1 Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA.
2 Department of Health Research and Policy, Stanford University School of Medicine, Stanford, CA.
3 Division of Preventive and Behavioral Medicine, Department of Medicine, University of Massachusetts Medical School, Worcester, MA.
Received for publication February 13, 2003; accepted for publication July 30, 2004.
![]() |
ABSTRACT |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
accidental falls; aged; fractures; prospective studies; women
![]() |
INTRODUCTION |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
![]() |
MATERIALS AND METHODS |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Measurement of falls and fractures
Following the baseline visit, the participants falls were monitored every 4 months. A letter with a return postcard was mailed to each participant asking whether she had fallen in the past 4 months and, if so, how many times. A fall was not defined in the letter but was described to participants during the baseline visit and semiannual interviews as "landing on the floor or ground, or falling and hitting an object like a table or stair." For the results reported here, information on falls from the first 12 postcards, or approximately 4 years of follow-up, was used to determine the rate of falling for each participant. Two hundred and nineteen participants who returned fewer than six postcards were excluded. The remaining 9,485 women returned an average of 11.8 postcards (standard deviation, 0.8), for an average follow-up time of approximately 3.9 years (standard deviation, 0.3).
Study participants were asked to notify the local clinical center as soon as possible after any fracture. In addition, every 4 months, participants were asked about the occurrence of a fracture in the letter requesting information on falls. If a fracture was reported, the participant was contacted by telephone for additional information, including the immediate cause of the fracture. Medical records were requested for confirmation of the participants report of a fracture. Only fractures confirmed by a radiologists report were included (13).
The results reported here included fractures that occurred after the 12th postcard report (approximately 4 years after the baseline visit), up to October 1998, for a median follow-up time (counting from the 12th postcard) of 6.3 years. Of the baseline cohort of 9,704 women, 522 were deceased and 76 were lost to follow-up, leaving 9,106 participants available for analysis of fracture risk. All of these women had returned at least six of the 12 postcards; 99.8 percent had returned at least 10, and 92.3 percent had returned all 12. Fractures due to pathologic conditions, such as a neoplasm, and those caused by severe trauma, such as a motor vehicle accident, were excluded. Only the first fracture occurring after the 12th postcard at each specific site considered was included in these analyses. The specific fracture sites of interest were the hip, the proximal humerus, the distal forearm, the ankle, and the foot. In addition, all nonspine fractures were analyzed as a group.
Measurement of covariates
Measurement of covariates has been described previously (3, 1416). At the baseline clinic visit, a self-administered questionnaire and in-clinic interview included assessment of physical activity, alcohol consumption in the past year, current cigarette smoking, medical history, personal and family history of fracture, use of medications, performance of instrumental activities of daily living, and cognitive function.
The following measurements were obtained during the baseline clinic visit: height, weight, waist and hip circumferences, grip strength, triceps extensor strength, tandem stand, gait speed, chair stand, corrected visual acuity, near and far depth perception, and contrast sensitivity. Bone mineral density was measured at the distal radius, the proximal radius, and the calcaneus (11).
Statistical analysis
Age-specific incidence rates and 95 percent confidence intervals for number of falls per year were calculated using age at the time of the fall. The numerator was the number of falls occurring during the 4-year study period, and the denominator was person-years of follow-up during the same 4 years, based on the number of postcards returned (17). Change in the rate of falling over the first 4 years was estimated for each participant using a within-person linear regression method. The rate of falls (determined using each returned postcard) was regressed on time, and the resulting slope is reported as the change in the rate of falls per year (falls/year/year).
The Cox proportional hazards model (18) in SAS (19) was used to assess the association between rate of falls in the first 4 years and time to first subsequent fracture. Since the rate of falls and the rate of fracture increased with age, data in all of the models were adjusted for age at baseline. In these models, the participants rate of change in the fall rate (slope described above) was used as a main independent variable, with the participants average rate of falls entered as a covariate. Both the change in the rate of falls and the average rate of falls were entered into the model as categorical variables. The reference group for the average rate of falls was participants who reported no falls in the first 4 years. For change in the rate of falls, the reference group was women who had a stable or decreasing rate of falls in the first 4 years, including those who reported no falls.
In the reported analyses, except where specifically noted, we included fractures due to a fall from any height and fractures due to other minimal or moderate trauma. When the analyses were restricted to fractures due to a fall, the associations with number of falls and change in the rate of falls were not altered substantially, and the results are not shown.
To assess the relations between an increasing rate of falls and variables known to be associated with fracture risk, such as impaired functional ability, we used logistic regression models. The outcome was being in the top quartile of persons with an increasing rate of falls. All models were adjusted for age at baseline.
Using variables that are known to be associated with fracture risk, we then constructed separate multivariate Cox proportional hazards models for fractures of the hip, proximal humerus, distal forearm, ankle, and foot using backward regression. Covariates were selected for initial entry into the models on the basis of factors (excluding falls) associated with fractures of the hip (3), proximal humerus (20), distal forearm (20), ankle (9), and foot (9) in previous reports on the SOF cohortincluding body size, medication use, lifestyle factors, physical function, cognitive function, vision, and comorbid conditions. Variables for the average rate of falls and the change in the rate of falls for the first 4 years were added to the variables selected as a result of backward regression (p < 0.05) to obtain the multivariate models discussed here.
![]() |
RESULTS |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
During follow-up, the rate of falls increased for approximately 30 percent of the participants and decreased for another 30 percent. The average change in the rate of falls increased with age, ranging from an annual increase of 1.2 falls per 100 years per year for women aged 6569 years to 17.4 falls per 100 years per year for women aged 85 years or more.
During follow-up after the 12th postcard, 1,541 women reported at least one confirmed nonspine fracture, excluding fractures due to severe trauma or pathology. The 1,933 confirmed fractures included fractures of the hip (n = 388), distal forearm (n = 326), proximal humerus (n = 212), ankle (n = 148), foot (n = 144), and other sites.
Compared with the 3,634 women who had no falls in the first 4 years, women who reported an average rate of more than 1.75 falls per year in the first 4 years of follow-up ("frequent fallers") had nearly double the rate of subsequent hip fracture (rate ratio (RR) = 1.85) and distal forearm fracture (RR = 1.87) (table 1). Frequent fallers had a somewhat increased rate of foot fracture (RR = 1.50) but only a slightly increased rate of ankle (RR = 1.24) and proximal humerus (RR = 1.17) fracture in comparison with women who never fell. Frequent fallers also had an increased rate of all nonspine fractures (RR = 1.88).
|
In age-adjusted models, women in the top quartile of rate of increase in falls during the first 4 years of follow-up were at greater risk of subsequent hip fracture (RR = 1.83, 95 percent confidence interval (CI): 1.35, 2.48), proximal humerus fracture (RR = 1.58, 95 percent CI: 1.02, 2.44), and all nonspine fractures (RR = 1.49, 95 percent CI: 1.26, 1.76) than women who had no change or a decline in the rate of falls. In models adjusted for the average rate of falls in the first 4 years (table 2), being in the top quartile of increasing falls continued to be associated with hip (RR = 1.57) and proximal humerus (RR = 1.65) fracture. An increasing rate of falls was not associated with a higher rate of distal forearm, ankle, or foot fracture, with or without controlling for the average rate of falls. These results were similar in analyses that excluded the 3,634 women who did not report any falls (results not shown).
|
To determine whether an increase in the rate of falls was associated with higher fracture rates because of an association with other known risk factors for fractures, such as poor physical function, we used the risk factors for fracture identified in previous studies of this cohort (3, 9, 20). We first assessed whether these risk factors for fracture were also associated with being in the top quartile of increasing falls. For the variables considered, the associations were relatively weak (for a one-standard-deviation change, odds ratio (OR) < 2.0). For example, women with weaker grip strength (for a reduction of 4.3 kg, OR = 1.13, 95 percent CI: 1.04, 1.23), slower walking speed (for a reduction of 0.22 seconds, OR = 1.14, 95 percent CI: 1.05, 1.24), or poorer visual acuity (for a reduction of 7.3 letters read, OR = 1.10, 95 percent CI: 1.02, 1.19) were just slightly more likely to be in the top quartile of increasing falls. The largest association was with use of seizure medications at baseline (OR = 1.87, 95 percent CI: 1.03, 3.37).
We next assessed whether these previously identified risk factors for fracture might alter the association between an increase in the rate of falls and risk of fracture. The results for hip and proximal humerus fracture are presented in table 3. For hip fracture, the association between being in the top quartile of an increasing rate of falls and subsequent fracture (RR = 1.42, 95 percent CI: 0.99, 2.04) in the resulting multivariate model was attenuated by approximately 10 percent in comparison with models adjusted only for age and number of falls (RR = 1.57, 95 percent CI: 1.10, 2.23). For proximal humerus fracture, there was a slightly greater association between the upper quartile of increase in falls and the risk of proximal humerus fracture (RR = 1.79, 95 percent CI: 1.08, 2.95) in the multivariate model than in the model adjusted only for age and number of falls (RR = 1.65, 95 percent CI: 1.00, 2.72). For the other specific fracture sites considered (distal forearm, ankle, and foot), there was no association in the multivariate models between being in the upper quartile of increase in the rate of falls and the risk of fracture, as found in the models adjusted only for age and number of falls.
|
![]() |
DISCUSSION |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|
Our finding of an association between an increased rate of falls and hip and proximal humerus fractures, but not foot, ankle, or forearm fractures, is consistent with our hypothesis that an increased rate of falls is indicative of greater frailty. Hip and proximal humerus fractures are considered "frailty" fractures, distinguished by their strong association with declines in physical function. Different risk factor profiles among older women for sustaining a hip fracture versus a distal forearm fracture (21, 22) or for sustaining a proximal humerus fracture versus a distal forearm fracture (20) have been previously reported.
The increases in falling associated with higher fracture risk were relatively modest. Among women in the top quartile of an increasing rate of falls (n = 672), the average increase was 1.04 falls per year per year (range, 0.4523.7 falls/year/year). At this average rate of increase, a participant who fell once during the first year of the study would have had four falls in the fourth year of the study.
Using prospective data on 4 years of fall history, we also confirmed previous reports, based on retrospective reports of falls, of a positive association between a history of falls and the risk of fractures of the hip (35) and distal forearm (6, 8, 20) and a lack of association for foot fractures (9). A previous report from the SOF using a baseline report of falls in the previous year also found no increased risk of proximal humerus fracture among women who had fallen (20). However, other investigators have reported that a history of falling is associated with risk of proximal humerus fracture (6, 7). We found little association between falls and subsequent ankle fracture, in contrast to a previous report of a positive association in the SOF cohort, using a baseline report of falls in the previous year (9).
An increase in the rate of falls appears to provide additional information regarding subsequent risk of fracture as compared with the absolute number of falls. An increasing rate of falls in one time period may simply be a better predictor of the subsequent rate of falls. However, it may also predict factors that contribute to the risk of fracture given a fall, including reduced protective responses, the direction of a fall, and lower bone mineral density. In our analyses, adjusting for the average rate of falls before (years 14) and during (years 58) the fracture follow-up period did not account for the association between an increasing rate of falls and the risk of hip and proximal humerus fractures. This suggests that an increase in the rate of falls is associated with an increased risk of sustaining a fracture when a fall occurs.
We had originally hypothesized that an increase in the rate of falls might be a marker for poor function and that any association between increasing falls and the risk of subsequent fracture would be largely accounted for by associated poor function or performance. We did find that an increasing rate of falls was weakly associated with several measures of poor physical function. However, in the multivariate models constructed for hip and proximal humerus fracture, we found that the association between increasing falls and the risk of fracture was not substantially attenuated in comparison with models adjusted only for age and the average rate of falls. This suggests that there is an aspect of poor function that was not adequately captured in the available measures. The battery of tests performed at the clinic visits included measures of the major risk factors generally associated with falls (2). However, the tests used may not be able to distinguish smaller decrements or specific aspects of performance that are nevertheless important in determining the outcome of a fall. In addition, level of function at baseline may not adequately predict changes in function over time, and these changes may be more influential in determining risk of fracture in a fall.
We have reported findings for all nonspine fractures, but we believe that these results should be interpreted with caution. In the analyses of specific fracture sites, associations between the average rate of falls and risk of fracture differed across sites, and so did associations between increasing falls and risk of fracture. Therefore, it can be misleading to combine them.
This study included extensive prospective data on both falls and fractures in older women. However, it also had certain limitations. Falls were ascertained every 4 months. It is likely that some falls were forgotten and not reported and also possible that some falls were reported more than once (23). However, the age-specific incidence rates of falls in this study are consistent with results from studies that collected fall reports on a monthly basis (24, 25). The study population was almost entirely White, and the study was conducted among community-dwelling women. The results may not apply to non-White women or to older women residing in institutions.
In summary, in our study, a more rapid increase in the rate of falls appeared to be associated with hip and proximal humerus fractures, taking into account the average rate of falls, but not with distal forearm, ankle, or foot fractures. The increasing rate of falls may be a marker for aspects of frailty that contribute to the risk of sustaining a hip or proximal humerus fracture in a fall. The associations between risk of hip and proximal humerus fracture and an increasing rate of falls were not fully accounted for by the baseline measurements of physical and cognitive function.
![]() |
ACKNOWLEDGMENTS |
---|
Investigators in the Study of Osteoporotic Fractures Research Group: San Francisco, California (Coordinating Center)S. R. Cummings (principal investigator), D. M. Black (coinvestigator), K. L. Stone (coinvestigator), J. Schneider (project director), D. C. Bauer (coinvestigator), M. C. Nevitt (coinvestigator), W. Browner (coinvestigator), R. Benard, T. Blackwell, P. Cawthon, M. Dockrell, S. Ewing, C. Fox, R. Fullman, D. Kimmel, S. Litwack, L. Y. Lui, J. Maeda, L. Nusgarten, L. Palermo, M. Rahorst, C. Schambach, R. Scott, D. Tanaka, and C. Yeung; University of MarylandM. C. Hochberg (principal investigator), L. Makell (coordinator), M. A. Walsh, and B. Whitkop; University of MinnesotaK. E. Ensrud (principal investigator), M. Homan (coinvestigator), C. Quinton (clinic coordinator), C. Bird, D. Blanks, C. Burckhardt, F. Imker-Witte, K. Jacobson, D. King, K. Knauth, and N. Nelson; University of PittsburghJ. A. Cauley (principal investigator), L. H. Kuller (co-principal investigator), J. Zmuda (coinvestigator), L. Harper (project director), L. Buck (clinic coordinator), C. Bashada, W. Bush, D. Cusick, A. Flaugh, A. Githens, M. Gorecki, D. Moore, M. Nasim, C. Newman, and N. Watson; Kaiser Permanente Center for Health Research, Portland, OregonT. Hillier (principal investigator), E. Harris (coinvestigator), E. Orwoll (coinvestigator), K. Vesco (coinvestigator), J. van Marter (project administrator), M. Rix (clinic coordinator), J. Wallace, K. Snider, T. Suvalcu-Constantin, A. MacFarlane, K. Pedula, and J. Rizzo.
![]() |
NOTES |
---|
![]() |
REFERENCES |
---|
![]() ![]() ![]() ![]() ![]() ![]() ![]() |
---|