Identifying patterns of obesity risk behavior to improve pediatric primary care

Clustering of diet, physical activity and sedentary behaviour and related physical and mental health outcomes: a systematic review

BACKGROUND

Physical activity (PA), sedentary behaviour (SB) and diet play an important role in the physical and mental health of young people. Understanding how these behaviours cluster, and the impact of clusters on health is important for the development of public health interventions. This review examines the prevalence of clusters of PA, sedentary time, and dietary behaviours, and how clusters relate to physical and mental health indicators among children, adolescents and young adults.

METHODS

Electronic (PubMed, Web of Science and Scopus) and manual searches were conducted for articles that were (i) observational studies including children, adolescents and/or young adults aged 5-24 years, (ii) examined the 'patterning', 'clustering', or 'co-existence' of each of PA, dietary behaviour and SB, and (iii) published in English up to and including July 2022. In addition to information on clustering, data on physical and mental health outcomes were extracted where reported. Included studies were assessed using the Cochrane risk of bias for observational studies. A narrative synthesis was conducted due to high heterogeneity. This review was registered with PROSPERO (CRD42021230976).

RESULTS

Forty-nine cross-sectional studies and four prospective cohort studies from eighteen countries reporting data from 778,415 individual participants were included. A broad range of clusters (n = 172) were found (healthy, unhealthy, and mixed). Mixed clusters were common (n = 98), and clusters of high diet quality, low PA and high SB were more prevalent in girls, while mixed clusters of high PA, high SB and low diet quality were more prevalent in boys. Unhealthy clusters comprising low moderate to vigorous PA, low consumption of fruits and vegetables, and high screen time were prevalent, particularly in those from lower socioeconomic status families. Compared to those with healthy behavioural clusters, those with unhealthy and mixed clusters had a higher adiposity, higher risk of cardiovascular disease, poorer mental health scores, and lower cardiorespiratory fitness.

CONCLUSIONS

PA, SB and diet cluster in healthy, unhealthy and mixed patterns in young people that differ across sociodemographic characteristics. Unhealthy clusters are associated with poorer health outcomes. Intervention strategies targeting un-clustering multiple unhealthy behaviours should be developed and evaluated for their impact on health outcomes.

Exploring factors associated with obesity in Argentinian children using structural equation modeling

Habits and behaviors related to obesity risk are strongly associated with the family environment and are affected by socioeconomic factors. Structural equation modeling (SEM) allows us to hypothesize on how the relationships between these factors occur and measure their impact. This study aimed to explore the relationship between family socioeconomic indicators and childhood obesity, mediated by habits linked to energy balance, applying a SEM. A cross sectional study was performed on 861 Argentinian schoolchildren aged 6-12 years, from 2015 to 2016. The model included three latent variables: socioeconomic status, healthy habits, and obesity. Socioeconomic status indicators and healthy habits were surveyed by self-administered parental questionnaires, whereas obesity indicators were evaluated with anthropometry. The applied model showed an acceptable fit (NFI = 0.966; CFI = 0.979; RMSEA = 0.048). Socioeconomic status positively influenced parental education, health insurance, and car possession, while negatively influenced crowding (p < 0.001). Healthy habits significantly influenced physical activity, meals frequency, and sleep hours, while negatively influenced sedentary hours and mother's nutritional status (p < 0.001). Obesity factor positively influenced body mass index, body fat, and waist-to-height ratio (p < 0.001). Finally, socioeconomic status positively influenced health habits, which in turn negatively influenced obesity factor. Healthy habits (especially physical activity and mother's nutritional status) mediated the relationship between socioeconomic status and child obesity. Further research should include other indicators related to diet, eating habits, and physical activity like neighborhood characteristics.

Clustering of diet, physical activity and sedentary behavior among Brazilian adolescents in the national school - based health survey (PeNSE 2015)

BACKGROUND

There is a lack of evidence regarding clusters of health-related behaviors among adolescents from low, lower-middle, and upper-middle income countries. This study aimed to identify clustering patterns of health-related behaviors (diet, physical activity [PA] and sedentary behavior [SB]) and association with sociodemographic variables among a population-based sample of Brazilian adolescents.

METHODS

Cross-sectional data from the 2015 National School-Based Health Survey (PeNSE). A total of 102,072 (females: 51.7%) students in ninth-grade (age: 14.3 ± 1.1 years-old) enrolled in public and private schools were investigated in this study. Healthy and unhealthy diet, PA and SB were measured using a validated questionnaire. Two-step cluster analysis was conducted to identify lifestyle patterns. The methodology for complex analysis and weighting was used to inferential statistical procedures. Multinomial logistic regression assessed associations between sociodemographic factors and the clusters.

RESULTS

Three reliable and meaningful clusters were identified and labelled as follows: (1) health-promoting SB and diet (32.6%); (2) health-promoting PA and diet (44.9%), and (3) health-risk (22.5%). Compared to boys, girls were less likely to be in clusters 1 (OR = 0.85; 95% CI = 0.78-0.93, p < 0.001) and 2 (OR = 0.43; 95% CI = 0.40-0.46, p < 0.001) than the health-risk cluster. Higher socioeconomic status was positively associated with health-promoting PA and diet, and negatively related to health-promoting SB and diet. Older adolescents were more likely to be in cluster 1 than in cluster 3, compared to younger adolescents.

CONCLUSION

Approximately one-quarter of the population (health-risk cluster) reported engaging in multiple risk behaviors. Interventions may need to be tailored to specific adolescent groups, especially considering sociodemographic differences.

'Life in the age of screens': parent perspectives on a 24-h no screen-time challenge

Screens have become ubiquitous in modern society. Their use frequently underlies sedentary behaviour, a well-established determinant of obesity. As part of a family oriented clinic offering a 2-year lifestyle program for obese children and youth, we explored parents' experiences with a 24-h no screen-time challenge, an intervention designed to raise awareness of screen-time habits and to help families develop strategies to limit their use. In total, 15 parents representing 13 families participated. A focus group with nine parents and six phone interviews with those who could not join in person were conducted. Interviews were transcribed verbatim and analysed qualitatively. Key elements to successful completion of the 24-h no screen-time challenge emerged, namely: clear rules about permitted activities during the 24-h period; togetherness, i.e. involving all family members in the challenge; and busyness, i.e. planning a full schedule in order to avoid idleness and preclude the temptation to use screens. Our findings suggest that practitioners aiming to increase awareness of screen-time or to limit their use may be more likely to succeed if they include all family members, offer concrete alternatives to screen-based activities and provide tailored strategies to manage discretionary time.