The authors have no conflict of interest
Risk Factors for Fractures of the Proximal Humerus: Results From the EPIDOS Prospective Study†
Article first published online: 1 MAY 2002
Copyright © 2002 ASBMR
Journal of Bone and Mineral Research
Volume 17, Issue 5, pages 817–825, May 2002
How to Cite
Lee, S. H., Dargent-Molina, P. and Bréart, G. (2002), Risk Factors for Fractures of the Proximal Humerus: Results From the EPIDOS Prospective Study. J Bone Miner Res, 17: 817–825. doi: 10.1359/jbmr.2002.17.5.817
- Issue published online: 2 DEC 2009
- Article first published online: 1 MAY 2002
- Manuscript Accepted: 7 DEC 2001
- Manuscript Revised: 17 OCT 2001
- Manuscript Received: 14 MAR 2001
- proximal humerus fractures;
- risk factors;
Fracture of the proximal humerus is one of the most frequent fractures attributable to osteoporosis; yet, it has seldom been studied. Two types of factors (related to bone fragility and falls) were evaluated to identify risk factors for proximal humerus fractures as well as to examine possible interactions between them. Subjects were 6901 white women aged ≥75 years and all participated in the EPIDOS study of risk factors for osteoporotic fractures (France, 1992-1998). The baseline examination included measurements of femoral neck bone mineral density (BMD) and calcaneal ultrasound parameters (speed of sound [SOS] and broadband ultrasound attenuation [BUA]), a functional clinical examination, and completing a questionnaire on health status and lifestyle. During a mean of 3.6 (0.8) years of follow-up, 165 women had a humeral fracture. Using multivariate Cox regression models, we identified three predictors related to bone fragility—low BMD (relative risk [RR] = 1.4; 95% CI, 1.1-1.7), low SOS (RR = 1.3; 95% CI, 1.0-1.6), and maternal history of hip fracture (RR = 1.8; 95% CI, 1.0-3.0)—and four fall-related predictors—a previous fall (RR = 3.0; 95% CI, 1.5-6.1), a low level of physical activity (RR = 2.2; 95% CI, 1.1-4.4), impaired balance (RR = 1.8; 95% CI, 1.1-2.9), and pain in lower limb extremity (RR = 1.4; 95% CI, 1.0-2.1). The effect of these fall-related predictors varied according to the BMD level; they were significantly associated with proximal humerus fractures in women with osteoporosis (BMD T score < −2.5) but not in nonosteoporotic women. The incidence of proximal humerus fracture in women with osteoporosis and a low fall risk score (5.1 per 1000 woman-years) was only slightly higher than in nonosteoporotic women (4.6 per 1000 woman-years) and similar to the incidence in women without osteoporosis but a high fall risk score (5.3 per 1000 woman-years). On the other hand, the incidence in women who had both types of risk factors was more than two times higher (12.1 per 1000 woman-years) than in women with only one of the two risk factors. These results suggest that women who have both types of risk factors should receive the highest priority for prevention.
FRACTURE OF THE PROXIMAL humerus is considered to be one of the most important fractures attributable to osteoporosis, yet it has seldom been studied. In the elderly, it is the third most frequent fracture after hip fracture and Colles' fracture.(1,2) The morbidity associated with it is quite substantial, with functional capacity impaired for the activities of daily living for an average of 2-3 months. The long-term functional outcome is satisfactory in ∼80% of patients after a simple humeral fracture without displacement.(3) Nevertheless, displaced proximal humeral fractures may require hospitalization and generally lead to long-term functional deficit. Hence, they have been considered the unsolved fracture.(4) These cases require a mean hospitalization length of 24 days, second only to hip fractures in the number of hospital days it causes.(5)
Low bone mineral density (BMD) has long been recognized as a major risk factor for fracture in the elderly. Although this factor is believed to be necessary, it generally is not sufficient for the occurrence of a fracture; there is a considerable overlap in bone density values between hip fracture patients and age- and gender-matched controls.(6,7) In the elderly, falling appears to be another major determinant of fractures, because most appendicular fractures are the consequence of a fall.(8) Several risk factors for falling have been found to be associated with an increased risk of hip fracture, including impaired vision, decreased balance and gait performances, and use of sedative-hypnotic drugs.(9,10) However, the importance of these factors rarely has been examined with regard to other types of fracture, in particular proximal humerus fracture.(11)
Although falling appears necessary in most cases, only 5% of falls result in fractures, which implies that the characteristics of the fall are very important in determining whether a fall will cause a fracture. Cummings and Nevitt(12) hypothesized that a sequence of conditions are necessary for a fall to cause a hip fracture: (a) the faller must be oriented to impact near the hip; (b) protective responses (such as landing on an outstretched hand) must fail; (c) local soft tissues must absorb less energy than necessary to prevent fracture, and (d) the residual energy of the fall applied to the proximal femur must exceed its strength. A few recent studies that compared the mechanics of falls with and without a fracture confirmed that the orientation of the fall and protective responses are important to determine whether a fracture will occur (once the fall has been initiated) and what type of fracture will occur.(13–15) These results suggest that factors that influence the orientation of the fall or the effectiveness of protective responses are important risk factors for fracture in the elderly. However, it has been difficult to identify risk factors that act specifically through these pathways. On the other hand, it has been noted that several risk factors for falling, in particular neuromuscular impairments, also can affect the effectiveness of protective responses and, possibly, the orientation of the fall.(12,15) Conceptual models of the pathogenesis of fracture(8,12) further suggest that the importance of risk factors for falls and increased trauma will depend on the level of bone resistance, that is, there is interaction between these two types of factors. However, there have been few attempts to assess the interaction between osteoporosis and fall-related factors.
We used data from a prospective cohort study, the Epidémiologie de l'Ostéoporose Study (EPIDOS), to identify important risk factors for proximal humeral fractures, including both those related to bone fragility and those related to falls. In this study, the fall-related factors include factors that increase the risk of falling and, possibly, the risk of trauma once a fall occurs. A second important goal of this analysis was to assess potential interactions between bone fragility, as measured by BMD, and fall-related factors.
MATERIALS AND METHODS
The study population consisted of 6901 participants in the EPIDOS study, a French prospective cohort study of risk factors for hip fractures. From January 1992 through January 1994, 7575 white women aged 75 years or older were enrolled in the cohort in five French areas: Amiens, Lyon, Montpellier, Paris, and Toulouse.(9) Eligible women were contacted by mail, based on voter registration or health insurance membership rolls. All participants were volunteers who accepted the invitation to participate in the study. Women who were unable to walk independently or who had bilateral hip replacement or a history of hip fracture were excluded from the EPIDOS cohort. For this analysis, a history of proximal humeral fracture was an additional exclusion criteria.
Assessment of risk factors
The baseline examination was performed in the local clinical center by trained nurses; it included a structured questionnaire, a clinical and functional examination, and BMD and ultrasound measurements. We distinguished two groups of risk factors: those related to bone fragility and those related to falls.
Factors related to bone fragility
Included in this group of factors are BMD and ultrasonographic measurements, personal and family history of fractures, reproductive history, anthropometric factors, calcium intake, cigarette smoking habits, and certain medical conditions associated with the risk of low bone mass.
Femoral neck BMD (g/cm2) was measured by dual-energy X-ray absorptiometry (DXA) with a GE Lunar device (Lunar Corp., Madison, WI, USA). Calcaneal ultrasound parameters included measurements of speed of sound (SOS; m/s) and of broadband ultrasound attenuation (BUA; Db/MHz) with a GE Lunar Achilles device (Lunar Corp.).
Family history of fractures was evaluated by asking women if their mother had had a hip fracture. Reproductive history was evaluated by asking women how many pregnancies and live-born children they had had, how many children they had breast fed, and their age at menopause.
Anthropometric factors included height and weight at the age of 30 years, weight at menopause, present height and weight, height loss since the age of 30 years, body mass index (BMI), and weight change since the age of 30 years, since menopause, and between the age of 30 years and menopause.
Calcium intake was measured by a specific validated French dietary calcium content questionnaire.(16) Cigarette smoking habits were evaluated by asking women if they smoke, had smoked, or never smoked, as well as the number of cigarettes smoked daily. Medical conditions associated with low bone mass included hyperthyroidism, long-term corticosteroid treatment (during at least 3 months a year), and long-term bed rest (for at least 2 consecutive months).
Factors related to falls
The factors studied include physical capacity, mobility and physical activity, vision, use of certain medications, history of previous falls within the last 6 months, alcohol intake, hearing difficulties, cognitive function, orthostatic hypotension, and other medical conditions related to falls.
Physical capacity was assessed by self-report and objective measurements of neuromuscular function. Self-reported capacity to do nine basic and instrumental daily activities without assistance(17) was scored as the number of activities (from none to two or more) for which assistance was needed. Self-reported difficulty in carrying out various physical movements such as walking, going up and down stairs, standing up from a chair, bending over, lifting heavy weights, reaching up, putting on socks, and getting out of bed was scored as the number of movements (from none to three or more) that caused serious difficulty to the participant. The women also took a series of standard tests of physical performance including the time taken to stand up and sit down 5 times with arms crossed (chair stands), the time taken to tap one foot back and forth 10 times between two circles placed 30 cm apart in a sitting position (foot tapping), and the time taken to walk 6 m at a normal pace (average of two trials). Static balance was assessed by the woman's ability to stand (up to 10 s) with the feet in three successive positions: side-by-side (position 1), semitandem (position 2), and tandem (heel-to-toe, position 3). This test was performed with eyes open and closed and scored from 0 (unable to stand in position 1) to 3 (able to stand in position 3). Dynamic balance was assessed by the woman's ability to walk with the heel of her front foot touching the big toe of her rear foot (tandem walk) and scored 1, able to complete four tandem steps; 2, unable to complete four tandem steps; 3, unable or unwilling to put feet in tandem position.
Mobility and physical activity were assessed by self-reported activities such as daily outdoors walking, traveling out of their neighborhood, doing housework, and regular (at least once a week) sports or physical leisure activity. Calf circumference as well as grip, triceps, and quadriceps strength were measured.
Visual function assessment included corrected binocular distant visual acuity, depth perception, and contrast sensitivity. Visual acuity was measured at a distance of 5 m with a Snellen letter test chart (decimal scale). Depth perception was measured with a Randot stereotest containing contoured circles at nine levels of disparity. Contrast sensitivity was measured with a Vistech (VCTS 6500; Vistech Consultants, Inc., Dayton, OH, USA) wall chart at five different spatial frequencies (1.5, 3, 6, 12, and 18 cycles per degree of visual angle).
Use of sedative-hypnotic, anxiolytic, antidepressive, or antihypertensive (European Pharmaceutical Marketing Research Association classification) drugs was evaluated by asking women to bring all medication they were taking regularly to the clinical center.
Alcohol intake (number of drinks daily), hearing problems (self-report and interviewer's appreciation), cognitive function,(18) orthostatic hypotension, and other medical conditions associated with falls such as history of stroke, hypertension, angina pectoris, diabetes, Parkinson's disease, depression, glaucoma, and cataract were evaluated also. Finally, self-evaluation of overall health compared with other people their age (better, the same, or worse), and the presence of symptoms such as dizziness, back pain, and pain in the hip, knee, and ankle or foot also were taken into account.
Assessment of proximal humeral fractures
Participants were contacted by mail or telephone every 4 months for 4 years and asked whether they had had a fracture. When a participant had a fracture, we sought a radiographic or surgery report and the report of her primary-care physician to confirm the fracture and its location (in 9% of the reported cases, no element of confirmation was available). When a participant died, we interviewed a friend or relation, her primary-care physician, or both to find out whether she had had a fracture since her last contact with the clinical center. A fracture of the proximal humerus was defined as one in the proximal one-third of the humerus, including humeral head, lesser tuberosity, greater tuberosity, and the proximal humeral shaft.
The bivariate analysis calculated the relative risk (RR) and corresponding 95% CI for the association between each individual predictive variable and the risk of humeral fracture. Values of continuous variables were grouped into quartiles or when possible, in categories based on standard clinical cut-offs. Categories of a variable were combined when there were no apparent differences in degree of risk. Within each group of predictors, we used κ2 significance tests to select variables for the multivariate analysis; a value of p < 0.10 was considered significant.
In the multivariate analysis, we assessed the hazard (instantaneous incidence density) of a first humeral fracture by Cox proportional hazard regression. The recorded time of follow-up was the time from the date of inclusion in the study to the date of occurrence of the fracture, the date of death, or the date of the last questionnaire.
The selection of the most predictive factors took place in several stages using forward stepwise regression procedures. Within the group of factors related to bone fragility, we distinguished two subgroups of factors: direct measures of bone fragility (i.e., BMD, SOS, and BUA) and other factors that are considered to cause bone fragility. We first selected the most predictive variables within these two subgroups separately. To assess the extent to which the effect of factors from the second subgroup was explained by bone mass (as measured by BMD or bone quality (reflected by ultrasound parameters), we then examined how the magnitude of their RRs changed when the independent measures of bone fragility were introduced one by one into the model. For the rest of the analysis, we retained the independent measures of bone fragility and the predictors from the other subgroup that were independent of these measures. We also used stepwise Cox regression procedures to select the most predictive variables from the fall-related factors. In the final stage of selection, we selected the most predictive variables from both groups of factors together. We report adjusted hazard rate ratios (RRs) and 95% CI for the association of each independent predictor of the final model and the risk of humeral fracture.
To evaluate possible interactions between the factors related to bone fragility and those related to falls, we first evaluated and compared the effect of the latter in osteoporotic (defined by a BMD value 2.5 SD or more below the young adult mean) and nonosteoporotic women. We then assessed the incidence of humeral fracture in groups of women defined both by their BMD status (osteoporotic vs. nonosteoporotic) and by their fall risk status (risk score above vs. risk score below median). The fall risk score has been calculated based on the regression equation of a Cox model that included only the independent fall-related predictors.
The proportionality assumption of the Cox proportional hazards regression model was tested by introducing time-dependent variables into the final model and by the graphic method (parallelism of log minus log survivor curves). The analysis was performed with SAS software (SAS Institute, Cary, NC, USA).
The mean age of the 6901 participants was 80.5 years (SD, 3.7). They were followed for an average of 3.6 years (SD, 0.8), and the total follow-up represents 25,033 person-years. During follow-up, 439 women (6.4%) discontinued participation, 83 women (1.2%) were lost to follow-up, and 629 women (9.1%) died. We recorded 165 first humeral fractures (incidence rate, 6.6 per 1000 person-years), which occurred at a mean age of 82.2 years (SD, 4). Over the age range included in this study, the incidence of proximal humeral fracture had no significant association with age.
In the group of factors related to bone fragility, all three measures of bone fragility—BMD, SOS, and BUA—as well as five other factors—personal history of fractures, maternal history of hip fracture, number of pregnancies (<4 vs. ≥4), number of live-born children (<4 vs. ≥4), and weight at the age of 30 years (<60 kg vs. ≥60 kg)—were significantly associated with the risk of humeral fracture in the bivariate analysis. The crude RR of proximal humerus fracture associated with these factors are presented in Table 1. In the multivariate analysis, the direct measures of bone fragility were distinguished from the other factors. Of the direct measures of bone fragility, only BMD and SOS were independent predictors of the risk of humeral fracture. In the other subgroup of factors, all but the number of pregnancies were selected as independent predictors. However, only two—maternal history of hip fracture and number of live births—remained significant after adjustment for BMD and/or SOS, and all four of these variables were retained for the final stage of selection.
In the fall-related factors, 12 variables were significantly associated with the risk of humeral fracture in the bivariate analysis: history of falls, dizziness, hip pain, ankle or foot pain, benzodiazepine use, number of physical activities, a test of visual function (contrast sensitivity), two tests of muscular strength (grip and triceps strength), ability to complete five chair stands with crossed arms, and two tests of balance (scores of static balance with eyes open and closed). The crude RRs associated with these variables are presented in Table 1. In the multivariate analysis, stepwise Cox regression procedures selected all but four of these 12 variables (benzodiazepine use, visual contrast sensitivity, triceps strength, and open-eyes static balance score) for the final stage of analysis.
Finally, another stepwise Cox regression procedure selected the independent predictors from all the factors previously selected in both groups. The final model included seven independent predictors (after adjustment for study center): low BMD, low SOS, maternal history of hip fracture, history of falls, low number of physical activities, low balance score (eyes closed), and foot or ankle pain. Their adjusted RRs and 95% CI are presented in Table 2. For the variable “history of falls,” the proportionality assumption was not satisfied. The effect of this factor varied with time; the associated RR increased from 1.1 (95% CI, 0.6-2.0) for the first year of follow-up to 3.0 (95% CI, 1.5-6.1) for the fourth year of follow-up, that is, the risk of humeral fracture associated with this factor increased 1.4-fold each year of follow-up.
Table 3 shows the RRs and 95% CI associated with the four fall-related factors included in the final model (history of falls, number of physical activities, balance score, and ankle or foot pain) in osteoporotic (n = 3079 and 98 humeral fractures) and nonosteoporotic women (n = 3646 and 62 humeral fractures), respectively. Globally, the RRs were of greater magnitude in the subgroup of osteoporotic women than in nonosteoporotic women. Moreover, the four fall-related predictors were significantly associated to the risk of proximal humerus fracture only among osteoporotic women. Given these results, we performed a complementary analysis specifically in the subgroup of osteoporotic women; we performed a stepwise Cox regression analysis starting with all available fall-related factors to examine whether a larger (or different) set of independent fall-related factors would better predict the risk of proximal humerus fracture in this subgroup. This analysis resulted in the same set of independent fall-related predictors.
Table 4 shows the incidence of proximal humerus fracture per 1000 woman-years in groups of women defined by their BMD status (osteoporotic vs. nonosteoporotic) and fall-risk status (risk score above vs. risk score below median). The incidence of proximal humerus fracture in women with osteoporosis and a low fall risk score (5.1 per 1000 woman-years) were only slightly higher than in nonosteoporotic women (4.6 per 1000 woman-years) and similar to the incidence in women without osteoporosis but a high fall risk score (5.3 per 1000 woman-years). On the other hand, the incidence in women who had both types of risk factors was more than two times higher (12.1 per 1000 woman-years) than in women with only one of the two risk factors.
We found that both types of factors, related to bone fragility and to falls, influenced the risk of proximal humerus fracture in older women. Furthermore, fall-related factors seemed to affect osteoporotic and nonosteoporotic women differently. They were significantly associated with the risk of humeral fracture only in women with low BMD.
In agreement with previous studies,(1,11) we found that low BMD, as measured by DXA, is associated with an increased risk of proximal humeral fracture. In the only other cohort study that investigated a large set of risk factors for proximal humeral fracture (the Study of Osteoporotic Fractures), this association was of a greater magnitude than in our study.(11) This SOF study may be caused by the fact that in the SOF study, BMD was measured in the distal radius that is closer to the site of fracture. Furthermore, the SOF participants are on the average almost 10 years younger than the EPIDOS participants. In an older population, other factors may influence the risk of proximal humerus fracture and the relative importance of BMD, therefore, may be decreased.
We also found that the measure of the SOS at the calcaneum, with a water-based ultrasound system, is able to predict humeral fractures independently of BMD. Furthermore, the strength of the association between SOS and fracture is similar to that observed with BMD. This is in agreement with previous findings from the EPIDOS and other prospective studies regarding the prediction of hip fracture(19–21) and suggests that ultrasound measurements could be a useful screening tool for identifying elderly women at high risk of osteoporotic fractures.
Our results show that maternal history of hip fracture is another significant predictor of humeral fracture. This factor is believed to reflect family transmission of factors that influence the determination of bone mass.(22–26) In this study, we found that maternal history of hip fracture remained significantly associated with the risk of humeral fracture even after taking into account the level of BMD and SOS. Hence, it probably reflects other factors not measured by BMD and SOS. Our results are in line with results from the SOF study that showed a positive association between maternal history of hip fracture and the risk of future hip fractures, independent of the level of BMD.(10)
Other risk factors related to bone fragility such as weight at the age of 30 years and personal history of fractures were associated with the risk of humeral fracture in the bivariate analysis. However, these factors were no more significantly associated to humeral fracture after adjustment for the two measures of bone fragility (BMD and SOS). This finding suggests that their effect on the risk of humeral fractures can be explained, in great part, by their association with these measures. Current weight (or BMI) was not significantly associated to the risk of proximal humerus fracture, although previous analyses of the EPIDOS data showed that it is associated to the risk of hip fracture(26) and is a very strong predictor of a low BMD.(27) However, it has to be noted that BMD appears less strongly associated to the risk of proximal humerus fracture than to the risk of hip fracture.(9)
A history of falling at least once during the previous 6 months is a strong predictor of humeral fracture, and its effect increases over time. Falls are common events in the elderly: 30% of people aged 65 years or older fall at least once per year and 50% of them have recurrent falls.(28,29) Longitudinal studies comparing fallers to nonfallers suggest that falls accelerate normal age-related functional decline,(30) leading to physical deconditioning. This may explain that history of falling is associated with an increased risk of humeral fracture over time.
We also found that impaired balance, which is one of the most important risk factors for falling in the elderly,(31,32) is a significant predictor of the risk of humeral fracture. Pain in the distal lower extremity was associated also with an increased risk of humeral fracture. This factor can reflect several foot problems that, simple as they may be (inadequate shoes, bunions, toe deformities, ulcers, or ingrown nails), also may contribute to postural and gait instability.(31)
Globally, a low level of physical activity, as measured by the number of activities regularly practiced, is associated with increased risk of humeral fracture. This is in agreement with the general concept that physical activity helps protect against falls and fractures.(33–35) In the elderly, physical activity can decrease the risk of fracture by slowing bone loss, reducing the risk of falling, and increasing the effectiveness of protective responses through the improvement of muscular strength, balance, coordination, and reaction time. However, some studies suggest that physical activity also may be associated with an increased risk of falling and of fracture, especially in subjects with physical limitations or functional impairments.(36) This could explain our finding that women practicing one physical activity were at higher risk of humeral fracture than women who did not practice any activity at all. These data indicate that physical activity can be hazardous for some subjects and suggest that to ensure safety, some precautions should be taken when designing preventive programs aimed at improving physical activity levels, especially for the elderly with some functional limitation.
To the best of our knowledge, only one other prospective study, the SOF study, examined a large number of fall-related risk factors for proximal humeral fractures, in addition to BMD and other bone-related factors.(11) In this study, no significant association was found between previous falls and risk of humeral fractures. In the multivariate analysis, infrequent walking and poor balance were associated with the risk of humeral fractures, although only at the 10% significance level. An explanation for the difference in findings between EPIDOS and SOF may lie in the different mean age of the two populations (80.5 years vs. 72.0 years for EPIDOS and SOF, respectively). Because the SOF population was almost 10 years younger than ours, its proportion of women who had previously fallen might have been much smaller than in our population. Indeed, the incidence of falls increases almost 2-fold between the 65- and 69-year age group and the group 85 years and older.(37) Furthermore, the authors analyzed only the first 2 years of follow-up and observed only 79 humeral fractures. Thus, they may not have had enough statistical power to show the effect of previous falls and other fall-related variables.
Notably, in our population, age was not associated with the risk of humeral fracture, even in bivariate analysis. This may be caused by the narrow age range and the high mean age of our population (80.5 ± 3.7 years). Indeed, previous incidence studies report that the incidence of proximal humeral fracture in women increases with age after 59 years of age, but tends to reach a plateau around 80 years of age.(38–41)
The second part of our analysis showed that the effect of the fall-related factors varies according to the level of BMD; in women with osteoporosis (T score ≤ −2.5), but not nonosteoporotic women, these factors are significantly associated with an increased risk of humeral fracture. Furthermore, women with osteoporosis but a low fall risk score have a risk of humeral fracture (5.1 per 1000 woman-years) only slightly higher than nonosteoporotic women (4.6 per 1000 woman-years) and comparable with women without osteoporosis but a high fall risk score (5.3 per 1000 woman-years). On the other hand, women who have both type of risk factors have a risk of humeral fracture more than two times higher (12.1 per 1000 woman-years) than women with only one or the two types of risk factor. These results suggest that preventive measures should be targeted in priority to women with both types of risk factors.
The present findings should be interpreted as conditional on a number of potential limitations. First, the participants were volunteers who lived independently at home and probably were healthier than average for their age. Our results may not be applicable to less mobile, less healthy women, such as nursing home residents. On the other hand, mobile women who live independently at home are more likely to participate in preventive programs than their less healthy peers. Second, we included in the analysis all self-reported fractures, even unconfirmed (9% of fractures). In this study, “unconfirmed” fracture means that the hospital or clinics in which the woman received care did not respond to our request of information regarding the fracture. A few hospitals and clinics were not very cooperative and never answered any of our demands. Most unconfirmed cases come from these places. Hence, “unconfirmed” fractures are not necessarily false positives. We rerun the final Cox regression model after excluding unconfirmed fractures, and found similar results than those reported here. Finally, the division of risk factors into bone fragility and fall-related factors is somewhat artificial because some risk factors may be involved both in the risk of falling and in the pathogenesis of bone fragility. Among the factors included in the final regression model, physical activity is the only one that may be difficult to classify. Walking is the activity most frequently reported by EPIDOS participants (70%). Then, comes gymnastics (24%) and gardening (20%). These activities probably are not intense enough to significantly affect bone loss, although their effect may be significant on the long term. Given the age of the population and the type of activities reported, it is likely that the measure of physical activity also reflects ability and physical function, which is influenced by diseases and the aging process and is strongly associated with the risk of falling.(28,29,31,32) It has to be noted that adjustment for BMD and other indicators of bone fragility did not affect significantly the magnitude of the RR associated to the measure of physical activity. This suggests that the association with the risk of fracture may be interpreted as en effect of reduced ability more than the effect of physical inactivity.
In conclusion, our data show that several factors related to bone fragility and to falls increase the risk of humeral fractures in elderly white women living in the community. Furthermore, women who have both a low BMD and a high fall risk score have a particularly high risk of humeral fracture compared with women who have none or only one of these two criteria for high risk. These results suggest that preventive programs should target in priority women with both types of risk factor. Further research to better evaluate common and specific risk factors as well as interactions between the two groups of risk factors for the major osteoporotic fractures would be very useful in helping to establish more complete and effective prevention programs for osteoporotic fractures in the elderly.
The EPIDOS study was supported by INSERM-MSD-Chibret.
- 11991 Which fractures are associated with low appendicular bone mass in elderly women? Ann Intern Med 115:837–842., , , , ,
- 21993 Changing incidence and residual lifetime risk of common osteoporosis-related fractures. Osteoporos Int 3:127–132., , , ,
- 31980 Fractures of the neck of humerus: A review of late results. Injury 12:991–995.
- 41985 Fractures of the proximal humerus in adults. J Trauma 25:801–805.,
- 51997 Incidence and direct medical costs of hospitalisations due to osteoporotic fractures in Switzerland. Osteoporos Int 7:414–425., , , ,
- 61985 Are patients with hip fractures more osteoporotic? Review of evidence. Am J Med 78:487–494.
- 71990 Screening for osteoporosis. Ann Intern Med 112:516–528., ,
- 81987 Heterogeneity of age-related fractures: Implications for epidemiology. Bone Miner 2:321–331.,
- 91996 Fall-related factors and risk of hip fracture: The EPIDOS prospective study. Lancet 348:145–149., , , , , ,
- 10for the Study of Osteoporotic Fractures Research Group 1995 Risk factors for hip fracture in white women. N Engl J Med 332:767–773., , , , , , , ,
- 111992 Risk factors for fractures of the distal forearm and proximal humerus. Am J Epidemiol 135:477–489., , , ,
- 121989 A hypothesis: The causes of hip fractures. J Gerontol Med Sci 44:M107–M111.,
- 131994 Fall severity and bone mineral density as risk factors for hip fracture in ambulatory elderly. JAMA 271:128–133., , , ,
- 142000 The injury mechanism of osteoporotic upper extremity fractures among older adults: A controlled study of 287 consecutive patients and their 108 controls. Osteoporos Int 11:822–834., , , , , ,
- 151993 Type of fall and risk of hip and wrist fractures: The study of osteoporotic fractures. JAGS 41:1226–1234.,
- 161991 Evaluation of the calcium content of diet by frequential self-questionnaire (French). Rev Rhum Mal Osteoartic 58:99–103., , , , , , ,
- 171969 Assessment of older people: Self-maintaining and instrumental activities of daily living. Gerontologist 9:179–86.,
- 181975 A short portable mental status questionnaire for the assessment of organic brain deficit in elderly patients. J Am Geriatr Soc 23:433–441.
- 191996 Ultrasonographic heel measurements to predict hip fracture in elderly women: The EPIDOS prospective study. Lancet 348:511–514., , , , , , , , ,
- 201990 Prediction of hip fracture in elderly women: A prospective study. BMJ 301:638–641., , ,
- 211997 Broadband ultrasound attenuation predicts fractures strongly and independently of densitometry in older women. Arch Intern Med 157:629–634., , , , ,
- 221993 Heritable and life-style determinants of bone mineral density. J Bone Miner Res 8:1–9.,
- 231995 Bone density determinants in elderly women: A twin study. J Bone Miner Res 10:1607–1613., , , , ,
- 241998 Bone mass, lean mass, and fat mass: Same genes or same environments? Am J Epidemiol 147:3–16., , ,
- 251999 Familial resemblance of bone mineral density (BMD) and calcaneal ultrasound attenuation: The BMD in mothers and daughters study. J Bone Miner Res 14:102–110., , , , , ,
- 26for the EPIDOS Group 1998 How hip and whole-body bone mineral density predict hip fracture in elderly women: The EPIDOS prospective study. Osteoporos Int 8:247–254., , , , , , , , , ,
- 27for the EPIDOS group 2000 In elderly women weight is the best predictor of a very low bone mineral density: Evidence from the EPIDOS Study. Osteoporos Int 11:881–888., ,
- 28Kellogg international work group on the prevention of falls in the elderly 1987 The prevention of falls in later life. Dan Med Bull 34(Suppl 4):1–24.
- 291989 Prevention of falls among the elderly. N Engl J Med 320:1055–1059.,
- 301995 Falls in community-dwelling older persons. JAGS 43:1146–1154.,
- 311988 Risk factors for falls among elderly persons living in the community. N Engl J Med 319:1701–1707., ,
- 321989 Risk factors for recurrent nonsyncopal falls: A prospective study. JAMA 261:2663–2668., , ,
- 33for the FICSIT group 1995 The effects of exercise on falls in elderly patients. A preplanned meta-analysis of the FICSIT Trials. JAMA 273:1341–1347., , , , , , , , ,
- 341997 Physical activity and predisposition for hip fractures: A review. Osteoporos Int 7:503–513., ,
- 351998 Physical activity and osteoporotic fracture risk in older women. Ann Intern Med 129:81–88., , , ,
- 361997 Physical activity, functional limitations, and risk of fall-related fractures in community-dwelling elderly. Ann Epidemiol 7:54–61., , , ,
- 371992 Falls and fractures in older women. In: BVellas, MTouper, LRubenstein, JLAlbarède, YChristen (eds.) Falls, Balance and Gait Disorders in the Elderly. Elsevier, Paris, France. pp. 69–80.,
- 381993 Changing incidence and residual lifetime risk of common osteoporosis-related fractures. Osteoporos Int 3:127–132., , , ,
- 391994 Racial differences in fracture risk. Epidemiology 5:42–47., , , , , ,
- 401998 Epidemiology of fractures in 15000 adults. The influence of age and gender. J Bone Joint Surg Br 80:243–248., , ,
- 411996 The incidence of osteoporotic fractures at the university hospital of Tartu, Estonia. Scand J Rheumatol 25(Suppl 103):13–15., ,