Understanding Accelerated Summer Body Mass Index Gain by Tracking Changes in Children's Height, Weight, and Body Mass Index Throughout the Year.

Background: Drivers of summer body mass index (BMI) gain in children remain unclear. The Circadian and Circannual Rhythm Model (CCRM) posits summer BMI gain is biologically driven, while the Structured Days Hypothesis (SDH) proposes it is driven by reduced structure. Objectives: Identify the mechanisms driving children's seasonal BMI gain through the CCRM and SDH. Methods: Children's (N = 147, mean age = 8.2 years) height and weight were measured monthly during the school year, and once in summer (July-August). BMI z-score (zBMI) was calculated using CDC growth charts. Behaviors were measured once per season. Mixed methods regression estimated monthly percent change in children's height (%HΔ), weight (%WΔ), and monthly zBMI for school year vs. summer vacation, seasonally, and during school months with no breaks vs. school months with a break ≥1 week. Results: School year vs. summer vacation analyses showed accelerations in children's %WΔ (Δ = 0.9, Standard Error (SE) = 0.1 vs. Δ = 1.4, SE = 0.1) and zBMI (Δ = -0.01, SE = 0.01 vs. Δ = 0.04, SE = 0.3) during summer vacation, but %HΔ remained relatively constant during summer vacation compared with school (Δ = 0.3, SE = 0.0 vs. Δ = 0.4, SE = 0.1). Seasonal analyses showed summer had the greatest %WΔ (Δ = 1.8, SE = 0.4) and zBMI change (Δ = 0.05, SE = 0.03) while %HΔ was relatively constant across seasons. Compared with school months without a break, months with a break showed higher %WΔ (Δ = 0.7, SE = 0.1 vs. Δ = 1.6, SE = 0.2) and zBMI change (Δ = -0.03, SE = 0.01 vs. Δ = 0.04, SE = 0.01), but %HΔ was constant (Δ = 0.4, SE = 0.0 vs. Δ = 0.3, SE = 0.1). Fluctuations in sleep timing and screen time may explain these changes. Conclusions: Evidence for both the CCRM and SDH was identified but the SDH may more fully explain BMI gain. Interventions targeting consistent sleep and reduced screen time during breaks from school may be warranted no matter the season.

Diet Quality among Pre-Adolescent African American Girls in a Randomized Controlled Obesity Prevention Intervention Trial.

Consuming an unhealthy diet increases health risks. This study assessed the impact of a culturally adapted behaviorally innovative obesity prevention intervention (The Butterfly Girls and the Quest for Founder's Rock) on diet quality in pre-adolescent non-Hispanic Black/African American girls. The RCT consisted of three groups (experimental, comparison, and waitlist control); block randomization allocated participants to each group. The two treatment groups varied in terms of whether or not they set goals. Data were collected at baseline (prior to receiving the intervention), post 1 (3 months post-baseline), and post 2 (6 months post-baseline). Two dietitian-assisted 24 h dietary recalls were collected at each timepoint. Healthy Eating Index 2015 (HEI-2015) was used to determine diet quality. A total of 361 families were recruited; 342 completed baseline data collection. No significant differences in overall HEI score or component scores were observed. To attain more equitable health outcomes, future efforts to promote dietary intake change among at-risk children should explore other behavior change procedures and employ more child-friendly dietary assessment methods.

Examination of parent-reported differences in children's daily screen use, sleep, and sleep hygiene behaviors during the school year and summer and their association with BMI.

OBJECTIVE: The current study examined school-summer differences in children's sleep patterns and sleep hygiene. Cross-sectional relationships with children's sleep, sleep hygiene, and weight status were explored during the school year and summer. METHODS: Children (5-8 years) and their parents (n = 197 dyads) were recruited from 4 schools in southeastern Texas and via Facebook. Parents reported children's school year and summer sleep, sleep hygiene, and screen media use. Children's body mass index (BMI) was objectively assessed at the beginning and end of the summer. Associations between children's sleep hygiene and screen media use, sleep duration, and weight status were explored. RESULTS: Children's sleep midpoint was earlier during the school year (1:54 AM ± 0.03) than in the summer (2:06 AM ± 0.03; t = 4.07, p < .0001). During summer, children increased their screen media use by 38 minutes (t = 2.32, p = .023) and decreased their caffeine intake from 7.43 to 7.0 (with scores ranging from 3 to 15; t = 2.83, p = .006). Greater sleep-inhibiting (ß = 0.40, p = .011) and fewer sleep-promoting (ß = -0.28, p = .049) behaviors during the school year were associated with having a higher BMI. There were no associations among sleep patterns, sleep hygiene and BMI during summer. CONCLUSIONS: More positive school year sleep hygiene behaviors were supportive of having a healthier weight status. Changes in these behaviors during the summer did not portend worse weight outcomes. Supporting families in the establishment of sleep-promoting behaviors, particularly during the school year may help address the child obesity epidemic.

Validation of the Entrainment Signal Regularity Index and associations with children's changes in BMI.

OBJECTIVE: This study examined the validity of a novel metric of circadian health, the Entrainment Signal Regularity Index (ESRI), and its relationship to changes in BMI during the school year and summer. METHODS: In a longitudinal observational data set, this study examined the relationship between ESRI score and children's (n = 119, 5- to 8-year-olds) sleep and physical activity levels during the school year and summer, differences in ESRI score during the school year and summer, and the association of ESRI score during the school year and summer with changes in BMI across those time periods. RESULTS: The ESRI score was higher during the school year (0.70 ± 0.10) compared with summer (0.63 ± 0.11); t(111) = 5.484, p < 0.001. Whereas the ESRI score at the beginning of the school year did not significantly predict BMI change during the school year (ß = 0.05 ± 0.09 SE, p = 0.57), having a higher ESRI score during summer predicted smaller increases in BMI during summer (ß = -0.22 ± 0.10 SE, p = 0.03). CONCLUSIONS: Overall, children demonstrated higher entrainment regularity during the school year compared with the summer. During summer, having a higher entrainment signal was associated with smaller changes in summertime BMI. This effect was independent of the effects of children's sleep midpoint, sleep regularity, and physical activity on children's BMI.

The roles of sleep and eating patterns in adiposity gain among preschool-aged children.

BACKGROUND: Short sleep durations are related to risks for obesity in preschool children. However, the underlying mechanism or mechanisms are not clear. OBJECTIVES: We evaluated the relationships between sleep characteristics and body composition, energetics, and weight-regulating behaviors in preschool-aged children, as well as the longitudinal associations between children's sleep and eating patterns and body composition at a 1-year follow-up. METHODS: Data were drawn from a longitudinal study of 118 children aged 3-5 years. Sleep (duration, midpoint, regularity) and physical activity (PA) were measured by accelerometry over 6 consecutive days; total energy expenditure (TEE) was measured using the doubly labeled water method; body composition (fat mass, fat-free mass, and percent body fat) was measured by DXA; and dietary intake (energy intake, timing) was measured using two 24-hour recalls. Multivariable regression was used to estimate interindividual associations of sleep parameters with body composition, PA, TEE, and dietary outcomes and to examine the relationships between sleep and dietary behaviors and body composition 1 year later. RESULTS: Cross-sectionally, later sleep midpoint is associated with having a greater fat mass (0.33; 95% CI: 0.05, 0.60) and a higher percent body fat (0.92; 95% CI: 0.15, 1.70). Later sleep midpoint was associated with delayed morning mealtimes (0.51; 95% CI: 0.28, 0.74) and evening mealtimes (0.41; 95% CI: 0.29, 0.53), higher nighttime energy intakes (45.6; 95% CI: 19.7, 71.4), and lower morning energy intakes (-44.8; 95% CI: -72.0, -17.6). Longitudinally, shorter sleep duration (-0.02; 95% CI: -0.03, 0.00) and later meal timing (0.83; 95% CI: 0.24, 1.42) were associated with higher percent body fat measurements 1 year later. CONCLUSIONS: Shorter sleep duration and later meal timing are associated with adiposity gains in preschoolers.

Seasonality of Children's Height and Weight and Their Contribution to Accelerated Summer Weight Gain.

Background: While children have been shown to have increased BMI during the summer compared to the school year, it is not known if this may be due to seasonal variations in height or weight separately. Methods: Trained nurses measured heights (cm) and weights (kg) in a cohort of Kindergarteners (n = 7648) twice per year from the beginning of kindergarten through 5th grade. Variation in height and weight by season (school year vs. summer) was examined using separate mixed-effects models. Season, sex, and BMI trajectory group were tested as fixed effects. Random effects included repeated measurements of time, students nested within a school, intercept, and slope for growth over time. Similar models using BMIz as the outcome examined the interaction of height or weight with season. Results: The rate of height gain was greater during the school year (∼Sept to April) compared to summer (∼April to Sept) (ß = -0.05, SE = 0.013, p < 0.0001). The rate of weight gain did not differ seasonally. Height gain was more strongly associated with increased BMIz during summer compared to the school year (ß =.02, SE = 0.005, p <0 .0001), mainly among children who remained healthy weight throughout elementary school (ß = 0.014, SE = 0.003, p < 0.0001) and those who transitioned to a healthier weight status (ß = 0.026, SE = 0.008, p = 0.004). We found a similar seasonal effect for the association between weight with BMIz among children who maintained a healthy weight status (ß = 0.014, SE = 0.014, p < 0.0001). Conclusion: This study indicates seasonality in children's height gain, gaining height at a faster rate during the school year compared to the summer, while weight gain remained relatively more consistent throughout the year. Seasonality in height and weight gain had the greatest impact on BMIz among children with a healthy weight status. Future research with more frequent measurements is needed to better understand the seasonal regulation of children's growth and weight gain.

Evaluation of a Circadian Rhythm and Sleep-Focused Mobile Health Intervention for the Prevention of Accelerated Summer Weight Gain Among Elementary School-Age Children: Protocol for a Randomized Controlled Feasibility Study.

BACKGROUND: The i♥rhythm project is a mobile health adaptation of interpersonal and social rhythm therapy designed to promote healthy sleep and behavioral rhythms among 5-8-year olds during summer for the prevention of accelerated summer weight gain. OBJECTIVE: This pilot study will examine the feasibility, acceptability, and preliminary efficacy of the i♥rhythm intervention. This will ensure that the research protocol and procedures work as desired and are acceptable to families in preparation for the fully powered randomized controlled trial. The proposed study will examine the willingness of participants to participate in the intervention and determine whether modifications to the intervention, procedures, and measures are needed before conducting a fully powered study. We will assess our ability to (1) recruit, consent, and retain participants; (2) deliver the intervention; (3) implement the study and assessment procedures; (4) assess the reliability of the proposed measures; and (5) assess the acceptability of the intervention and assessment protocol. METHODS: This study will employ a single-blinded 2-group randomized control design (treatment and no-treatment control) with randomization occurring after baseline (Time 0) and 3 additional evaluation periods (postintervention [Time 1], and 9 months [Time 2] and 12 months after intervention [Time 3]). A sample of 40 parent-child dyads will be recruited. RESULTS: This study was approved by the institutional review board of Baylor College of Medicine (H-47369). Recruitment began in March 2021. As of March 2022, data collection and recruitment are ongoing. CONCLUSIONS: This study will address the role of sleep and circadian rhythms in the prevention of accelerated summer weight gain and assess the intervention's effects on the long-term prevention of child obesity. TRIAL REGISTRATION: ClinicalTrials.gov NCT04445740; https://clinicaltrials.gov/ct2/show/NCT04445740. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/37002.

Estimating circadian phase in elementary school children: leveraging advances in physiologically informed models of circadian entrainment and wearable devices.

STUDY OBJECTIVES: Examine the ability of a physiologically based mathematical model of human circadian rhythms to predict circadian phase, as measured by salivary dim light melatonin onset (DLMO), in children compared to other proxy measurements of circadian phase (bedtime, sleep midpoint, and wake time). METHODS: As part of an ongoing clinical trial, a sample of 29 elementary school children (mean age: 7.4 ± .97 years) completed 7 days of wrist actigraphy before a lab visit to assess DLMO. Hourly salivary melatonin samples were collected under dim light conditions (<5 lx). Data from actigraphy were used to generate predictions of circadian phase using both a physiologically based circadian limit cycle oscillator mathematical model (Hannay model), and published regression equations that utilize average sleep onset, midpoint, and offset to predict DLMO. Agreement of proxy predictions with measured DLMO were assessed and compared. RESULTS: DLMO predictions using the Hannay model outperformed DLMO predictions based on children's sleep/wake parameters with a Lin's Concordance Correlation Coefficient (LinCCC) of 0.79 compared to 0.41-0.59 for sleep/wake parameters. The mean absolute error was 31 min for the Hannay model compared to 35-38 min for the sleep/wake variables. CONCLUSION: Our findings suggest that sleep/wake behaviors were weak proxies of DLMO phase in children, but mathematical models using data collected from wearable data can be used to improve the accuracy of those predictions. Additional research is needed to better adapt these adult models for use in children. CLINICAL TRIAL: The i Heart Rhythm Project: Healthy Sleep and Behavioral Rhythms for Obesity Prevention https://clinicaltrials.gov/ct2/show/NCT04445740.

Validation of the Family Health Behavior Scale for the Brazilian population

Abstract Objective: To validate the Family Health Behavior Scale (FHBS) for Brazilian families. Methods: The sample included 272 children aged 5 to 12 years old. Caregivers and their healthy answered the FHBS and questions about physical activity. In addition, anthropometric measurements of the children's weight and height were performed, as well as the bioimpedance exam. The scale was translated and the following validities were assessed: content (qualitative analysis and content validity index), construct (factor analysis) and concurrent validity (difference between domains and the total score with the categories of BMI, fat percentage and physical activity). Reliability (Cronbach's alpha, ceiling-floor effect, two-half test, intraclass correlation and Bland - Altman) was also assessed. Results: FHBS instrument performed well with regard to the psychometric properties in the Brazilian population. The content validity index was 0.987. Fit indices of the factor analysis were considered satisfactory, according to Bartlett's sphericity test (χ 2 = 1927, df = 351; p < 0.001) and the Kaiser-Meyer-Olkin index (KMO = 0.789). Concurrent validity, the differences between the mean of the domains and the total score between the categories of BMI (p = 0.011), percentage of fat (0.004) and physical activity (p < 0.001) were all significant. The reliability results were Cronbach's alpha internal consistency = 0.83, adequate ceiling-floor effect, 0.8105 (0.09 SD) two-half test, 0.626 intraclass correlation (95% CI: 0.406 to 0.777) and Bland - Altman -0.840 (-22.76 to 21.07). Conclusion: The FHBS adapted for the Brazilian population showed evidence of adequate psychometric performance.

Validation of the Family Health Behavior Scale for the Brazilian population.

OBJECTIVE: To validate the Family Health Behavior Scale (FHBS) for Brazilian families. METHODS: The sample included 272 children aged 5 to 12 years old. Caregivers and their healthy answered the FHBS and questions about physical activity. In addition, anthropometric measurements of the children's weight and height were performed, as well as the bioimpedance exam. The scale was translated and the following validities were assessed: content (qualitative analysis and content validity index), construct (factor analysis) and concurrent validity (difference between domains and the total score with the categories of BMI, fat percentage and physical activity). Reliability (Cronbach's alpha, ceiling-floor effect, two-half test, intraclass correlation and Bland - Altman) was also assessed. RESULTS: FHBS instrument performed well with regard to the psychometric properties in the Brazilian population. The content validity index was 0.987. Fit indices of the factor analysis were considered satisfactory, according to Bartlett's sphericity test (χ 2 = 1927, df = 351; p < 0.001) and the Kaiser-Meyer-Olkin index (KMO = 0.789). Concurrent validity, the differences between the mean of the domains and the total score between the categories of BMI (p = 0.011), percentage of fat (0.004) and physical activity (p < 0.001) were all significant. The reliability results were Cronbach's alpha internal consistency = 0.83, adequate ceiling-floor effect, 0.8105 (0.09 SD) two-half test, 0.626 intraclass correlation (95% CI: 0.406 to 0.777) and Bland - Altman -0.840 (-22.76 to 21.07). CONCLUSION: The FHBS adapted for the Brazilian population showed evidence of adequate psychometric performance.

Later sleep timing predicts accelerated summer weight gain among elementary school children: a prospective observational study.

OBJECTIVES AND BACKGROUND: Social demands of the school-year and summer environment may affect children's sleep patterns and circadian rhythms during these periods. The current study examined differences in children's sleep and circadian-related behaviors during the school-year and summer and explored the association between sleep and circadian parameters and change in body mass index (BMI) during these time periods. METHODS: This was a prospective observational study with 119 children ages 5 to 8 years with three sequential BMI assessments: early school-year (fall), late school-year (spring), and beginning of the following school-year in Houston, Texas, USA. Sleep midpoint, sleep duration, variability of sleep midpoint, physical activity, and light exposure were estimated using wrist-worn accelerometry during the school-year (fall) and summer. To examine the effect of sleep parameters, physical activity level, and light exposure on change in BMI, growth curve modeling was conducted controlling for age, race, sex, and chronotype. RESULTS: Children's sleep midpoint shifted later by an average of 1.5 h during summer compared to the school-year. After controlling for covariates, later sleep midpoints predicted larger increases in BMI during summer, (γ = .0004, p = .03), but not during the school-year. Sleep duration, sleep midpoint variability, physical activity levels, and sedentary behavior were not associated with change in BMI during the school-year or summer. Females tended to increase their BMI at a faster rate during summer compared to males, γ = .06, p = .049. Greater amounts of outdoor light exposure (γ = -.01, p = .02) predicted smaller increases in school-year BMI. CONCLUSIONS: Obesity prevention interventions may need to target different behaviors depending on whether children are in or out of school. Promotion of outdoor time during the school-year and earlier sleep times during the summer may be effective obesity prevention strategies during these respective times.

Variability of Sleep and Relations to Body Weight Among First-Year College Students.

BACKGROUND: Existing research suggests that greater sleep variability may increase risk for weight gain. College often marks a transition to a less consistent daily schedule, which may adversely impact sleep routines and further increase risk for weight gain. The current study is among the first to explore relations between nighttime sleep variability and daytime sleep (napping) and body weight among first-year college students. METHODS: Using daily diary methods, first-year college students (N = 307; 84.7% female) self-reported their sleep for seven days. Several indices were created to capture sleep variability for reported bedtime, wake time, and sleep duration, including weekday versus weekend differences (WvW), day to day differences (D2D), and overall standard deviation (SD). Napping was also assessed. Based on body mass index (BMI), individuals were categorized as underweight, healthy weight, overweight, and obese. RESULTS: Across indices, students' sleep varied over an hour on average across the week. Hierarchical regressions revealed that greater differences in wake time D2D, wake time SD, and sleep duration WvW were all associated with higher BMI, after accounting for gender, depressive symptoms, and sleep duration. Longer napping was also associated with higher BMI, using the same covariates. Finally, greater sleep variability was reported by overweight and obese than healthy weight individuals. CONCLUSION: These findings suggest that sleep variability, particularly wake times and napping may be important modifiable sleep behaviors to investigate in future studies. More longitudinal research is needed to explore relations between multiple facets of sleep variability and weight gain, including possible mechanisms.

Symptom prevalence differences of depression as measured by BDI and PHQ scales in the Look AHEAD study.

OBJECTIVE: To compare depressive symptomatology as assessed by two frequently used measures, the Beck Depression Inventory (BDI-1A) and Patient Health Questionnaire (PHQ-9). METHODS: Investigators conducted a cross-sectional secondary analysis of data collected as part of the follow-up observational phase of the Look AHEAD study. Rates of agreement between the BDI-1A and PHQ-9 were calculated, and multivariable logistic regression was used to examine the relationship between differing depression category classifications and demographic factors (ie, age, sex, race/ethnicity) or comorbidities (ie, diabetes control, cardiovascular disease). RESULTS: A high level of agreement (κ = 0.47, 95% CI (0.43 to 0.50)) was found in the level of depressive symptomatology between the BDI-1A and PHQ-9. Differing classifications (minimal, mild, moderate, and severe) occurred in 16.8% of the sample. Higher scores on the somatic subscale of the BDI-1A were significantly associated with disagreement as were having a history of cardiovascular disease, lower health-related quality of life, and minority racial/ethnic classification. CONCLUSIONS: Either the BDI-1A or PHQ-9 can be used to assess depressive symptomatology in adults with overweight/obesity and type 2 diabetes. However, further assessment should be considered in those with related somatic symptoms, decreased quality of life, and in racial/ethnic minority populations.

Physiological mechanisms underlying children's circannual growth patterns and their contributions to the obesity epidemic in elementary school age children.

Several studies since the 1990s have demonstrated that children increase their body mass index at a faster rate during summer months compared with the school year, leading some to conclude that the out-of-school summer environment is responsible. Other studies, however, have suggested that seasonality may play a role in children's height and weight changes across the year. This article reviews evidence for seasonal differences in the rate of children's height and weight gain and proposes potential physiological mechanisms that may explain these seasonal variations.

Integrating wearable data into circadian models.

The emergence of wearable health sensors in the last decade has the potential to revolutionize the study of sleep and circadian rhythms. In particular, recent progress has been made in the use of mathematical models in the prediction of a patient's internal circadian state using data measured by wearable devices. This is a vital step in our ability to identify optimal circadian timing for health interventions. We review the available data for fitting circadian phase models with a focus on wearable data sets. Finally, we review the current modeling paradigms and explore avenues for developing personalized parameter sets in limit cycle oscillator models in order to further improve prediction accuracy.

Spanish Version of the Family Health Behavior Scale: Adaptation and Validation.

Different studies around the world indicate that the percentages of overweight and obesity in childhood and adolescence are high. In this context, it would be useful to have a common, valid, and reliable instrument to assess health behaviors of families that allows comparisons of data from different countries. The objective is the adaptation of a Spanish version of the Family Health Behavior Scale (FHBS). The questionnaire originally developed by Moreno group was translated and adapted following the International Test Commission protocol. Its psychometric properties were evaluated through analysis of internal consistency, factor analysis and other evidences of validity. The Spanish version of the FHBS demonstrated adequate reliability coefficients, and its factor structure sufficiently replicated that obtained by the original measurement. The results suggested that the adapted version of the questionnaire was an adequate and valid measure for the evaluation of family health behaviors related to the prevention of overweight and obesity.

Potential circadian and circannual rhythm contributions to the obesity epidemic in elementary school age children.

Children gain weight at an accelerated rate during summer, contributing to increases in the prevalence of overweight and obesity in elementary-school children (i.e., approximately 5 to 11 years old in the US). Int J Behav Nutr Phys Act 14:100, 2017 explained these changes with the "Structured Days Hypothesis" suggesting that environmental changes in structure between the school year and the summer months result in behavioral changes that ultimately lead to accelerated weight gain. The present article explores an alternative explanation, the circadian clock, including the effects of circannual changes and social demands (i.e., social timing resulting from societal demands such as school or work schedules), and implications for seasonal patterns of weight gain. We provide a model for understanding the role circadian and circannual rhythms may play in the development of child obesity, a framework for examining the intersection of behavioral and biological causes of obesity, and encouragement for future research into bio-behavioral causes of obesity in children.

Multi-etiological Perspective on Child Obesity Prevention.

PURPOSE OF REVIEW: The simple energy balance model of obesity is inconsistent with the available findings on obesity etiology, prevention, and treatment. Yet, the most commonly stated causes of pediatric obesity are predicated on this model. A more comprehensive biological model is needed upon which to base behavioral interventions aimed at obesity prevention. In this light, alternative etiologies are little investigated and thereby poorly understood. RECENT FINDINGS: Three candidate alternate etiologies are briefly presented: infectobesity, the gut microbiome, and circadian rhythms. Behavioral child obesity preventive investigators need to collaborate with biological colleagues to more intensively analyze the behavioral aspects of these etiologies and to generate innovative procedures for preventing a multi-etiological problem, e.g., group risk analysis, triaging for likely causes of obesity.