Health Services Research Department, Institute of Psychiatry, Kings College London, UK
Correspondence: Dr Louise Howard, PO 29, Health Services Research Department, Institute of Psychiatry, De Crespigny Park, London SE5 8AF, UK. Email: l.howard{at}iop.kcl.ac.uk
Declaration of interest None. Funding detailed in Acknowledgements.
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Aims To investigate whether patients with a history of schizophrenia are at increased risk of hip fracture.
Method In a casecontrol study, we compared cases of hip fracture on the General Practice Research Database (n=16 341) with matched controls (n=29 889).
Results Hip fracture was associated with schizophrenia (OR=1.73; 95% CI 1.322.28), and prolactin-raising antipsychotics (OR=2.6; 95% CI 2.432.78), in the univariate analysis. In the multivariate analysis, prolactin-raising antipsychotics were independently associated with hip fracture but schizophrenia was not. A significant interaction between gender and antipsychotics was foundinthe association with hip fracture (P=0.042); OR=2.12 (95% CI1.732.59) for men, OR=1.93 (95% CI1.782.10) for women.
Conclusions The association between prolactin-raising antipsychotic medication and hip fracture may have serious implications for public health. Mental health service patients may require preventive measures including dietary and lifestyle advice.
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Hip fracture is the most important fracture in terms of patient morbidity and mortality and for utilisation of health service resources (Cumming et al, 1997). As fracture is common in the older population, a small increase in the risk of fracture associated with psychotic disorders could have a considerable public health effect. We therefore chose to investigate whether there was an association between schizophrenia and hip fractures, using a casecontrol study design with data from a UK primary care data-set, the General Practice Research Database (GPRD). Our hypothesis was that patients with a history of schizophrenia would have a significantly increased risk of antipsychotic-induced osteoporotic hip fractures compared with a control group matched for age and general practice.
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Casecontrol analysis
Stata version 8.2 for Windows was used for statistical analysis. All
patients registered on the GPRD between 1 August 1987 and 22 November 1999
with a recorded diagnosis of fractured neck of femur or hip
fracture were identified, and designated as cases. Two controls per
case were identified, matching on age, gender, general practice and duration
of available GPRD data. For statistical efficiency a 1:1 ratio of cases to
controls is ideal when the number of cases can be chosen. In our study, since
the number of cases was limited, the number of controls was increased to two
per case in order to achieve adequate power. Each case was assigned a date of
diagnosis, defined as the date of the first hip fracture, and matching control
individuals were assigned an identical pseudo date of diagnosis.
Only records that were up to research standard were used.
Variables included the patients medical and psychiatric history, medication history and demographic details, as well as lifestyle factors (alcohol consumption, smoking and body mass index). All recorded diagnoses of schizophrenia were extracted and recorded for each case and control on an ever/never basis. Ever having had a prescription for a neuroleptic drug prior to or on the day of the first fracture was extracted and recorded. Where comorbid disorders were examined all disorders under the main relevant ICD9 heading were included e.g. intestinal diseases includes all diseases under this heading in ICD9 (World Health Organization, 1978). To enable all the data to be used, a category missing was created for each variable where needed. Imputation would have added no extra information, since all the variables available to make imputations were already included in the analysis.
Variables that had been previously identified in the research literature as being significantly associated with hip fracture were examined in univariate analyses and those that were significantly associated in this analysis were selected for multivariate analysis. Conditional logistic regression was used to calculate an unadjusted odds ratio for each selected variable. The selected variables were added one by one into bivariate models to identify potential confounders with the schizophrenia diagnosis variable and to see how much, if at all, they reduced or increased the odds ratio obtained with the schizophrenia diagnosis variable alone. A multivariable model was fitted using conditional logistic regression in a forward stepwise process using likelihood ratio tests. Variables that had become non-significant were removed and again the fit of the model was tested. By including interaction terms, gender and age at the time of the first fracture were tested to assess for modification of the effect of the schizophrenia diagnosis and of ever having had a prescription for neuroleptic medication on the incidence of hip fracture.
Ethical approval was granted by the Scientific Advisory and Ethical Group at the Medicines Control Agency, who are responsible for ethical issues for all projects using the GPRD.
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View this table: [in a new window] | Table 1 Associations between clinical and drug variables and hip fracture, General Practice Research Database, 1987-1999 |
Although schizophrenia was significantly associated with hip fractures in
the univariate analysis, this association was not significant when
antipsychotic medication was added to a multivariate model as a potential
confounder. A significant interaction was found between gender and having ever
had a prescription for neuroleptic medication (
2=4.15, d.f.=1,
P=0.042, likelihood ratio test). No such interaction was found for
schizophrenia diagnosis. The model was therefore fitted separately for women
(Table 2) and men
(Table 3). There were some
differences between the two gender-based models. Only in the female model were
diseases of the urinary system, having ever had inhaled corticosteroids and
diseases of the ear and mastoid process found to be significant. Only in the
male model were alcohol consumption above recommended levels and diseases of
the intestines and peritoneum found to be significant.
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View this table: [in a new window] | Table 2 Adjusted odds ratios for hip fractures in women: General Practice Research Database 1987-1999 (n=36 330) |
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View this table: [in a new window] | Table 3 Adjusted odds ratios for hip fractures in men: General Practice Research Database 1987-1999 (n=9900) |
Dementia had been diagnosed in 3461 patients of this data-set 1815
(11%) cases and 1646 (6%) controls;
2=478.36, d.f.=1,
P<0.01. Antipsychotic medication could have been prescribed for
behavioural disturbance in dementia, so patients receiving such medication
were excluded and the analyses repeated: this made negligible difference to
any result (further details available from the authors upon request). The
analyses were repeated using the cluster option in Stata, but
there was no evidence of clustering of fractures by general practice (further
information available from the authors upon request).
There was also a significant interaction between age at the time of the
first fracture (categorised) and having ever had a prescription for
neuroleptic medication (
2=28.27, d.f.=3, P<0.001,
likelihood ratio test). The interaction was most marked for those aged under
85 years (n=31 071; OR for neuroleptic medication 2.29, 95% CI
2.062.53) compared with those aged 85 years and over (n=15
113; OR for neuroleptic medication 1.66, 95% CI 1.491.85). Since there
was an interaction for both age and gender, the model was also fitted
separately with the data-set stratified by both these variables into women
under 85 years old (n=23 289; OR for neuroleptic medication 2.31, 95%
CI 2.062.58); women 85 years or older (n=13 027; OR=1.65, 95%
CI 1.471.86); men under 85 years old (n=7788; OR=2.42, 95% CI
1.893.09); and men 85 years old or older (n=2098; OR=2.12, 95%
CI 1.512.99). Odds ratios were calculated for each of the individual
neuroleptic medications which went to make up the combined neuroleptic
variable, and are presented in Table
4. Also included here are figures for prochlorperazine, which was
not included as part of the combined neuroleptic variable as it was felt that
this might have been used largely as an anti-emetic. Atypical antipsychotic
medications (which were only prescribed in the last few years of this
data-set), were also considered separately, as there were too few prescribed
to include in a combined antipsychotic variable, and odds ratios for these are
also presented.
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View this table: [in a new window] | Table 4 Odds ratios for individual antipsychotic medications prescribed before or on day of fracture: General Practice Research Database 1987-1999 |
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A number of recent studies have indicated that low bone mineral density is highly prevalent in people with a chronic psychiatric disorder treated with prolactin-raising antipsychotic medication (Bilici et al, 2002; Liu-Seifert et al, 2004). Meaney et al (2004) also reported that higher doses of potent typical and atypical antipsychotic medications that block dopamine D2 receptors were associated with increased rates of both hyperprolactinaemia and bone mineral density loss. However, possibly because of a lack of research into the secondary consequences of antipsychotic-induced hyperprolactinaemia, the World Health Organization does not include antipsychotic drugs in its list of prescribed drugs associated with the development of osteoporosis.
Although postmenopausal women are generally most at risk of osteoporosis, possibly owing to low serum oestradiol concentrations (Cummings et al, 1998), we found a higher risk of fracture associated with neuroleptic medication in men. This result is in agreement with several studies of psychiatric patients, which found significantly lower bone mineral density in men than women associated with neuroleptic use (Halbreich et al, 1995; Hummer et al, 2005). These gender differences may be owing to the age differences in onset of schizophrenia (Hafner et al, 1998): men have an age at onset approximately 5 years younger than that in women, and illness-related factors including medication will therefore have had a longer-lasting impact on male patients. An alternative explanation suggested by Hummer & Huber (2004) is that women with schizophrenia take better care of themselves with regard to adequate nutrition and exercise than men and therefore have less osteoporosis. Unfortunately the data are not available here to test either hypothesis.
There are a number of other known risk factors for osteoporosis among patients with schizophrenia which may be acting as confounders here, including inadequate exercise and exposure to sunshine, poor nutrition, cigarette smoking and polydipsia (Naidoo et al, 2003). Of these, only smoking could be controlled for in this analysis and was found to be a significant factor, but the association was not as strong as with neuroleptic medication. Other mechanisms may also be relevant in causing hip fracture: for example, neuroleptic medications are known to cause sedation, orthostatic hypotension and extrapyramidal side-effects, which may predispose some patients on these treatments to falls (Misra et al, 2004).
We used the GPRD, a large UK primary care data-set, which provided one of the largest data-sets of hip fracture. Like other studies, we found an increased risk of hip fracture to be associated with smoking (Cumming et al, 1997), low body mass index (Farahmand et al, 2000), alcohol intake (for men) (Yuan et al, 2001) and anticonvulsants (Kinjo et al, 2005), and obesity to be protective against hip fracture (Farahmand et al, 2000), giving a high level of face validity to this study.
Limitations of the study
Although using a large, nationally representative database provides
important data from a large sample, detailed clinical information is less
available than in smaller studies. Diagnostic categories found on the GPRD are
not operationalised and are therefore unlikely to be exactly the same as those
found in research or psychiatric practice, and information such as bone
mineral density is not available. Lifestyle variables (body mass index,
smoking and alcohol intake) are recorded optionally and were missing in a
significant number of cases and controls. We created a missing
category to enable us to use these fields in the analysis. Residual
confounding is therefore possible. Some prescribing of neuroleptics occurs in
secondary care only and information on secondary care prescriptions was not
available. For this reason details of dosages of antipsychotic medication over
time were not reliable, and we categorised neuroleptic exposure as a
dichotomous variable (ever/never); some patients might not have received large
doses of antipsychotics, and if this were the case the relationship between
antipsychotic medication might be owing to mechanisms such as falls, rather
than secondary to hyperprolactinaemia. In addition, we could not examine the
effect of atypical antipsychotic medications because too few patients had been
prescribed them on the GPRD during the exposure period, nor could we examine
the effect of individual neuroleptic drugs in a multivariable analysis as
there was insufficient statistical power. Larger, more up-to-date data-sets
could address these issues in the future.
Although casecontrol studies are prone to bias, one advantage of using a data-set such as the GPRD is that the two major biases in this type of study selection and recall bias should be minimised by the prospective collection of data by general practitioners. Reverse causation is normally a possible explanation in casecontrol studies; this possibility should have been excluded here by looking at exposure prior to the occurrence of the first fracture. These findings should also be generalisable.
This study found significant evidence of an association between a diagnosis of schizophrenia and hip fracture, which appeared to be partly explained by neuroleptic medication. This adds to the growing body of evidence of an association between neuroleptic medication and bone mineral density loss. Patients with psychiatric disorders are less likely to have their medical illness diagnosed (Koranyi, 1979; Koran et al, 1989; Redelmeier et al, 1998) and medically managed (Redelmeier et al, 1998), and there is some evidence to suggest that they are less likely to have osteoporosis screened for or treated compared with age-matched control patients (Bishop et al, 2004). If this is the case this has serious public health implications, because the patients who have taken long-term neuroleptic medications are precisely those patients who are probably not being screened for osteoporosis. The evidence base for routinely screening patients prescribed neuroleptics is not available at present and clinicians urgently need more data on who is at highest risk and when (we do not yet know whether psychiatric patients are most at risk of developing osteoporosis after antipsychotic medication is initiated, or after dose-dependent long-term exposure). Randomised controlled trials of interventions to prevent fractures in these patients would enable more effective prophylaxis to be provided by mental health services and by primary care. However, if our findings are replicated, preventive measures should become part of the treatment of patients taking long-term prolactin-raising antipsychotic drugs and may include advice to patients about the importance of a balanced diet containing sufficient amounts of calcium and vitamin D, regular weight-bearing exercise, avoidance of tobacco, caffeine and alcohol, and sufficient exposure to sunlight.
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