Latent Class Analysis of Obesogenic Behaviors among Korean Adolescents: Associations with Weight-Related Outcomes

This study aimed to explore sex-specific latent class models of adolescent obesogenic behaviors (OBs), predictors of latent class membership (LCM), and associations between LCM and weight-related outcomes (i.e., weight status and unhealthy weight control behaviors). We analyzed nationally representative data from the 2019 Korea Youth Risk Behavior Survey. To identify latent classes for boys (n = 29,841) and girls (n = 27,462), we conducted a multiple-group latent class analysis using eight OBs (e.g., breakfast skipping, physical activity, and tobacco product use). Moreover, we performed a multinomial logistic regression analysis and a three-step method to examine associations of LCM with predictors and weight-related outcomes. Among both sexes, the 3-class models best fit the data: (a) mostly healthy behavior class, (b) poor dietary habits and high Internet use class, and (c) poor dietary habits and substance use class. School year, residential area, academic performance, and psychological status predicted the LCM for both sexes. In addition, perceived economic status predicted the LCM for girls. The distribution of weight-related outcomes differed across sex-specific classes. Our findings highlight the importance of developing obesity prevention and treatment interventions tailored to each homogeneous pattern of adolescent OBs, considering differences in their associations with predictors and weight-related outcomes.

Prevalence of and Trends in the Co-Existence of Obesogenic Behaviors in Adolescents From 15 Countries

Background: The global epidemic of pediatric obesity is well-known, but data on co-existence of obesogenic behaviors are limited. We aim to report the prevalence of and trends in the co-existence of obesogenic behaviors in adolescents from 15 countries.Methods: This study was based on the Global School-based Student Health Survey 2003–2017 and included 121,963 adolescents aged 12–15 years from 15 countries where at least 2 cross-sectional surveys were conducted. We used sampling weights and calculated the country-level prevalence of and trends in the co-existence of obesogenic behaviors (low fruit and vegetable intake, anxiety-induced insomnia, no physical activity, and sedentary behavior) during survey years. Pooled prevalence and trend estimates were calculated with random-effects models.Results: Pooled prevalence of exposure ≥ 1, ≥2, and ≥3 obesogenic behaviors was 88.2, 44.9, and 9.8% in the first survey and 88.4, 46.4, and 10.2% in the last survey, respectively. Plateauing, increasing, and decreasing trends in the co-existence of obesogenic behaviors were observed in different countries. Specifically, we identified a plateauing pooled trend in the exposure ≥ 1, ≥2, and ≥3 obesogenic behaviors [odds ratios (95% confidence intervals): 1.03 (0.93, 1.14), 1.05 (0.97, 1.13), and 1.06 (0.95, 1.18), respectively].Conclusion: Trends in the prevalence of the co-existence of obesogenic behaviors varied significantly across different countries, but the prevalence remained high in most countries. These findings suggest the need for behavioral interventions to mitigate obesogenic behaviors in adolescents for overweight and obesity prevention.

The impact of summer vacation on children’s obesogenic behaviors and body mass index: a natural experiment

Background Children’s BMI gain accelerates during summer. The Structured Days Hypothesis posits that the lack of the school day during summer vacation negatively impacts children’s obesogenic behaviors (i.e., physical activity, screen time, diet, sleep). This natural experiment examined the impact of summer vacation on children’s obesogenic behaviors and body mass index (BMI). Methods Elementary-aged children (n = 285, 5-12 years, 48.7% male, 57.4% African American) attending a year-round (n = 97) and two match-paired traditional schools (n = 188) in the United States participated in this study. Rather than taking a long break from school during the summer like traditional schools, year-round schools take shorter and more frequent breaks from school. This difference in school calendars allowed for obesogenic behaviors to be collected during three conditions: Condition 1) all children attend school, Condition 2) year-round children attend school while traditional children were on summer vacation, and Condition 3) summer vacation for all children. Changes in BMI z-score were collected for the corresponding school years and summers. Multi-level mixed effects regressions estimated obesogenic behaviors and monthly zBMI changes. It was hypothesized that children would experience unhealthy changes in obesogenic behaviors when entering summer vacation because the absence of the school day (i.e., Condition 1 vs. 2 for traditional school children and 2 vs. 3 for year-round school children). Results From Condition 1 to 2 traditional school children experienced greater unhealthy changes in daily minutes sedentary (∆ = 24.2, 95CI = 10.2, 38.2), screen time minutes (∆ = 33.7, 95CI = 17.2, 50.3), sleep midpoint time (∆ = 73:43, 95CI = 65:33, 81:53), and sleep efficiency percentage (−∆ = 0.7, 95CI = -1.1, − 0.3) when compared to year-round school children. Alternatively, from Condition 2 to 3 year-round school children experienced greater unhealthy changes in daily minutes sedentary (∆ = 54.5, 95CI = 38.0, 70.9), light physical activity minutes (∆ = − 42.2, 95CI = -56.2, − 28.3) MVPA minutes (∆ = − 11.4, 95CI = -3.7, − 19.1), screen time minutes (∆ = 46.5, 95CI = 30.0, 63.0), and sleep midpoint time (∆ = 95:54, 95CI = 85:26, 106:22) when compared to traditional school children. Monthly zBMI gain accelerated during summer for traditional (∆ = 0.033 95CI = 0.019, 0.047) but not year-round school children (∆ = 0.004, 95CI = -0.014, 0.023). Conclusions This study suggests that the lack of the school day during summer vacation negatively impacts sedentary behaviors, sleep timing, and screen time. Changes in sedentary behaviors, screen time, and sleep midpoint may contribute to accelerated summer BMI gain. Providing structured programming during summer vacation may positively impact these behaviors, and in turn, mitigate accelerated summer BMI gain. Trial registration ClinicalTrials.gov Identifier: NCT03397940. Registered January 12th 2018.

The Impact of Summer Vacation on Children’s Obesogenic Behaviors and Body Mass Index: A natural experiment.

Background: Children’s BMI gain accelerates during summer. The Structured Days Hypothesis posits that the lack of the school day during summer vacation negatively impacts children’s obesogenic behaviors (i.e., physical activity, screen time, diet, sleep). This natural experiment examined the impact of summer vacation on children’s obesogenic behaviors and body mass index (BMI).Methods: Elementary-aged children (n=285, 5-12years, 48.7% male, 57.4% African American) attending a year-round (n=97) and two match-paired traditional schools (n=188) in the United States participated in this study. Rather than taking a long break from school during the summer like traditional schools, year-round schools take shorter and more frequent breaks from school. This difference in school calendars allowed for obesogenic behaviors to be collected during three conditions: Condition 1) all children attend school, Condition 2) year-round children attend school while traditional children were on summer vacation, and Condition 3) summer vacation for all children. Changes in BMI z-score were collected for the corresponding school years and summers. Multi-level mixed effects regressions estimated obesogenic behaviors and monthly zBMI changes. It was hypothesized that children would experience unhealthy changes in obesogenic behaviors when entering summer vacation because the absence of the school day (i.e., Condition 1 vs. 2 for traditional school children and 2 vs. 3 for year-round school children).Results: From Condition 1 to 2 traditional school children experienced greater unhealthy changes in daily minutes sedentary (∆=24.2, 95CI=10.2, 38.2), screen time minutes (∆=33.7, 95CI=17.2, 50.3), sleep midpoint time (∆=73:43, 95CI=65:33, 81:53), and sleep efficiency percentage (-∆=0.7, 95CI=-1.1, -0.3) when compared to year-round school children. Alternatively, from Condition 2 to 3 year-round school children experienced greater unhealthy changes in daily minutes sedentary (∆=54.5, 95CI=38.0, 70.9), light physical activity minutes (∆=-42.2, 95CI=-56.2, -28.3) MVPA minutes (∆=-11.4, 95CI=-3.7, -19.1), screen time minutes (∆=46.5, 95CI=30.0, 63.0), and sleep midpoint time (∆=95:54, 95CI=85:26, 106:22) when compared to traditional school children. Monthly zBMI gain accelerated during summer for traditional (∆=0.033 95CI=0.019, 0.047) but not year-round school children (∆=0.004, 95CI=-0.014, 0.023).Conclusions: This study suggests that the lack of the school day during summer vacation negatively impacts sedentary behaviors, sleep timing, and screen time. Changes in sedentary behaviors, screen time, and sleep midpoint may contribute to accelerated summer BMI gain. Providing structured programming during summer vacation may positively impact these behaviors, and in turn, mitigate accelerated summer BMI gain. Trial Registration: ClinicalTrials.gov Identifier: NCT03397940. Registered January 12th 2018.

Late eating is associated with cardiometabolic risk traits, obesogenic behaviors, and impaired weight loss

ABSTRACT Background There is a paucity of evidence regarding the role of food timing on cardiometabolic health and weight loss in adults. Objectives To determine whether late eating is cross-sectionally associated with obesity and cardiometabolic risk factors at baseline; and whether late eating is associated with weight loss rate and success following a weight loss intervention protocol. Also, to identify obesogenic behaviors and weight loss barriers associated with late eating. Methods Participants were recruited from a weight-loss program in Spain. Upon recruitment, the midpoint of meal intake was determined by calculating the midway point between breakfast and dinner times, and dietary composition was determined from diet recall. Population median for the midpoint of meal intake was used to stratify participants into early (before 14:54) and late (after 14:54) eaters. Cardiometabolic and satiety hormonal profiles were determined from fasting blood samples collected prior to intervention. Weekly weight loss and barriers were evaluated during the ∼19-wk program. Linear and logistic regression models were used to assess differences between late and early eaters in cardiometabolic traits, satiety hormones, obesogenic behaviors, and weight loss, adjusted for age, sex, clinic site, year of recruitment, and baseline BMI. Results A total of 3362 adults [mean (SD): age: 41 (14) y; 79.2% women, BMI: 31.05 (5.58) kg/m2] were enrolled. At baseline, no differences were observed in energy intake or physical activity levels between early and late eaters (P >0.05). Late eaters had higher BMI, higher concentrations of triglycerides, and lower insulin sensitivity compared with early eaters (all P <0.05) prior to intervention. In addition, late eaters had higher concentrations of the satiety hormone leptin in the morning (P = 0.001). On average, late eaters had an average 80 g lower weekly rate of weight loss [early, 585 (667) g/wk; late, 505 (467) g/wk; P = 0.008], higher odds of having weight-loss barriers [OR (95% CI): 1.22 (1.03, 1.46); P = 0.025], and lower odds of motivation for weight loss [0.81 (0.66, 0.99); P = 0.044] compared with early eaters. Conclusion Our results suggest that late eating is associated with cardiometabolic risk factors and reduced efficacy of a weight-loss intervention. Insights into the characteristics and behaviors related to late eating may be useful in the development of future interventions aimed at advancing the timing of food intake.