Links between obesity, weight stigma and learning in adolescence: a qualitative study

Background Educational attainment is a key social determinant of health. Health and education are linked by multiple pathways, many of which are not well understood. One such pathway is the association between being above a healthy weight and lower academic achievement. While various explanations have been put forward to explain this relationship, evidence for causal pathways is sparse and unclear. This study addresses that evidence gap. Methods We interviewed 19 adults (late 20s; 14 female, 5 male) and one young person (14 years, male) from the UK in 2019/2020. Participants were recruited from the ALSPAC 1990s birth cohort, sampled to ensure diversity in socio-economic status and educational attainment, and a community-based weight management group for young people. Interviews focused on experiences of being above a healthy weight during secondary school and how this may have affected their learning and achievement. Interviews were face-to-face, digitally recorded, and transcribed verbatim. We analysed the data thematically. Results We identified key pathways through which higher body weight may negatively impact educational performance and showed how these are linked within a novel theoretical model. Because larger body size is highly stigmatised, participants engaged in different strategies to minimise their exposure to negative attention. Participants sought to increase their social acceptance or become less socially visible (or a combination of both). A minority navigated this successfully; they often had many friends (or the ‘right’ friends), experienced little or no bullying at school and weight appeared to have little effect on their achievement at school. For most however, the behaviours resulting from these strategies (e.g. disruptive behaviour, truanting, not working hard) or the physical, social or mental impacts of their school experiences (e.g. hungry, tired, self-conscious, depressed) made it difficult to concentrate and/or participate in class, which in turn affected how teachers viewed them. Conclusions Action to combat weight stigma, both within schools and in wider society, is urgently required to help address these educational disparities that in turn can impact health in later life.

Tracking sentiments toward fat acceptance over a decade on Twitter

The fat acceptance (FA) movement aims to counteract weight stigma and discrimination against individuals who are overweight/obese. We developed a supervised neural network model to classify sentiment toward the FA movement in tweets and identify links between FA sentiment and various Twitter user characteristics. We collected any tweet containing either “fat acceptance” or “#fatacceptance” from 2010–2019 and obtained 48,974 unique tweets. We independently labeled 2000 of them and implemented/trained an Average stochastic gradient descent Weight-Dropped Long Short-Term Memory (AWD-LSTM) neural network that incorporates transfer learning from language modeling to automatically identify each tweet’s stance toward the FA movement. Our model achieved nearly 80% average precision and recall in classifying “supporting” and “opposing” tweets. Applying this model to the complete dataset, we observed that the majority of tweets at the beginning of the last decade supported FA, but sentiment trended downward until 2016, when support was at its lowest. Overall, public sentiment is negative across Twitter. Users who tweet more about FA or use FA-related hashtags are more supportive than general users. Our findings reveal both challenges to and strengths of the modern FA movement, with implications for those who wish to reduce societal weight stigma.

Interrelation between weight and weight stigma in youth: is there evidence for an obesogenic vicious cycle?

Many children and adolescents are confronted with weight stigma, which can cause psychological and physical burden. While theoretical frameworks postulate a vicious cycle linking stigma and weight status, there is a lack of empirical evidence. The aim was to analyze the longitudinal bidirectional relationship between body weight and weight stigma among children and adolescents. The sample consisted of 1381 children and adolescents, aged 9–19 years at baseline (49.2% female; 78% normal weight), from a prospective study encompassing three measurement points over 6 years. Participants provided self-reported data on experienced weight-related teasing and weight/height (as indicators for weight status). Latent structural equation modelling was used to examine the relationship between weight-related teasing experiences and weight. Additionally, gender-related differences were analyzed. Between the first two waves, there was evidence for a bidirectional relationship between weight and weight-related teasing. Between the last two waves, teasing predicted weight, but there was no reverse association. No gender-related differences were found. The data indicate a reciprocal association between weight stigma and body weight across weight groups and independent of gender. To prevent vicious cycles, approaches that simultaneously promote healthy weight and reduce weight stigma are required.

Weight Stigma and Social Media: Evidence and Public Health Solutions

Weight stigma is a pressing issue that affects individuals across the weight distribution. The role of social media in both alleviating and exacerbating weight bias has received growing attention. On one hand, biased algorithms on social media platforms may filter out posts from individuals in stigmatized groups and concentrate exposure to content that perpetuates problematic norms about weight. Individuals may also be more likely to engage in attacks due to increased anonymity and lack of substantive consequences online. The critical influence of social media in shaping beliefs may also lead to the internalization of weight stigma. However, social media could also be used as a positive agent of change. Movements such as Body Positivity, the Fatosphere, and Health at Every Size have helped counter negative stereotypes and provide more inclusive spaces. To support these efforts, governments should continue to explore legislative solutions to enact anti-weight discrimination policies, and platforms should invest in diverse content moderation teams with dedicated weight bias training while interrogating bias in existing algorithms. Public health practitioners and clinicians should leverage social media as a tool in weight management interventions and increase awareness of stigmatizing online content among their patients. Finally, researchers must explore how experiences of stigma differ across in-person and virtual settings and critically evaluate existing research methodologies and terminology. Addressing weight stigma on social media will take a concerted effort across an expansive set of stakeholders, but the benefits to population health are consequential and well-worth our collective attention.