Greater body mass is associated with a greater risk of mental health conditions and more frequent mental health treatment use. However, factors that might influence perceived mental health treatment need and mental health treatment use among those of greater weight, including hope thinking, trauma history and perceived mental health treatment stigma, are not well understood.

The objective of this study was to determine if hope thinking, trauma history and/or perceived mental health treatment stigma mediate the relationships of body mass index [BMI] with perceived mental health treatment need and mental health treatment use.

Primary care clinic patients in the Midwest United States (N = 196; BMI range = 18.5 to 47.0, mean = 29.26 ± 6.61, median = 27.90) were recruited to complete a battery of self-report measures that assessed perceived mental health treatment need, mental health treatment use, hope thinking (Trait Hope Scale), trauma history (a single-item traumatic event history screen from the posttraumatic stress disorder module of the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition), and perceived mental health treatment stigma (Stigma Scale for Receiving Psychological Help).

Reduced hope thinking and a greater incidence of past trauma accounted for greater perceived mental health treatment need and greater mental health treatment use among those of greater BMI. BMI was not related to perceived unmet mental health treatment need.

Increased perceived mental health treatment need and mental health treatment use among those of greater BMI may be explained by lower hope thinking and a greater incidence of trauma in this population. Heavier patients may benefit from interventions designed to augment hope and address traumatic histories.

The U.S. population has shown increasing rates of overweight and obesity in recent years, but similar analyses do not exist for U.S. military personnel. It is important to understand these patterns in the military because of their impact on fitness and readiness.

To assess prevalence and trends in overweight/obesity among U.S. service members and to examine the associations of sociodemographic characteristics, exercise, depression, and substance use with these patterns.

Analyses performed in 2013 used five large population-based health-related behavior surveys conducted from 1995 to 2008. Main outcome measures were overweight and obesity among active duty military personnel based on BMI.

Combined overweight and obesity (BMI≥25) increased from 50.6% in 1995 to 60.8% in 2008, primarily driven by the rise in obesity (BMI≥30) from 5.0% to 12.7%. For overweight, military women showed the largest increase. For obesity, all sociodemographic groups showed significant increases, with the largest among warrant officers, senior enlisted personnel, and people aged 36-45 years. Adjusted multinomial logit analyses found that service members aged 26 years and older, men, non-Hispanic blacks and Hispanics, enlisted personnel, married personnel, and heavy drinkers had the highest risk both for overweight and obesity.

Combined overweight and obesity in active duty personnel rose to more than 60% between 1995 and 2008, primarily because of increased obesity. The high prevalence of overweight and obesity needs attention and has implications for Department of Defense efforts to improve the health, fitness, readiness, and quality of life of the Active Forces.

Cognitive-behavioral therapy (CBT) has proven to be effective in weight reduction. This study explores whether individual, 8-session CBT can promote weight loss in midlife women.

Anthropometric (weight, abdominal perimeter, and body mass index calculation), psychological (health-related and sexual quality of life, stress, anxiety, and depression), and behavioral measures (binge eating disorder and restrained, external, and emotional eating) were assessed at baseline (T1), posttreatment (T2), and 4-month follow-up (T3), for a total of 21 women at baseline; the CBT group (n = 11) and the control group (n = 10; waiting list) were compared.

Statistically significant effects that were dependent on the intervention were observed on weight (F = 4.402; P = 0.035; η(p) (2) = 0.404; π = 0.652) and body mass index (F = 3.804; P = 0.050; η(p) (2) = 0.369; π = 0.585); furthermore, marginally significant effects were observed on external eating (F = 2.844; P = 0.095; η(p) (2) = 0.304; π = 0.461). At follow-up, women in the CBT group presented with lower weight, abdominal perimeter, body mass index, and external eating; higher health-related quality-of-life and restrained eating were also observed in this group. Most differences identified were at a marginally significant level. Moreover, at follow-up, none of the participants of the CBT group met the criteria for binge eating disorder, whereas the number of women with binge eating disorder in the control group remained the same through all three assessments.

An effective, though small, weight loss was achieved. Changes in quality of life were also observed. Moreover, changes in external eating behavior were successful.

Epidemiologic data suggest an association between obesity and depression, but findings vary across studies and suggest a stronger relationship in women than men.

To evaluate the relationship between obesity and a range of mood, anxiety, and substance use disorders in the US general population.

Cross-sectional epidemiologic survey.

Nationally representative sample of US adults.

A total of 9125 respondents who provided complete data on psychiatric disorder, height, and weight. Response rate was 70.9%.

Participants completed an in-person interview, including assessment of a range of mental disorders (assessed using the World Health Organization Composite International Diagnostic Interview) and height and weight (by self-report).

Obesity (defined as body mass index [calculated as weight in kilograms divided by the square of height in meters] of > or =30) was associated with significant increases in lifetime diagnosis of major depression (odds ratio [OR], 1.21; 95% confidence interval [CI], 1.09-1.35), bipolar disorder (OR, 1.47; 95% CI, 1.12-1.93), and panic disorder or agoraphobia (OR, 1.27; 95% CI, 1.01-1.60). Obesity was associated with significantly lower lifetime risk of substance use disorder (OR, 0.78; 95% CI, 0.65-0.93). Subgroup analyses found no difference in these associations between men and women, but the association between obesity and mood disorder was strongest in non-Hispanic whites (OR, 1.38; 95% CI, 1.20-1.59) and college graduates (OR, 1.44; 95% CI, 1.14-1.81).

Obesity is associated with an approximately 25% increase in odds of mood and anxiety disorders and an approximately 25% decrease in odds of substance use disorders. Variation across demographic groups suggests that social or cultural factors may moderate or mediate the association between obesity and mood disorder.

To investigate the construct validity of the Short Form-36 (SF-36) Health Survey questionnaire in obese patients.

Our series consisted of 1735 obese patients (age, 44.7 +/- 11.0 years; 1346 women) consecutively enrolled in the QUOVADIS study, an observational multicenter study of obese treatment-seeking outpatients. The construct validity of the SF-36 was assessed by main component analysis. Age-, gender-, and education-adjusted general linear models were used to investigate the relationship between BMI and SF-36 domains or factors identified by main component analysis.

BMI was significantly associated with poor health-related quality of life in all eight SF-36 domains, and the strongest association was observed with physical activity. Main components analysis generated a six-factor solution explaining 59% of the observed variance. BMI was strongly associated with factors based on the loading of items regarding the physical activity domain and factors based on role-physical and role-emotional items or general health and bodily pain items. In contrast, mental health-, vitality-, and social functioning-based factors were not related to BMI.

In obese treatment-seeking outpatients, the clustering of SF-36 items in main components is not significantly different from the domain-based approach generally used, thus confirming the robustness of such a generic questionnaire in this specific condition. However, the peculiar clustering of some SF-36 items and their relationship with BMI suggest that the health-related quality of life profile of subjects belonging to that population may be better described with alternative aggregations of the SF-36 items or with disease-tailored questionnaires.