Activity-related behavior typologies in youth: a systematic review

Parker, Kate; Salmon, Jo; Costigan, Sarah A.; Villanueva, Karen; Brown, Helen; Timperio, Anna

doi:10.1186/s12966-019-0804-7

Cited by 39 publications

(69 citation statements)

References 69 publications

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“…Few studies have aimed to identify clusters of young children (< 6 years) based on their patterns of diet, PA, sedentary behavior and sleep [14,[20][21][22]; none of them concurrently examined behaviors from all four domains and they captured only limited contextual information. Three literature reviews have analyzed the results of studies using cluster analysis to identify lifestyle patterns, in particular diet and/or activity-related behaviors, in school-aged children and adolescents [6,8,13]. Despite differences in population sample characteristics, the range and contexts of behaviors considered, and the behavior measurement tools and clustering methods used, some results have been consistent and remain so in our study.…”

Section: Discussionmentioning

confidence: 55%

“…These potentially modifiable obesogenic factors tend to co-occur in some individuals and may interact in multiple ways that modify the risk of OW-OB, with potentially synergistic effects [4,5]. Evermore studies have examined patterns of diet, PA and sedentary behaviors in children and adolescents with exploratory data-driven methods [6][7][8]. These include cluster analysis, based on either geometric (e.g., k-means) or probabilistic (e.g., mixture models) methods, they are aimed at grouping observations into homogeneous clusters [9].…”

Section: Introductionmentioning

confidence: 99%

“…Reviews of studies using cluster analysis to uncover patterns of diet and/or activity-related behaviors in children and adolescents report that these behaviors cluster in complex ways [6,8,13]. Mixed clusters characterized by a mixture of both healthy and unhealthy behaviors being frequently reported (e.g., children who engage in high levels of sports activities but also spend a lot of time on television-based sedentary activities).…”

Section: Introductionmentioning

confidence: 99%

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Clusters of diet, physical activity, television exposure and sleep habits and their association with adiposity in preschool children: the EDEN mother-child cohort

Saldanha-Gomes

Marbac

Sedki

et al. 2020

Int J Behav Nutr Phys Act

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Background: Despite the growing interest in the relation between adiposity in children and different lifestyle clusters, few studies used a longitudinal design to examine a large range of behaviors in various contexts, in particular eating-and sleep-related routines, and few studies have examined these factors in young children. The objectives of this study were to identify clusters of boys and girls based on diet, sleep and activity-related behaviors and their family environment at 2 and 5 years of age, and to assess whether the clusters identified varied across maternal education levels and were associated with body fat at age 5. Methods: At 2 and 5 years, respectively, 1436 and 1195 parents from the EDEN mother-child cohort completed a questionnaire including behavioral data. A latent class analysis aimed to uncover gender-specific behavioral clusters. Body fat percentage was estimated by anthropometric and bioelectrical impedance measurements. Association between cluster membership and body fat was assessed with mutivariable linear regression models. Results: At 2 years, two clusters emerged that were essentially characterized by opposite eating habits. At 5 years, TV exposure was the most distinguishing feature, but the numbers and types of clusters differed by gender. An association between cluster membership and body fat was found only in girls at 5 years of age, with girls in the cluster defined by very high TV exposure and unfavorable mealtime habits (despite high outdoor playing and walking time) having the highest body fat. Girls whose mother had low educational attainment were more likely to be in this high-risk cluster. Girls who were on a cluster evolution path corresponding to the highest TV viewing time and the least favorable mealtime habits from 2 to 5 years of age had higher body fat at 5 years. Conclusions: Efforts to decrease TV time and improve mealtime routines may hold promise for preventing overweight in young children, especially girls growing up in disadvantaged families. These preventive efforts should start as early in life as possible, ideally before the age of two, and should be sustained over the preschool years.

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Section: Discussionmentioning

confidence: 55%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Clusters of diet, physical activity, television exposure and sleep habits and their association with adiposity in preschool children: the EDEN mother-child cohort

Saldanha-Gomes

Marbac

Sedki

et al. 2020

Int J Behav Nutr Phys Act

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“…The mechanisms underlying HRB clustering are poorly understood [2]. Although there has been growing interest in HRB clustering from other parts of the world such as Europe and North America [6][7][8][9], there is a dearth of research on this topic among adolescents from sub-Saharan Africa (SSA), which has the largest proportion of young people [10]. Besides, existing research suggests that a multiplerisk-behavior approach is often not reflected in the formulation of policies and interventions to reduce adolescent HRB [7].…”

Section: Introductionmentioning

confidence: 99%

Clustering of health risk behaviors among adolescents in Kilifi, Kenya, a rural Sub-Saharan African setting

et al. 2020

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Background Adolescents tend to experience heightened vulnerability to risky and reckless behavior. Adolescents living in rural settings may often experience poverty and a host of risk factors which can increase their vulnerability to various forms of health risk behavior (HRB). Understanding HRB clustering and its underlying factors among adolescents is important for intervention planning and health promotion. This study examines the co-occurrence of injury and violence, substance use, hygiene, physical activity, and diet-related risk behaviors among adolescents in a rural setting on the Kenyan coast. Specifically, the study objectives were to identify clusters of HRB; based on five categories of health risk behavior, and to identify the factors associated with HRB clustering. Methods A cross-sectional survey was conducted of a random sample of 1060 adolescents aged 13–19 years living within the area covered by the Kilifi Health and Demographic Surveillance System. Participants completed a questionnaire on health behaviors which was administered via an Audio Computer-Assisted Self–Interview. Latent class analysis on 13 behavioral factors (injury and violence, hygiene, alcohol tobacco and drug use, physical activity, and dietary related behavior) was used to identify clustering and stepwise ordinal logistic regression with nonparametric bootstrapping identified the factors associated with clustering. The variables of age, sex, education level, school attendance, mental health, form of residence and level of parental monitoring were included in the initial stepwise regression model. Results We identified 3 behavioral clusters (Cluster 1: Low-risk takers (22.9%); Cluster 2: Moderate risk-takers (67.8%); Cluster 3: High risk-takers (9.3%)). Relative to the cluster 1, membership of higher risk clusters (i.e. moderate or high risk-takers) was strongly associated with older age (p<0.001), being male (p<0.001), depressive symptoms (p = 0.005), school non-attendance (p = 0.001) and a low level of parental monitoring (p<0.001). Conclusion There is clustering of health risk behaviors that underlies communicable and non-communicable diseases among adolescents in rural coastal Kenya. This suggests the urgent need for targeted multi-component health behavior interventions that simultaneously address all aspects of adolescent health and well-being, including the mental health needs of adolescents.

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“…The analysis of 24-hour movement behaviors has recently shown that physical activity, sedentary behaviors, and sleep are associated with a number of health outcomes within the pediatric population [1][2][3][4]. The 24-hour movement behavior recommendations are relevant to the pediatric population regardless of sex, race/ethnicity, or socioeconomic status [1,2].…”

Section: Introductionmentioning

confidence: 99%

Movement Behaviors and Perceived Loneliness and Sadness within Alaskan Adolescents

Burns

Bai

Pfledderer

et al. 2020

IJERPH

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Physical activity, screen use, and sleep are behaviors that integrate across the whole day. However, the accumulative influence of meeting recommendations for these 24-h movement behaviors on the mental health of Alaskan adolescents has not been examined. The purpose of this study was to examine the associations between movement behaviors, loneliness, and sadness within Alaskan adolescents. Data were obtained from the 2019 Alaska Youth Risk Behavior Survey (YRBS). The number of adolescents participating in the 2019 Alaska YRBS was 1897. Associations between meeting recommendations for movement behaviors with loneliness and sadness were examined using weighted logistic regression models, adjusted for age, sex, race/ethnicity, and body mass index (BMI). Approximately 5.0% of the sample met recommendations for all three movement behaviors. Meeting 2 or 3 movement behavior recommendations was associated with lower odds of loneliness (odds ratio (OR) range = 0.23 to 0.44, p < 0.01). Additionally, meeting 1 to 3 movement behavior recommendations was associated with lower odds of sadness (OR range = 0.29 to 0.52, p < 0.05). Joint association analyses determined that these relationships were primarily driven by meeting the sleep recommendation for loneliness and meeting the screen use recommendation for sadness. The results support use of multiple movement-based behavior programming to attenuate feelings of loneliness and sadness within Alaskan adolescents.

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Activity-related behavior typologies in youth: a systematic review

Cited by 39 publications

References 69 publications

Clusters of diet, physical activity, television exposure and sleep habits and their association with adiposity in preschool children: the EDEN mother-child cohort

Clusters of diet, physical activity, television exposure and sleep habits and their association with adiposity in preschool children: the EDEN mother-child cohort

Clustering of health risk behaviors among adolescents in Kilifi, Kenya, a rural Sub-Saharan African setting

Movement Behaviors and Perceived Loneliness and Sadness within Alaskan Adolescents

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