Adolescent BMI trajectories with clusters of physical activity and sedentary behaviour: an exploratory analysis

Enjoyment of Physical Activity-Not MVPA during Physical Education-Predicts Future MVPA Participation and Sport Self-Concept

There exists a general understanding that physical education (PE) is a means to create a physically healthy population. However, disagreements arise over primary practices within PE to achieve this end. The primary divergence is whether PE facilitators should primarily ensure participants exert a specific level of energy during class or develop their confidence, competence, knowledge, and motivation for meaningful physical activity (PA) participation outside of the PE classroom (referred to as physical literacy (PL)). This study uses structural equation modeling to examine associations between enjoyment of PA and minutes of moderate to vigorous physical activity (MVPA) in PE class in grade 5 (mean age = 10) and participation in PA and feelings about PA 1 year later, in grade 6 (mean age = 11), in the NICHD Study of Early Child Care and Youth Development (SECCYD, N = 1364). Enjoyment of PA in grade 5 predicted sport self-concept (β = 0.347, p ≤ 0.001), MVPA (β = 0.12, p ≤ 0.001), and enjoyment of PA (β = 0.538, p ≤ 0.001) in grade 6. These associations remained when including weekday MVPA performed in grade 5 as an indirect effect (β = 0.058, p ≤ 0.001). MVPA performed during PE in grade 5 was not associated with any PA outcomes in grade 6. Findings suggest PE instructors should prioritize PL development over maintenance of high energy expenditure during PE class for long-term MVPA.

Relations between body mass index trajectories and habitual physical activity measured by smartwatch in the electronic cohort of the Framingham Heart Study: Cohort Study (Preprint)

Background

Objective

Methods

Results

Conclusions

Determinants of Physical Activity for Latino and White Middle School-Aged Children

BACKGROUND

Physical activity (PA) has long been acknowledged to contribute health benefits among children. However, research has consistently shown that PA declines as children grow older. Thus, this study examined the factors which are associated to children's PA in order to identify potential barriers to PA.

METHODS

Using data from the KidQuest Program, we conducted bivariate and multivariate analyses on survey data collected from fifth to seventh grade students in a small Midwestern city.

RESULTS

We found that food knowledge, eating breakfast, and talking with family about eating healthy foods, are positively related to PA. On the other hand, screen time is negatively related to PA. In addition, our results evinced differences between ethnicities and found that Latino children's screen time affects their PA levels more than their white counterpart.

CONCLUSIONS

There are different factors which can be tapped to increase PA among middle school-aged children. Given the differences between the Latino and white samples especially in screen time, schools should consider individualized intervention, rather than a "one size fits all" program, to increase PA participation.

Trajectories of Body Mass Index from Childhood to Young Adulthood among Patients with Type 1 Diabetes-A Longitudinal Group-Based Modeling Approach Based on the DPV Registry

OBJECTIVE

To identify distinct longitudinal patterns of body mass index (BMI) z score in type 1 diabetes from childhood to young adulthood and secondly to determine sex differences as well as associated clinical covariates.

STUDY DESIGN

A total of 5665 patients with type 1 diabetes (51% male) with follow-up from 8 to 20 years of age from the multicenter diabetes prospective registry DPV were studied (baseline diabetes duration ≥1 years, BMI z score aggregated per year of life). Latent class growth modeling (SAS: PROC TRAJ) was applied to analyze BMI z score over time.

RESULTS

Six distinct BMI z score trajectories were identified (group 1: 7% of patients, group 2: 22%, group 3: 20%, group 4: 16%, group 5: 25%, and group 6: 10%). Group 1, 2, 5, and 6 had an almost stable BMI z score, either in the low, near-normal, high stable, or chronic overweight range. Group 3 (60% girls) increased their BMI during puberty, whereas group 4 (65% boys) had a BMI decrease. Similar patterns were observed for girls only, whereas boys followed nearly stable trajectories without fluctuation over time. Between the near-normal and the other groups, significant differences (P < .05) in sex ratio, migration background, mental health, height z score, glycated hemoglobin A1c, diabetes treatment, dyslipidemia, hypertension, and smoking were observed.

CONCLUSIONS

In youth with type 1 diabetes, a great heterogeneity of BMI z score trajectories exists that highlight the importance of personalized sex-specific intervention programs for subjects at risk for unfavorable BMI development.

Paediatric obesity and cardiovascular risk factors - A life course approach

Childhood obesity is increasingly prevalent worldwide, and Portugal presents one of the highest prevalence of obesity and overweight among the European countries. Since childhood obesity is a risk factor for obesity in adulthood, the high prevalence of overweight and obesity in paediatric age currently experienced is expected to lead to even higher prevalence of obesity in adulthood in future decades. It is well known that the prenatal period and infancy are critical or sensitive periods for obesity development, but a growing body of evidence also suggests a relevant role of childhood and adolescence. The exposure to some factors during these periods or specific time frames within these periods may confer additional risk for obesity development. Paediatric obesity is associated with cardiovascular risk factors both in the short or medium-term, but also in the long term, conferring additional risk for future adult health. However, it is not clear whether the relation between paediatric obesity and adult health is independent of adult adiposity. There is a moderate to high tracking of obesity from paediatric age into adulthood, which may partially explain the association with adult outcomes. Therefore, there has been increasing interest on life course frameworks to study the effect of the dynamics of adiposity across paediatric age on adult outcomes, namely on the cardiovascular disease risk. The use of this approach to study determinants and consequences of obesity raises methodological challenges to summarize the exposure to adiposity/obesity across the life span, being the identification of growth trajectories and the quantification of the duration of obesity among the most used methods. However, further investigation is still needed to explore the best methods to summarize exposure to adiposity and its variation across time.

Adolescent BMI trajectories with clusters of physical activity and sedentary behaviour: an exploratory analysis

Objective

The purpose of this study is to identify distinct body mass index (BMI) trajectories associated with weight classification, and to examine demographic characteristics and clusters of obesogenic behaviours in adolescents with these trajectories.

Methods

Data were extracted from the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development (n = 1,006, Grades 5–8). The independent variables were physical activity (accelerometer and child report), sports participation, television/video watching time and recreational computer use. The dependent variable was raw BMI. Growth mixture modelling, mixture modelling and independent t‐test analyses were used.

Results

Two distinct BMI trajectories were identified – one with the mean BMI within the Overweight–Obese classification (≥85^th percentile) and the other within the healthy weight classification (5^th– 84^th percentile). Two clusters of physical and sedentary behaviours were identified in adolescents with the Overweight–Obese BMI trajectory. These clusters differed in the type of sedentary behaviour (computer vs. television/video). Three clusters were identified in adolescents with the Healthy Weight BMI trajectory. These clusters differed in levels of physical activity and types of sedentary behaviour.

Conclusion

This study contributes to the understanding of multi‐dimensional obesogenic behavioural patterns and highlights the importance of understanding types of sedentary behaviour in adolescents.