Determinants of Overweight and Obesity in Patients With Bipolar Disorder

Elmslie, Jane; Mann, J; Silverstone, J. T.; Williams, SM; Romans, Sarah

doi:10.4088/jcp.v62n0614

Cited by 179 publications

(126 citation statements)

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“…This finding was also in contrast to observations of other workers who have reported a significant increase in the prevalence of MS in BPD patients. The increased prevalence of obesity in BPD patients reported in most western studies is possibly related to the dietary habits of these patients who consume more sugar and carbohydrates than controls [27,28]. The absence of an increased prevalence of MS in BPD in our study is likely to be due to lifestyle differences in the Western versus the Indian population but, to our knowledge, no study has specifically handled this issue [29].…”

Section: Discussionmentioning

confidence: 55%

Assessment of Insulin Resistance and Metabolic Syndrome in Drug Naive Patients of Bipolar Disorder

et al. 2013

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The levels of fasting glucose, fasting insulin, insulin resistance (IR) and the prevalence of metabolic syndrome (MS) in a sample population of bipolar disorder (BPD) patients who were newly diagnosed and psychotropically naïve were assessed and compared with an age, sex and racially matched control population. 55 BPD-I patients (15-65 years) who were non-diabetic, nonpregnant, and drug naïve for a period of at least 6 months were included in the study. Diagnosis was made using the structured clinical interview for DSM-IV axis I disorders (SCID IV). IR was assessed using homeostasis model of insulin resistance (HOMA-IR); MS was defined according to National Cholesterol Education Program-Adult Treatment Panel III (NCEP-ATP III). Data were compared with 25 healthy controls. BPD patients had significantly higher mean levels of fasting plasma insulin (13.2 ± 9.2 vs. 4.68 ± 3.1 lIU/ ml, p \ 0.05), postprandial plasma insulin (27.2 ± 14.5 vs. 18.1 ± 9.3 lIU/ml, p \ 0.05) and a higher value of HOMA-IR (3.16 ± 2.2 vs. 1.19 ± 0.8, p \ 0.05) when compared to the controls. A significantly higher proportion of patients of BPD compared to controls were manifesting levels of fasting plasma glucose, serum triglyceride and blood pressure higher than the cut off while waist circumference and serum HDL cholesterol failed to show any significant difference in the proportion. There was a significantly higher proportion of prevalence of IR between BPD cases and controls (26/55 vs. 2/25, z value 9.97, p \ 0.05) while there was no significant difference in proportion of prevalence of MS between these two groups. Within BPD patients, logistic regression analysis showed that age, sex or current mood status (depressed/ manic) were not significantly predictive of presence or absence of MS or increased IR.

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Section: Discussionmentioning

confidence: 55%

Assessment of Insulin Resistance and Metabolic Syndrome in Drug Naive Patients of Bipolar Disorder

et al. 2013

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“…16 studies used as part or in full an OBM to capture physical activity Berle, Hauge, Oedegaard, Holsten, & Fasmer, 2010;Farrow, Hunter, Wilikinson, Green, & Spence, 2005;Gothelf et al, 2002;Hauge, Berle, Oedegaard, Holsten, & Fasmer, 2011;Janney et al, 2008;Jerome et al, 2009;McCormick et al, 2009;McCormick et al, 2008;McKibbin et al, 2006;Scheewe, 2008;Scheewe et al, 2011;Sharpe et al, 2006a;Wichniak et al, 2011;Yamamoto et al, 2011. 19 studies utilised SRQs Archie et al, 2007Arbour, Faulkner, & Cohn, 2010;Brown, Birtwistle, Roe, & Thompson, 1999, Brown, Goetz, Van Sciver, Sullivan, & Hamera, 2006Dubbert et al, 2006;Ellingrod et al, 2011;Elmslie, Mann, Silverstone, Williams, & Romans, 2001;Faulkner et al, 2006;Lassenigus, kerlind, Wiklund-Gustin, Arman, & Söderlund, 2013;Lindamer et al, 2008;McLeod, Jaques, & Deane, 2009;Osborn, Nazareth, & King, 2007;Ratliff et al, 2012;Ussher, 2003;Ussher, Doshi, Sampuran, & West, 2011;Van Citters et al, 2010;Vancampfort, Probst, Knapen, Carraro, & De Hert, 2012. Excluded studies (with reason) 55 did not use an outcome measure that provided an assessment of the three fundamental domains of physical activity Acil, Dogan, & Dogan, 2008;Adams, 1995;Aquila, 2000;Archie,...…”

Section: The Identification Of the Different Outcome Measures Usedmentioning

confidence: 99%

“…One major problem of studies measuring physical activity is the failure of researchers to consider or justify why they have chosen a particular OBM or SRQ. For example past research studies (Archie et al, 2007;Brill et al, 2007;Buhagiar et al, 2011;Chuang et al, 2008;Crone et al, 2004;Daumit et al, 2005;Davidson et al, 1999;Davidson et al, 2001;Ellingrod et al, 2011;Elmslie et al, 2001;Farnam et al, 1999;Lassenigus et al, 2013;McCreadie, 2003;Osborn et al, 2007;Ratliff et al, 2012;Samele et al, 2007;SØrensen, 2006;Van Citters et al, 2010;Vancampfort et al, 2011a,b,c;Vancampfort et al (2011d) have utilised a specific SRQ and justified its choice solely on the original study which validated the SRQ. This is often problematic if the tool has been validated in a certain population or if the original study was not validated correctly.…”

Section: The Problems Regarding the Justification Of Outcome Measure mentioning

confidence: 99%

Selection, Use and Psychometric Properties of Physical Activity Measures to Assess Individuals with Severe Mental Illness: A Narrative Synthesis

Soundy¹,

Roskell²,

Stubbs³

et al. 2014

Archives of Psychiatric Nursing

128

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a b s t r a c tThis research provides a critical consideration of the outcome measures used to assess physical activity in individuals with severe mental illness. A narrative synthesis was utilised to provide a simple juxtapose of the current research. A sensitive topic-based search strategy was conducted in order to identify studies that met the eligibility criteria. Fifty two studies met the inclusion criteria and 5 were identified specially as validation studies. The current research identified several methodological shortcomings. The justification and choice of outcome measure used is often weak and only five studies have validated a specific outcome measure of physical activity. Within these validation studies, the validation process often lacked a consideration of agreement between measures. Accelerometers have been most frequently used as a criterion measure, notably the RT3 tri-axial accelerometer. Objective based measures may be best placed to consider physical activity levels, although, methodological considerations for the utilization of such tools is required. Self-report questionnaires have benefits for use in this population but require further validation. Researchers and clinicians need to carefully consider what outcome measure they are using and be aware of the development, scope and purpose of that measure.Crown

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“…7 Other factors, such as reduction in physical activity (secondary to sedation caused by some of those drugs), increased thirst, leading to excessive consumption of sweet beverages, and recovery of weight loss caused by the mental disorder should also be considered. 4,7,[13][14][15][16] Several studies about antipsychotic-induced weight gain have focused on brain neurotransmitter systems. Transmission mediated by α-adrenergic receptors seems to stimulate appetite, whereas transmission mediated by β-adrenergic, histaminergic and dopaminergic receptors causes satiety.…”

Section: Etiologic Factorsmentioning

confidence: 99%

Efeitos adversos metabólicos de antipsicóticos e estabilizadores de humor

Teixeira¹,

Rocha

2006

Rev. psiquiatr. Rio Gd. Sul

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INTRODUÇÃO: Um aumento na incidência de obesidade e diabetes melito entre pacientes psiquiátricos foi observado ainda na década de 60, como resultado indesejável do uso de antipsicóticos. Nos anos 80 e 90, a reabilitação da clozapina, a síntese dos demais antipsicóticos atípicos e a disseminação do uso do lítio e do ácido valpróico chamaram novamente a atenção para os efeitos metabólicos desses medicamentos. Este estudo tem por objetivo revisar a literatura médica a respeito dos efeitos adversos metabólicos associados ao uso de antipsicóticos e estabilizadores de humor. MÉTODO: Foi realizada uma extensa pesquisa nas bases de dados MEDLINE e LILACS até outubro de 2005. CONCLUSÃO: Os efeitos adversos metabólicos permanecem como problemas importantes da psicofarmacologia. Ganho de peso clinicamente relevante ocorre com freqüência em pacientes em uso de antipsicóticos e estabilizadores de humor, principalmente naqueles em uso de clozapina, olanzapina, lítio e ácido valpróico. A clozapina e a olanzapina associam-se também a uma maior incidência de diabetes melito e dislipidemias, seja devido ao ganho de peso, seja por ação deletéria direta sobre o metabolismo da glicose. A incidência de obesidade e outros distúrbios metabólicos é menor com a risperidona, se comparada à olanzapina ou à clozapina. Carbamazepina associa-se a menor ganho de peso, se comparada ao lítio ou ao ácido valpróico. Drogas como o haloperidol, a ziprasidona, o aripiprazol e a lamotrigina não estão associadas a ganho importante de peso ou a maior incidência de diabetes melito e são alternativas para pacientes mais propensos a desenvolver tais efeitos adversos.

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Determinants of Overweight and Obesity in Patients With Bipolar Disorder

Cited by 179 publications

References 0 publications

Assessment of Insulin Resistance and Metabolic Syndrome in Drug Naive Patients of Bipolar Disorder

Assessment of Insulin Resistance and Metabolic Syndrome in Drug Naive Patients of Bipolar Disorder

Selection, Use and Psychometric Properties of Physical Activity Measures to Assess Individuals with Severe Mental Illness: A Narrative Synthesis

Efeitos adversos metabólicos de antipsicóticos e estabilizadores de humor

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