Network analysis based on big data in social media of Korean adolescents’ diet behaviors

Adolescents are increasingly interested in weight control; hence, proper health education is important for helping them control their weight properly. This study was designed to pick out social media words that express adolescents’ diet behaviors, and identify the associations and types between such words and the behaviors. It used text-mining techniques and semantic network analysis for related big data collected from the Internet on adolescents’ diet behaviors. Text mining was used to extract meaningful information from unstructured text data, whereas semantic network analysis was used to understand the relationships between keywords. The top five keywords were “obesity,” “health,” “exercise,” “eat,” and “increase” in online news, and “exercise,” “eat,” “weight loss,” “obesity,” and “health” in blogs. The betweenness centrality of “appearance” was particularly higher than that of other centralities in online news. As a result of the CONCOR analysis, eight clusters each were identified in online news and blogs. This study’s results will serve as a basis for weight management-related intervention strategies, reflecting the perspectives of adolescents. It also has significance as basic data to provide correct information, and establish desirable weight control in the future.

Does perceived overweight increase risk of depressive symptoms and suicidality beyond objective weight status? A systematic review and meta-analysis

Obesity is associated with a significant disease burden, but whether recognising as opposed to failing to recognise personal overweight is beneficial or detrimental to mental health is unclear. Here we examine the associations between perceived overweight and depressive symptoms and suicidality. A systematic search of three electronic databases yielded 10,398 unique records, from which 32 studies (110 observations) were eligible for inclusion. Pooled odds ratios (OR) and 95% confidence intervals (CI) were calculated for each outcome using random effects meta-analyses and potential publication bias was examined. Perceived overweight was associated with an increased risk of depressive symptoms (OR: 1.42, CI: 1.31, 1.54 p <.0001, N >128,585) and suicidality (OR: 1.41, CI: 1.28, 1.56, p <.0001, N = 133,576) in both cross-sectional and longitudinal studies. The association between perceived overweight and poorer mental health was observed irrespective of study origin, participant age (children vs. adults), gender, and whether or not a person was objectively overweight. The pooled statistical relationship between objective weight status and poorer mental health was attenuated to non-significance when perceived overweight was accounted for, suggesting that the detrimental effect of overweight on mental health is largely dependent on whether or not a person identifies as overweight.