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Fracture Risk From Psychotropic Medications: A Population-Based Analysis

Bolton, James M. MD, FRCPC*; Metge, Colleen PhD; Lix, Lisa PhD; Prior, Heather MSc; Sareen, Jitender MD, FRCPC*‡; Leslie, William D. MSc, MD, FRCPC§

Author Information
Journal of Clinical Psychopharmacology: August 2008 - Volume 28 - Issue 4 - p 384-391
doi: 10.1097/JCP.0b013e31817d5943
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Osteoporosis is a major public health issue.1 In white populations older than 50 years, approximately 50% of women and 20% of men will sustain an osteoporotic fracture in their remaining lifetime.2 Fragility fractures are associated with considerable morbidity and mortality and result in significant health care costs.3 In the United States alone, the cost of osteoporotic fractures in 2005 was estimated at $17 billion.4

Recent studies have demonstrated an association between psychotropic medications and risk of osteoporotic fractures.5-7 Selective serotonin reuptake inhibitors (SSRIs) have been associated with lower bone mineral density (BMD)8,9 and increased risk of fractures in several studies.6,10-13 Other psychotropic medications have a more controversial relationship with osteoporotic fractures. Although some studies report a relationship between use of benzodiazepines and fractures,14-16 others do not.17,18 Conflicting results also exist regarding antipsychotics.7,19-21 Lithium, interestingly, may be protective against fragility fractures.22,23

Despite emerging evidence suggesting psychotropic medications as potential risk factors for osteoporotic fractures, significant limitations persist in the literature. Studies have inconsistently controlled for confounding variables, and several have relied on participating subjects' self-report of medication use. The relationship between medication dose and fracture risk has been understudied with contrasting results. Some findings suggest a dose effect with SSRIs,6,13 whereas at least one does not.10 Another limitation pertains to polypharmacy and comorbidity. Schizophrenia and major depression, for example, are frequently comorbid24 and often result in an individual receiving multiple medications. These illnesses are both associated with fragility fractures25,26 as are the medications used in their treatment; however, no study has systematically examined the independent risk imparted by these variables in a single model. Furthermore, no study has examined whether polypharmacy is associated with greater risk of osteoporotic fractures when compared with the effects of individual psychotropic medications. The present study addressed these limitations using a large population-based database. We used a provincial registry that records dispensed prescriptions for all individuals in the population and, therefore, overcomes the bias associated with self-report of medication use. This allowed for a comprehensive examination of the relationship between osteoporotic fractures, physical and mental disorders, and a wide range of psychotropic medications including SSRIs, antipsychotics, benzodiazepines, and lithium.


Setting and Data Sources

A case-control study was conducted using de-identified population-based administrative health data from the Manitoba Department of Health (Manitoba Health) housed at the Manitoba Centre for Health Policy of the University of Manitoba.27 Manitoba Health provides comprehensive coverage for essentially all residents of the province of Manitoba. Because Manitoba residents are not obliged to pay premiums for health care coverage, nonparticipation in the plan is rare, and claims data are relatively complete for the population.

Manitoba Health maintains computerized databases of physician services and hospitalizations provided for all persons registered with the system. All Manitoba residents have a unique personal health identification number through which all health system encounters are tracked. A computerized record of all outpatient pharmaceutical dispensations occurring since April 1, 1995, is also maintained. In addition to a unique personal identifier, each prescription record contains the date of dispensation, exact identification of the dispensed drug (including strength), and the number of doses provided. All drugs are classified according to the Anatomical Therapeutic Chemical (ATC) system of the World Health Organization.28 The pharmacy database has been deemed to be accurate for both capture of drug dispensations and the prescription details.29 Each physician and hospital system contact includes information on a person's demographic characteristics, date and type of service, and diagnoses, which are coded using the International Classification of Diseases Ninth Revision, Clinical Modification (ICD-9-CM). The personal health identification number allows for linkage of the health records and the prescription drug database and, hence, the creation of a longitudinal record of a person's health service use including contacts with health care providers and community-based pharmaceutical dispensations. The accuracy of these administrative data has been established for a wide range of clinical disorders including fractures.30

Study Population

Persons aged 50 years and older with an osteoporotic fracture (ICD-9-CM code 805 for vertebral fracture, ICD-9-CM code 813 for wrist fracture, and ICD-9-CM code 820-821 for hip fracture plus a code for hip fracture reduction or fixation) from April 1, 1996, to March 31, 2004, were selected as cases. Age was taken from Manitoba Health's registry file as of the date of fracture. Each case was randomly matched to 3 controls by year of birth (within 5 years), sex (male vs female), ethnicity (aboriginal vs nonaboriginal),31 and a comorbidity index based upon the Johns Hopkins Ambulatory Care Group system.32 Ambulatory diagnostic groups (ADGs) represent 32 comorbidity clusters of every ICD-9-CM diagnostic code. Depending upon the variety of ICD-9-CM codes an individual receives over a period of 1 year, the number of ADGs can range from 0 to 32. The number of ADGs was categorized as none (0), 1 to 2, 3 to 5, and 6 or more in the year before index date (case fracture) using a previous definition.33 The selected controls were assigned the same index date as their matched fracture case.

Cases and controls were eligible for inclusion in the study if they had continuous coverage for health services from the Manitoba government between April 1, 1988, and March 31, 2004, or until death, unless death occurred during exposure and before fracture at which point the subject was excluded. Other case and control subject exclusions included residence in a long-term care facility because of incomplete drug data, as well as osteoporosis drug use in the year before case index date (selective estrogen receptor modulators, natural and semisynthetic estrogens, bisphosphonates, parathyroid hormone analogues, and salmon calcitonin).

Of the 15,796 fracture cases, 15,793 were successfully matched. Three cases were excluded: 2 cases because their registry birth date (the matching criteria for age) was less than 50 years of age; one which did not match any controls (men; 6 or more ADGs; and age, 85-89 years). One fracture case was subsequently removed because the case was not a Manitoba resident at the time of fracture. More than 99.5% of cases (n = 15,704) were fully matched to 3 controls.

Assessment of Medication Use

Antidepressant drugs were classified by the 4-digit third classification level ATC code N06A. These drugs were subclassified as SSRIs (N06AB); and others, monoamines (nonselective monoamine reuptake inhibitors, N06AA [eg, amitriptyline]; nonselective monoamine oxidase inhibitors, N06AF [eg, phenelzine]; monoamine oxidase A inhibitors, N06AG [eg, moclobemide]; and other antidepressants, N06AX [eg, nefazodone]). The ATC code N05A classified antipsychotics, and these were further subclassified as typical (phenothiazines, N05AA/N05AB/N05AC, N05AD [eg, haloperidol], N05AF [eg, flupentixol], N05AG [eg, pimozide]) versus atypical antipsychotics (N05AH [eg, clozapine, olanzapine, and quetiapine] and N05AX [eg, risperidone]). The ATC code for lithium was N05AN. Benzodiazepines included short-acting (N05C [eg, triazolam] and N05BA10 [ketazolam]), intermediate-acting (N05BA [eg, lorazepam] and N05CD [eg, temazepam]) and long-acting (N05CD [eg, flurazepam] and N05BA01 [diazepam]) subclasses.

Exposure to all drugs was categorized as nonuse (reference category), past use, and current use. Current use was at least 1 dispensation from the drug category within 120 days preceding the index date of the fracture. Past use was at least 1 dispensation in the 121 to 365 days preceding the fracture's index date, and nonuse was no recorded dispensations within the 365 days before the index date. Rationale for choosing these duration categories was based on evidence suggesting that median antidepressant trial duration is 120 days, and a previous study showing that many important treatment-related events occur within 15 weeks of initiating an antidepressant.34,35 Once identified as a "current user," individual exposure was categorized by dosage intensity. Total defined daily doses (DDDs) per person were calculated, and all persons were categorized into 3 tertiles (lowest to highest).36

Ascertainment of Potential Confounders

Potential confounders included in this study were variables that could be accessed from the administrative data and that had been previously associated with risk of fracture.37 In particular, we controlled for specific diagnostic definitions from ICD-9-CM codes from physician office visits and/or hospitalizations found during the 3 years before case fracture index date: diabetes, ischemic heart disease, myocardial infarction, hypertension (as proxies for obesity), epilepsy, rheumatoid arthritis, solid organ transplant, chronic obstructive pulmonary disease (COPD), substance abuse or dependence, depression (bipolar or unipolar), dementia, schizophrenia, and home care use (as a proxy for frailty). The diagnostic definition of substance abuse or dependence included ICD-9-CM codes for alcoholic psychoses, drug psychoses, alcohol dependence, drug dependence, and nondependent abuse of drugs. This definition has been previously used38 and found to correlate with prevalence figures of substance use disorders in the general population.39 Psychiatric diagnoses were based upon definitions that have been previously used in population-based studies.30,38,40

Current use of anticonvulsants, diuretics, anticoagulants, and thyroid hormones was also controlled for as a potential confounder. Current use was defined according to the same parameters used for psychotropic medications. These medications have been previously associated with osteoporotic fractures and have been controlled for in studies of similar design.22,41

Region of residence (rural north, rural south, and the urban center of Winnipeg) and neighborhood income quintiles (2001 Canada census public use files) were used to describe cases and control subjects. Mean household income for enumeration areas was obtained from 2001 Canada census public use files and subsequently used to define quintiles (5 groupings of approximately 20% of the population each; income quintile groupings are from 1 [lowest] to 5 [highest]).42 Income quintiles were grouped into lower (quintiles Q1-Q2) and higher (quintiles Q3-Q5) income to improve model fit.

Statistical Analysis

Conditional logistic regression analysis was used to calculate odds ratios (ORs) with 95% confidence intervals (CIs). Sequential models estimated the odds of fracture for each psychotropic drug group, controlling for demographic and confounding covariates as follows: baseline (partially adjusted) model included current drug exposure covariates as well as demographic variables describing neighborhood income quintile (higher income as reference), region of residence (urban center as reference), and the interaction of income quintile and region of residence; final (fully adjusted) model included all covariates from the baseline model as well as all confounding diagnoses and medications listed above but with all covariates in the same model instead of being modeled separately. Two-way interactions between the medication exposure variables were tested and were not statistically significant. Therefore, all analyses are based upon medication drug main effects. To assess linear trends between fracture risk and medication dosage, a linear trend model was created using all covariates from the final model but with current drug exposure entered into the model as tertiles of DDDs instead of as indicator variables of current use (yes/no). Contrast estimates were calculated to estimate the linear trend of fracture risk with increasing tertiles of DDDs and to test if the trend was significant. Because of the nature of conditional logistic regression, matching variables were not included as covariates in the models. All tabulations and statistical analysis were done using SAS (SAS Institute Inc., Cary, NC) version 9.1.43

We performed a sensitivity analysis to determine whether the observed association between psychotropic medications and fractures could be explained solely on the basis of confounding. Frailty was selected as an example of a confounder, and we investigated it in terms of its influence on the association between SSRI use and fractures. Using methods described in previous studies,44,45 we calculated the association between frailty and fracture, as well as the association between frailty and current SSRI use, to estimate the strength of association that would be needed to explain the relationship between SSRI use and fracture based solely on the confounding effect of frailty.


Table 1 lists the characteristics of fracture cases (n = 15,792) and controls (n = 47,289). The most common site of fracture was the wrist (52%). Fracture cases were more likely to occur among urban-dwelling adults and those in the lowest income quintiles. Diagnoses more prevalent among fracture cases included long-term diabetes, epilepsy, arthritis, COPD, and all the psychiatric diagnoses assessed: depression, substance abuse, schizophrenia, and dementia. Fracture cases were also more likely to have received home care. The use of all psychotropic medications was more prevalent among those with fractures with the exception of lithium.

Characteristics of Cases and Controls

The relationship between current psychotropic medication use, mental conditions, and osteoporotic fractures is shown in Table 2. In the partially adjusted model, all psychotropic medications were significantly associated with an increased risk of fracture with the exception of lithium. In the multivariate model, this relationship was maintained for SSRIs, other monoamine antidepressants, and benzodiazepines. Selective serotonin reuptake inhibitors had the strongest positive association with fractures among all psychotropics (OR = 1.45; 95% CI, 1.32-1.59; P < 0.01). Neither typical nor atypical antipsychotics were significantly related to fracture in the multivariate model. Lithium was associated with a lower likelihood of osteoporotic fractures (OR = 0.63; 95% CI, 0.43-0.93; P < 0.05). Among individuals categorized as past users, none of the psychotropic medications were associated with increased fracture risk (data not shown). All mental conditions in the study were significantly associated with fractures in the multivariate model. A diagnosis of substance abuse carried the highest odds of fracture (OR = 1.72; 95% CI, 1.53-1.95; P < 0.01), closely followed by schizophrenia (OR = 1.61; 95% CI, 1.27-2.04; P < 0.01).

Odds Ratios for Osteoporotic Fractures

Figure 1 shows the risk of fracture by dosage intensity of current medication use. Selective serotonin reuptake inhibitors showed a significant trend of increasing fracture risk with increasing dose (P < 0.05). Selective serotonin reuptake inhibitors had the strongest relationship with fractures in all dosage tertiles when compared with the other medications in their respective tertiles. Benzodiazepines also showed a significant trend of increasing fracture risk with higher dosage (P < 0.001). The dosage effects of other monoamine antidepressants, antipsychotics, and lithium were nonsignificant.

Risk of fracture by dosage intensity, adjusted for demographic variables, medications, physical conditions, and mental disorders.

For the sensitivity analysis, we fixed the following: observed OR for the association between SSRI use and fracture = 1.45, prevalence of the confounder (ie, frailty) = 0.18 (based on results for the proxy marker reported in the manuscript), and prevalence of drug exposure = 0.04 (based on results reported in the manuscript). We varied the association between frailty and fracture to range from OR of 1.5 to 2.5 (from our data, we estimated the OR between home care use and fracture to be 1.75). Using the methods proposed by Schneeweiss,44 we found that the association between SSRI use and frailty would need an OR of greater than 6.6 if the association we observed between SSRI use and osteoporotic fracture was due to confounding. We conclude that this association is unlikely to be due to confounding because, in our data, we estimated that the OR for SSRI use and home care use was not greater than 2.50.


This study provides a comprehensive assessment of the risk of osteoporotic fractures associated with psychotropic medications and related mental illness. Selective serotonin reuptake inhibitors were the medication most strongly correlated with fractures, even after adjusting for physical and psychiatric diagnoses and other medications implicated in fracture pathophysiology. The OR of 1.45 is within the range of 1.15 to 2.4 that has been found in previous studies.6,10-13,17 The consistency of these results provides strong evidence that the use of SSRIs is associated with increased risk of fractures in older individuals.

Our findings show an association between lithium use and lower likelihood of fracture risk. Only 2 studies, to our knowledge, have examined the effect of lithium on fracture incidence, and both have found similar results. The adjusted OR of 0.63 in the current study is slightly lower than that in the recent study by Wilting et al,22 which found an adjusted OR of 0.75. A noteworthy observation in our study, similar to the study by Wilting et al,22 is that the lowered risk gained significance only when potentially confounding diagnoses and medications were controlled for. One explanation for this finding may be that lithium is used in the treatment of psychiatric disorders that are associated with an increased risk of osteoporotic fractures. The mechanism underlying the relationship between lithium and fractures is currently under investigation but may involve the Wnt intracellular signaling cascade that is involved in osteoclastogenesis.46 Lithium has been shown to activate Wnt signaling in mice and lead to increased bone formation and bone density.47 In vitro studies have found that lithium stimulates the proliferation of bone marrow-derived mesenchymal stem cells.48,49 If further studies in humans confirm these effects of lithium on bone, then it may warrant clinical testing as a treatment for osteoporosis.

Depression, dementia, schizophrenia, and substance abuse were all correlated with an elevated risk of fractures. Although osteoporosis is known to affect individuals with schizophrenia, the relationship is complex and has been attributed to both antipsychotic medications and the illness proper.50 Previous studies have shown decreased BMD among individuals with schizophrenia,26,51 which may be mediated by elevated homocysteine levels.52,53 A recent study, however, did not find schizophrenia to be associated with risk of hip fracture when the effects of neuroleptic medications were accounted for.7 In our study, a diagnosis of schizophrenia, but not current use of antipsychotic medication, was significantly associated with risk of fracture in the multivariate analysis. The lack of significance for antipsychotic medications may be explained by the fact that they were not stratified according to propensity for hyperprolactinemia, which has been shown to differentially affect the risk of fracture.54

Our results suggest that individuals who abuse alcohol and drugs are at greater risk for fragility fractures than people with depression or schizophrenia. There is evidence that chronic alcohol ingestion decreases BMD and predisposes to osteoporosis.55-57 The increased risk persists even in periods of abstinence, indicating that fractures in this population are not merely a result of trauma during acute intoxication.58

An important contribution of this study relates to the dosage effects of psychotropics on fractures. Multivariate analysis revealed a dose-effect relationship across tertiles of medication dosage for SSRIs and benzodiazepines but not for other monoamine antidepressants, lithium, or antipsychotic medications. Our findings support the relationship between fracture risk and dosage of SSRIs and benzodiazepines seen in previous studies.6,13,15 Selective serotonin reuptake inhibitors are recommended as first-line pharmacological management for depression in the elderly59; although starting doses should be low, the final therapeutic doses should be similar to those used in young adults.60 However, there is debate surrounding the alleged benefit of higher doses of antidepressants for the treatment of depression. Some evidence suggests that escalating the dose of antidepressants confers no additional therapeutic benefit when side effects and treatment discontinuation are accounted for in intent-to-treat analysis.61,62 The risk-benefit ratio of antidepressant medications in the elderly is further affected by alterations in pharmacokinetics, pharmacodynamics, and reduced homeostatic reserve.63 Taken together, these results suggest that higher doses of certain psychotropic medications may require more careful consideration in the elderly population.

Polypharmacy is another important issue in older individuals. The average older adult takes 3 prescription medications daily, and 11% of the elderly take 10 or more medications.64 Psychotropic medications are often combined in augmentation strategies in treatment-resistant illness or to target comorbid conditions. Despite several of the studied medications being significantly associated with an increased risk of fracture, all 2-way interactions were nonsignificant. This may reflect a power limitation, and thus, at this point, it would be premature to infer that combining medications does not heighten the risk of fracture beyond the risk attributable to individual medications. Additional study of this particular issue is warranted, given the high prevalence of polypharmacy in the elderly.

There are several limitations of the current study that warrant discussion. The first pertains to the assessment of psychotropic medication use. A provincial drug-dispensing database was used as a proxy measure of medication use, but as such, we were unable to determine whether the individuals actually took the medications that were dispensed. Furthermore, it is possible that compliance differed by medication class. Nonetheless, our use of pharmacy records is preferable to patient self-report as used by some other studies, given that the recorded dispensations are accurate for date and dosage of medication. A second limitation is the accuracy of diagnostic codes used in the database. Psychiatric diagnoses may be prone to physician bias and, therefore, not accurately recorded in administrative datasets. Recognizing this limitation, efforts were made to define psychiatric diagnoses by using ICD-9-CM constructs from previous studies.30,38,40 Regarding the diagnosis of osteoporotic fractures, it is conceivable that some of the fractures may have been traumatic in nature. The association between psychotropic medications and falls in the elderly65 may partially explain the relationship with osteoporotic fractures, although the definition of osteoporotic fractures used in this study has been validated in previous studies.66,67 Furthermore, there is evidence from a recent large prospective cohort analysis showing that among older adults, traumatic fractures represent less than 10% of all fractures and likely reflect underlying osteoporosis, given the similar low BMD and propensity for future fractures seen in individuals with osteoporotic fractures.68 The authors of that study suggest that traumatic fractures should be included as outcomes in osteoporosis trials. Considering these findings, even if a small fraction of fractures in our study were traumatic, they likely reflect osteoporotic changes in these individuals and, therefore, do not confound our results. Third, causal inferences cannot be generated based on the study design, although we controlled for many confounding variables. We did demonstrate, however, that past users of psychotropic medications did not have an increased risk of fracture. This strengthens the possibility of a causal connection because the proximity of medication exposure becomes a principal factor distinguishing the otherwise similar risk profile of a current versus past user. A fourth limitation pertains to the assessment of potential confounders. There are other important risk factors for fracture (such as diet, smoking, and lifestyle) that could not be directly examined in the current study. These risk factors are prominent in many of the conditions examined in this study. Individuals with depression, schizophrenia, and substance abuse are prone to poor eating and exercise and use tobacco more frequently than their mentally healthy counterparts.69-72 It is possible that these factors may account for the association between psychotropic medications and fractures. However, there is also evidence that suggests that some of these factors may not increase the risk of osteoporotic fractures as previously thought. In a recent large prospective cohort study of postmenopausal women, calcium, vitamin D, and the quality of diet were not predictive of fractures.73 These findings, paired with contradictory results from previous studies, suggest that the effects of these confounders are not completely understood. We attempted to address this limitation by including proxy measures for obesity (diabetes, ischemic heart disease, myocardial infarction, and hypertension) and smoking (COPD). The influence of potentially unmeasured confounders needs to be considered when interpreting the findings of this study. Bone mineral density is another potential confounder that was not assessed directly; however, individuals being treated for osteoporosis were removed from the analysis. A future study incorporating these variables would be invaluable in determining the independent effect of these common potential risk factors. Finally, we did not examine the risk attributable to individual medications within each subclass. An extremely large number of subjects would be required to differentiate effects that are common to a specific subclass of medication from drug-specific effects.

The results of this study have important clinical implications in the medical management of older adults. Careful assessment of mental and physical comorbidity may identify a subgroup more prone to osteoporotic fractures. The presence of specific mental illnesses, the medications used in their treatment, and their dosages seem to independently exert an increased risk of fracture. The consistency of the findings in several studies, in particular with respect to SSRIs, suggests that informed consent may now require mention of fracture risk. Clinicians may choose psychotherapy or electroconvulsive therapy as alternative treatment approaches in depressed individuals with higher risk profiles. Similar considerations apply to the management of a broadening group of conditions as the potential etiologic agents in the pathophysiology of osteoporotic fractures encompass an increasing number of both medications and illnesses.


The authors are indebted to Ms Shelley Derksen, MSc, for performing the cohort matching and to Manitoba Health for providing the data used in this study. The results and conclusions are those of the authors, and no official endorsement by Manitoba Health is intended or should be inferred.


Dr Leslie, in the last 5 years, has received speaker's fees from Merck Frosst Canada Ltd; honoraria and unrestricted education grants from The Alliance for Better Bone Health: Sanofi-Aventis and Procter & Gamble Pharmaceuticals Canada, Inc; unrestricted research grants from Novartis Pharmaceuticals Canada, Inc; and unrestricted educational grants from Genzyme Canada.

Dr Sareen is a member of the speaker's bureau of Wyeth, AstraZeneca, and Bioval.

Dr Metge has received consultant fees from Paladin Labs Inc for over-the counter scheduling of levonorgestrel for emergency contraception in Canada and consultant fees from Merck Frosst Canada Ltd and GlaxoSmithKline for formulary listing advice. She also received an annual unrestricted education grant from Sanofi-Aventis for teachers of pharmacy administration.

The other authors have no disclosures to declare. The authors had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.


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