Women With Obesity Are Not as Curvy as They Think: Consequences on Their Everyday Life Behavior

Exploring weight management beliefs during the menopausal transition (ME-WEL project): A qualitative comparative study based on Health Belief Model

OBJECTIVES

While most women experience weight gain during the menopausal transition, a subset successfully maintains a healthy weight. This study explores the determinants influencing different weight experiences during the menopausal transition, using the Health Belief Model (HBM).

DESIGN

Qualitative design.

METHODS

Semi-structured individual interviews with 62 Portuguese post-menopausal women were performed. Among them, 31 women maintained a normal weight from pre-menopause to post-menopause, with a variation not exceeding 5% of pre-menopausal weight, while another 31 women transitioned from normal weight in pre-menopause to overweight or obesity in post-menopause, with an increase above 7% of pre-menopausal weight. Deductive-dominant content analysis and multiple correspondence analysis were performed.

RESULTS

Prominent differences exist between the Unhealthy Weight Gain Group (UWG-G) and the Healthy Weight Maintenance Group (HWM-G). The UWG-G lacks perceived susceptibility in pre-menopause and perceives obesity as stigmatizing. They prioritize immediate changes as benefits, while the HWM-G focuses on self-concept. Both groups face barriers like food cravings and weight loss challenges in middle-aged. For cues to action, the UWG-G emphasizes social support and self-care resources, while the HWM-G emphasizes age progression and healthy behaviour adherence. The HWM-G presents higher self-efficacy.

CONCLUSION

This study confirms the suitability of the HBM in understanding weight management beliefs among post-menopausal women, highlighting differences between women who maintain a healthy weight and those who experience weight gain during this life phase. This facilitates identifying key determinants (perceived susceptibility, perceived severity, perceived benefits, perceived barriers, cues to action and self-efficacy) crucial for future interventions in weight management.

Social media use and weight bias internalization: association moderated by age and weight perception

BACKGROUND

The current study examined whether weight perception or age moderated associations between time spent on image-based social media and weight bias internalization (WBI).

METHODS

Data come from the baseline visit of the Tracking Our Lives Study, a randomized control trial of college women (n = 200). Participants completed questionnaires assessing time spent on social media (continuous, overall and individual platforms Instagram, Facebook, and Snapchat), WBI (continuous), weight perception (perceive their weight as "overweight" vs. do not perceive their weight as "overweight"), age (continuous, 18-49 years), and confounders (race/ethnicity, parent education, sexual orientation, and BMI). Adjusted zero-inflated Poisson regressions were performed to determine if weight perception and age moderated associations between time spent on image-based social media and WBI.

RESULTS

As expected, we found a positive association between overall time spent on image-based social media and WBI (β = 0.826, p < 0.001). In moderation analyses, the strength of the association was weakened among women who perceived their weight as "overweight" (β=-0.018, p = 0.006). Associations also weakened with age (β=-0.001, p < 0.001). The association between time spent on Instagram and WBI was also weakened with age (β=-0.014, p = 0.018), which was the only significant moderation found for individual social media platforms.

CONCLUSIONS

Our results suggest that image-based social media use is more strongly associated with increases in WBI among younger women.

Traditional Machine Learning Models and Bidirectional Encoder Representations From Transformer (BERT)-Based Automatic Classification of Tweets About Eating Disorders: Algorithm Development and Validation Study

BACKGROUND

Eating disorders affect an increasing number of people. Social networks provide information that can help.

OBJECTIVE

We aimed to find machine learning models capable of efficiently categorizing tweets about eating disorders domain.

METHODS

We collected tweets related to eating disorders, for 3 consecutive months. After preprocessing, a subset of 2000 tweets was labeled: (1) messages written by people suffering from eating disorders or not, (2) messages promoting suffering from eating disorders or not, (3) informative messages or not, and (4) scientific or nonscientific messages. Traditional machine learning and deep learning models were used to classify tweets. We evaluated accuracy, F1 score, and computational time for each model.

RESULTS

A total of 1,058,957 tweets related to eating disorders were collected. were obtained in the 4 categorizations, with The bidirectional encoder representations from transformer-based models had the best score among the machine learning and deep learning techniques applied to the 4 categorization tasks (F1 scores 71.1%-86.4%).

CONCLUSIONS

Bidirectional encoder representations from transformer-based models have better performance, although their computational cost is significantly higher than those of traditional techniques, in classifying eating disorder-related tweets.

Mental health of adolescents after bariatric surgery: A textual analysis

Mental health after bariatric surgery during adolescence has been little explored. This is a sensitive period in terms of self-image on which bariatric surgery could have negative effects because of the rapid and significant changes in morphology it induces. Previous studies have explored mental effects using questionnaires and only related to psychopathological disorders. The objective of our study was to complement these studies by exploring, via in-depth interviews, the adolescents' views on changes after bariatric surgery at psychological as well as socio-emotional levels. Fourteen adolescents with obesity were recruited in a French hospital 6-43 months after surgery. They participated in one-on-one interviews lasting an average of 45 minutes. A lexical analysis (using ALCESTE software^© ) of their speech highlighted the most positive effects, particularly in terms of social relationships, physical activities, self-esteem and reduced stigma, along with less positive effects in terms of eating behaviour and skin. In terms of clinical implications, this study confirmed the value of bariatric surgery for adolescents at psychological and social levels and its contribution to their mental health. However, it also highlighted the importance of pre- and post-operative support.

Body Image Disturbances and Weight Bias After Obesity Surgery: Semantic and Visual Evaluation in a Controlled Study, Findings from the BodyTalk Project

Purpose

Body image has a significant impact on the outcome of obesity surgery. This study aims to perform a semantic evaluation of body shapes in obesity surgery patients and a group of controls.

Materials and Methods

Thirty-four obesity surgery (OS) subjects, stable after weight loss (average 48.03 ± 18.60 kg), and 35 overweight/obese controls (MC), were enrolled in this study. Body dissatisfaction, self-esteem, and body perception were evaluated with self-reported tests, and semantic evaluation of body shapes was performed with three specific tasks constructed with realistic human body stimuli.

Results

The OS showed a more positive body image compared to HC (p < 0.001), higher levels of depression (p < 0.019), and lower self-esteem (p < 0.000). OS patients and HC showed no difference in weight bias, but OS used a higher BMI than HC in the visualization of positive adjectives (p = 0.011). Both groups showed a mental underestimation of their body shapes.

Conclusion

OS patients are more psychologically burdened and have more difficulties in judging their bodies than overweight/obese peers. Their mental body representations seem not to be linked to their own BMI. Our findings provide helpful insight for the design of specific interventions in body image in obese and overweight people, as well as in OS.