Article

Psychiatric disorder comorbidity and association with eating disorders in bariatric surgery patients: A cross-sectional study using structured interview-based diagnosis.

Department of Epidemiology & Public Health, Yale University School of Medicine, New Haven, CT 06519, USA.
The Journal of Clinical Psychiatry (Impact Factor: 5.14). 08/2006; 67(7):1080-5. DOI: 10.4088/JCP.v67n0710
Source: PubMed

ABSTRACT This study examined the prevalence of DSM-IV Axis I psychiatric disorders in severely obese bariatric surgery candidates and explored whether eating disorders were associated with psychiatric comorbidity.
The Structured Clinical Interview for DSM-IV Axis I Disorders was administered to a study group of 174 consecutively evaluated bariatric surgery candidates. All evaluations were completed between September 2002 and November 2004.
Overall, 36.8% of the participants met criteria for at least one lifetime psychiatric disorder, with 24.1% meeting criteria for a current disorder. The most commonly observed lifetime psychiatric diagnoses were affective disorders (22.4%), anxiety disorders (15.5%), and eating disorders (13.8%). Participants with eating disorders were significantly more likely than those without eating disorders to meet criteria for psychiatric disorders overall (66.7% vs. 26.7%) and specifically for anxiety disorders (45.8% vs. 10.7%).
Psychiatric disorders are not uncommon among severely obese patients who present for bariatric surgery. The observed prevalence rates based on structured diagnostic interviews are lower than previously reported based on questionnaire, clinical, and chart review methods but are similar to those reported for nationally representative samples. Among bariatric surgery candidates, the presence of eating disorders is associated with higher rates of other psychiatric disorders. The findings highlight the importance of systematic diagnostic assessment using a structured diagnostic interview for determining the full spectrum of Axis I disorders.

4 Followers
 · 
179 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Background Morbid obesity is the fastest growing BMI group in the U.S. and the prevalence of morbid obesity worldwide has never been higher. Bariatric surgery is the most effective treatment for severe forms of obesity especially with regard to a sustained long-term weight loss. Psychological factors are thought to play an important role for maintaining the surgical weight loss. However, results from prior research examining preoperative psychological predictors of weight loss outcome are inconsistent. The aim of this article was to review more recent literature on psychological predictors of surgical weight loss. Methods We searched PubMed, PsycInfo and Web of Science, for original prospective studies with a sample size >30 and at least one year follow-up, using a combination of search terms such as ‘bariatric surgery’, ‘morbid obesity’, ‘psychological predictors’, and ‘weight loss’. Only studies published after 2003 were included. Results 19 eligible studies were identified. Psychological predictors of surgical weight loss investigated in the reviewed studies include cognitive function, personality, psychiatric disorder, and eating behaviour. Conclusion In general, recent research remains inconsistent, but the findings suggest that pre-surgical cognitive function, personality, mental health, composite psychological variables and binge eating may predict post-surgical weight loss to the extent that these factors influence post-operative eating behaviour.
    Obesity Research & Clinical Practice 01/2013; 8(4). DOI:10.1016/j.orcp.2013.09.003 · 0.70 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Candidates for bariatric surgery frequently have co-morbid psychiatric problems. This study investigated the course and the prognostic significance of preoperative and postoperative anxiety and depressive disorders in 107 extremely obese bariatric surgery patients in a prospective design with face-to-face interviews (SCID) conducted prior to the surgery and postoperatively after 6-12 months and 24-36 months. The point prevalence of depressive disorders but not of anxiety disorders decreased significantly after surgery. Preoperative depressive disorders predicted depressive disorders 24-36 months but not 6-12 months after surgery, whereas preoperative anxiety significantly predicted postoperative anxiety disorders at both follow-up time points. Preoperative lifetime and current depressive disorders were unrelated to postoperative weight loss whereas preoperative lifetime, but not current anxiety disorders were of negative prognostic value for postoperative weight loss. Patients with both depressive and anxiety disorders at baseline (current and lifetime) lost significantly less weight after surgery. Postoperative anxiety disorder was not associated with the degree of weight loss at any follow-up time-point; however postoperative depressive disorder was negatively associated with weight loss at the 24-36 month follow-up assessment point. Missing data, limited statistical power, self-reported height and weight are the limitations of this study. As opposed to anxiety disorders, the point prevalence of depressive disorders decreased significantly after bariatric surgery. However, the presence of depressive disorders after bariatric surgery significantly predicted attenuated post-surgical improvements and may signal a need for clinical attention.
    Journal of Affective Disorders 04/2011; 133(1-2):61-8. DOI:10.1016/j.jad.2011.03.025 · 3.71 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: In this study, an evolutionary computing algorithm is utilized for data preparation and analysis of synthetic aperture radar (SAR) imagery for planetary geology. Since its invention by J.H. Holland in the 1990s, the Genetic Algorithm (GA) has already gained popularity in a wide range of engineering applications. The genetic approach is used for processing of SAR imagery to find a region of a pre-defined criterion. It was seen that the algorithm is superior to deterministic methods in terms of processing times and finding the global minimum points. The proposed method is suitable to SAR image processing where huge amounts of data have to be processed in very short time intervals.
    Recent Advances in Space Technologies, 2003. RAST '03. International Conference on. Proceedings of; 12/2003