Clustering of specific health-related behaviours among Toronto adolescents

Clustering Health Behaviors in Mexican Adolescents: The HELENA-MEX Study

Purpose: The prevalence of excess weight within the adolescent population is rapidly increasing in Mexico, especially in areas with lower socioeconomic status. The present study aimed to identify lifestyle clustered patterns in adolescents and analyze the associations among these clusters and body composition. Method: A final sample of n=259 participants (13 to 17 years old, 58.7% girls), residents in rural and urban areas, were included. Hierarchical and k-means clusters analyses included moderate to vigorous physical activity (MVPA), cardiorespiratory fitness (CRF), handgrip strength, screen time, sleep time, and diet. The associations between cluster membership and body composition were analyzed through general linear models (ANCOVA), including sex, age, place of residence, and socioeconomic status as covariates. Results: Three different clusters were identified: Cluster 1, [Unhealthy] (low values in all lifestyle patterns), Cluster 2, [Low Physical Fitness] (low values in CRF and handgrip strength) and Cluster 3, [High Physical Activity and CRF] (highest values in CRF, handgrip strength and MVPA). Clusters 2 and 3 showed high values in screen time and industrialized food consumption. There were no differences in sleep between the 3 Clusters. ANCOVA analysis revealed that participants belonging to Cluster 3 showed significantly lower adiposity and a higher Fat Free Mass compared with the other two clusters (p < 0.05). Conclusion: Our findings suggest that a lifestyle characterized by high levels of physical activity and physical fitness and low consumption of industrialized food may be protective against the problem of obesity, which could be helpful to develop interventions to reduce excess weight in Mexican adolescents.

Physical activity, screen time and dietary behaviours in New Zealand adolescents prior to and following the onset of the COVID-19 pandemic

BACKGROUND

Insufficient physical activity, high screen time, and unhealthy dietary patterns among adolescents may have worsened during the pandemic, but data are lacking. This study compared physical activity, screen time and fruit and vegetable intake in adolescents from Dunedin, New Zealand, 5-6 years before (Study 1) and during (Study 2) the COVID-19 pandemic.

METHODS

Adolescents completed an online survey as part of the Built Environment and Active Transport to School (BEATS) studies in 2014/2015 (Study 1; n = 1,266; age: 15.3 ± 1.4 years; 54.6% female) and 2021/2022 (Study 2; n = 819; age: 15.2 ± 1.4 years; 47.4% female). The proportion of adolescents meeting guidelines for physical activity (≥ 60 min/day of moderate-to-vigorous physical activity), outside school screen time (≤ 2 h/day) and fruit and vegetable intake (> 1 serving/day for both fruit and vegetables) was calculated. Data were analysed using multivariable linear and logistic regression modelling.

RESULTS

Few adolescents met recommended health behaviour guidelines. Compared to Study 1, significantly greater proportions of adolescents at Study 2 met guidelines for physical activity (16.7% vs. 23.1%; p < 0.001) and outside school screen time (13.3% vs. 18.3%; p < 0.001) while fruit and vegetable intake was not different (29.6% vs. 27.0%; p = 0.322). Compared to Study 1, average outside school screen time at Study 2 was lower on both weekdays (5.0 ± 2.9 vs. 4.6 ± 2.9; p < 0.001) and weekend days (6.9 ± 3.5 vs. 6.1 ± 3.6 h/day; p < 0.001). Reported frequency of consuming sweets was higher and soft drinks lower at Study 2 versus Study 1.

CONCLUSIONS

Despite observed higher levels of physical activity and lower levels of outside school screen time during the pandemic compared to the pre-pandemic levels, few adolescents met health behaviour guidelines at both time points. Therefore, comprehensive health promotion that aims to improve physical activity levels, screen time and dietary patterns for adolescents is still necessary to prevent chronic health conditions adulthood.

Obesogenic behavior clusters associated with weight status among Brazilian students: a latent class analysis

This study aimed to examine the association between clusters of physical activity (PA), diet, and television viewing (TV) with weight status among a representative sample of Brazilian students. Data from the National Health School-based Survey (PeNSE) 2015 were analyzed (n = 16,521; mean age 14.8, standard deviation 0.03 year). PA (minutes/week spent in leisure-time, and commuting to/from school), TV (hours/day), and weekly consumption of deep-fried empanadas, candies, sodas, ultra-processed foods, fast foods, green salads or vegetables, and fruits were self-reported on the validated PeNSE questionnaire. Latent class analysis defined behavior classes, and binary logistic regression assessed the association between clustering and weight status. Six classes' types with positive and negative behaviors were identified. Adolescents belonging to the "low TV time and high healthy diet" class had higher chances of being overweight (including obesity) compared to their peers in the "moderate PA and mixed diet" class. No associations were found in the other clusters. Mixed classes with healthy and unhealthy behaviors characterized adolescents' lifestyles and these profiles were related to weight status.

Congruence between Physical Activity Patterns and Dietary Patterns Inferred from Analysis of Sex Differences in Lifestyle Behaviors of Late Adolescents from Poland: Cophylogenetic Approach

Global trends toward physical inactivity and the replacement of healthy dietary behaviors with unhealthy food consumption, particularly in late adolescence, were commonly observed. Thus, the aim of this work was twofold: (1) to examine congruence between PAPs and DPs by identifying sex differences in healthy and unhealthy behaviors and (2) to assess the explanation behind why certain participants were classified into clusters using BMI and fat mass covariates. Late adolescents (19-21 years of age, n = 107) were selected to study. PAPs and DPs were assessed with questionnaires (IPAQ, QEB) and body height, weight, and fat mass percentage were self-reported (the accuracy and reliability of self-reported data were empirically verified). A cophylogenetic approach with several clustering procedures (heatmaps and tanglegrams) was the way to solve the stated problems. Results showed that students achieved the minimal level of physical activity, lower than students from other regions in Poland, Czech Republic, or Germany. There was congruence between PAPs and DPs in some males' and females' behaviors. Significant similarities in sex patterns of behaviors were revealed (Mantel tests-PAPs: r = 0.70, p < 0.001; DPs: r = 0.84, p < 0.001). Similarities in PAPs were related to transportation cycling and school/work activities behaviors. Non-healthy triads in dietary behaviors were found: fast-food, sweetened beverages, and alcoholic drinks in the first, and sweets, fried meals, and yellow cheese in the second. One healthy diad was revealed: vegetables and fruits. Only females' dietary behaviors were reflected in body mass index (F = 3.19, p = 0.049), percentage of body fat (F = 3.87, p = 0.027), and fat mass index (F = 3.83, p = 0.028). The usefulness of the cophenetic approach in patterns study was verified. Sex similarities and specific disparities could help preparing targeted tailored intervention programs that improve healthy habits in late adolescents. This is especially important in relation to females, who more strongly reflected dietary behaviors in body composition.

Clustering of Physical Activity, Diet and Sedentary Behavior among Youth from Low-, Middle-, and High-Income Countries: A Scoping Review

Background: The interaction between physical activity (PA), diet, and sedentary behavior (SB) plays an important role on health-related outcomes. This scoping review (Prospero CRD42018094826) aims to identify and appraise clusters of PA, diet, and SB among youth (0–19 years) according to country income. Methods: Five databases were searched. Fifty-seven articles met the inclusion criteria. Results: Fifty-five cluster types were identified, with greater variety in high-income than lower income countries. The most prevalent profiles were “High SB and consumption of sugar, salt, and beverages (SSB)” (n = 17) and “High PA” (n = 13–5), both of which presented in all income countries. The healthiest profile, “High PA and fruit and vegetables (F&V); Low SB and SSB” (n = 12), was present in upper-middle and high-income countries, while the unhealthiest “Low PA and F&V; High SB and SSB” (n = 6) was present only in high-income countries. Conclusions: High SB and unhealthy diet (SSB) were more prevalent in clusters, mainly in high-income countries. The results support the need for multi-component actions targeting more than one behavior at the same time.

Obesogenic Clusters Associated with Weight Status in Brazilian Adolescents of the Movimente School-Base Intervention

Background: the relationship between behavior clusters and weight status, mainly in low- and middle-income countries, remains unclear. This study aimed to examine the association between profiles of physical activity (PA), diet and sedentary behavior (SB) with weight status in adolescents from a southern Brazilian city, according to sex. Methods: data from the Movimente Intervention study were analyzed (n = 812 / mean age 13.0 years (sd 1.04). Data on SB hours per day, PA minutes per week and weekly consumption frequencies of fruits, vegetables, salty snacks, candies and soda were self-reported on the validated Movimente questionnaire. Classes of healthy and unhealthy behaviors were derived by latent class analysis. Logistic regression analysis was used to estimate the associations between adolescents’ weight status and classes. Results: two classes were identified for the whole sample and for boys and girls. All classes had high probabilities of engaging high time in SB. Male adolescents in the unhealthy class had low probabilities of being active and high probability of consuming a low-quality diet. In contrast, girls’ healthiest profile presented lower probabilities of being active compared to boys’ healthiest profiles. No association was found between weight status and classes. Conclusion: All classes had at least one unhealthy behavior, for both the whole sample, and for girls and boys. Girls’ profiles were unhealthier compared to boys’ profiles. Hence, it is recommended that intervention strategies to change behaviors need to be distinct according to sex, targeting more than one obesogenic behavior at the same time.

Clustering of health-related behaviours within children aged 11-16: a systematic review

OBJECTIVE

We aimed to systematically review and synthesise evidence on the clustering of a broad range of health-related behaviours amongst 11-16 year olds.

METHOD

A literature search was conducted in September 2019. Studies were included if they used cluster analysis, latent class analysis, prevalence odds ratios, principal component analysis or factor analysis, and considered at least three health-related behaviours of interest among 11-16 year olds in high-income countries. Health-related behaviours of interest were substance use (alcohol, cigarettes and other drug use) and other behavioural risk indicators (diet, physical activity, gambling and sexual activity).

RESULTS

The review identified 41 studies, which reported 198 clusters of health-related behaviours of interest. The behaviours of interest reported within clusters were used to define eight behavioural archetypes. Some included studies only explored substance use, while others considered substance use and/or other health-related behaviours. Consequently, three archetypes were comprised by clusters reporting substance use behaviours alone. The archetypes were: (1) Poly-Substance Users, (2) Single Substance Users, (3) Substance Abstainers, (4) Substance Users with No/Low Behavioural Risk Indicators, (5) Substance Abstainers with Behavioural Risk Indicators, (6) Complex Configurations, (7) Overall Unhealthy and (8) Overall Healthy.

CONCLUSION

Studies of youth health behavioural clustering typically find both a 'healthy' cluster and an 'unhealthy' cluster. Unhealthy clusters are often characterised by poly-substance use. Our approach to synthesising cluster analyses may offer a means of navigating the heterogeneity of method, measures and behaviours of interest in this literature.

Association between Clustering of Lifestyle Behaviors and Health-Related Physical Fitness in Youth: The UP&DOWN Study

OBJECTIVES

To examine clustering of lifestyle behaviors in Spanish children and adolescents based on screen time, nonscreen sedentary time, moderate-to-vigorous physical activity, Mediterranean diet quality, and sleep time, and to analyze its association with health-related physical fitness.

STUDY DESIGN

The sample consisted of 1197 children and adolescents (597 boys), aged 8-18 years, included in the baseline cohort of the UP&DOWN study. Moderate-to-vigorous physical activity was assessed by accelerometry. Screen time, nonscreen sedentary time, Mediterranean diet quality, and sleep time were self-reported by participants. Health-related physical fitness was measured following the Assessing Levels of Physical Activity battery for youth. A 2-stage cluster analysis was performed based on the 5 lifestyle behaviors. Associations of clusters with fatness and physical fitness were analyzed by 1-way ANCOVA.

RESULTS

Five lifestyle clusters were identified: (1) active (n = 171), (2) sedentary nonscreen sedentary time-high diet quality (n = 250), (3) inactive-high sleep time (n = 249 [20.8%]), (4) sedentary nonscreen sedentary time-low diet quality (n = 273), and (5) sedentary screen time-low sleep time (n = 254). Cluster 1 was the healthiest profile in relation to health-related physical fitness in both boys and girls. In boys, cluster 3 had the worst fatness and fitness levels, whereas in girls the worst scores were found in clusters 4 and 5.

CONCLUSIONS

Clustering of different lifestyle behaviors was identified and differences in health-related physical fitness were found among clusters, which suggests that special attention should be given to sedentary behaviors in girls and physical activity in boys when developing childhood health prevention strategies focusing on lifestyles patterns.

Clustering of unhealthy lifestyle behaviours and associations with perceived and actual weight status among primary school children in China: A nationally representative cross-sectional study

Few studies have focused on clustering of unhealthy lifestyle behaviours among primary school children and potential associations with perceived and actual weight status. An index was constructed from adding up 13 unhealthy behaviours measured by survey responses. Multilevel linear regressions were used to analyse associations between child personal characteristics, perceived and actual weight status with the unhealthy lifestyle index among 11,157 children in primary schools across China. Parental and area factors were also taken into account, including education, weight status, physical activity, urban/rural and area socioeconomic circumstances. The unhealthy lifestyle index normally distributed, with 84.5% of children reporting between 2 and 6 unhealthy behaviours. Boys reported more unhealthy behaviours compared with girls (coefficient 0.32, 95%CI 0.26 to 0.37) and children in urban areas had fewer unhealthy behaviours than their rural counterparts (-0.29, 95%CI -0.56 to -0.03). An interaction revealed stronger 'protective' effects of living in cities for girls than boys, which were not explained by differences in child overweight/obesity. More unhealthy behaviours were characteristic of children in more affluent areas, and of those born to mothers and/or fathers with lower educational attainment. Children who perceived themselves as overweight or underweight both scored higher on the unhealthy lifestyle index. Unhealthy behaviours that could increase the risk of childhood obesity are common among Chinese primary school children, particularly among boys in cities, those in more affluent areas and with parents with lower education. There was no effect of actual weight status on number of unhealthy behaviours. Perceived, but not actual weight status, was also a significant correlate of unhealthy behaviours. Clustering of unhealthy lifestyle behaviours that could increase the risk of childhood obesity are common among Chinese primary school children, particularly among boys in cities, those in more affluent areas and with parents with lower education. Perceived, but not actual weight status, was also a significant correlate of unhealthy lifestyle. This has important implications for public health because understanding clustering of unhealthy lifestyle behaviours can be used to assist in the development of targeted obesity prevention initiatives.

Clustering of multiple energy balance related behaviors is associated with body fat composition indicators in adolescents: Results from the HELENA and ELANA studies

The objective of this study was to identify clustering patterns of four energy balance-related behaviors (EBRB): television (TV) watching, moderate and vigorous physical activity (MVPA), consumption of fruits and vegetables (F&V), and consumption of sugar-sweetened beverages (SSB), among European and Brazilian adolescents. EBRB associations with different body fat composition indicators were then evaluated. Participants included adolescents from eight European countries in the HELENA (Healthy Lifestyle in Europe by Nutrition in Adolescents) study (n = 2,057, 53.8% female; age: 12.5-17.5 years) and from the metropolitan region of Rio de Janeiro/Brazil in the ELANA study (the Adolescent Nutritional Assessment Longitudinal Study) (n = 968, 53.2% female; age: 13.5-19 years). EBRB data allowed for sex- and study-specific clusters. Associations were estimated by ANOVA and odds ratios. Five clustering patterns were identified. Four similar clusters were identified for each sex and study. Among boys, different cluster identified was characterized by high F&V consumption in the HELENA study and high TV watching and high MVPA time in the ELANA study. Among girls, the different clusters identified was characterized by high F&V consumption in both studies and, additionally, high SSB consumption in the ELANA study. Regression analysis showed that clusters characterized by high SSB consumption in European boys; high TV watching, and high TV watching plus high MVPA in Brazilian boys; and high MVPA, and high SSB and F&V consumption in Brazilian girls, were positively associated with different body fat composition indicators. Common clusters were observed in adolescents from Europe and Brazil, however, no cluster was identified as being completely healthy or unhealthy. Each cluster seems to impact on body composition indicators, depending on the group. Public health actions should aim to promote adequate practices of EBRB.

The clustering of diet, physical activity and sedentary behavior in children and adolescents: a review

Diet, physical activity (PA) and sedentary behavior are important, yet modifiable, determinants of obesity. Recent research into the clustering of these behaviors suggests that children and adolescents have multiple obesogenic risk factors. This paper reviews studies using empirical, data-driven methodologies, such as cluster analysis (CA) and latent class analysis (LCA), to identify clustering patterns of diet, PA and sedentary behavior among children or adolescents and their associations with socio-demographic indicators, and overweight and obesity. A literature search of electronic databases was undertaken to identify studies which have used data-driven methodologies to investigate the clustering of diet, PA and sedentary behavior among children and adolescents aged 5–18 years old. Eighteen studies (62% of potential studies) were identified that met the inclusion criteria, of which eight examined the clustering of PA and sedentary behavior and eight examined diet, PA and sedentary behavior. Studies were mostly cross-sectional and conducted in older children and adolescents (≥9 years). Findings from the review suggest that obesogenic cluster patterns are complex with a mixed PA/sedentary behavior cluster observed most frequently, but healthy and unhealthy patterning of all three behaviors was also reported. Cluster membership was found to differ according to age, gender and socio-economic status (SES). The tendency for older children/adolescents, particularly females, to comprise clusters defined by low PA was the most robust finding. Findings to support an association between obesogenic cluster patterns and overweight and obesity were inconclusive, with longitudinal research in this area limited. Diet, PA and sedentary behavior cluster together in complex ways that are not well understood. Further research, particularly in younger children, is needed to understand how cluster membership differs according to socio-demographic profile. Longitudinal research is also essential to establish how different cluster patterns track over time and their influence on the development of overweight and obesity.

Clustering of children's obesity-related behaviours: associations with sociodemographic indicators

BACKGROUND/OBJECTIVES

Research suggests obesity-related behaviours cluster together in children and adolescents, but how these cluster patterns differ by sociodemographic indicators remains unclear. Furthermore, few studies examining clustering of behaviours have included younger children or an objective measure of physical activity (PA) and sedentary behaviour. Therefore, the aim of this study was to examine clustering patterns of diet, PA and sedentary behaviour in 5- to 6- and 10- to 12-year-old children, and their cross-sectional associations with sociodemographic indicators.

SUBJECTS/METHODS

In this cross-sectional study, data from the baseline wave (2002/2003) of the Health Eating and Play study (HEAPS) were used. Questionnaires were completed by parents of Australian children aged 5-6 (n=362) and 10-12 years (n=610). Children wore accelerometers for up to 7 days. K-medians cluster analysis identified groups of children with similar diet, PA and sedentary behaviours. Chi-square tests assessed cluster differences by gender, maternal education and marital status.

RESULTS

For each age group, three reliable and meaningful clusters were identified and labelled 'most healthy', 'energy-dense (ED) consumers who watch TV' and 'high sedentary behaviour/low moderate-to-vigorous PA (MVPA)'. Clusters varied by sociodemographic indicators. For example, a higher proportion of older girls comprised the 'high sedentary behaviour/low MVPA' cluster (χ(2)=22.4, P<0.001). Among both age groups, the 'ED consumers who watch TV' cluster comprised more children with lower educated mothers (younger children: χ(2)=34.9, P<0.001; older children: χ(2)=27.3, P<0.001).

CONCLUSIONS

Identification of cluster patterns of obesity-related risk factors in children, and across sociodemographic groups may assist the targeting of public health initiatives, to those most in need.