Controlled Study of Obesity Among Adolescents with Bipolar Disorder

Abstract

Objective:

Despite numerous studies regarding obesity (OB) in adult bipolar disorder (BP), there are few studies on this topic among adolescents. The current study attempts to extend the literature on prevalence and correlates of OB in adolescent BP by including control participants, and determining OB by direct measurement.

Methods:

Participants were 75 treatment-seeking adolescents, ages 13–19 years, with BP-I, -II, or -not otherwise specified, and 47 adolescents without major psychiatric illness. Diagnoses and clinical characteristics were assessed using the Kiddie Schedule for Affective Disorders and Schizophrenia for School Age Children, Present and Lifetime version (KSADS-PL). Family psychiatric history was assessed using the Family History Screen. OB was defined as adjusted body-mass index ≥95th percentile. Variables associated with OB in univariate analyses informed variable selection for within-group logistic regression analysis among BP adolescents.

Results:

BP participants had a significantly higher rate of OB (18%) compared to controls (4%; χ² = 5.3; p = 0.02). BP remained a significant predictor for OB when controlling for race (odds ratio [OR] = 5.1, 95% confidence interval [CI] = 1.1–24.0, p = 0.04). In univariate analyses among BP adolescents, OB was significantly associated with suicide attempt, self-injurious behavior, and oppositional defiant disorder. In multivariable analyses, suicide attempt and antidepressants that were not selective serotonin reuptake inhibitors were significantly associated with OB.

Conclusions:

OB is excessively prevalent among adolescents with BP and is associated with proxies for illness severity, including suicide attempts. Additional research is warranted to identify strategies to prevent and treat OB among BP adolescents, and to elucidate processes underlying the elevated risk of suicide attempts.

Introduction

Bipolar disorder (BP) is a prevalent and burdensome illness characterized by psychiatric comorbidity, functional impairment, and neurocognitive dysfunction (Krishnan 2005; Goldberg and Chengappa 2009). In addition to symptomatic burden, cardiovascular disease (CVD) rates are elevated in adults with BP, and CVD occurs at earlier ages than in adults without mood disorders (Kilbourne et al. 2004; Goldstein et al. 2009). The prevalence of obesity (OB), an important CVD risk factor, is increased among adults with BP (McIntyre et al. 2006; Goldstein et al. 2011). Moreover, OB in BP is associated with markers of illness severity (Fagiolini et al. 2002; McElroy et al., 2002; Fagiolini et al. 2003), such as suicidality (McElroy et al. 2002; Fagiolini et al. 2005).

Few studies have examined OB among adolescents with BP. Rates of OB are also elevated in adolescent BP (Goldstein et al. 2008; Jerrell et al. 2010; Goldstein et al. 2011). The etiological factors underlying increased prevalence of OB in BP remain unclear, as existing evidence supports a multifactorial explanatory model (Wildes et al. 2006). Psychotropic medications are often cited as contributors to OB in BP, as second generation antipsychotics and other commonly used medications can cause weight gain (Fagiolini et al. 2002; Keck and McElroy 2003).

Correlates of overweight/OB in adolescents with BP include younger age, history of physical abuse, non-Caucasian race, substance use disorder, psychiatric hospitalization, female gender, and greater exposure to treatments associated with weight gain (Goldstein et al. 2008; Jerrell et al. 2010). Despite these preliminary findings, studies regarding OB among youth with BP have been constrained by two primary limitations: Lack of a control group (Goldstein et al. 2008) and lack of direct measurement of OB (Goldstein et al. 2008; Jerrell et al. 2010). In addition, previous studies are based primarily on samples from the United States, and there may be cross-national differences relevant to OB in BP (Weissman et al. 1996).

The present study seeks to extend the literature on OB in adolescent BP by examining this topic in a Canadian sample, determining OB based on direct measurement, and comparing adolescents with BP with a control group without major psychiatric disorders. We hypothesized that OB would be more prevalent among BP adolescents than among controls, and that, among BP adolescents, OB would be associated with female gender, weight-promoting psychotropic medications, suicide attempts, physical or sexual abuse, and substance use disorder.

Methods

Sample and setting

Demographic characteristics of study participants are listed in Table 1. The current study includes 75 adolescents, ages 13–19 years, with BP-I, -II, or -not otherwise specified (NOS) and 47 adolescents without major psychiatric illness. Participants with BP were seeking assessment and/or treatment at a subspecialty clinic in a tertiary academic health sciences center. Data were extracted from patient and control research registries, each with its own protocol approved by the institutional review board. Written informed consent was provided by adolescents and parent/guardians (at least one per adolescent) before study commencement. At least one parent/guardian for each adolescent also participated in the interview. Control participants were recruited through advertisements, and did not have a history of depression or BP, psychosis, or substance abuse/dependence. Control participants also did not have a first- or second-degree family history of BP, schizophrenia, or psychosis.

Table 1.

Characteristics of Adolescents with Versus Those Without Bipolar Disorder

	Overall (n = 122)	Bipolar (n = 75)	Control (n = 47)
	mean ± SD	mean ± SD	mean ± SD	Statistic ^a	p
Age	16.0 ± 1.5	16.1 ± 1.5	15.8 ± 1.7	−1.0	0.30
Socioeconomic status	50.8 ± 12.7	49.8 ± 13.0	52.4 ± 12.2	1.1	0.27
	n(%)	n(%)	n(%)
Gender (males)	47(38)	26(35)	21(45)	1.2	0.27
Race (white)^b,c	93(77)	63(84)	30(65)	5.7	0.02^*
Intact family,^b,c,d	68(56)	43(57)	25(54)	0.1	0.75
Obese^e	16(13)	14(18)	2(4)	5.3	0.02^*

p < 0.05.

Two tailed Pearson χ² analyses were performed for categorical variables and two tailed t tests were conducted for continuous variables.

n = 46 for control group.

n = 121 overall.

Subject lives with both biological parents.

Body mass index (BMI) at or above the 95th percentile.

Subject assessment

Current and lifetime diagnoses of BP were determined via the Kiddie Schedule for Affective Disorders and Schizophrenia for School Age Children, Present and Lifetime version (KSADS-PL) (Kaufman et al. 1997), which uses information from both adolescents and their parent(s). Interviewers completed KSADS training under the guidance of B.G. and had a bachelor's or master's degree in a health sciences field. The mood sections of the KSADS-PL were substituted with the KSADS Depression Rating Scale (DRS) (Chambers et al. 1985) and KSADS Mania Rating Scale (MRS) (Axelson et al. 2003). All available information was factored into diagnoses, clinical judgement was used when information conflicted, and diagnoses were confirmed in consensus meetings with a child psychiatrist (B.G.). The KSADS-PL, MRS, and DRS were also completed with control participants.

Criteria for BP-NOS was operationalized according to the criteria used in the Course and Outcome of Bipolar Illness in Youth (COBY) study (Birmaher et al. 2006): Elevated and/or irritable mood, plus 1) two Diagnostic and Statistical Manual of Mental Disorder, 4th ed. (DSM-IV) manic symptoms (three if only irritable mood is reported), 2) change in functioning, 3) mood and symptom duration of at least 4 hours during a 24 hour period, and 4) at least four cumulative 24 hour periods of episodes over the participant's lifetime that meet the mood, symptom severity, and functional change criteria (American Psychiatric Association 1994).

Age of BP onset was defined as the age at which the individual first experienced an episode of mania, hypomania, or major depressive disorder according to DSM-IV, or when study criteria for BP-NOS was met. A parent-reported medical history questionnaire and the posttraumatic stress disorder screen within the KSADS-PL were used to ascertain history of physical and sexual abuse. A Safety Assessment Form, an interviewer-administered questionnaire, was used to ascertain information regarding lifetime aggression and suicidality. Dimensional traits such as impulsivity, emotional dysregulation, identity confusion, and interpersonal problems were examined using the Life Problems Inventory (LPI) self-report (Rathus and Miller 1995). The self-reported Children's Affective Lability Scale (CALS) assesses affect regulation and was completed by the participants and their parents (Gerson et al. 1996). The Family History Screen (Weissman et al. 2000) was used to obtain information regarding psychiatric status and history of first- and second-degree relatives from the adolescent and parent. Socioeconomic status (SES) was determined via the four factor Hollingshead Scale (Hollingshead 1975). Weight-promoting medications were defined as antimanic anticonvulsants, second generation antipsychotics, and lithium.

Height and weight were measured, using a Tanita scale and separate stadiometer, in accordance with the National Health and Nutrition Examination (NHANES) anthropometry procedures manual (2007). Weight was adjusted according to clothing (1.4 kg for long pants and long shirt/sweatshirt, 1.1 kg for short pants or short sleeves, and 0.9 kg for both short pants and short sleeves). Participants with body mass index (BMI) at or above the 95th percentile, based on CDC norms, were considered obese (Ogden et al., 2014).

Data analysis

Univariate analyses for categorical data, used to screen variables for association with OB or BP illness status, consisted of χ² and Fisher exact tests. Where variables were continuous, t tests were performed. For the purpose of this analysis, the dimensional LPI questionnaire was dichotomized as high score versus low score on the basis of a median split. The median score was 152. Variables with p < 0.2 in univariate analyses were entered into a backward elimination Wald logistic regression model. Significance level on two tailed tests was set to α = 0.05. The Statistical Package for the Social Sciences Version 21 (SPSS) was used to perform statistical analyses.

Results

Sociodemographic characteristics of adolescents with BP versus healthy controls

Sociodemographic characteristics of adolescents with BP and healthy controls can be found in Table 1. There were no significant between-group differences in age, gender, SES, or whether or not the subject was living with both natural parents. However, adolescents with BP were more likely to be Caucasian (χ² = 5.7; p = 0.02). The prevalence of OB was significantly elevated in the BP group (18%) compared with the control group (4%; χ² = 5.3; p = 0.02). Age, gender, SES, and living with both natural parents were not significantly associated with BP. The Hosmer–Lemeshow test was used to confirm that the logistic regression model was appropriate (p = 0.74). When controlling for race, the association between OB and BP remained significant (odds ratio [OR] = 5.1, 95% confidence interval [CI] = 1.1–24.0, p = 0.04). Race was also significant (OR = 2.8, 95% CI = 1.2–6.8, p = 0.02). The interaction term for BP and race was tested and was not significant.

Correlates of OB among adolescents with BP

Sociodemographic, clinical, and familial characteristics of adolescents with BP with and without OB can be found in Table 2. There were no significant associations between demographic characteristics or family psychiatric history and OB. There were associations of OB with history of suicide attempt (p = 0.001), self-injurious behaviour (χ² = 4.4; p = 0.04), and oppositional defiant disorder (ODD) (χ² = 5.3; p = 0.02). OB was not significantly associated with the number of weight-promoting medications used.

Table 2.

Characteristics of Adolescents with Bipolar Disorder (BP) with Versus Those Without Obesity

	Overall (n = 75)	Obese (n = 14)	Not obese (n = 61)	Statistic ^a	p
Demographics	mean ± SD	mean ± SD	mean ± SD
Age	16.1 ± 1.5	15.9 ± 1.7	16.2 ± 1.4	0.71	0.48
Socioeconomic status	49.8 ± 13.0	47.0 ± 15.9	50.4 ± 12.4	0.88	0.38
	n (%)	n (%)	n (%)
Gender (males)	49(65)	3(21)	23(38)	-	0.35
Race (white)	63(84)	11(79)	52(85)	-	0.69
Intact family^b	43(57)	9(64)	34(56)	0.34	0.56
Clinical characteristics
BP subtype				-	0.42
BP-I	19(25)	2(14)	17(28)
BP-II	32(43)	9(64)	23(38)
BP-NOS	24(32)	3(21)	21(34)
Psychiatric hospitalization^c	33(47)	7(54)	26(46)	0.29	0.59
Psychosis	20(27)	4(29)	16(26)	-	1.00
Suicide attempt^d	20(27)	9(64)	11(18)	-	0.001^**
Self-injurious behavior	40(53)	11(79)	29(48)	4.4	0.04^*
Physical or sexual abuse^e	4(5)	0(0)	4(7)	-	1.00
Physical abuse^e	4(5)	0(0)	4(7)	-	1.00
Sexual abuse^f	1(1)	0(0)	1(2)	-	1.00
LPI^g (% high)^h	38(54)	9(69)	29(50)	1.6	0.21
	mean ± SD	mean ± SD	mean ± SD
Birth weight (kg)ⁱ	3.27 ± 0.59	3.14 ± 0.64	3.36 ± 0.50	1.0	0.30
Comorbidity	n(%)	n(%)	n(%)
ADHD	32(43)	5(36)	27(44)	0.34	0.56
SUD	27(36)	7(50)	20(33)	1.5	0.23
ODD	28(37)	9(64)	19(31)	5.3	0.02^*
Anxiety	60(80)	11(79)	49(80)	-	1.00
MDE^j	63(88)	13(93)	50(86)	-	0.68
Lifetime medication	mean ± SD	mean ± SD	mean ± SD
Total number of weight-promoting medications^k	0.73 ± 0.81	0.86 ± 1.1	0.70 ± 0.74	−0.63	0.53
	n(%)	n(%)	n(%)
Second generation antipsychotics^l	39(52)	6(43)	33(54)	0.58	0.45
Lithium	11(15)	3(21)	8(13)	-	0.42
SSRI antidepressants^m	26(35)	7(50)	19(31)	-	0.22
Non-SSRI antidepressantsⁿ	8(11)	3(21)	5(8)	-	0.16
Stimulants^o	14(19)	2(14)	12(20)	-	1.00
Family history^p
Mania/ hypomania	42(56)	9(64)	33(54)	0.48	0.49
MDE	59(79)	12(86)	47(77)	-	0.72
ADHD	25(33)	3(21)	22(36)	-	0.36
SUD	37(49)	6(43)	31(51)	0.29	0.59
Anxiety	41(55)	10(71)	31(51)	1.9	0.16

p < 0.05.

p < 0.01

Two tailed Pearson χ² or Fisher's exact test (indicated by a dash) analyses were performed for categorical variables, and two tailed t tests were conducted for continuous variables.

Subject lives with both biological parents.

n = 70 overall, n = 13 for obese group, n = 57 for non-obese group.

n = 74 overall, n = 60 for non-obese group.

n = 74 overall, n = 13 for obese group.

n = 73 overall, n = 59 for non-obese group.

Life Problems Inventory; measures borderline personality spectrum symptoms.

n = 71 overall, n = 13 for obese group, n = 58 for non-obese group.

n = 66 overall, n = 12 for obese group, n = 54 for non-obese group.

n = 72 overall, n = 14 for obese group, n = 58 for non-obese group.

Weight-promoting medication = antimanic anticonvulsants, second generation antipsychotics, lithium.

Second generation antipsychotics = risperidone, olanzapine, aripiprazole, ziprasidone, quetiapine.

SSRI antidepressants = sertraline, paroxetine, fluoxetine, fluvoxamine, citalopram, escitalopram.

Non-SSRI antidepressants = bupropion, mirtazapine, venlafaxine, duloxetine.

Stimulants = methylphenidate, amphetamine, dextroamphetamine,

First and second degree.

BP, bipolar disorder; BP-I, bipolar I disorder; BP-II, bipolar II disorder; BP-NOS, bipolar disorder not otherwise specified; ADHD, attention-deficit hyperactivity disorder; SUD, substance use disorder; ODD, oppositional defiant disorder; MDE, major depressive episode; SSRI, selective serotonin reuptake inhibitor.

The multivariable analysis included the following variables: ODD, family history of anxiety, use of selective serotonin reuptake inhibitor (SSRI) antidepressants or non-SSRI antidepressants, history of suicide attempt, and self-injurious behaviour. The Hosmer–Lemeshow test determined that the model was a good fit (p = 0.87). History of suicide attempt (OR = 11.7, 95% CI = 2.7–50.1, p = 0.001) and use of non-SSRI antidepressants (OR = 6.9, 95% CI = 1.1–45.4, p = 0.04) were retained in the model, whereas self-injurious behaviour and ODD were not. Multicollinearity was not a concern, as Pearson's r correlation between history of suicide attempt and use of non-SSRI antidepressants was −0.114.

Discussion

To our knowledge, this is the first study in adolescents with BP to implement case–control design in examining OB as determined by directly measured height and weight. As predicted, prevalence of OB was elevated in adolescents with BP (18%) compared with healthy controls (4%). OB in adolescents with BP was significantly associated history of suicide attempt, self-injurious behaviour, and ODD. In multivariable analysis, non-SSRI antidepressant use and history of suicide attempt were significantly associated with OB.

The 18% rate of OB in the current study is similar to the rate found in a large study on OB in pediatric BP that was part of the COBY study (Goldstein et al. 2008), which found an OB prevalence of 16.5% in a sample of children and adolescents with BP. Studies on adults with BP tend to report higher prevalence of OB, with findings ranging from 21% to 50% (McElroy et al. 2002; Shah et al. 2006; Fiedorowicz et al. 2008; Goldstein et al. 2013). The prevalence of OB in Canadian adolescents ages 12–17 in the general population from 2009–2011 (10%) is higher than that among controls in the present study (Roberts et al. 2012). Although the rate of OB was very low in the control group (which was also characterized by very low rates of psychopathology), the rate of obesity in the BP group was also greater than that of the contemporaneous general population of Canadian adolescents.

In accordance with the hypothesis, history of suicide attempts was significantly associated with OB in adolescent BP. This converges with literature in adults (Fagiolini et al. 2005; Gomes et al. 2010; Goldstein et al. 2013), but not with the COBY study (Goldstein et al. 2008). Self-injurious behavior, which is associated with suicide attempts in adolescent BP (Goldstein et al. 2005), also predicted OB. Whereas the COBY study did not examine self-injurious behavior, adolescents who perceive themselves as overweight have previously been shown to be at greater risk for deliberate self-harm (Brunner et al. 2007).

ODD was significantly associated with OB in univariate analysis. Although ODD is related to chronic OB in adolescents (Mustillo et al. 2003), no study has reported a link to obese BP patients in particular. Association of OB with non-SSRI antidepressants was also significant. This is in line with a study (Jerrell et al. 2011) on adolescents with BP that found overweight and OB to be associated with serotonin-norepinephrine reuptake inhibitors and heterocyclic antidepressants. These findings were not mirrored in the COBY study (Goldstein et al. 2008). Differences in several findings between the current study and the COBY study may be related to cross-national factors, the inclusion of children together with adolescents in the COBY study, the lack of directly measured BMI in the COBY study, or other factors.

Counter to the hypothesis, obese and non-obese BP adolescents did not differ significantly in lifetime exposure to weight-promoting medication. Many studies find associations between use of weight-promoting medication and overweight or OB in adults (McElroy et al. 2002; Keck and McElroy 2003; McIntyre et al. 2006) and adolescents (Goldstein et al. 2008) with BP. However, the prevalence of OB has been found to be increased in medication-naïve clinical BP samples (Maina et al. 2008), which suggests that factors other than medications are also contributory. The dichotomous measurement approach for medication exposure used in the current study has yielded positive findings regarding medication and OB in past research (Goldstein et al. 2008). Nonetheless, the current approach to measurement of medication exposure, as well as small sample size, mean that the possibility of a type II error should be considered.

There are several limitations to the current study. Adolescents with BP were treatment-seeking patients in a subspecialty clinic of a tertiary hospital, and controls were recruited through advertisements. These samples may not be representative of adolescents with BP and controls in the general population. This is apparent in the discrepancy in the prevalence of OB in the control group compared with Canadian adolescents in general. The chronology of the development of OB and BP could not be determined, given the cross-sectional retrospective nature of this study. Therefore, it is possible that patients with more severe and/or longer course of illness may have had higher risk of obesity because of greater cumulative exposure to weight-promoting medication. These participants may have also had higher risk of self-harm. Future prospective studies are warranted in order to elucidate the direction of the observed associations. Given the focus of the current study, data on family history of OB may have helped yield further insights; however, this information was not collected systematically, and was therefore omitted. Finally, this study examined a large number of variables, which increases the probability of type I error. Given the limited available data on correlates of OB in adolescents with BP, the current design was chosen over a more conservative approach. Multivariable analyses were included in order to militate against confounding and false positives, although the possibility of type I errors cannot be eliminated.

Conclusions

The current study yielded both expected and novel findings relative to the literature on adolescents and adults, including several notable negative results. OB in BP is associated with some factors that relate to more severe course of illness, and is linked to CVD, which is the primary cause of early mortality in BP. Although the etiology of OB in BP remains unclear, the current study contributes to an understanding of the characteristics of this phenotype in adolescents. Furthering knowledge on this comorbidity in adolescents is important, as attention to precipitating factors and associated characteristics can lead to better treatment approaches for young patients, and improve outcomes through development into adulthood.

Clinical Significance

The results of the present study have clinical significance in light of the limited literature on OB in adolescents with BP. The prevalence of OB among adolescents with BP in this study is substantially higher than in the controls in the study, and is also higher than the population prevalence of OB among Canadian adolescents. This study also replicates the previously reported association between OB and suicidality in BP. Obese BP patients may require closer monitoring in regards to suicidality. Further research on this topic is needed to guide approaches toward prevention and treatment of OB in BP early in its development, and to better understand the association between OB and suicidality in BP.

Footnotes

Acknowledgments

The authors thank the study participants.

Disclosures

No competing financial interests exist.

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