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Psychosocial correlates in patterns of adolescent emotional eating and dietary consumption.

Patrece L JosephCarolina GonçalvesSasha A Fleary
Published in: PloS one (2023)
Unhealthy eating behaviors, such as consumption of unhealthy diet and emotional eating, are common in adolescence and tend to co-occur. However, how these behaviors are patterned may vary among adolescents. This study identified patterns of dietary consumption and emotional eating behaviors in adolescents and examined the sociodemographic and psychosocial (e.g., self-efficacy beliefs and motivation) covariates associated with these eating patterns. Data were from the Family Life, Activity, Sun, Health and Eating study. Latent class analysis was used to estimate adolescent dietary patterns from dietary consumption (i.e., fruits, vegetables, sugar-sweetened beverages, junk food, etc.) and emotional eating variables (i.e., eating when feeling sad or anxious). The sample included 1,568 adolescents (Mean age = 14.48-years-old, 49% girls, 55% White). A four-class solution best fit the data (e.g., Bayesian Information Criteria [BIC] = 12263.568, three-class model BIC = 12271.622). Four unhealthy eating behavior patterns were identified: poor diet/high emotional eating, mixed diet/high emotional eating, poor diet/low emotional eating, and mixed diet/low emotional eating. Compared to the poor diet/high emotional eating group, the other groups were less likely to include older adolescents, girls, and adolescents who experienced food insecurity, and more likely to have higher self-efficacy for eating fruits and vegetables and limiting junk foods as well as motivation for consuming fruits and vegetables and limiting junk foods. Our findings highlight adolescents' complex dietary patterns that include dietary consumption and emotional eating behaviors. Future studies should examine other potential dietary patterns that include emotional eating. Efforts to address unhealthy patterns of adolescents' dietary consumption and emotional eating behaviors should be expanded.
Keyphrases
  • physical activity
  • weight loss
  • young adults
  • healthcare
  • mental health
  • machine learning
  • artificial intelligence
  • big data
  • current status
  • heavy metals
  • middle aged
  • social media