Association of insufficient sleep and skipping breakfast with overweight/obesity in children and adolescents: Findings from a cross‐sectional provincial surveillance project in Jiangsu

Abstract

Background: Insufficient sleep and skipping breakfast are very common phenomena in China and have been proposed as possible causes of overweight/obesity, but the results of former studies remain inconsistent. Objective: To investigate the individual and joint association of insufficient sleep and skipping breakfast with overweight/obesity among children and adolescents in Jiangsu Province, China. Methods: Participants were 36 849 students aged 8-17 years from the 2019-2020 project "Surveillance for common disease and health risk factors among students." Self-reported insufficient sleep and skipping breakfast were ascertained by selfreported sleep duration and breakfast habit. Overweight/obesity was assessed according to the gender-and age-specific body mass index. We used logistic regression models to explore the association of sleep and breakfast with overweight/obesity, and stratification analyses to test age or gender differences. Results: The overall prevalence of overweight/obesity was 33.2%. Insufficient sleep (OR = 1.09, 95% CI = 1.03-1.16) or skipping breakfast (OR = 1.14, 95% CI = 1.07-1.21) was associated with overweight/obesity. Compared to participants with 'sufficient sleep and breakfast', ORs were 1.25 (95% CI = 1.15-1.35) for those with 'both insufficient sleep and skipping breakfast'. The separate and joint association of sleep and breakfast with overweight/obesity remained generally consistent across different age and gender subgroups, except that the 8-12-year-olds group and female students appear more susceptible. Conclusions: Insufficient sleep and skipping breakfast were jointly associated with overweight/obesity in children and adolescents. Appropriate attention should be paid to these modifiable behaviours including sleep and breakfast in the context of the rapidly growing obesity epidemic among children and adolescents.

Changes in the prevalence of obesity in Czech adolescents between 2018 and 2022 and its non-genetic correlates – HBSC study

“…There is published evidence that skipping breakfast [41,42] and insu cient sleep [42][43][44][45] are signi cantly associated with childhood and adolescent obesity, but these studies did not account for the SES of adolescent families [41,[43][44][45] or nd differences between groups of adolescents from families with different SES [42]. Of note, skipping breakfast is signi cantly associated with lower odds of obesity only among adolescents from low-SES families, whereas insu cient sleep is signi cantly associated with lower odds of obesity, in contrast, only among adolescents from medium-and high-SES families.…”

Neighborhood Food Environment and Children’s BMI: A New Framework with Structural Equation Modeling

“…The total prevalence rate of overweight and obesity was 27.23%, which is considerably higher than the national level (19% in 2020) [ 32 ] and the international level (20% in 2016) [ 1 ], and lower than the prevalence rate among children and adolescents in the Jiangsu province, China (33.2% in 2019–2020) [ 33 ]; Shanghai, China (30.31% in 2019) [ 34 ]; Maya, Mexico (39%) [ 35 ]; and Thrace, NE Greece (48.5% in 2018) [ 36 ]. This study examined a conceptual and multi-factorial model and offered an understanding of the intricate relationship between children’s neighborhood food environment and their BMI by applying SEM.…”

Pattern of lifestyle behaviors and associated risk of being bullied at schools: A latent class analysis of 25,379 adolescents in Jiangsu Province of China

“…Training sessions for the field data collection and pilot studies were carried out to validate the project instruments before the rollout across the entire province. Strict quality control measures and field supervision have been carried out during implementation, from the validation of the survey instruments to the verification of the returned questionnaires, and from data input to the checking of data discrepancies such as inconsistent formats, duplicate records, and other quality issues (Chen et al, 2022; Zhang et al, 2018). The current study included participants from junior high school (aged 10–17 years old with a typical age range between 12 and 14 years and a typical average age of 13.59 years), senior high school, and vocational schools (aged 14–20 years old with a typical age range between 15 and 17 years and a typical average age of 16.58 years).…”