Search tips
Search criteria 


Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Osteoporos Int. Author manuscript; available in PMC 2013 September 9.
Published in final edited form as:
PMCID: PMC3767033

Clinical and Demographic Factors Associated with Fractures Among Older Americans



This study investigates the associations of a history of fracture, comorbid chronic conditions, and demographic characteristics with incident fractures among Medicare beneficiaries. The majority of fracture incidence studies have focused on the hip and on white females. This study examines a greater variety of fracture sites and more population subgroups than prior studies.


We used Medicare claims data to examine the incidence of fracture at six anatomic sites in a random 5% sample of Medicare beneficiaries during the time period 2000 through 2005.


For each type of incident fracture, women had a higher rate than men, and there was a positive association with age and an inverse association with income. Whites had a higher rate than nonwhites. Rates were lowest among African Americans for all sites except ankle and tibia/fibula, which were lowest among Asian Americans. Rates of hip and spine fracture were highest in the South, and fractures of other sites were highest in the Northeast. Fall-related conditions and depressive illnesses were associated with each type of incident fracture, conditions treated with glucocorticoids with hip and spine fractures and diabetes with ankle and humerus fractures. Histories of hip and spine fractures were associated positively with each site of incident fracture except ankle; histories of nonhip, nonspine fractures were associated with most types of incident fracture.


This study confirmed previously established associations for hip and spine fractures and identified several new associations of interest for nonhip, nonspine fractures.

Keywords: epidemiology, fractures, osteoporosis, incidence, Medicare


Prospective cohort studies indicate that the incidence of fragility fractures increases with age (13), is higher among women than men (27), and is higher among whites than other ethnic sub-groups (8, 9). Other risk factors include low bone mineral density (10, 11), history of prior fracture (1215), history of falls (16), chronic medical conditions including diabetes (16), renal disease (17), depressive illness (18), low body weight (19), and use of certain medications (e.g., glucocorticoids) (20). Much of this research has concentrated on hip fractures. Vertebral fractures have been less well-studied, and data on the incidence of nonhip, non-vertebral fractures are relatively sparse (21).

Medicare beneficiaries have a high risk of fragility fractures due to age. Research using Medicare claims data has estimated the incidence of fractures at various anatomic sites by age, race, and sex (4, 2224) and by geographic region (2528). Several other studies have evaluated a single fracture site (2932). Studies of potential risk factors for fractures among Medicare beneficiaries have been limited to demographic factors, to a single clinical risk factor or to special populations, such as nursing facility patients (3342). No study of Medicare beneficiaries has used nationwide data to analyze the relation between multiple clinical factors and the incidence of fractures at various sites.

We used recent Medicare claims data to examine the incidence of fracture at six anatomic sites in a sample of beneficiaries. The use of Medicare claims offers two distinct advantages. First, we are able to examine differences in fracture incidence by detailed population subgroups, including Asian- and Hispanic-Americans. Second, longitudinal claims data allow us to examine the association between prior fractures and chronic conditions and site-specific fracture incidence.


Study design and data sources

We conducted a retrospective cohort study using claims from 2000 through 2005 for a 5% random sample of Medicare beneficiaries, obtained from the Center for Medicare and Medicaid Services (CMS) Chronic Condition Warehouse (43). The data consisted of beneficiaries' claims for all Medicare covered services and included International Classification of Diseases, Ninth Revision (ICD-9) diagnosis and procedure codes, as well as Healthcare Common Procedure Coding System (HCPCS) codes indicating surgical, diagnostic or other medical procedures performed. We used the Medicare data to identify cohorts at risk of developing fractures at six of the most common fracture sites among older adults (spine, hip, distal radius/ulna, tibia/fibula, humerus and ankle) and to identify incident cases of these fractures. The study protocol was approved by the Institutional Review Board at the University of Alabama at Birmingham and by CMS.


We studied a “baseline” cohort of beneficiaries who had fee-for-service coverage continuously for at least 13 months, were included in the 5% national sample, were 65 years of age or older as of their first month of coverage and lived in the fifty States or the District of Columbia. In order to minimize missing data and to ensure completeness of beneficiary data/case ascertainment, we excluded beneficiaries without both Medicare Parts A and B coverage and those enrolled in a Medicare Advantage plan at any time during the observation period. This restriction was necessary because medical care transactions for these beneficiaries may not be reported completely to CMS.

For the analysis of each specific fracture site, we further restricted the baseline cohort to beneficiaries who did not have any claim for that particular fracture during their first 12 months of Medicare coverage. We applied this restriction in order to avoid misclassification of prevalent fractures as incident fractures. Follow-up of beneficiaries began at the start of the thirteenth month of continuous enrollment in Medicare. Follow-up continued until the occurrence of the first fracture of the site being analyzed, loss of full Medicare coverage, death or December 31, 2005, which ever was earliest.

Incident fractures

We identified incident fractures using ICD-9 diagnosis codes and HCPCS procedure codes specific to the particular fracture sites. Similar approaches have been used and validated by other investigators (4, 23, 44, 45). A “qualifying” claim for an incident fracture had to occur on or after the follow-up start date and before the end of the study period and had to be one of the following: 1) an inpatient hospital claim with a discharge diagnosis of the specific fracture (for spine fractures, we counted only primary diagnoses; for other fractures, we counted both primary and secondary diagnoses); 2) a physician or outpatient hospital claim for the fracture diagnosis code accompanied by a HCPCS code for a site-specific fracture repair; or 3) for spine fractures only, a physician evaluation and management claim with a spine fracture diagnosis code, plus, up to 10 days earlier, a HCPCS code for spine imaging (45). We selected fracture sites for inclusion in the analysis based on frequency of their occurrence in the Medicare data. Our fracture identification algorithms are available upon request.

Independent variables

Medical variables analyzed for possible associations with fracture included indicators for previous fractures at specific sites and comorbid chronic conditions, including glucocorticoid-related and fall-related (predisposing to falls) conditions, diabetes, renal disease, depressive illness, acute myocardial infarction, other heart disease, bone disease and cancer. The Appendix provides the ICD-9 diagnosis codes used to identify the chronic conditions. Glucocorticoid-related conditions included illnesses for which glucocorticoid medications typically are prescribed; we did not have data on actual medication use. Each claims-based medical history variable was treated as time-dependent and was measured on a monthly basis. In order to avoid misclassifying fractures and chronic conditions diagnosed concurrently with an incident fracture as medical history, in each month of follow-up we counted only those claims occurring at least three months earlier. We classified a beneficiary as having a history of the other chronic conditions if the beneficiary's inpatient, outpatient hospital or physician claims records included at least one claim with an ICD-9 code pertaining to the condition (see Appendix).

Demographic variables analyzed for possible associations with fracture were age, gender, race, urban or nonurban residence, geographic region and income. We analyzed age as of the start of follow-up and also as a time-varying covariate, using categories of 65–69, 70–74, 75–79, 80–84 and 85+ years. Categories of self-reported race/ethnicity were white (referent group), African-American, Asian-American, Hispanic-American and other. These data did not allow classification of the Hispanic-American population by race. We included Native Americans in the “other” category due to small numbers. We determined urban v. nonurban residential status by linking beneficiaries' nine-digit ZIP Codes to the rural-urban commuting area code for the corresponding census blockgroup (46, 47). We also used beneficiaries' ZIP Codes to assign them to one of four United States (US) Census Bureau-defined geographic regions: Northeast (referent group), Midwest, West or South. We assigned each beneficiary to an income category (<$30,000 (referent group), $30,000 to <$45,000, $45,000 to <$60,000, $60,000 to <$75,000 and $75,000 or more) by linking his or her census block group of residence (based on the nine-digit ZIP Code) to the Census 2000 median income data (48).

Statistical analysis

Descriptive analyses of the baseline cohort included frequency distributions and median values, where appropriate, for each demographic variable. We used Poisson regression to estimate adjusted rate ratios (RRs) and 95% confidence intervals (CIs) for each type of incident fracture, for the entire cohort and separately for women and men. The analytic approach allowed a person with a first fracture at a particular anatomic site to be eligible for subsequent fractures at other anatomic sites but not at the same site. RRs for each time-dependent medical history variable were adjusted for all demographic variables, as well as for all of the other medical history variables. We also performed an analysis stratified according to reported history of osteoporosis or osteopenia. A history of osteoporosis or osteopenia may have implications for a fracture being considered osteoporotic, particularly as we have not excluded fractures due to high trauma. Analyses were performed using SAS (SAS Institute, Inc., Cary, NC). We present results in tabular form for the entire cohort of women and men, combined, and mention gender-specific results in the text only when findings differed for women and men. Because of the large size of the study, conventional statistical significance was not a useful criterion for identifying results of potential interest. Thus, we focused instead on statistically significant results that had an RR of at least 1.2 or less than 0.9, both for women and for men.


The baseline cohort of 1,694,051 eligible beneficiaries was 58% women and 88% white and had a median age 72 years (Table 1). The median income in the census blocks where beneficiaries lived was $40,541 in 2000 dollars. About 73% of subjects began follow-up in 2000. Women and men were similar with regard to demographic variables. For each cohort, the average amount of follow-up was 4.2 person-years.

Table 1
Baseline cohort characteristics; Medicare beneficiaries, 2000–2005

The number of incident fractures by site was largest for hip (N=60,354), followed by spine (N=44,075), distal radius/ulna (N=24,655), humerus (N=19,393), ankle (N=13,454) and tibia/fibula (N=6,385) (Table 2). The positive association with age was strongest for hip and spine fractures, intermediate for distal radius/ulna, humerus and tibia/fibula fractures and weakest for ankle fracture.

Table 2
Fracture incidence rate ratio* (and 95% confidence interval) for demographic variables, by type of fracture; Medicare beneficiaries, 2000–2005

Men had a lower rate of each type of fracture than women. Median household income was associated inversely with the incidence of all six fracture types. Nonurban/urban residence was largely unassociated with incident fractures. Hip and spine fracture rates were highest in the South, whereas rates of the other four types of fracture were highest in the Northeast. Hip fracture was the only type of fracture displaying a trend of decreasing incidence over the six-year study period, and spine fracture was the only fracture for which the incidence appeared to increase during the study years. Asian, African, and Hispanic-Americans showed lower fracture incidence than white Americans for all sites, and Asian and African-Americans showed lower incidence than Hispanic-Americans for all sites. For fractures of the ankle and the tibia/fibula, incidence was lowest among Asian-Americans. For fractures of the hip, spine, distal radius/ulna, and humerus, incidence was lowest among African-Americans. Histories of hip and closed spine fractures were associated with each incident fracture site except ankle (Table 3). RRs for positive associations with a history of hip fracture ranged from 1.33 for incident distal radius/ulna fracture to 1.75 for incident tibia/fibula fracture. RRs for positive associations with a history of closed spine fracture ranged from 1.38 for incident distal radius/ulna fracture to 1.63 for incident hip fracture. For incident ankle fracture, a history of hip fracture was protective (RR=0.86), and there was no association with a history of spine fracture. History of fractures at nonhip, nonspine sites were associated positively with most types of incident fracture, although associations tended to be weaker and less consistent for histories of carpal bone, femur (other than hip) and ankle fractures than for other nonhip, nonspine sites.

Table 3
Fracture incidence rate ratio* (and 95% confidence interval) for predisposing factors, by type of fracture; Medicare beneficiaries, 2000–2005

A history of glucocorticoid-related conditions was associated weakly with each type of incident fracture, but spine was the only incident fracture site for which the RR was at least 1.2 among both women (RR=1.44) and men (RR=1.54) (Table 3). Fall-related conditions and depressive illnesses were associated with an RR of at least 1.2 for each type of incident fracture. Diabetes was associated positively with ankle and humerus fractures. Other positive associations reported in Table 3 were inconsistent for women and men.


Compared with previous research on fractures among Medicare beneficiaries, our study examined a more recent time period, focused on minority and ethnic populations, and assessed a broader range of potential risk factors in relation to greater variety of nonhip, nonspine fracture sites. In particular, our assessment of income, fracture history and history of individual comorbid conditions as potential risk factors for incident fractures among Medicare beneficiaries is novel. The following discussion concentrates on several interesting associations emerging from these new analyses, including those pertaining to income and to history of prior fractures, diabetes, conditions for which glucocorticoid medications are prescribed and depressive illnesses.

We observed a decrease in hip fracture incidence and an increase in spine facture incidence over the six-year study period. A possible reason for the decrease in hip fractures, which has also been reported recently in another US study (49), and a Canadian study (50), is better screening and rates of treatment. It is possible that the apparent increase in spine fracture is attributable to improved detection and/or reporting, through both increased awareness of osteoporosis and increased screening.

We found an inverse relationship between median household income in a beneficiary's census block group, a proxy measure of socioeconomic status (SES), and incidence of each fracture. This relationship has been investigated previously in the US only for hip fracture, with results similar to ours (38, 51, 52). SES affects the likelihood of receiving screening and preventive services, medication adherence and overall health status. Thus, our finding underscores the need for targeted fracture interventions.

Prior fracture is a significant predictor of subsequent fracture among older adults (12, 13, 16, 5359). In our study of Medicare beneficiaries, histories of typical osteoporotic fractures (hip, spine and distal radius/ulna) were associated positively and consistently with the incidence of each of the six fracture types analyzed, except for ankle fracture. Furthermore, prior fractures at most traditionally understudied, nonhip, nonspine sites, were associated positively and consistently for women and men with the incidence of traditional fragility fracture incidence sites (hip, distal radius/ulna and spine), as well as with fractures of the humerus and tibia/fibula. Among the nonhip, nonspine sites examined as prior history risk factors, associations were least consistent across the incident fracture sites for history of ankle, carpal bone and femur (other than hip) fractures than for history of other nonhip, nonspine sites – results consistent with previous research. In our study, a history of hip fracture was protective for incident ankle fracture. We speculate that this unexpected result might be due to lower mobility following a hip fracture and the consequent limited opportunity to sustain an ankle fracture.

Others have reported an association between depressive illnesses and fracture (60). Depressive illnesses are associated with many chronic conditions and may constitute a component of an overall frailty syndrome (61). In addition, depressive illnesses are often treated with anti-depressants and sedatives, which increase the risk of falls (62). Furthermore, depressive illnesses have been independently associated with both low bone mineral density (63) and with fragility fractures (60). In our study group, the most common depressive illnesses were depressive disorders not elsewhere classified, neurotic depression, major depressive disorders and senile dementia depression.

We observed that a history of glucocorticoid-related conditions was associated weakly with all fracture types, but the relationship was characterized by an RR of at least 1.2 for both women and men only for spine fracture. These results are consistent with past research showing that long-term glucocorticoid use consistently leads to secondary, medication-induced osteoporosis and increased fracture risk, particularly for sites of trabecular bone such as the spine and hip (20, 53). It was somewhat surprising that our study found an RR as high as 1.47 for glucocorticoid-related conditions and spine fracture, given the relatively large amount of misclassification for this type of fracture (45), as well as the misclassification and diversity of the conditions presumed to be treated with glucocorticoids, the most common of which in our study group were chronic obstructive pulmonary disease, chronic bronchitis, asthma, rheumatoid arthritis and emphysema.

Previous studies of the relationship between diabetes and fractures have reported positive associations for fractures of the ankle (64, 65) and humerus (66, 67) that are consistent with our results. In contrast to previous research (68), we did not find an increased rate of hip fracture among people with a history of diabetes. Possible reasons for our null results include bias towards the null due to misclassification and our inability to analyze time since diagnosis and severity of diabetes. Multiple mechanisms by which diabetes may increase the risk of fracture have been proposed (69). Although diabetes is associated with higher bone mineral density, bone mineral density measurements may not fully reflect bone strength (69), and Thrailkill et al.(70) have suggested that insulin has an anabolic effect. Reduced skeletal load, which may result from physical inactivity often associated with diabetes, may decrease bone strength (71), and diabetic complications such as retinopathy, peripheral neuropathy and renal insufficiency, increase the risk of falls.

A history of fall-related conditions was associated positively with all six incident fracture sites. Falls are strongly associated with fractures (72), and a number of conditions predispose older Americans to falls, the most common of which in our analysis were history of overall body weakness and fatigue, stroke, senile and presenile organic psychotic conditions, Alzheimer's disease and previous accidental falls.

With regard to commonly analyzed demographic factors, our findings support those of other studies of fracture incidence among Medicare beneficiaries. For example, earlier studies of Medicare beneficiaries noted that hip fracture rates were highest in the South (25) or Southeast (28, 31, 73), that rates of hip, spine and nonhip/nonspine fractures were higher for whites than for blacks (8, 9, 22, 44) and that rates of most fractures were higher for women compared to men (4). Our finding of a higher incidence of clinical spine fractures in the South has not previously been reported, and it could represent true variation in fracture incidence or variation due to differences in detection.

Asian, African and Hispanic-Americans had lower incidence rates than white Americans for all fracture sites. Consistent with other studies (9), we found that African-Americans had the lowest rate of hip fracture. However, Asian-Americans had the lowest rate of ankle and tibia/fibula fracture, a finding not previously reported. Asian-American women have relatively low bone mineral density compared to white women (9, 74, 75) and women of other racial and ethnic groups (9, 74), and Asian descent is often listed as a risk factor for osteoporosis (76). However, studies examining hip fracture by race have found lower fracture rates among Asian than white Americans (9, 33, 77). A reason hypothesized for the lower rate of hip fracture among Asian-Americans is a difference in hip geometry (74, 78, 79). This may not explain the lower fracture rates for other anatomic sites. Several studies have reported hip fracture incidence rates for Hispanic-Americans greater than for African-Americans but less than those for white Americans (9, 34). Our findings support those for hip, and we found this relationship to hold true for all other fracture sites examined. Lauderdale et al. (34) found marked differences in hip fracture rates among different Hispanic subpopulations, suggesting that considerable heterogeneity may be masked by our analysis of the Hispanic population in aggregate.

Our results for ankle fracture differed from those for other fracture sites, suggesting, as reported by others, that determinants of ankle fracture may differ from those of other fractures (8, 80), including foot fracture (81). Among our findings for ankle fracture are associations with history of fracture of the distal radius/ulna, other radius/ulna, humerus, femur and tibia/fibula. Others have reported a lack of association between bone mineral density and ankle fracture (8082) and, consistent with our findings, no clear effect of age (81). The extent to which osteoporosis may contribute to ankle fracture remains unresolved and must be disentangled from the role of trauma, diabetes, overweight and obesity, and other health conditions.

Our results add to ongoing deliberations about which fractures may be considered osteoporosis-related (4). To the extent that observation of an increasing incidence of a fracture site with increasing age and a positive association with a history of prior fractures (especially those of the hip and spine) suggest that the fracture is attributable to osteoporosis, our results support an attribution to osteoporosis for fractures of the hip, spine, distal radius/ulna, humerus and tibia/fibula, but not for fracture of the ankle.

Our study has several strengths. Our large sample, including large numbers of racial and ethnic minorities, allowed us to evaluate fracture incidence for Hispanic and Asian-Americans, to examine the association between several chronic conditions, as well as a broad range of previous fractures, and specific incident fracture sites.

Use of Medicare claims data has inherent limitations (30, 83, 84). These include lack of information on medications, severity of the associated comorbidities, lifestyle factors, body composition of the patient and radiographic or clinical test results, as well as inaccuracies and inconsistencies in data coding by medical providers. Despite our efforts to address these limitations through the development of comprehensive algorithms for identification of fractures and through the use of diagnosis codes to identify people who potentially have comorbidities, some misclassification may remain, leading to the underestimation of associations. Misclassification of race and ethnicity in the Medicare claims data may have resulted in undercounting of minority populations, particularly self-reported Hispanic-Americans (85). Additionally, in interpreting the observed associations, the possible effect of multiple comparisons must be taken into consideration.

Because we did not have medication information, we used disease conditions for which glucocorticoids medications are prescribed as a proxy for actual use of these medications. This approach did not allow us to estimate the independent effects of these diseases and their treatments. The use of Medicare prescription drug data, available beginning in 2006, to examine these associations may be a useful direction for future research.

This study contributes to the understanding of patterns of osteoporosis-related fractures and of population groups at high risk for fracture, essential both to informing clinical practice and to targeting interventions. Targeted interventions addressing the risk of specific fractures should be developed for Americans of lower SES, those residing in the Southern US, and those with histories of conditions pre-disposing them to falls, conditions for which glucocorticoid medications are prescribed, depression, diabetes, renal disease, cancer, and those having sustained previous fractures. Additionally, our results suggest that the definition of osteoporosis-related fractures be expanded to include fractures having incidence rates that increase with age and those associated with increased risk of subsequent fracture.

Supplementary Material


This research was supported by a contract between UAB and Amgen, Inc. Only the authors from UAB had access to the Medicare data used. The analysis, presentation and interpretation of the results were solely the responsibility of the authors. Some of the investigators (JRC, KGS) also receive salary support from the National Institutes of Health (AR053351, AR052361), the Agency for Healthcare Research and Quality (U18 HS016956), and the Arthritis Foundation (JRC). Two investigators received research support from Novartis, Merck, Eli Lilly, Amgen (JRC, KGS) and Procter & Gamble (JRC), in a consulting and/or advisory board role for Procter & Gamble (JRC), Novartis, Merck, Eli Lilly, and Amgen (KGS) and as members of the speakers bureau for Novartis (JRC, KGS) and for Procter & Gamble and Eli Lilly (JRC). Should Osteoporosis International request the data upon which this manuscript is based, we will share that data in a format consistent with the Center for Medicare and Medicaid Services (CMS) privacy rules, including suppression of cell sizes ≤10.


Table A

Other Medical Conditions: Categories and Codes

Condition CategoryCode(s)
Glucocorticoid-related (summary indicator)
 COPD, asthma491, 492, 493, 494, 496
 Rheumatoid arthritis714
 Polymyalgia rheumatica725
 Pemphigus694.4, 694.5, 694.6
 Systemic lupus erythematosus710.0
 Inflammatory myopathy710.3, 710.4
 Multiple sclerosis340
 Myasthenia gravis358.0
 Inflammatory bowel disease, Crohn's disease555, 556
 Wegener granulomatosis446.4
 Giant cell arteritis446.5
 Cushing's disease255.0
 Ankylosing spondylitis720.0
 Psoriatic arthritis (Psoriatic arthropathy)696.0
 Reactive arthritis / Reiter's099.3
Bone Disease-Related
 Paget's disease of bone731.0
Osteoporosis / Osteopenia733.0, 733.90
Diabetes mellitus250
Renal Disease
 Nephrotic syndrome581
 Other specified disorders resulting from impaired
renal function
585, 586, 588.8
Other Bone Mass-Related
 Ectopic hormone secretion259.3
 Tobacco addiction305.1
Fall Related Conditions
 Stroke430, 431, 432, 433, 434, 436
 Transient ischemic attack (TIA)435
 Convulsions780.31, 780.39
 Accidental fallsE880-E888
 Senile and presenile organic psychotic conditions290
 Drug-induced dementia292.82
 Alzheimer's, Parkinson's, Huntington's
(Neurological disorder, including all ICDs starting
with substrings 331, 332 or 333)
331, 332, 333
 General paresis094.1
 Dementia in conditions classified elsewhere294.1
 Disorders of the autonomic nervous system337
 Overall body weakness and fatigue780.79
Cancer140–<209 except 173, V10
Acute myocardial infarction410, 412
Other heart conditions398, 402, 404, 415, 425.4, 428, 429.4
Depressive illness290.13, 290.21, 290.43, 292.84,
293.83, 295.70–295.75, 296.20–296.26,
296.50–296.56, 296.60–296.66, 296.7,
296.80, 296.82,
296.89, 296.90, 296.99, 298.0, 300.4,
300.5, 301.10,
301.12, 301.13, 309.0, 309.1, 311


1. Melton LJ. Epidemiology of hip fractures: implications of the exponential increase with age. Bone. 1996;18:121S–125S. [PubMed]
2. Felsenberg D, Silman AJ, Lunt M, Armbrecht G, Ismail AA. Incidence of vertebral fracture in Europe: results from the European Prospective Osteoporosis Study (EPOS) J Bone Miner Res. 2002;17:716–724. [PubMed]
3. Chang KP CJ, Nguyen TV. Incidence of hip and other osteoporotic fractures in elderly men and women: Dubbo Osteoporosis Epidemiology Study. J Bone Miner Res. 2004;19:532–536. [PubMed]
4. Baron JA, Karagas M, Barrett J, Kniffin W, Malenda D, Mayor M, Keller RB. Basic epidemiology of fractures of the upper and lower limb among Americans over 65 years of age. Epidemiology. 1996;7:612–618. [PubMed]
5. van Staa TP, Dennison EM, Leufkens HG, Cooper C. Epidemiology of fractures in England and Wales. Bone. 2001;29:517–522. [PubMed]
6. Jones G, Nguyen T, Sambrook PN, Kelly PJ, Gilbert C, Eisman JA. Symptomatic fracture incidence in elderly men and women: the Dubbo Osteoporosis Epidemiology Study (DOES) Osteoporos Int. 1994;4:277–282. [PubMed]
7. Sanders KM, Seeman E, Ugoni AM, Pasco JA, Martin TJ, Skoric B, Nicholson GC, Kotowicz MA. Age- and gender-specific rate of fractures in Australia: a population-based study. Osteoporos Int. 1999;10:240–247. [PubMed]
8. Baron JA, Barrett J, Malenka D, Fisher E, Kniffin W, Bubolz T, Tosteson T. Racial differences in fracture risk. Epidemiology. 1994;5:42–47. [PubMed]
9. Barrett-Connor E, Siris ES, Wehren LE, Miller PD, Abbott TA, Berger ML, Santora AC, Sherwood LM. Osteoporosis and fracture risk in women of different ethnic groups. J Bone Miner Res. 2005;20:185–194. [PubMed]
10. Cauley JA, Lui LY, Ensrud KE, Zmuda JM. Bone mineral density and the risk of incident nonspinal fractures in black and white women. JAMA. 2005;293:2102–2108. [PubMed]
11. Stone KL, Seeley DG, Lui LY, Cauley JA, Ensrud K, Browner WS, Nevitt MC, Cummings SR. BMD at multiple sites and risk of fracture of multiple types: long-term results from the Study of Osteoporotic Fractures. J Bone Miner Res. 2003;18:1947–1954. [PubMed]
12. Klotzbuecher CM, Ross PD, Landsman PB, Abbott TA, Berger M. Patients with prior fractures have an increased risk of future fractures: A summary of the literature and statistical synthesis. J Bone Miner Res. 2000;15:721–739. [PubMed]
13. Kanis JA, Johnell O, De Laet C, Johansson H, Oden A, Delmas P, Eisman J. A meta-analysis of previous fracture and subsequent fracture risk. Bone. 2004;35:375–382. [PubMed]
14. Nguyen ND, Pongchaiyakul C, Center JR, Eisman JA, Nguyen TV. Identification of high-risk individuals for hip fracture: a 14-year prospective study. J Bone Miner Res. 2005;20:1921–1928. [PubMed]
15. LaFleur J, McAdam-Marx C, Kirkness C, Brixner DI. Clinical risk factors for fracture in postmenopausal osteoporotic women: a review of the recent literature. Ann Pharmacother. 2008;42:375–386. [PubMed]
16. Cummings SR, Melton LJ. Epidemiology and outcomes of osteoporotic fractures. The Lancet. 2002;359:1761–1767. [PubMed]
17. Nickolas TL, Leonard MB, Shane E. Chronic kidney disease and bone fracture: a growing concern. Kidney Int. 2008;74:721–731. [PubMed]
18. Whooley MA, Kip KE, Cauley JA, Ensrud KE, Nevitt MC, Browner WS, Study of Osteoporotic Fractures Research Group Depression, falls, and risk of fracture in older women. Arch Intern Med. 1999;159:484–490. [PubMed]
19. De Laet C, Kanis JA, Oden A, Johanson H, Johnell O. Body mass index as a predictor of fracture risk: a meta-analysis. Osteoporos Int. 2005;16:1330–1338. [PubMed]
20. Kanis JA, Johansson H, Oden A JO, de Laet C, Melton LJ, III, Tenenhouse A, Reeve J, Silman AJ, Pols HA, Eisman JA, McCloskey EV, Mellstrom D. A meta-analysis of prior corticosteroid use and fracture risk. J Bone Miner Res. 2004;19:893–899. [PubMed]
21. Delmas PD, Marin F, Marcus R, Misurski DA, Mitlak BH. Beyond hip: importance of other nonspinal fractures. Am J Med. 2007;120:381–387. [PubMed]
22. Griffin MR, Ray W, Fought RL, Melton JL. Black-white differences in fracture rates. Am J Epidemiol. 1992;136:1378–1385. [PubMed]
23. CDC Incidence and costs to Medicare of fractures among Medicare beneficiaries aged > or = 65 years--United States, July 1991-June 1992. MMWR. 1996;45:877–883. [PubMed]
24. Brauer CA, Coca-Perraillon M, Cutler DM, Rosen AB. Incidence and mortality of hip fractures in the United States. JAMA. 2009;302:1573–1579. [PubMed]
25. Stroup NE, Freni-Titulaer LWJ, Schwartz JJ. Unexpected geographic variation in rates of hospitalization for patients who have fracture of the hip. J Bone Joint Surg Am. 1990;72:1294–1298. [PubMed]
26. Karagas MR, Baron JA, Barrett JA, Jacobsen SJ. Patterns of fracture among the United States elderly: geographic and fluoride effects. Ann Epidemiol. 1996;6:209–216. [PubMed]
27. Lauderdale DS, Thisted RA, Goldberg J. Is geographic variation in hip fracture rates related to current or former region of residence? Epidemiology. 1998;9:574–577. [PubMed]
28. Sporer SM, Weinstein JN, Koval KJ. The geographic incidence and treatment variation of common fractures of elderly patients. J Am Acad Orthop Surg. 2006;14:246–255. [PubMed]
29. Jacobsen SJ, Goldberg J, Miles TP, Brody JA, Stiers W, Rimm AA. Regional variation in the incidence of hip fracture. US white women aged 65 years and older. JAMA. 1990;264:500–502. [PubMed]
30. Jacobsen SJ, Cooper C, Gottlieb MS, Goldberg J, Yahnke DP, Melton LJ., 3rd Hospitalization with vertebral fracture among the aged: a national population-based study, 1986–1989. Epidemiology. 1992;3:515–518. [PubMed]
31. Hinton RY, Lennox DW, Ebert FR, Jacobsen SJ, Smith GS. Relative rates of fracture of the hip in the United States. Geographic, sex, and age variations. Bone Joint Surg Am. 1995;77:695–702. [PubMed]
32. Koval KJ, Lurie J, Zhou W, Sparks MB, Cantu RV, Sporer SM, Weinstein J. Ankle fractures in the elderly: what you get depends on where you live and who you see. J Orthop Trauma. 2005;19:635–639. [PubMed]
33. Lauderdale DS, Jacobsen SJ, Furner SE, Levy PS, Brody JA, Goldberg J. Hip fracture incidence among elderly Asian-American populations. Am J Epidemiol. 1997;146:502–509. [PubMed]
34. Lauderdale DS, Jacobsen SJ, Furner SE, Levy PS, Brody JA, Goldberg J. Hip fracture incidence among elderly Hispanics. Am J Public Health. 1998;88:1245–1247. [PubMed]
35. Yuan Z, Dawson N, Cooper GS, Einstadter D, Cebul R, Rimm AA. Effects of alcohol-related disease on hip fracture and mortality: a retrospective cohort study of hospitalized Medicare beneficiaries. Am J Public Health. 2001;91:1089–1093. [PubMed]
36. Sugarman JR, Connell FA, Hansen A, Helgerson SD, Jessup MC, Lee H. Hip fracture incidence in nursing home residents and community-dwelling older people, Washington State, 1993–1995. J Am Geriatr Soc. 2002;50:1638–1643. [PubMed]
37. Colón-Emeric CS, Biggs DP, Schenck AP, Lyles KW. Risk factors for hip fracture in skilled nursing facilities: who should be evaluated? Osteoporos Int. 2003;14:484–489. [PubMed]
38. Lamont EB, Lauderdale DS. Low risk of hip fracture among elderly breast cancer survivors. Ann Epidemiol. 2003;13:698–703. [PubMed]
39. Baxter NN, Habermann EB, Tepper JE, Durham SB, Virnig BA. Risk of pelvic fractures in older women following pelvic irradiation. JAMA. 2005;294:2587–2593. [PubMed]
40. Gage BF, Birman-Deych E, Radford MJ, Nilasena DS, Binder DF. Risk of osteoporotic fracture in elderly patients taking warfarin. Arch Intern Med. 2006;166:241–246. [PubMed]
41. Liperoti R, Onder G, Lapane KL, Mor V, Friedman JH, Bernabei R, Gambassi G. Conventional or atypical antipsychotics and the risk of femur fracture among elderly patients: results of a case-control study. J Clin Psychiatry. 2007;68:929–934. [PubMed]
42. Lyles KW SA, Colón-Emeric CS. Hip and other osteoporotic fractures increase the risk of subsequent fractures in nursing home residents. Osteoporos Int. 2008;19:1225–1233. [PMC free article] [PubMed]
43. Buccaneer Computer Systems and Services, Inc Chronic Condition Data Warehouse User Manual. 2008 Available from:
44. Ray WA, Griffin MR, Fought RL, Adams ML. Identification of fractures from computerized Medicare files. J Clin Epidemiol. 1992;45:703–714. [PubMed]
45. Curtis JR, Mudano A, Solomon DH, Kim Y, Saag KG. Identifying clinical vertebral fracture using administrative claims data: a validation study. J Bone Miner Res. 2007;22:S199. Abstract M354.
46. Morrill R, Cromartie J, Hart LG. Metropolitan, urban, and rural commuting area: toward a better depiction of the U.S. settlement system. Urban Geogr. 1999;20:727–748.
47. Rural-Urban Commuting Area Codes WWAMI Rural Health Research Center. Available from:
48. U.S. Census Bureau Census 2000 Summary File 3 (SF 3) - Sample Data. In.
49. Brauer CA, Coca-Perraillon M, Cutler DM, Rosen AB. Incidence and mortality of hip fractures in the United States. JAMA. 2009;302:1573–1579. [PubMed]
50. Leslie WD, O'Donnell S, Jean S, Lagace C, Walsh P, Bancej C, Morin S, Hanley DA, Papaioannou A. Trends in hip fracture rates in Canada. JAMA. 2009;302:883–889. [PubMed]
51. Zingmond DS, Soohoo NF, SL S. The role of socioeconomic status on hip fracture. Osteoporos Int. 2006;17:1562–1568. [PubMed]
52. Bacon WE, Hadden WC. Occurrence of hip fractures and socioeconomic position. J Aging Health. 2000;12:193–203. [PubMed]
53. van Staa TP, Leufkens HGM, Cooper C. The epidemiology of corticosteroid-induced osteoporosis: a metaanalysis. Osteoporos Int. 2002;10:777–787. [PubMed]
54. Ismail AA, Cockerill W, Cooper C, Finn JD, Abendroth K, Parisi G, Banzer D, Benevolenskaya LI, Bhalla AK, Armas JB, Cannata JB, Delmas PD. Prevalent vertebral deformity predicts incident hip though not distal forearm fracture: Results from the European Prospective Osteoporosis Study. Osteoporos Int. 2001;12:85–90. [PubMed]
55. Cuddihy MT, Gabriel SE, Crowson CS, O'Fallon WM, Melton LJ., 3rd Forearm fractures as predictors of subsequent osteoporotic fractures. Osteoporos Int. 1999;9:469–475. [PubMed]
56. Melton LJ, AEJ, Cooper C, O'Fallon WM, Riggs BL. Vertebral fractures predict subsequent fractures. Osteoporos Int. 1999;10:214–221. [PubMed]
57. Black DM, Arden NK, Palermo L, Pearson J, Cummings SR. Prevalent vertebral deformities predict hip fractures and new vertebral deformities but not wrist fractures. Study of Osteoporotic Fractures Research Group. J Bone Miner Res. 1999;14:821–828. [PubMed]
58. Davis JW, Grove JS, Wasnich RD, Ross PD. Spatial relationships between prevalent and incident spine fractures. Bone. 1999;24:261–264. [PubMed]
59. Ross PD, Genant HK, Davis JW, Miller PD, Wasnich RD. Predicting vertebral fracture incidence from prevalent fractures and bone density among non-black, osteoporotic women. Osteoporos Int. 1993;3:120–126. [PubMed]
60. Mezuk B, Eaton W, Golden SH. Depression and osteoporosis: epidemiology and potential mediating pathways. Osteoporos Int. 2008;19:1–12. [PMC free article] [PubMed]
61. Rolland Y, Abellan van Kan G, Benetos A, Blain H, Bonnefoy M, Chassagne P, Jeandel C, Laroche M, Nourhashemi F, Orcel P, Piette F, Ribot C, Ritz P, Roux C, Taillandier J, Tremollieres F, Weryha G, Vellas B. Frailty, osteoporosis and hip fracture: causes, consequences and therapeutic perspectives. J Nutr Health Aging. 2008;12:335–346. [PubMed]
62. Liu B, Anderson G, Mittmann N, To T, Axcell T, Shear N. Use of selective serotonin-reuptake inhibitors of tricyclic antidepressants and risk of hip fractures in elderly people. Lancet. 1998;351:1303–1307. [PubMed]
63. Robbins J, Hirsch C, Whitmer R, Cauley J, Harris T. The association of bone mineral density and depression in an older population. J Am Geriatr Soc. 2001;49:732–736. [PubMed]
64. Bonds DE, Larson JC, Schwartz AV, Strotmeyer ES, Robbins J, Rodriguez BL, Johnson KC, Margolis KL. Risk of fracture in women with type 2 diabetes: the Women's Health Initiative Observational Study. J Clin Endocrinol Metab. 2006;19:3404–3410. [PubMed]
65. Holmberg AH, Johnell O, Nilsson PM. Risk factors for fragility fracture in middle age. A prospective population-based study of 33,000 men and women. Osteoporos Int. 2006;17:1065–1077. [PubMed]
66. Schwartz A, Sellmeyer D, Ensrud K. Older women with diabetes have an increased risk of fracture: a prospective study. J Clin Endocrinol Metab. 2001:32–38. [PubMed]
67. Vestergaard P. Discrepancies in bone mineral density and fracture risk in patients with type 1 and type 2 diabetes-a meta-analysis. Osteoporos Int. 2007;81:427–444. [PubMed]
68. Janghorbani M, Van Dam RM, Willett WC, Hu FB. Systematic review of Type 1 and Type 2 diabetes mellitus and risk of fracture. Am J Epidemiol. 2007;166:495–505. [PubMed]
69. Schwartz AV. Diabetes Mellitus: Does it Affect Bone? Calcif Tissue Int. 2003;73:515–519. [PubMed]
70. Thrailkill KM, Lumpkin CK, Jr, Bunn RC, Kemp SF, Fowlkes JL. Is insulin an anabolic agent in bone? Dissecting the diabetic bone for clues. Am J Physiol Endocrinol Metab. 2005;289:E735–745. [PMC free article] [PubMed]
71. Beck TJ, Oreskovic TL, Stone KL, Ruff CB, Ensrud K, Nevitt MC, Genant HK, Cummings SR. Structural adaptation to changing skeletal load in the progression toward hip fragility: the study of osteoporotic fractures. J Bone Miner Res. 2001;16:1108–1119. [PubMed]
72. Geusens P, Milisen K, Dejaeger E, Boonen S. Falls and fractures in postmenopausal women: a review. J Br Menopause Soc. 2003;9:101–106. [PubMed]
73. Weinstein JN, Birkmeyer JD, editors. The Dartmouth Atlas of Musculoskeletal Health Care. American Hospital Publishing; Chicago, IL: 2000.
74. Finkelstein JS, Lee ML, Sowers M, Ettinger B, Neer RM, Kelsey JL, Cauley JA, Huang MH, Greendale GA. Ethnic variation in bone density in premenopausal and early perimenopausal women: effects of anthropometric and lifestyle factors. J Clin Endocrinol Metab. 2002;87:3057–3067. [PubMed]
75. Pothiwala P, Evans EM, Chapman-Novakofski KM. Ethnic variation in risk for osteoporosis among women: a review of biological and behavioral factors. J Womens Health (Larchmt) 2006;15:709–719. [PubMed]
76. International Osteoporosis Foundation Fixed risk factors. Available from:
77. Fang J, Freeman R, Jeganathan R, Alderman MH. Variations in hip fracture hospitalization rates among different race/ethnicity groups in New York City. Ethn Dis. 2004;14:280–284. [PubMed]
78. Cummings SR, Cauley JA, Palermo L, Ross PD, Wasnich RD, Black D, Faulkner KG. Racial differences in hip axis lengths might explain racial differences in rates of hip fracture. Study of Osteoporotic Fractures Research Group. Osteoporos Int. 1994;4:226–229. [PubMed]
79. Brownbill RA, Ilich JZ. Hip geometry and its role in fracture: what do we know so far? Curr Osteoporos Rep. 2003;1:25–31. [PubMed]
80. Seeley DG, Kelsey J, Jergas M, Nevitt MC. Predictors of ankle and foot fractures in older women. The Study of Osteoporotic Fractures Research Group. J Bone Miner Res. 1996;11:1347–1355. [PubMed]
81. Hasselman CT, Vogt MT, Stone KL, Cauley JA, Conti SF. Foot and ankle fractures in elderly white women. Incidence and risk factors. J Bone Joint Surg Am. 2003;85-A:820–824. [PubMed]
82. Guggenbuhl P, Meadeb J, Chales G. Osteoporotic fractures of the proximal humerus, pelvis, and ankle: epidemiology and diagnosis. Joint Bone Spine. 2005;72:372–375. [PubMed]
83. Baron JA, Karagas MR. Medicare studies of vertebral fractures. Epidemiology. 1992;3:475–476. [PubMed]
84. Barrett JA, Baron JA, Karagas MR, ML B. Fracture risk in the U.S. Medicare population. J Clin Epidemiol. 1999;52:243–249. [PubMed]
85. Eicheldinger C, Bonito A. More accurate racial and ethnic codes for Medicare administrative data. Health Care Financ Rev. 2008;29:27–42. [PubMed]