Prevalence of Overweight and Obesity and Associated Diet-Related Behaviours and Habits in a Representative Sample of Adolescents in Greece.
Rafaela MakriMichail KatsoulisAnastasios FotiouEleftheria KanavouMyrto StavrouClive RichardsonAfroditi KanellopoulouPhilippos OrfanosVassiliki BenetouAnna KokkeviPublished in: Children (Basel, Switzerland) (2022)
Excessive body weight during adolescence represents a significant public health problem worldwide. Identifying factors associated with its development is crucial. We estimated the prevalence of overweight and obesity in a representative sample of 11, 13 and, 15-year-olds living in Greece and explored the association with diet-related behaviours and habits. Self-reported data on weight, height, diet-related behaviours and habits were used from 3816 students (1898 boys, 1918 girls) participants in the Greek arm of the international Health Behaviour in School-Aged Children (HBSC) study during 2018. Overweight and obesity were defined using the 2007 WHO growth charts classification. Prevalence of overweight was 19.4% in the total sample, 24.1% for boys and 14.7% for girls, and prevalence of obesity was 5.3% in the total sample, 7.3% for boys and 3.4% for girls, respectively. In the total sample, overweight (including obesity) was positively associated with male gender, low family affluence, skipping breakfast, and being on a diet, and inversely associated with age and being physically active. Eating rarely with the family was positively associated with overweight only among boys and eating snacks/meals in front of screens only among girls. No association was noted for eating in fast-food restaurants, consuming vegetables, fruits, sweets, and sugar-sweetened beverages.
Keyphrases
- weight loss
- physical activity
- public health
- weight gain
- risk factors
- body weight
- mental health
- body mass index
- young adults
- healthcare
- machine learning
- type diabetes
- deep learning
- metabolic syndrome
- cross sectional
- insulin resistance
- electronic health record
- human health
- artificial intelligence
- high fat diet induced
- big data