*") and fracture*).mp.
9 6 or 7 or 8 10 5 and 9
ACCEPTED MANUSCRIPT
21
Appendix 2. Grading the evidence (Brennan et al. 2011 and Lievense et al. 2002)
Level of evidence Criteria
Strong evidence Generally consistent findings in:
multiple high-quality cohort studies
Moderate evidence Generally consistent findings in:
one high-quality cohort study and two or more high quality case–control studies
three or more high-quality case–control studies
Limited evidence Generally consistent findings in:
a single cohort study, one or two case–control studies multiple cross-sectional studies
Conflicting evidence <75% of studies reported consistent findings
No evidence No studies could be found
ACCEPTED MANUSCRIPT
22
Author (year) Score Factor(s) that reduced quality
Bean et al. (1995) 77.7% Confounding factors not addressed
Cawthon et al. (2008) 100%
Coupland et al. (1993) 100%
Elliot et al. (1992) 90% Insufficient follow up time
Karkkainen et al. (2008) 100%
Kauppi (2014) 100%
Lan et al. (2010) 100%
Lau et al. (2003) 30% Poor reporting through out
Meyer et al. (1995) 100%
EPIDOS study
Dargent-Molina (1996) 90.91% Measurement of outcome (HGS) not specified
Robbins et al. (2005) 90.91% Measurement of outcome (HGS) not specified
ACCEPTED MANUSCRIPT
23 Highlights
Hand grip strength is decreased in individuals with hip fracture near the time of injury
Decreased hand grip strength is associated with increased risk of sustaining a hip fracture
Hand grip strength might be a useful tool for identifying individuals at risk of sustaining a hip fracture
