Lifestyle Clusters in School-Aged Youth and Longitudinal Associations with Fatness: The UP&amp;DOWN Study

Sánchez‐Oliva, David; Grao‐Cruces, Alberto; Carbonell‐Baeza, Ana; Cabanas‐Sánchez, Verónica; Veiga, Óscar L.; Castro‐Piñero, José

doi:10.1016/j.jpeds.2018.07.092

Cited by 28 publications

(31 citation statements)

References 21 publications

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“…Overall, none of the identified clusters or subgroups of students were exclusively comprised of healthy or unhealthy behaviors, except for the Ideal Health profile. In line with our results, two of the four retained profiles identified by Dumuid et al [19][20][21] in children and Sánchez-Oliva et al [11] in older children, younger adolescents, and older adolescents, were also characterized by healthy and unhealthy behaviors. This clustering of behaviors revealed that healthy or unhealthy behaviors do not necessary ensure that other behaviors go in the same direction [58,61].…”

Section: Discussionsupporting

confidence: 92%

“…On the contrary, the most maladaptive profile was the Inactive Unhealthy Eaters profile, showing no association with meeting 24-hour movement guidelines. The great amount of time spent on different types of screen time in this profile could displace the required number of hours of sleep and PA [11,62]. This holistic approach is grounded in the idea that the whole day matters and should be considered to develop strategies that can lead to establishing an organized schedule that allows adolescents to reduce the time spent on sedentary screen time and increase the time spent on the other movement behaviors (i.e., PA and sleep duration).…”

Section: Discussionmentioning

confidence: 99%

“…Clustering PA, ST, and diet in children and adolescents is well-documented in research literature [9]. For example, the clustering pattern of PA, ST, diet quality, and sedentary screen time among older children, younger adolescents, and older adolescents has been recently identified [11]. Four different profiles were identified in the three mentioned groups: (a) a healthy lifestyle cluster (high MVPA, healthy diet, low sedentary screen time and low total ST), (b) a sedentary and healthy diet cluster, (c) a sedentary screen time cluster, and (d) a low MVPA and unhealthy diet cluster.…”

mentioning

confidence: 94%

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Healthy or Unhealthy? The Cocktail of Health-Related Behavior Profiles in Spanish Adolescents

Sevil‐Serrano

Solana

Abós

et al. 2019

IJERPH

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The aim of this study was to identify the prevalence and clustering of health-related behaviors in Spanish adolescents and to examine their association with sex, body mass index (BMI), different types of sedentary screen time, and adherence to 24-hour movement guidelines. A final sample of 173 students (M = 12.99 ± 0.51) participated in this study. Cluster analysis was conducted based on five health-related behaviors: PA and sedentary time derived from accelerometers, as well as healthy diet, sedentary screen time, and sleep duration derived from self-reported scales. Recommendations for 24-hour movement guidelines (i.e., physical activity (PA), screen time, and sleep duration) were analyzed both independently and combined. A total of 8.9% of the sample did not meet any of the guidelines, whereas 72.3%, 17.3%, and 1.7% of the sample met 1, 2, or all 3 guidelines, respectively. Six distinct profiles were identified, most of them showing the co-occurrence of healthy- and unhealthy-related behaviors. Given that most of the adolescents failed to meet the combination of PA, screen time, and sleep duration guidelines, these findings suggest the necessity to implement school-based interventions that target multiple health behaviors, especially because (un)healthy behaviors do not always cluster in the same direction.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 94%

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Healthy or Unhealthy? The Cocktail of Health-Related Behavior Profiles in Spanish Adolescents

Sevil‐Serrano

Solana

Abós

et al. 2019

IJERPH

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“…This observation is confirmed by the PAQ‐C questionnaire, a validated score of PA level that was negatively correlated with all indices of adiposity (BMI‐z‐score, WC, WtHR, and fat mass) in accordance with previous studies . In contrast, sedentary behavior (more than 2 hours/day ST) mainly affected central adiposity but not BMI‐z‐score or body fat mass, as reported in several published studies . This phenomenon may be due to the fact that the mere evaluation of BMI and body fat mass does not provide information about body fat distribution, resulting in an underestimation of visceral adiposity among children .…”

Section: Discussionsupporting

confidence: 87%

“…Not all studies found a positive association, and no study has considered Italian schoolchildren of a wide age range …”

Section: Introductionmentioning

confidence: 99%

Impact of unhealthy childhood and unfavorable parents' characteristics on adiposity in schoolchildren

Vinciguerra

Tumminia

Roppolo

et al. 2019

Diabetes Metabolism Res

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Background: Childhood obesity is encouraged by low physical activity (PA), time spent using screens (screen time, ST), and by sugar-sweetened beverage consumption (SSBc). It is also influenced by unfavorable parents' characteristics, such as a high body mass index (BMI) and low education level (EL). Our aim was to evaluate the overall and specific influence of these factors on childhood adiposity. Material and methods:Anthropometric parameters including BMI z-score, waist circumference (WC), waist to height ratio (WtHR), and fat mass were measured in a cohort of 1702 schoolchildren (6.0-14.5 years, mean 10.7 ± 1.8) and questionnaires concerning children's PA, ST, and SSBc, and parent's BMI and EL were administered to parents. Results:Overweight/obesity prevalence was higher (P < .0001) in males (57%) than in females (43%). Less physically active children (28.9%) had a higher prevalence of overweight/obesity and higher BMI z-score, WC, WtHR, and fat mass relative to more physically active children (P < .05). PA was negatively associated with the BMI z-score (r = 0.18, P < .0001) and fat mass percentage (r = 0.18, P < .0001).Children with more ST had higher WC and WtHR than non-ST viewers (P < .05) but not BMI. Moreover, SSBc did not influence the anthropometric parameters. At multivariate analysis, male gender, less PA, and parental risk factors (parent's overweight/obesity and low/medium EL) were independently associated with overweight and obesity among childhood with a progressively increasing odds ratio (1.65, 1.40, and 1.80, respectively). Conclusions:Male gender, behavioral risk factors (particularly low PA), and parent's characteristics are important correlates of obesity in children.

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Association Between Longitudinal Trajectories of Lifestyle Pattern and BMI in Early Childhood

Zheng

Lioret

Hesketh

et al. 2021

Obesity

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ObjectiveThis study examined the association between longitudinal trajectories of lifestyle patterns (LPs) and BMI z score in early childhood.MethodsData of children (n = 439) who participated in the 18‐, 42‐, and 60‐month follow‐ups of the Melbourne InFANT Program were used. Multitrajectory modeling identified groups of children following similar LPs and BMI z score trajectories, and multinomial logistic regression assessed the determinants of the trajectory groups.ResultsThree trajectory groups of child LPs and BMI z scores were identified: “Unhealthy LP, Low BMIz” (30%), “Healthy LP, Mid BMIz” (53%), and “Unhealthy LP, High BMIz” (17%). Relative to the “Unhealthy LP, Low BMIz” group, the maternal “Fruit and vegetables” dietary pattern was associated with higher odds (odds ratio [OR] 1.22, 95% CI: 1.01‐1.47) of children following the “Healthy LP, Mid BMIz” group. Maternal prepregnancy BMI (≥25 kg/m2) (OR 2.50, 95% CI: 1.31‐4.75) and maternal TV‐viewing time ≥130 min/d (OR 2.55, 95% CI: 1.13, 5.72) increased the odds of children following the “Unhealthy LP, High BMIz” group. Child sex, breastfeeding duration, and maternal physical activity were not associated with the identified trajectory groups.ConclusionsThree trajectory groups of LPs and BMI z scores in early childhood were revealed, with maternal prepregnancy BMI, dietary pattern, and TV‐viewing time being identified as significant determinants.

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Lifestyle Clusters in School-Aged Youth and Longitudinal Associations with Fatness: The UP&DOWN Study

Cited by 28 publications

References 21 publications

Healthy or Unhealthy? The Cocktail of Health-Related Behavior Profiles in Spanish Adolescents

Healthy or Unhealthy? The Cocktail of Health-Related Behavior Profiles in Spanish Adolescents

Impact of unhealthy childhood and unfavorable parents' characteristics on adiposity in schoolchildren

Association Between Longitudinal Trajectories of Lifestyle Pattern and BMI in Early Childhood

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