Abstract
Muscle strength and physical performance are associated with fracture risk in men. However, it is not known whether these measurements enhance fracture risk prediction beyond Garvan and FRAX tools. A total of 5665 community-dwelling men, aged 65+, from the Osteoporotic Fractures in Men (MrOS) Study, who had data on muscle strength (grip strength) and physical performance (gait speed and chair stand tests), were followed from 2000 to 2019 for any fracture, major osteoporotic fracture (MOF), initial hip and any hip fracture. The contributions to different fracture outcomes were assessed using Cox’s proportional hazard models. Tool-specific analysis approaches and outcome definitions were used. The added predictive values of muscle strength and physical performance beyond Garvan and FRAX were assessed using categorical net reclassification improvement (NRI) and relative importance analyses. During a median follow-up of 13 (IQR: 7-17) years, there were 1014 fractures, 536 MOFs, 215 initial hip and 274 any hip fractures. Grip strength and chair stand improved prediction of any fracture (NRI for grip strength: 3.9% and for chair stand: 3.2%) and MOF (5.2% and 6.1%). Gait speed improved prediction of initial hip (5.7%) and any hip (7.0%) fracture. Combining grip strength and the relevant performance test further improved the models (5.7%, 8.9%, 9.4% and 7.0% for any, MOF, initial, and any hip fractures, respectively). The improvements were predominantly driven by reclassification of those with fracture to higher risk categories. Apart from age and FNBMD, muscle strength and performance were ranked equal to or better than the other risk factors included in fracture models including prior fractures, falls, smoking, alcohol, and glucocorticoid use. Muscle strength and performance measurements improved fracture risk prediction in men beyond Garvan and FRAX. They were as or more important than other established risk factors. These measures should be considered for inclusion in fracture risk assessment tools.
Keywords: FRACTURE RISK ASSESSMENT, AGING, SARCOPENIA, GENERAL POPULATION STUDIES
INTRODUCTION:
Osteoporotic fractures represent a major public health problem.(1-3) Identifying those at higher risk of fracture becomes increasingly important as the population ages. Approximately 79% of fractures in men occur without BMD-defined osteoporosis.(4) Fracture risk assessment tools incorporate clinical risk factors to improve identification of people at high risk of fracture. The Garvan fracture risk calculator (Garvan)(5,6) and the Fracture Risk Assessment Tool (FRAX)(7) are among the most commonly used tools to estimate absolute fracture risk. These tools have been validated internationally.(8)
Garvan and FRAX have equivalent discriminative abilities(9) despite their methodological differences. Nevertheless, despite demonstrating improved predictive power over BMD alone, fracture prediction using these tools remains suboptimal.(10,11) Efforts to improve recognition of people at high fracture risk are therefore an active research area.(12)
Fall-related risk factors, including muscle strength and physical performance, have been found to be predictive of fracture risk in men.(13-18) Previous studies reported that muscle strength, as assessed by quadriceps or grip strength,(15,16) and physical performance, as assessed by gait speed(13,14,16,17) or five times repeated chair stands test,(14,16,18) contribute to fracture risk in men although the data are inconsistent in women.(17,19)
Two studies reported independent associations between muscle strength and physical performance and fracture risk in men after accounting for either Garvan or FRAX.(16,20) However, it has not been established whether inclusion of muscle strength and physical performance in men has incremental predictive value beyond that obtained by fracture risk tools. Using the well-established MrOS cohort of community-dwelling men, we therefore aimed to (i) assess the role of muscle strength and physical performance in fracture risk prediction over and above Garvan and FRAX risk factors and (ii) determine whether the inclusion of muscle strength or physical performance measures improves the predictive accuracy of Garvan and FRAX.
METHODS:
Study participants
The Osteoporotic Fractures in Men (MrOS) Study(21) is a prospective cohort study of 5994 community-dwelling men aged 65 years or older living in six communities in the United States (Birmingham, Alabama; Minneapolis, Minnesota; Monongahela Valley near Pittsburgh, Pennsylvania; Palo Alto, California; Portland, Oregon and San Diego, California). Study design and recruitment strategies have been previously described.(22,23) Participants were enrolled between March 2000 and April 2002. To be eligible for the study, participants had to be able to walk without aid, must not have had a bilateral hip replacement, and must have provided written informed consent.
The current study cohort included 5,665 men with a complete data on muscle strength and performance and risk factors included in the Garvan and FRAX algorithms and a follow-up of at least one year (Figure 1). Men with missing baseline muscle strength and physical performance measurements due to refusal or inability to perform the tests (n=318), missing any of Garvan or FRAX risk predictors (n=3), and those with follow-up < one year (n=8) were excluded from analysis. However, those who were unable to perform the chair stands were included in the sensitivity analysis in which measurements of chair stands were recorded as the number of stands per ten seconds for those who were able and 0 for those who were unable to do the test.
Figure 1: Flow chart of participants included in the analysis.
a The individual numbers do not add to the total as some participants had multiple exclusion criteria.
b Participants with fracture types other than hip (N=799) were excluded from this fracture outcome analysis.
c MOF: any major osteoporotic fracture (i.e., hip, clinical vertebral, wrist and proximal humerus).
The Institutional Review Boards at each site and the San Francisco Coordinating Center (University of California, San Francisco, and California Pacific Medical Center Research Institute) approved the study.
Assessment of risk factors and muscle strength and physical performance
Participants completed clinical examinations and a self-administered questionnaire(22) during the baseline visit to collect information about age (years), smoking status (current, no), alcohol use (<3, ≥3 standard drinks/day), history of falls in the previous 12 months (0, 1, 2-3, ≥ 4 falls), history of low trauma fractures from adulthood (yes/no) and after the age of 50 years (0, 1, 2, ≥ 3 fractures), parental history of hip fracture (yes/no), medical history of rheumatoid arthritis (yes/no), and glucocorticoid use (yes/no). Measurements of bone mineral density (BMD) were taken at the femoral neck(22) using dual-energy x-ray absorptiometry (DXA) machines (Hologic, Inc., Bedford, MA).
Grip strength was assessed using JAMAR dynamometers (Sammons Preston Rolyan, Bolingbrook, IL, USA). Two trials were performed on each hand, and the maximum measurement (Kg) was used. Gait speed (m/sec) was assessed by a six-metre walk test at usual pace. Chair stands were assessed by measuring the time in seconds required to do five repeated extended stands from a full sitting position on an armless chair, with arms crossed over the chest. The coefficients of variation for grip strength, gait speed, and chair stands were reported as 0.5%, 2.4%, and 4.9%, respectively.(24)
Main outcome measurements
Fractures were reported through a questionnaire every four months.(22) A follow-up telephone interview was conducted to collect information about the circumstances of reported fractures. All reported fractures were adjudicated by centralized physician review of the radiology reports. Only minimal to moderate trauma fractures were included. Severe and extreme trauma fractures (e.g., motor vehicle accidents), fractures of the skull, fingers, toes, and fractures near prostheses were excluded. Deaths were verified through state death certificates.
We assessed four different fracture outcomes to correspond to those used in the Garvan and FRAX algorithms. The Garvan “any fracture” outcome included all fracture sites excluding skull, finger, and toe. The FRAX "major osteoporotic fracture” (MOF) outcome included hip, proximal humerus, wrist and clinical vertebral fractures. The Garvan “initial hip fracture” outcome included hip fractures that were not preceded by any other fracture site.(5,6) The FRAX “any hip fracture” outcome included hip fractures, regardless of whether they were preceded by other fractures.(7)
Statistical analysis
The study included 5,665 men. Men who were followed for less than a year, had missing data on muscle strength and physical performance or risk factors were excluded. To account for differences in the Garvan and FRAX algorithms,(5-7) four separate datasets were constructed to correspond for the four fracture outcomes. Follow-up times were calculated from the baseline date until the date of fracture, death, or end of follow-up (6 August 2019), whichever came first. Fracture incidence rates were calculated as numbers of incident fractures per 1,000 person-years.
The role of muscle strength and physical performance in fracture risk
a. Assessing the independent contribution of muscle strength and physical performance to fracture risk
To quantify the independent contributions of muscle strength and physical performance to fracture risk, four sets of Cox proportional hazards regression models were constructed. The first model quantified the risk of any fracture making adjustment for Garvan predictors(5,6) and included all participants. The second model examined the risk of MOF adjusting for FRAX predictors(7) and competing risk of mortality.(25) in this model, participants who sustained a non-MOF were classified as fracture free participants. The third model assessed the risk of initial hip fracture making adjustment for Garvan predictors.(5,6) in this model, those who sustained a non- hip fracture were excluded. The fourth model examined the risk of any hip fracture, adjusting for FRAX predictors(7) and competing risk of mortality.(25) in this model, participants who sustained a non-hip fracture were classified as fracture free participants.
Cox models assessed fracture risk over the whole follow up time and therefore all fractures that occurred during the follow-up time were included. Muscle strength and physical performance measurements were analysed as continuous variables with the hazard ratios (HRs) reported per one SD change in predictor with their 95% confidence intervals (CIs). As chair stand time was not normally distributed, logarithm-transformed values were used. The assumption of proportional hazards was assessed graphically and statistically using Schoenfeld’s residuals for all models. There was no evidence of assumption violation.
b. Assessing the relative importance of muscle strength and physical performance in all fracture prediction models
We compared the contributions of grip strength, gait speed and chair stands to those of other risk factors using the relative importance analysis.(26) The analysis ranks the importance of each predictor on the model’s prediction power using their individual contribution to the overall R2 metric of the model. This analysis provides more accurate information compared to multiple regression about the contribution each predictor on the model’s prediction performance as it accounts for collinearity. All predictors in Garvan or FRAX as well as all muscle strength and physical performance tests were included in one single model to assess each fracture outcome separately. To facilitate interpretation, each predictor’s coefficient of determination (i.e., the individual R2) was scaled to the model’s most important predictor.
Incremental predictive accuracy of muscle strength and physical performance addition to Garvan and FRAX fracture models
The incremental predictive utility of muscle strength and physical performance tests beyond the Garvan or FRAX models was quantified using net reclassification improvement (NRI).(27,28) NRI quantifies the correct reclassification of subjects (with and without fractures) into more appropriate risk categories after the addition of muscle strength and performance to the fracture prediction model. In these models, fracture risk was only assessed over 10 years of follow up.
We defined three risk strata for ten-year prediction of any fracture and MOF as <10% as low risk, 10%-20% as medium risk, and >20% as high risk.(11) For initial hip fracture and any hip fracture, we defined the risk categories as <1% as low risk, 1%-3% as medium risk, and >3% as high risk. Two models were constructed for each tool and fracture outcome. The original model which is Garvan or FRAX and the modified model following addition of muscle strength and/or performance measurement to the original model. The individual ten-year predicted risk of fracture was calculated from each. Some subjects were reclassified between the original and modified models. Correct reclassification was assigning a higher risk category for those who suffered a fracture and a lower risk category for those who remained fracture-free. NRI was calculated as the number correctly reclassified by the modified model minus the number incorrectly reclassified by the modified model, scaled to the fracture incidence.(28) Thus, positive NRI values indicate improved prediction by the modified model or vice versa.
Sensitivity analysis
Two sensitivity analyses were considered. The first sensitivity analysis was conducted to assess the five-year incremental value of the addition of muscle strength and physical performance to Garvan model. this analysis was conducted to address whether mortality modelled over longer follow-up underestimated the ten-year NRIs. Another sensitivity analysis included participants previously excluded because they were unable to perform chair stands correctly. In this analysis, chair stand measurements were recorded as the number of stands per ten seconds for those who were able to do the test and 0 for those who were unable.
Analyses were conducted using SAS version 9.4 (SAS Institute Inc, Cary, NC) and R software version 3.6.3 (http://www.R-project.org/). Two-sided p-values < 0.05 were considered significant.
RESULTS:
Baseline characteristics of participants
The analysis included 5,665 men with mean age 73.5 (SD= 5.78) years and complete data on muscle strength, physical performance tests and covariates (Figure 1). The median duration of follow-up was 12.7 years (IQR, 7.3 - 17.3). During the follow-up period, 1,014 men (18%) sustained at least one incident low-trauma fracture, yielding an incidence rate of 15.1 fractures/1,000 person-years (95% CI: 14.2 - 16.1). The rates of MOF, initial hip, and any hip fracture were 7.6/1,000 (7.0-8.3), 3.5/1,000 (3.1 - 4.0), and 3.8/1,000 (3.4 - 4.3), respectively.
Overall, men had a median grip strength (IQR) of 42.0 (36-48) kg, gait speed of 1.26 (1.12-1.41) m/s and chair stand time of 10.53 (8.94-12.56) s. Men who sustained a fracture had lower grip strength and longer chair stand time than men who did not. Gait speed was lower in those who sustained MOFs or hip fractures, but not in those who sustained any fracture (Table 1, Supplemental table S1).(29) Men who sustained a fracture were significantly older, had lower FN BMD and were more likely to experience falls and prior fractures than those who remained fracture free. However, there was no difference in previous glucocorticoid use, rheumatoid arthritis, parent history of hip fracture, and smoking and alcohol consumption (Table 1, Supplemental table S1).(29)
Table 1:
Baseline characteristic of men included in any fracture and MOF outcome analyses stratified by fracture outcome
| Baseline characteristics |
No fracture N= 4651(82%) |
Any fracture N= 1014 (18%) |
No MOF N=5129 (90.5) |
MOF N= 536 (9.5%) |
|---|---|---|---|---|
| Age (year) a | 73.34 (5.81) | 74.24 (5.72) | 73.34 (5.79) | 75.12 (5.71) |
| BMI (kg/m2) b | 26.94 (24.86-29.51) | 26.55 (24.40-29.24) | 26.95 (24.85-29.51) | 26.24 (24.03-28.95) |
| FN BMD (g/cm2) a | 0.80 (0.13) | 0.74 (0.12) | 0.79 (0.13) | 0.72 (0.12) |
| FN BMD T-score a | −0.52 (1.06) | −0.97 (0.99) | −0.55 (1.05) | −1.13 (1.02) |
| Prior fractures from adulthood | 1165 (25%) | 319 (31%) | 1310 (26%) | 174 (32%) |
| Prior fractures after 50 years | ||||
| 0 | 3944 (85%) | 779 (77%) | 4322 (84%) | 401 (75%) |
| 1 | 555 (12%) | 162 (16%) | 624 (12%) | 93 (17%) |
| 2 | 121 (3%) | 55 (5%) | 146 (3%) | 30 (6%) |
| ≥ 3 | 31 (1%) | 18 (2%) | 37 (1%) | 12 (2%) |
| History of falls | ||||
| 0 | 3758 (81%) | 763 (75%) | 4119 (80%) | 402 (75%) |
| 1 | 527 (11%) | 144 (14%) | 590 (12%) | 81 (15%) |
| 2-3 | 302 (6%) | 94 (9%) | 350 (7%) | 46 (9%) |
| ≥ 4 | 64 (1%) | 13 (1%) | 70 (1%) | 7 (1%) |
| Glucocorticoids | 373 (8%) | 91 (9%) | 415 (8%) | 49 (9%) |
| Rheumatoid arthritis | 214 (5%) | 62 (6%) | 242 (5%) | 34 (6%) |
| Parent history of hip fracture | 587 (13%) | 145 (14%) | 647 (13%) | 85 (16%) |
| Smoking (current) | 155 (3%) | 41 (4%) | 173 (3%) | 23 (4%) |
| Alcohol (>3 standard drinks/day) | 189 (4%) | 33 (3%) | 208 (4%) | 14 (3%) |
| Muscle parameter | ||||
| Grip strength (kg)b | 42.00 (36.00-48.00) | 40.00 (36.00-46.00) | 42.00 (36.00-48.00) | 40.00 (34.00-45.00) |
| Gait speed (m/s)b | 1.26 (1.12-1.41) | 1.25 (1.09-1.40) | 1.26 (1.12-1.41) | 1.24 (1.07-1.39) |
| Chair stands time (s)b | 10.50 (8.90-12.47) | 10.82 (9.18-13.09) | 10.49 (8.91-12.48) | 11.07 (9.30-13.37) |
| Dead (yes) | 2724 (59%) | 639 (63%) | 2992 (58%) | 371 (69%) |
MOF = major osteoporotic fractures (hip, proximal humerus, wrist and clinical vertebral fractures), FN BMD = Femoral neck bone mineral density
Values are numbers (percentages), unless otherwise indicated.
Mean (SD)
Median (interquartile range).
Bold values indicate statistically significant differences between fracture group and the corresponding comparator group (p<0.05).
Men excluded from analysis
This analysis excluded 329 men (Figure 1). Those who were excluded were older, more likely to have lower BMD and higher prevalence of falls, prior fractures, rheumatoid arthritis, and glucocorticoid use. They also had higher incidence of fractures during follow-up.
Role of muscle strength and physical performance in fracture risk
a. The independent contribution of muscle strength and physical performance to fracture risk
Worse muscle strength and physical performance were associated with increased any, MOF, initial hip, and any hip fracture risk, over and above the established risk factors (Figure 2). Each one SD weaker (8.5kg decrease) grip strength, one SD slower (0.24m/s decrease) gait, and one SD longer (1.3s increase) chair stand time were associated with increased risk of any fracture (HRs ranged from 1.11 to 1.20), MOF (HRs 1.14 to 1.27), and hip fractures (HRs 1.21 to 1.37; Figure 2, Supplemental table S2a, table S2b).(29)
Figure 2: Independent contribution of muscle strength and physical performance measurements to fracture risk.
MOF: Major osteoporotic fracture
Hazard ratio (95% confidence interval) presented per 1 SD decline in the baseline grip strength (SD=8.5 kg) and gait speed (SD=0.24 m/s) and 1 SD increase in chair stands time (SD=1.3 s).
b. Relative importance of muscle strength and physical performance in all fracture prediction models
For Garvan any fracture risk calculation, the input variables, in decreasing order of importance, were FN BMD, age, chair stands, grip strength, prior fractures, and falls (Figure 3). The importance of chair stand test and grip strength test were 26% and 21% of FN BMD, the most important risk factor. This was similar to or greater than the importance of prior fracture and falls (Figure 3). For FRAX MOF risk calculation, the important predictors were ranked as age, FN BMD, grip strength, chair stands, BMI, gait speed, smoking, and then corticosteroid use. Relative to age, which was the most important predictor in FRAX models, the importance of grip strength and chair stands were 19% and 17% of age, which was similar to or greater than all other risk factors in FRAX model except age and FN BMD (Figure 3). Gait speed was not an important risk factor in any fracture and MOF models. In the models that assessed hip fracture (initial and any hip), all muscle strength and physical performance tests were of equal or greater importance than the established predictors other than age and FN BMD.
Figure 3: The importance of muscle strength and physical performance tests relative to other predictors of fracturea.
aThe importance of variables in the prediction model is estimated relative to the most important predictor in each model.
FNBMD was the most important predictor across Garvan models while across FRAX models, age was the most important predictor.
FN BMD: Femoral neck bone mineral density; BMI: Body mass index; R. Arthritis: Rheumatoid arthritis; fx: fracture.
Incremental predictive accuracy of muscle strength and physical performance addition to Garvan and FRAX models
Adding muscle strength and physical performance measurements improved prediction of all fracture outcomes. Indeed, the addition of grip strength and chair stands yielded significant improvements in prediction of any fracture (NRI: 3.9%; 95% CI: 2.3% to 6.1% and 3.2%; 95% CI: 0.1% to 6.1%), respectively, Supplemental table S3a, Figure 4).(29) However, adding gait speed test did not improve the prediction of any fracture (NRI: 0.8%; 95% CI: −2.0% to 2.6%). As expected, the addition of grip strength and chair stands combined yielded a greater improvement in the reclassification (NRI: 5.7%; 95% CI: 2.3% to 9.2%).
Figure 4: 10-year reclassification improvement of fracture prediction after the addition of muscle strength and physical performance.
MOF: Major osteoporotic fracture
Bold figures indicate significance at p<0.05
Figures on the top of the bars represent the overall NRI.
Figures next to the bars represent the NRI in the fracture (black) and no fracture (grey) group.
Example: After incorporating grip strength to Garvan any fracture model, 7.7% of the fracture cohort were correctly reclassified into a higher risk category and 4.6% were incorrectly reclassified into a lower risk category, yielding 7.7%−4.6%=3.5% improvement in the fracture cohort. Similarly in the no-fracture cohort, 5.5% were correctly reclassified into a lower risk category, while 4.7% were incorrectly reclassified into a higher risk category, yielding 5.5%−4.7%=0.4% improvement in the no-fracture cohort. Therefore, the net reclassification is 3.5%+0.4%=3.9%.
Similarly, the addition of grip strength and chair stands individually yielded significant improvements in MOF risk prediction (NRI: 5.2%; 95% CI: 1.7% to 9.6% and 6.1%; 95% CI: 0.3% to 11.5%, respectively, Supplemental table S3b,(29) Figure 4) while the addition of both grip strength and chair stands yielded the greatest improvement (NRI: 8.9%; 95% CI: 3.7 % to 13.8%).
In the assessment of initial hip fractures, only gait speed improved risk stratification (NRI: 5.7%; 95% CI: 0.5% to 12.3%). However, adding grip strength and gait speed jointly yielded greater significant improvement (NRI: 9.4%; CI: 6.0% to 14.2%, Supplemental table S3c,(29) Figure 4). The results obtained for any hip fracture followed the same pattern (Supplemental table S3d,(29) Figure 4).
The improvement in the model’s predictive power following the addition of muscle strength and physical performance measurements was predominantly driven by reclassification of those suffering fractures into a higher risk category.
Sensitivity analysis
The addition of grip strength, gait speed and chair stands yielded greater improvements in the five-year (6%, 13.3% and 9.5%, respectively) than ten-year prediction of initial hip fracture (Supplemental tables S4a, S4b).(29) The NRIs of five-year and ten-year prediction of any fracture were similar.
The second sensitivity analysis included an additional 163 men who were unable to perform chair stands and showed similar results to the primary analysis (Supplemental table S5).(29)
DISCUSSION
This study demonstrated that muscle strength and physical performance tests predict incident fracture risk in men independent of the risk factors included in the Garvan and FRAX tools. These tests had equal or even greater contribution in the prediction of fracture risk than many established risk factors including prior fractures and falls. Moreover, muscle strength and performance significantly enhanced the predictive accuracy of both Garvan and FRAX tools. Grip strength and chair stands were associated with the greatest predictive improvement for any fracture and MOF risk, while gait speed test resulted in the greatest improvement in prediction of initial hip and any hip fractures. Combining grip strength and the most relevant physical performance measure yielded even greater improvements.
Men have a steeper decline in their muscle mass and strength with ageing than women (30,31), which may explain why the association between muscle strength and physical performance and the risk of fracture is more consistent in men than women. Two previous studies have examined the independent associations between muscle strength and physical performance and fracture risk in men. The Dubbo Osteoporosis Epidemiology Study(20) reported a two- to three-fold increased fracture risk in men in the lowest quartile of quadriceps strength, get up and go, gait speed, and chair stands, independent of Garvan risk factors. The second was a meta-analysis(16) of three cohorts that reported significant associations between grip strength, gait speed and chair stands and fracture risk, independent of the FRAX probabilities. Here, we have extended such findings by demonstrating that muscle strength and physical performance enhance the predictive accuracy for fracture, by correctly reclassifying men with fractures into higher risk categories.
Interestingly, combining grip strength and the relevant physical performance measurement significantly improved the predictive accuracy of fracture in all models. This finding suggests that strength and the physical performance tests assess distinct biological contributions to fracture risk. Chair stands and grip strength, either individually or combined improved the prediction of any and MOFs. Gait speed either individually or combined with grip strength improved the prediction of hip fracture. That is expected as gait speed was associated with greater risk of hip fracture than other fracture types in the current study and in another previous study.(32) These tests are not routinely assessed in daily practice by health care professionals due to the required time and equipment. However, this study showed that these tests do improve the fracture risk prediction and therefore should strongly be considered as to how they could be included in a clinical setting, to identify more appropriate patients who would benefit from therapeutic intervention (e.g., pharmaceutical agents and resistance exercise programs). Notably, poor strength and performance can be improved with intervention.(33,34)
Our analysis also ranked the importance of various predictors to overall fracture risk. Muscle strength and performance tests were as important as major established risk factors included in the Garvan and FRAX tools including prior fractures, falls, smoking, alcohol, and glucocorticoid use. This finding, which was consistent in all models, indicates that these measurements which are easy and quick to assess may provide more valuable information than many other self-reported data included in Garvan and FRAX.
Although relative importance and NRI differ in their concepts and interpretations, the results of the two analyses are basically consistent. For example, the relative importance analysis showed that grip strength and chair stands were more important risk factors than other factors, apart from age and FN BMD, for predicting any or MOF. Similarly, NRI showed that grip strength and chair stands had the greatest improvement (especially when they were added jointly). For the prediction of hip fractures, the relative importance showed that both grip strength and gait speed are more important than other risk factors (except for age and FN BMD). NRI provided similar results by showing that both grip strength and gait speed, added individually, improved the prediction of initial hip fracture by 4.7% and 5.7%, respectively, although that was not significant for grip strength. Furthermore, grip strength and gait speed, added jointly, improved initial hip fracture prediction by 9.4%. This agreement between the two analyses supports the fact that muscle strength and performance are important and valuable addition to the fracture assessment tools.
This study has several strengths. MrOS is a well-characterised cohort of community-dwelling men with standardized prospective recording and assessment of fractures. Multiple measures of muscle strength and performance were reliably assessed. The large sample size allowed assessment of multiple fracture outcomes using robust statistical approaches.(26,28) Most importantly, we obtained consistent results across fracture assessment tools, prediction models, and fracture outcomes. However, some limitations exist. MrOS includes high-functioning, mostly white men who were able to walk without aids, potentially limiting generalizability. Further studies are warranted to replicate our findings in women, non-whites, and less mobile populations.
In summary, this study demonstrated that poor muscle strength and physical performance measurements were independently associated with greater risk of fractures in men beyond that predicted by the Garvan and FRAX instruments. These findings held across fracture risk tools and fracture sites. Poor strength and/or physical performance has similar importance to recognized fracture risk factors. Measurements of muscle strength and/or performance should be considered for inclusion in fracture risk assessment tools.
Supplementary Material
Funding/Support
The Osteoporotic Fractures in Men (MrOS) Study is supported by National Institutes of Health funding. The following institutes provide support: the National Institute on Aging (NIA), the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), the National Center for Advancing Translational Sciences (NCATS), and NIH Roadmap for Medical Research under the following grant numbers: U01 AG027810, U01 AG042124, U01 AG042139, U01 AG042140, U01 AG042143, U01 AG042145, U01 AG042168, U01 AR066160, and UL1 TR000128. JC is the recipient of an Australian Medical Research Futures Fund (MRFF) grant 1137462. DA is the recipient of an Australian Government Research Training Program (RTP) Scholarship.
Role of the funding source
The funders of this study had no role in the study design, data collection, analysis, or interpretation, writing the manuscript, or the decision to submit the manuscript for publication. All authors had full access to all the data in the study and had final responsibility for the decision to submit for publication.
Footnotes
Declaration of interests
Alajlouni, Tran, Bliuc, and Cawthon reported no competing interests. Blank has been a consultant for Bristol Myers Squibb, served on an advisory board for Amgen, received authorship royalties from Wolters Kluwer, received an editorial stipend from Elsevier, received travel support from Amgen, and owns stock in Abbott Labs, Abbvie, Amgen, JangoBio, and Procter & Gamble. Orwoll has received consulting support from Bayer and Biocon and served on an advisory board for Radius. Center has received support from Amgen for attending educational meetings, received advisory board honoraria from Amgen and Bayer, and received educational talks honoraria from Amgen.
Data availability
MrOS data is publicly available at https://mrosonline.ucsf.edu
Data related to the study results is available on request from the authors.
Supplementary material is available in “figshare” at https://doi.org/10.6084/m9.figshare.16910911
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
MrOS data is publicly available at https://mrosonline.ucsf.edu
Data related to the study results is available on request from the authors.
Supplementary material is available in “figshare” at https://doi.org/10.6084/m9.figshare.16910911