Diabetes mellitus and first episode mania associated with cardiovascular diseases in patients with older-age bipolar disorder

Author’s Accepted Manuscript Diabetes mellitus and first episode mania associated with cardiovascular diseases in patients with older-age bipolar disorder Pao-Huan Chen, Chi-Kang Chang, Shuo-Ju Chiang, Yen-Kuang Lin, Shang-Ying Tsai, ShouHung Huang www.elsevier.com/locate/psychres

PII: DOI: Reference:

S0165-1781(16)31175-1 http://dx.doi.org/10.1016/j.psychres.2017.01.004 PSY10194

To appear in: Psychiatry Research Received date: 14 July 2016 Revised date: 1 January 2017 Accepted date: 1 January 2017 Cite this article as: Pao-Huan Chen, Chi-Kang Chang, Shuo-Ju Chiang, YenKuang Lin, Shang-Ying Tsai and Shou-Hung Huang, Diabetes mellitus and first episode mania associated with cardiovascular diseases in patients with older-age bipolar disorder, Psychiatry Research, http://dx.doi.org/10.1016/j.psychres.2017.01.004 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Diabetes mellitus and first episode mania associated with cardiovascular diseases in patients with older-age bipolar disorder Pao-Huan Chen

a,b,

*, Chi-Kang Chang c, Shuo-Ju Chiang d,e, Yen-Kuang Lin f, Shang-Ying

Tsai a,b, Shou-Hung Huang a,b a

Department of Psychiatry, Taipei Medical University Hospital, Taipei, Taiwan

b

Department of Psychiatry, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan

c

Department of Psychiatry, Taipei City Psychiatric Center, Taipei City Hospital, Taipei, Taiwan

d

Division of Cardiology, Department of Internal Medicine, Taipei Medical University Hospital, Taipei, Taiwan

e

Department of Internal Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan

f

Biostatistics Center, Taipei Medical University, Taipei, Taiwan

* Corresponding author: Pao-Huan Chen Department of Psychiatry, Taipei Medical University Hospital, Taipei, Taiwan #252 Wu-Hsing Street, Taipei, 110, Taiwan. Tel: 886-2-27372181 ext: 3666; Fax: 886-2-66315033. [email protected]

Abstract Patients with bipolar disorder (BD) are at high risk for developing cardiovascular diseases (CVDs) during aging process. However, investigations are lacking regarding the risk factors for CVDs specific to BD patients. The aim of this study was to examine the

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relationship between CVDs and traditional risk factors in association with the characteristics of BD in older age. Totally, we recruited 124 patients with BD-I (DSM-IV) who had at least one psychiatric admission and cardiologist-confirmed CVD diagnosis (ICD-9 code 401-414) at mean age of 61.7+4.9 years. Each case subject was matched with one BD-I patient without CVDs based on age, sex, and date of the most recent psychiatric admission (+2 years). Clinical data were obtained by retrospectively reviewing the medical record. A multiple logistic regression model showed that not only traditional risk factor (e.g., diabetes mellitus) but also non-traditional one associated with BD (e.g., first episode mania) significantly increased the risk of CVDs. Given the limitation of this cross-sectional study, longitudinal investigations are needed to elucidate the contributions of both traditional risk factors and the BD characteristics for CVD risk in patients with BD. Keywords: bipolar disorder; ischemic heart disease; hypertension; diabetes mellitus; obesity; mania

1. Introduction Bipolar disorder (BD) is a chronic and recurrent mental illness associated with a 2 to 4 times higher mortality rate than that of the general population (Angst et al., 2002; Crump et al., 2013; Weiner et al., 2011; Westman et al., 2013). Notably, this higher mortality rate results in at least a 10-year reduction in life expectancy (Angst et al., 2002; Crump et al.,

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2013; Weiner et al., 2011; Westman et al., 2013). Evidence from both Western and Eastern studies has repeatedly shown that cardiovascular disease (CVD) is among the leading causes contributing to the excess and premature deaths in patients with BD (Angst et al., 2002; Crump et al., 2013; Tsai et al., 2005; Weiner et al., 2011; Westman et al., 2013). Given the higher medical burden and shorter lifespan in BD patients as compared with that of general population, International Society for Bipolar Disorders Task Force recently proposed age 50 years to be considered as a demarcation of older-age bipolar disorder (Sajatovic et al., 2015). Robust evidence has shown that patients with BD are more vulnerable than the general population to develop traditional CVD risk factors, including obesity, diabetes mellitus, dyslipidemia, cigarette smoking, and heavy alcohol use (Chen et al., 2015; Diaz et al., 2009; Gildengers et al., 2008; Goldstein et al., 2009; Grant et al., 2015; Sajatovic et al., 2005; Tsai et al., 2009); however, vulnerability to traditional CVD risk factors might not completely explain the high CVD burden in patients with BD. Recently, studies from both Western and Eastern countries demonstrated that traditional risk factors alone might not fully predict risk of CVDs in patients with BD (Chen et al., 2015; Osborn et al., 2015). Unhealthy life styles, suboptimal treatment of medical diseases, adverse effects of psychotropic medications, and the pathophysiology of BD itself have all been suspected as possible reasons for the gap in the rates of CVDs between patients with BD and the general population (Krishnan, 2005; Tsai et al., 2009). Furthermore, Eastern patients with BD were found to have lower levels of

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blood cholesterol as well as lower rates of cigarette smoking and alcohol abuse when compared with Western patients with BD (Chen et al., 2015; Chung et al., 2007; Tang et al., 2015; Tsai et al., 2009), which may reflect racial difference in CVD risk profiles for BD. Taken together, these findings suggest that CVD risk profiles could be more complicated in patients with BD than those in the general population. Evidence has suggested that the affective and psychotic symptoms of BD were correlated with cardiovascular morbidity and mortality (Chouinard et al., 2016; Fiedorowicz et al., 2009; Ramsey et al., 2010; Slomka et al., 2012). The association between BD psychopathology and CVDs could be related to an unhealthy lifestyle and decrease in the ability for self-care as well as to dysregulation of the hypothalamic-pituitary-adrenal axis, endothelial dysfunction, and inflammation (Chouinard et al., 2016; Fiedorowicz et al., 2009; McElroy and Keck, 2014; Ramsey et al., 2010; Slomka et al., 2012; Wildes et al., 2006; Vancampfort et al., 2016). Moreover, mood stabilizers and antipsychotics are the first-line options in the treatment of BD but could worsen endocrinological and metabolic functions (Correll et al., 2015a, 2015b; Vancampfort et al., 2013; Vuksan-Ćusa et al., 2011; Weiner et al., 2011). Consequently, aging patients with BD might actually have an extra-high risk for CVDs because of features unique to BD. However, few studies have directly explored the risk factors for CVDs specific to these patients in older age. We hypothesized that, aging patients with BD have unique risk profiles for CVDs which

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contain not only the traditional risk factors but also extra-traditional ones linked to the psychopathology of BD and to psychopharmacotherapy. In order to obtain more comprehensive data to identify potential risk factors, we utilized hospital records in this exploratory study. We investigated patients with only BD-I but not other bipolar-spectrum disorders in order to increase the reliability of the diagnosis. The CVD categories used in this study included ischemic heart disease (IHD) and hypertension (HTN) which are the principle causes if cardiovascular morbidity in patients with BD (Chen et al., 2015; Goldstein et al., 2009). The aim of this study was to determine the relationship between CVDs and traditional risk factors in association with the characteristics of BD-I in older age. 2. Methods 2.1. Study sample and procedure All subjects in this study were enrolled from two teaching hospitals affiliated with Taipei Medical University: (1) Taipei Medical University Hospital (TMUH), a general hospital with 75 psychiatric beds; and (2) Taipei City Psychiatric Center (TCPC), a mental health center with 300 acute beds and 312 chronic beds for the Northern Taiwan catchment region of 7 million people. Using computer data files from the two hospitals, we initially identified 572 potential subjects based on the following criteria: (1) age 50 or older; (2) having had at least one psychiatric admission to TMUH or TCPC between January 1, 2006 and December 31, 2014; and (3) having the International Statistical Classification of Diseases and Related

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Health Problems 9th Revision (ICD-9) code 296 on discharge. At TMUH and TCPC, a case-note form has been utilized since 1980. This contains over 95 items structured to obtain a patient’s demographic data, clinical features, concurrent physical illness, family history, and results of physical examinations and laboratory tests. Two board-certified psychiatrists (P.H. Chen and C.K. Chang) independently reviewed the medical chart of each potential subject to determine the psychiatric diagnosis. A total of 244 subjects with a final principle diagnosis other than DSM-IV bipolar I disorder (BD-I) were excluded (major depressive disorder: n=68, bipolar II disorder: n=27, cyclothymia: n=7, bipolar disorder not otherwise specified: n=5, schizoaffective disorder: n=21, schizophrenia: n=5, delusional disorder: n=2, mood disorder due to general medical condition: n=54, mood disorder due to substance: n=36, dementia: n=17, personality disorder: n=2). Among the remaining 328 subjects with BD-I, 148 were determined to have comorbid CVDs (ICD-9 code 401-414). The criteria for a diagnosis of CVD were: (1) a definitive diagnosis of CVDs on the discharge note; (2) standard treatment for CVDs for at least six months, or (3) significant physical or laboratory findings that supported the diagnosis of CVDs as determined by a board-certified cardiologist (S.J. Chiang) who was blinded to the psychiatric data. Those subjects with BD-I and comorbid CVDs were assigned to the case group. Each subject in the case group was matched with one patient with BD-I but without

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CVD (as a control subject) based on age, sex, and date of the most recent psychiatric admission (+2 years). Because there was no suitable control available for 24 case subjects, a total of 124 case subjects and their 124 matched controls were ultimately included in this study. The Institutional Review Board of TMUH (Taipei Medical University Joint Institutional Review Board) and TCPC (Taipei City Hospital Institutional Review Board) approved wavier of informed consent for this protocol. 2.2. Collection of clinical variables Sociodemographic and clinical variables were retrospectively obtained by reviewing the medical records. For all subjects, we recorded details of concurrent physical diseases as well as blood tests routinely done on the morning after the most recent psychiatric admission following overnight fasting. As suggested by the Health Promotion Administration at the Ministry of Health and Welfare in Taiwan (Health Promotion Administration, 2002), the cut-off points used to define diabetes mellitus and impaired fasting glucose were serum fasting glucose levels above 126mg/dL and between 100mg/dL and 125mg/dL, respectively. The cut-off points used to define dyslipidemia were a serum triglyceride level above 200mg/dL, total cholesterol above 240mg/dL, low-density lipoprotein above 160mg/dL, or high-density lipoprotein below 40mg/dL for men and 50 mg/dL for women. The cut-off point for obesity was a body mass index (BMI) over 27kg/m2 and for overweight a BMI between 24 and 27kg/m2. Subjects who received regular treatment for diabetes mellitus or

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dyslipidemia were also recorded as having these two metabolic diseases even if the results of blood tests were within the normal range. The categories of renal diseases used in this study were nephritis, nephrotic syndrome, and renal failure (ICD-9 code 581-586). The categories of thyroid diseases were hyperthyroidism, hypothyroidism, goiters, and thyroiditis (ICD-9 code 240-246). In this study, we defined the onset of BD as the occurrence of affective symptoms, either depression or mania, which caused severe impairment of a subject’s psychosocial function or resulted in psychiatric hospitalization. The rapid cycling feature was defined as a subject having at least four episodes of mood disturbance that met DSM-IV criteria for hypomania, mania, or major depressive episode within a 12 month period. A psychotic feature was recorded if subjects had experienced hallucinations or delusions within any mood episode. Regular alcohol users were identified as such only if they drank alcohol more than three times per week (McLellan et al., 1980). 2.3. Statistical analysis Group comparisons between subjects with and without CVDs were made by using independent sample t tests when explanatory variables were continuous, and Pearson’s χ2 test along with the Yates’ correction or Fisher’s exact test for categorical variables. A multiple logistic regression was performed on statistically significant (p< 0.05) independent variables from the univariate analysis to assess the simultaneous impact of several potential factors for

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CVD as an outcome. A logistic regression model with the best goodness-of-fit was determined using the Hosmer-Lemeshow statistic. All data analyses were performed with the SPSS version 18.0 software. P values <0.05 were considered significant. 3. Results In the present study, we totally enrolled 328 subjects with BD-I beyond age 50. Forty-five percent (n=148) of them had CVDs confirmed by the medical records and the cardiologist’s diagnosis (IHD only: n=35, HTN only: n=90, both IHD and HTN: n=23). The comorbid rate of IHDs and HTN was 17.7% and 34.5%, respectively. Among these, 124 patients with BD-I and CVDs at a mean age of 61.7+4.9 years were included in the case group. When compared with the age- and sex-matched control subjects, case subjects did not show significant differences in socio-demographic characteristics including cigarette smoking and the problematic use of alcohol (Table 1). Table 2 compares the features of BD in the case and control groups. In addition to the mean age at the most recent psychiatric admission for BD, the two groups also had comparable mean ages at the onset of BD and at the first psychiatric admission. Significantly, subjects in the case group were more likely to have mania as their first episode than were those in the control group. Moreover, a significantly higher proportion of case subjects received carbamazepine treatment during their most recent psychiatric hospitalizations. Conversely, control subjects were more likely to receive second generation antipsychotics

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during their most recent psychiatric hospitalizations. Table 3 shows the cardio-metabolic characteristics during the most recent psychiatric hospitalizations. Case subjects had significantly higher mean values for body mass index and higher rates of obesity than did the controls. Although the difference in mean levels of fasting serum glucose did not reach statistical significance between the two groups, a significantly higher proportion of case subjects were diagnosed with diabetes mellitus and received therapy during their most recent hospitalizations. On the other hand, no difference was determined between the two groups in terms of mean serum levels of total cholesterol, high-density lipoprotein, low-density lipoprotein, triglycerides, or the rate of dyslipidemia. In order to assess the impact of diabetes mellitus and obesity on CVD as an outcome in the context of BD, the psychopathological factor (i.e., first episode mania) and the psychopharmacological factors (i.e., the use of carbamazepine and second generation antipsychotics during the most recent hospitalizations) were chosen as the independent variables in a logistic regression model. According to the model, the diagnosis of diabetes mellitus but not obesity remained statistically significant (95% C.I. for odds ratio=1.31-4.26) in association with first episode mania (95% C.I. for odds ratio=1.12-4.17) and second generation antipsychotic therapy (95% C.I. for odds ratio=0.98-0.99) to predict CVDs as the outcome (Table 4). The goodness-of-fit of this logistic regression model was acceptable with χ2=10.02 and p= 0.264.

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4. Discussion In this study, we found that 17.7% and 34.5% of patients with BD in older age had comorbid IHDs and HTN, respectively. These results are consistent with those in several Western reports (Chen et al., 2015; Gildengers et al., 2008; Goldstein et al., 2009; Sajatovic et al., 2005; Tsai et al., 2009) and therefore indicate that the problems of CVDs in BD are also severe in the Eastern population. Furthermore, we found that diabetes mellitus was the main traditional risk factor associated with CVDs when the psychopathology of BD and psychopharmcotherapy were taken into consideration. In contrast to what has been reported in the general population (Chia et al., 2015; Wilson et al., 1987), obesity, dyslipidemia, cigarette smoking, and problematic alcohol use were not associated with CVDs in our analyses. This supports the contention that aging patients with BD may have distinct risk profiles for CVDs when compared with those of the general population because of features specific to BD. The strength of our findings is that the diagnoses of CVDs and diabetes mellitus were all determined by the results of laboratory examinations, records of standard treatment, and confirmation by a cardiologist and were therefore valid and reliable. The comorbid rate of diabetes mellitus was strikingly high in our BD patients with CVDs (43.5%). This rate was not only higher than that of control subjects in this study but also higher than the 17.6% to 31.3% reported in previous studies (Chen et al., 2015; Chien et al., 2010; Gildengers et al., 2008; Goldstein et al., 2009; Sajatovic et al., 2005; Tsai et al.,

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2009). Meanwhile, 31.1% of our patients with BD were obese, a percentage significantly higher than the 18.3% to 20% reported in Taiwanese adults over middle age (Hwang et al., 2006). Taken together, these results suggest that both diabetes mellitus and obesity are the major metabolic morbidities possibly linked to CVDs in older-age patients with BD. However, we could find an association between CVDs and diabetes mellitus only in our multivariate analyses. Emerging evidence suggests that obesity is prevalent even among youth with BD (Goldstein et al., 2008; Shapiro et al., 2016). In contrast, the prevalence of diabetes mellitus is not high at this early stage but increases significantly after age 50 (Chien et al., 2010). Consequently, diabetes mellitus could be a late complication of obesity in patients with BD and closely linked to CVDs in older age. More longitudinal studies are needed to better understand the temporal relationship between obesity and diabetes mellitus in patients with BD and CVDs. In addition to the traditional risk factors for CVDs, first episode mania was also related to our patients with BD and CVDs in older age. Our result was consistent with previous findings that manic symptoms elevated about 2 times risk for CVDs in patients with BD (Fiedorowicz et al., 2009; Ramsey et al., 2010). Notably, the study of Fiedorowicz et al. found that patients with BD-I were at even greater risks of CVD mortality as compared with patients with BD-II (Fiedorowicz et al., 2009). This difference in CVD risks could be explained by manic burden. In previous studies, patients with the first episode mania have

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been found to be at greater risks of mania in subsequent episodes (Perugi G et al., 2000). Manic burden has also been found to be associated with arterial stiffness (Sodhi SK et al., 2012) and endothelial dysfunction (Fiedorowicz JG et al., 2012). Furthermore, the observed association between mania and CVDs may be mediated by the pathophysiology of BD itself or the patients’ propensity to engage in unhealthy behaviors. In this study, we did not find significant differences in unhealthy behaviors such as cigarette smoking and problematic alcohol use between BD-I patients with and without CVDs. A pathophysiological mechanism intrinsic to BD might therefore be the potential explanation. It has been recently proposed that patients with BD begin to have dysfunctional allostasis across multiple organ systems after their first mood episode (Kupfer et al., 2015). Given the present findings that manic symptoms and diabetes mellitus could collectively contribute to CVDs in patients with BD, investigations into the pathophysiology of BD linked with dysfunctional regulation of both mood and glucose metabolisms are therefore suggested. Contrary to our hypothesis, we found that the use of second generation antipsychotics during the most recent psychiatric hospitalization did not elevate risk of CVDs in older-age patients with BD. This contrasts with previous studies which found that second generation antipsychotics were associated with increased risk for CVDs in patients with BD (Correll et al., 2015a, 2015b; Vancampfort et al., 2013; Vuksan-Ćusa et al., 2011; Weiner et al., 2011). In our sample, BD patients with CVDs were noted to have remarkably high rates of diabetes

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mellitus and obesity. Meanwhile, these patients were also less likely to receive second generation antipsychotics for acute therapy during their most recent hospitalizations. Therefore, our findings may actually reflect a growing awareness of the potentially cardiometabolic risks in BD patients treated with second generation antipsychotics (i.e. clinicians prevent use of second generation antipsychotics to minimize cardiometabolic problems). Another possible explanation is that the therapeutic effects of second generation antipsychotics on BD psychopathology minimize unhealthy behaviors and enhance the ability for self-care relative to CVDs. However, evidence has indicated that the pharmacodynamic profiles, duration of exposure, and dosages of antipsychotics have to be taken into consideration when examining the effects of antipsychotics on the risk for CVDs (Correll et al., 2015a, 2015b; Crump et al., 2013). In the present study, we only calculated the second generation antipsychotics as a whole class of medication but not split them as each kind of drug. Furthermore, we merely obtained the dichotomous variables (i.e. exposure and not exposure of medications) derived from medical records in a single hospitalization. Consequently, the limitations of our study design cannot facilitate inferences related to medication effects on CVD risk. Several methodological shortcomings of this study should be addressed. First, the cross-sectional design of this study limited the ability to determine causal relationships. Second, the sample size was still modest and therefore may have limited the statistical power

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to detect differences in other traditional risk factors between BD patients with and without CVDs. Third, selection bias may exist in this study because our sample was formed by convenience and not consecutively. Fourth, utilizing information only based on medical records has limitations in terms of missing data. Consequently, we could possibly underestimate the rate of depression as first episode. Similarly, we also lacked the data from direct interview to validate our chart review diagnoses. Fifth, to obtain more comprehensive information from chart review, our subjects must have had at least one acute psychiatric hospitalization. Therefore, readers should be cautious to generalize our results to all patients with BD-I. In conclusion, the high CVD burden in patients with BD is probably due not only to traditional risk factors (e.g., diabetes mellitus) but also to non-traditional ones associated with the BD (e.g., first episode mania). To elucidate the pathogenesis of CVDs specific to patients with BD, longitudinal studies are needed to address the interplay between traditional risk factors and BD characteristics across the lifespan. Conflict of interest All authors declare that they have no conflict of interest.

Acknowledgements This study was supported by a research grant from the Ministry of Science and

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Technology of Taiwan (MOST 104-2314-B-038-022). The authors thank Miss Tse-Yi Chen for her administrative support.

References Angst, F., Stassen, H.H., Clayton, P.J., Angst, J., 2002. Mortality of patients with mood disorders: follow-up over 34-38 years. J. Affect. Disord. 68, 167–181. Chen, P.H., Gildengers, A.G., Lee, C.H., Chen, M.L., Kuo, C.J., Tsai, S.Y., 2015. High serum sodium level in affective episode associated with coronary heart disease in old adults with bipolar disorder. Int. J. Psychiatry Med. 50, 422–433. Chia, Y.C., Gray, S.Y., Ching, S.M., Lim, H.M., Chinna, K., 2015. Validation of Framingham general cardiovascular risk score in a multiethnic Asian population: a retrospective cohort study. BMJ Open 5, e007324. Chien, I.C., Chang, K.C., Lin, C.H., Chou, Y.J., Chou, P., 2010. Prevalence of diabetes in patients with bipolar disorder in Taiwan: a population-based national health insurance study. Gen. Hosp. Psychiatry 32, 577–582. Chouinard, V.A., Pingali, S.M., Chouinard, G., Henderson, D.C., Mallya, S.G., Cypess, A.M., Cohen, B.M., Öngür, D., 2016. Factors associated with overweight and obesity in schizophrenia, schizoaffective and bipolar disorders. Psychiatry Res. 237, 304–310. Chung, K.H., Tsai, S.Y., Lee, H.C., 2007. Mood symptoms and serum lipids in acute phase of

16

bipolar disorder in Taiwan. Psychiatry Clin. Neurosci. 61, 428–433. Correll, C.U., Detraux, J., De Lepeleire, J., De Hert, M., 2015. Effects of antipsychotics, antidepressants and mood stabilizers on risk for physical diseases in people with schizophrenia, depression, and bipolar disorder. World Psychiatry 14, 119–136. Correll, C.U., Joffe, B.I., Rosen, L.M., Sullivan, T.B., Joffe, R.T., 2015. Cardiovascular and cerebrovascular

risk

factors

and

events

associated

with

second-generation

antipsychotic compared to antidepressant use in a non-elderly adult sample: results from a claims-based inception cohort study. World Psychiatry 14, 56–63. Crump, C., Sundquist, K., Winkleby, M.A., Sundquist, J., 2013. Comorbidities and mortality in bipolar disorder: a Swedish national cohort study. JAMA Psychiatry 70, 931–939. Diaz, F.J., James, D., Botts, S., Maw, I., Susce, M.T., de Leon, J., 2009. Tobacco smoking behaviors in bipolar disorder: a comparison of the general population, schizophrenia, and major depression. Bipolar Disord. 11, 154–165. Fiedorowicz, J.G., Solomon, D.A., Endicott, J., Leon, A.C., Li, C., Rice, J.P., Coryell, W.H., 2009. Manic/hypomanic symptom burden and cardiovascular mortality in bipolar disorder. Psychosom. Med. 71, 598–606. Fiedorowicz, J.G., Coryell, W.H., Rice, J.P., Warren, L.L., Haynes, W.G., 2012. Vasculopathy related to manic/hypomanic symptom burden and first-generation antipsychotics in a sub-sample from the collaborative depression study. Psychother. Psychosom. 81, 235–

17

243. Gildengers, A.G., Whyte, E.M., Drayer, R.A., Soreca, I., Fagiolini, A., Kilbourne, A.M., Houck, P.R., Reynolds, C.F. 3rd, Frank, E., Kupfer, D.J., Mulsant, B.H., 2008. Medical burden in late-life bipolar and major depressive disorders. Am. J. Geriatr. Psychiatry 16, 194–200. Goldstein, B.I., Birmaher, B., Axelson, D,A. Goldstein, T.R., Esposito-Smythers, C., Strober, M.A., Hunt, .J, Leonard, H., Gill, M.K., Iyengar, S., Grimm, C., Yang, M., Ryan, N.D., Keller, M.B., 2008. Preliminary findings regarding overweight

and obesity in

pediatric bipolar disorder. J. Clin. Psychiatry 69, 1953–1959. Goldstein, B.I., Fagiolini, A., Houck, P., Kupfer, D.J., 2009. Cardiovascular disease and hypertension among adults with bipolar I disorder in the United States. Bipolar Disord. 11, 657–662. Grant, B.F., Goldstein, R.B., Saha, T.D., Chou, S.P., Jung, J., Zhang, H., Pickering, R.P., Ruan, W.J., Smith, S.M., Huang, B., Hasin, D.S., 2015. Epidemiology of DSM-5 alcohol use disorder: results from the National Epidemiologic Survey on Alcohol and Related Conditions III. JAMA Psychiatry 72, 757–766. Health Promotion Administration, Ministry of Health and Welfare, Taiwan. 2002. 2002 survey on prevalence of hypertension, hyperglycemia, and hyperlipidemia in Taiwan. http://www.hpa.gov.tw/English/ClassShow.aspx?No=200803260038 (accessed 14.04.24).

18

Hwang, L.C., Bai, C.H., Chen, C.J., 2006. Prevalence of obesity and metabolic syndrome in Taiwan. J. Formos. Med. Assoc. 105, 626–635. Krishnan, K.R., 2005. Psychiatric and medical comorbidities of bipolar disorder. Psychosom. Med. 67, 1–8. Kupfer, D.J., Frank, E., Ritchey, F.C., 2015. Staging bipolar disorder: what data and what models are needed? Lancet Psychiatry 2, 564–570. McElroy, S.L., Keck, P.E. Jr., 2014. Metabolic syndrome in bipolar disorder: a review with a focus on bipolar depression. J. Clin. Psychiatry 75, 46–61. McLellan, A.T., Luborsky, L., Woody, G.E., O’Brien, C.P., 1980. An improved diagnostic evaluation instrument for substance abuse patients. The Addiction Severity Index. J. Nerv. Ment. Dis. 168, 26–33. Osborn, D.P., Hardoon, S., Omar, R.Z., Holt, R.I., King, M., Larsen, J., Marston, L., Morris, R.W., Nazareth, I., Walters, K., Petersen, I., 2015. Cardiovascular risk prediction models for people with severe mental illness: results from the prediction and management of cardiovascular risk in people with severe mental illnesses (PRIMROSE) research program. JAMA Psychiatry 72, 143–151. Perugi, G., Micheli, C., Akiskal, H.S., Madaro, D., Socci, C., Quilici, C., Musetti, L., 2000. Polarity of the first episode, clinical characteristics, and course of manic depressive illness: a systematic retrospective investigation of 320 bipolar I patients. Compr.

19

Psychiatry 41, 13–18. Ramsey, C.M., Leoutsakos, J.M., Mayer, L.S., Eaton, W.W., Lee, H.B., 2010. History of manic and hypomanic episodes and risk of incident cardiovascular disease: 11.5 year follow-up from the Baltimore Epidemiologic Catchment Area Study. J. Affect. Disord. 125, 35–41. Sajatovic, M., Bingham, C.R., Campbell, E.A., Fletcher, D.F., 2005. Bipolar disorder in older adult inpatients. J. Nerv. Ment. Dis. 193, 417–419. Sajatovic, M., Strejilevich, S.A., Gildengers, A.G., Dols, A., Al Jurdi, R.K., Forester, B.P., Kessing, L.V., Beyer, J., Manes, F., Rej, S., Rosa, A.R., Schouws, S.N., Tsai, S.Y., Young, R.C., Shulman, K.I., 2015. A report on older-age bipolar disorder from the International Society for Bipolar Disorders Task Force. Bipolar Disord. 17, 689-704. Shapiro, J., Mindra, S., Timmins, V., Swampillai, B., Scavone, A., Collinger, K., Collins, J., Goldstein, B.I., 2016. Controlled study of obesity among adolescents with bipolar disorder. J. Child. Adolesc. Psychopharmacol. doi: 10.1089/cap.2015.0154. Slomka, J.M., Piette, J.D., Post, E.P., Krein, S.L., Lai, Z., Goodrich, D.E., Kilbourne, A.M., 2012. Mood disorder symptoms and elevated cardiovascular disease risk in patients with bipolar disorder. J. Affect. Disord. 138, 405–408. Sodhi, S.K., Linder, J., Chenard, C.A., Miller, del D., Haynes, W.G., Fiedorowicz, J.G., 2012. Evidence for accelerated vascular aging in bipolar disorder. J. Psychosom. Res. 73, 175–

20

179. Tang, H.C., Chen, P.H., Chung, K.H., Kuo, C.J., Huang, S.H., Tsai, S.Y., 2015. Psychological outcomes and medical morbidity of patients with bipolar disorder and co-occurring alcohol use disorder. J. Dual Diagn. 11, 184–188. Tsai, S.Y., Lee, C.H., Kuo, C.J., Chen, C.C., 2005. A retrospective analysis of risk and protective factors for natural death in bipolar disorder. J. Clin. Psychiatry 66, 1586–1591. Tsai, S.Y., Kuo, C.J., Chung, K.H., Huang, Y.L., Lee, H.C., Chen, C.C., 2009. Cognitive dysfunction and medical morbidity in elderly outpatients with bipolar disorder. Am. J. Geriatr. Psychiatry 17, 1004–1011. Vancampfort, D., Vansteelandt, K., Correll, C.U., Mitchell, A.J., De Herdt, A., Sienaert, P., Probst, M., De Hert, M., 2013. Metabolic syndrome and metabolic abnormalities in bipolar disorder: a meta-analysis of prevalence rates and moderators. Am. J. Psychiatry 170, 265–274. Vancampfort, D., Sienaert, P., Wyckaert, S., De Hert, M., Stubbs, B., Probst, M., 2016. Sitting time, physical fitness impairments and metabolic abnormalities in people with bipolar disorder: An exploratory study. Psychiatry Res. 242, 7–12. Vuksan-Ćusa, B., Jakovljević, M., Sagud, M., Mihaljević Peleš, A., Marčinko, D., Topić, R., Mihaljević, S., Sertić, J., 2011. Metabolic syndrome and serum homocysteine in patients with bipolar disorder and schizophrenia treated with second generation antipsychotics.

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Psychiatry Res. 189, 21–25. Weiner, M., Warren, L., Fiedorowicz, J.G., 2011. Cardiovascular morbidity and mortality in bipolar disorder. Ann. Clin. Psychiatry 23, 40–47. Westman, J., Hallgren, J., Wahlbeck, K., Erlinge, D., Alfredsson, D., Osby, U., 2013. Cardiovascular mortality in bipolar disorder: a population-based cohort study in Sweden. BMJ Open 3, pii: e002373. Wildes, J.E., Marcus, M.D., Fagiolini, A., 2006. Obesity in patients with bipolar disorder: a biopsychosocial-behavioral model. J. Clin. Psychiatry 67, 904–915. Wilson, P.W., Castelli, W.P., Kannel, W.B., 1987. Coronary risk prediction in adults: the Framingham Heart Study. Am. J. Cardiol. 59, 91G–94G.

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Table 1 Comparison of sociodemographic characteristics between cases and age- and sex-matched controls Cases

Controls

(N=124)

(N=124)

Category variables

N

%

N

%

χ2

p

Male

42

33.9

42

33.9

0.00

0.893

Education > 9 years

66

53.2

68

54.8

0.11

0.745

Married/widowed

93

75.0

102

82.3

1.94

0.163

Living with nuclear family

105

84.7

107

86.3

0.13

0.718

First-degree family history of

41

33.1

43

34.7

0.07

0.788

History of cigarette smoking

33

26.6

32

25.8

0.02

0.885

History of regular alcohol use

16

12.9

14

11.3

0.07

0.784

major psychiatric disorder

23

Table 2 Comparison of bipolar characteristics between cases and age- and sex-matched controls

Continuous variables

Cases

Controls

(N=124)

(N=124)

Mean

SD

Mean

SD

t

P

Age at onset of bipolar disorder, years

31.9

11.1

32.0

10.7

-0.09

0.930

Age at the first psychiatric admission, years

34.8

11.8

34.5

11.8

0.18

0.857

Age at the most recent psychiatric admission,

59.5

5.4

59.7

5.6

-0.32

0.746

Total number of psychiatric hospitalizations

4.8

4.1

5.4

4.5

-1.16

0.247

Category variables

N

%

N

%

χ2

First episode mania

102

82.3

84

67.7

8.66

0.013

History of depressive episode

61

49.2

53

42.7

1.04

0.308

History of rapid cycling

21

16.9

26

21.0

0.66

0.418

History of psychotic features

66

53.2

66

53.2

0.00

1.000

Lithium

40

32.2

49

39.5

1.42

0.233

Valproate

71

57.3

76

61.3

0.42

0.518

years

Psychotropic drugs used during the most recent hospitalization

24

Carbamazepine

13

10.5

3

2.4

6.68

0.010

Lamotrigine

1

1.0

4

3.2

1.84

0.175

First generation antipsychotics

28

22.6

19

15.3

2.13

0.145

Second generation antipsychotics

84

67.7

98

79.0

4.05

0.044

Antidepressants

6

4.8

10

8.1

1.07

0.301

β-blockers

26

21.0

24

19.4

0.10

0.752

25

Table 3 Comparison of cardiometabolic characteristics between cases and age- and sex-matched controls during the most recent hospitalization

Continuous variables

Cases

Controls

(N=124)

(N=124)

Mean

SD

Mean

SD

t

P

Body mass index, kg/m2

26.3

4.4

24.9

4.2

2.40

0.017

Fasting serum glucose, mg/dL

117.9

47.0

108.8

47.9

1.48

0.139

Serum total cholesterol, mg/dL

189.3

37.3

182.4

43.2

1.25

0.211

Serum high-density lipoprotein, mg/dL

48.0

11.1

52.2

16.1

-1.54

0.100

Serum low-density lipoprotein, mg/dL

112.0

39.4

112.6

42.3

-0.08

0.940

Serum triglycerides, mg/dL

138.1

54.6

125.0

50.9

1.26

0.208

Creatinine, mg/dL

0.96

0.69

0.85

0.28

1.16

0.097

Thyroxine, μg/dL

1.28

0.27

1.26

0.25

1.24

0.214

Category variables

N

%

N

%

χ2

Obesity

46

37.1

31

25.0

4.24

0.049

Overweight

36

29.0

38

30.6

0.08

0.781

Diabetes mellitus

54

43.5

31

25.0

9.47

0.002

Impaired fasting glucose

22

17.7

27

21.8

0.63

0.425

Dyslipidemia

43

34.7

48

38.7

0.43

0.510

26

Renal disease Thyroid disease

9

7.3

5

4.0

1.21

0.271

14

11.3

12

9.7

0.17

0.678

Table 4 Logistic regression of factors for cardiovascular diseases in patients with older-age bipolar disorder Factors

Adjusted OR

95% CI for OR

P

Diabetes mellitus

2.36

1.31-4.26

0.001

Obesity

1.72

0.94-3.13

0.079

First episode mania

2.16

1.12-4.17

0.004

Carbamazepine use in the most recent

1.00

1.00-1.01

0.072

0.99

0.98-0.99

0.031

hospitalization Second generation antipsychotic use in the most recent hospitalization Goodness of fit: χ2 =10.02, p=0.264 Abbreviations: OR=odds ratio, CI=confidence interval

Highlights   

Cardiovascular diseases (CVDs) are prevalent in older-age bipolar disorder (BD). Diabetes mellitus along with mania increase risk for CVD in older-age BD. Studies need to elucidate risk factors for CVDs specific to BD across lifespan.

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