scholarly journals Do differences in compositional time use explain ethnic variation in the prevalence of obesity in children? Analyses using 24-hour accelerometry

2020 ◽  
Author(s):  
RW Taylor ◽  
JJ Haszard ◽  
VL Farmer ◽  
R Richards ◽  
Lisa Te Morenga ◽  
...  
Keyword(s):  
Physical Activity ◽  
Ethnic Differences ◽  
Time Use ◽  
Vigorous Physical Activity ◽  
Obesity Prevalence ◽  
Z Score ◽  
Movement Data ◽  
Increased Risk ◽  
Prevalence Of Obesity ◽  
Log Ratio

© 2019, Springer Nature Limited. Background/Objectives: Whether variation in sleep and physical activity explain marked ethnic and socioeconomic disparities in childhood obesity is unclear. As time spent in one behaviour influences time spent in other behaviours across the 24-hour day, compositional analyses are essential. The aims of this study were to determine how ethnicity and socioeconomic status influence compositional time use in children, and whether differences in compositional time use explain variation in body mass index (BMI) z-score and obesity prevalence across ethnic groups. Methods: In all, 690 children (58% European, 20% Māori, 13% Pacific, 9% Asian; 66% low-medium deprivation and 34% high deprivation) aged 6–10 years wore an ActiGraph accelerometer 24-hours a day for 5 days yielding data on sedentary time, sleep, light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA). Height and weight were measured using standard techniques and BMI z-scores calculated. Twenty-four hour movement data were transformed into isometric log-ratio co-ordinates for multivariable regression analysis and effect sizes were back-transformed. Results: European children spent more time asleep (predicted difference in minutes, 95% CI: 16.1, 7.4–24.9) and in MVPA (6.6 min, 2.4–10.4), and less time sedentary (−10.2 min, −19.8 to −0.6) and in LPA (−12.2 min, −21.0 to −3.5) than non-European children. Overall, 10% more sleep was associated with a larger difference in BMI z-score (adjusted difference, 95% CI: −0.13, −0.25 to −0.01) than 10% more MVPA (−0.06, −0.09 to −0.03). Compositional time use explained 35% of the increased risk of obesity in Pacific compared with European children after adjustment for age, sex, deprivation and diet, but only 9% in Māori and 24% in Asian children. Conclusions: Ethnic differences in compositional time use explain a relatively small proportion of the ethnic differences in obesity prevalence that exist in children.

scholarly journals Do differences in compositional time use explain ethnic variation in the prevalence of obesity in children? Analyses using 24-hour accelerometry

2020 ◽  
Author(s):  
RW Taylor ◽  
JJ Haszard ◽  
VL Farmer ◽  
R Richards ◽  
Lisa Te Morenga ◽  
...  
Keyword(s):  
Physical Activity ◽  
Ethnic Differences ◽  
Time Use ◽  
Vigorous Physical Activity ◽  
Obesity Prevalence ◽  
Z Score ◽  
Movement Data ◽  
Increased Risk ◽  
Prevalence Of Obesity ◽  
Log Ratio

© 2019, Springer Nature Limited. Background/Objectives: Whether variation in sleep and physical activity explain marked ethnic and socioeconomic disparities in childhood obesity is unclear. As time spent in one behaviour influences time spent in other behaviours across the 24-hour day, compositional analyses are essential. The aims of this study were to determine how ethnicity and socioeconomic status influence compositional time use in children, and whether differences in compositional time use explain variation in body mass index (BMI) z-score and obesity prevalence across ethnic groups. Methods: In all, 690 children (58% European, 20% Māori, 13% Pacific, 9% Asian; 66% low-medium deprivation and 34% high deprivation) aged 6–10 years wore an ActiGraph accelerometer 24-hours a day for 5 days yielding data on sedentary time, sleep, light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA). Height and weight were measured using standard techniques and BMI z-scores calculated. Twenty-four hour movement data were transformed into isometric log-ratio co-ordinates for multivariable regression analysis and effect sizes were back-transformed. Results: European children spent more time asleep (predicted difference in minutes, 95% CI: 16.1, 7.4–24.9) and in MVPA (6.6 min, 2.4–10.4), and less time sedentary (−10.2 min, −19.8 to −0.6) and in LPA (−12.2 min, −21.0 to −3.5) than non-European children. Overall, 10% more sleep was associated with a larger difference in BMI z-score (adjusted difference, 95% CI: −0.13, −0.25 to −0.01) than 10% more MVPA (−0.06, −0.09 to −0.03). Compositional time use explained 35% of the increased risk of obesity in Pacific compared with European children after adjustment for age, sex, deprivation and diet, but only 9% in Māori and 24% in Asian children. Conclusions: Ethnic differences in compositional time use explain a relatively small proportion of the ethnic differences in obesity prevalence that exist in children.

Association between Metabolic Syndrome Diagnosis and the Physical Activity—Sedentary Profile of Adolescents with Obesity: A Complementary Analysis of the Beta-JUDO Study

Nutrients ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 60
Author(s):  
Valérie Julian ◽  
Iris Ciba ◽  
Roger Olsson ◽  
Marie Dahlbom ◽  
Dieter Furthner ◽  
...  
Keyword(s):  
Physical Activity ◽  
Metabolic Syndrome ◽  
Cardiometabolic Risk ◽  
Vigorous Physical Activity ◽  
Density Lipoprotein ◽  
Z Score ◽  
Increased Risk ◽  
Syndrome Diagnosis ◽  
Objectively Measured ◽  
Complementary Analysis

Metabolic syndrome (MetS) is highly prevalent in children and adolescents with obesity and places them at an increased risk of cardiovascular-related diseases. However, the associations between objectively measured movement-related behaviors and MetS diagnosis remain unexplored in youths with obesity. The aim was to compare profiles of sedentary (SED) time (more sedentary, SED+ vs. less sedentary, SED−), moderate to vigorous physical activity (MVPA) time (more active, MVPA+ vs. less active, MVPA−) and combinations of behaviors (SED−/MVPA+, SED−/MVPA−, SED+/MVPA+, SED+/MVPA−) regarding the MetS diagnosis. One hundred and thirty-four adolescents with obesity (13.4 ± 2.2 years) underwent 24 h/7 day accelerometry, waist circumference (WC), blood pressure (BP), high-density lipoprotein-cholesterol (HDL-c), triglycerides (TG) and insulin-resistance (IR) assessments. Cumulative cardiometabolic risk was assessed by using (i) MetS status (usual dichotomic definition) and (ii) cardiometabolic risk z-score (MetScore, mean of standardized WC, BP, IR, TG and inverted HDL-c). SED− vs. SED+ and MVPA+ vs. MVPA− had lower MetS (p < 0.01 and p < 0.001) and MetScore (p < 0.001). SED−/MVPA+ had the lowest risk. While SED and MVPA times were lower in SED−/MVPA− vs. SED+/MVPA+ (p < 0.001), MetScore was lower in SED−/MVPA− independently of body mass index (BMI) (p < 0.05). MVPA, but not SED, time was independently associated with MetS diagnosis (p < 0.05). Both MVPA (p < 0.01) and SED times (p < 0.05) were associated with MetScore independently of each other. A higher MVPA and lower SED time are associated with lower cumulative cardiometabolic risk.

scholarly journals Balancing time use for children’s fitness and adiposity: Evidence to inform 24-hour guidelines for sleep, sedentary time and physical activity

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245501
Author(s):  
Dorothea Dumuid ◽  
Melissa Wake ◽  
David Burgner ◽  
Mark S. Tremblay ◽  
Anthony D. Okely ◽  
...  
Keyword(s):  
Physical Activity ◽  
Time Use ◽  
Daily Activity ◽  
Sedentary Time ◽  
Vigorous Physical Activity ◽  
Population Based ◽  
Optimal Time ◽  
Cross Sectional ◽  
Trade Offs ◽  
Log Ratio

Purpose Daily time spent on one activity cannot change without compensatory changes in others, which themselves may impact on health outcomes. Optimal daily activity combinations may differ across outcomes. We estimated optimal daily activity durations for the highest fitness and lowest adiposity. Methods Cross-sectional Child Health CheckPoint data (1182 11-12-year-olds; 51% boys) from the population-based Longitudinal Study of Australian Children were used. Daily activity composition (sleep, sedentary time, light physical activity [LPA], moderate-to-vigorous physical activity [MVPA]) was from 8-day, 24-hour accelerometry. We created composite outcomes for fitness (VO2max; standing long jump) and adiposity (waist-to-height ratio; body mass index; fat-to-fat-free log-ratio). Adjusted compositional models regressed activity log-ratios against each outcome. Best activity compositions (optimal time-use zones) were plotted in quaternary tetrahedrons; the overall optimal time-use composition was the center of the overlapping area. Results Time-use composition was associated with fitness and adiposity (all measures p<0.001). Optimal time use differed for fitness and adiposity. While both maximized MVPA and minimized sedentary time, optimal fitness days had higher LPA (3.4 h) and shorter sleep (8.25 h), but optimal adiposity days had lower LPA (1.0 h) and longer sleep (10.9 h). Balancing both outcomes, the overall optimal time-use composition was (mean [range]): 10.2 [9.5; 10.5] h sleep, 9.9 [8.8; 11.2] h sedentary time, 2.4 [1.8; 3.2] h LPA and 1.5 [1.5; 1.5] h MVPA. Conclusion Optimal time use for children’s fitness and adiposity involves trade-offs. To best balance both outcomes, estimated activity durations for sleep and LPA align with, but for MVPA exceed, 24-h guidelines.

Physical activity volume in relation to risk of atrial fibrillation. A non-linear meta-regression analysis

2018 ◽  
Vol 25 (8) ◽  
pp. 857-866 ◽  
Author(s):  
Cristian Ricci ◽  
Federico Gervasi ◽  
Maddalena Gaeta ◽  
Cornelius M Smuts ◽  
Aletta E Schutte ◽  
...  
Keyword(s):  
Physical Activity ◽  
Atrial Fibrillation ◽  
Relative Risk ◽  
Vigorous Physical Activity ◽  
Response Analysis ◽  
Metabolic Equivalents ◽  
Increased Risk ◽  
Non Linear ◽  
Meta Regression ◽  
Physical Activity Volume

Background Light physical activity is known to reduce atrial fibrillation risk, whereas moderate to vigorous physical activity may result in an increased risk. However, the question of what volume of physical activity can be considered beneficial remains poorly understood. The scope of the present work was to examine the relation between physical activity volume and atrial fibrillation risk. Design A comprehensive systematic review was performed following the PRISMA guidelines. Methods A non-linear meta-regression considering the amount of energy spent in physical activity was carried out. The first derivative of the non-linear relation between physical activity and atrial fibrillation risk was evaluated to determine the volume of physical activity that carried the minimum atrial fibrillation risk. Results The dose–response analysis of the relation between physical activity and atrial fibrillation risk showed that physical activity at volumes of 5–20 metabolic equivalents per week (MET-h/week) was associated with significant reduction in atrial fibrillation risk (relative risk for 19 MET-h/week = 0.92 (0.87, 0.98). By comparison, physical activity volumes exceeding 20 MET-h/week were unrelated to atrial fibrillation risk (relative risk for 21 MET-h/week = 0.95 (0.88, 1.02). Conclusion These data show a J-shaped relation between physical activity volume and atrial fibrillation risk. Physical activity at volumes of up to 20 MET-h/week is associated with reduced atrial fibrillation risk, whereas volumes exceeding 20 MET-h/week show no relation with risk.

scholarly journals Dynamics of sleep, sedentary behavior, and moderate-to-vigorous physical activity on school versus nonschool days

SLEEP ◽  
2020 ◽  
Author(s):  
Bridget Armstrong ◽  
Michael W Beets ◽  
Angela Starrett ◽  
Keith Brazendale ◽  
Gabrielle Turner-McGrievy ◽  
...  
Keyword(s):  
Physical Activity ◽  
Sedentary Behavior ◽  
Time Use ◽  
Structural Equation ◽  
Time Series Data ◽  
Vigorous Physical Activity ◽  
Series Data ◽  
Equation Modeling ◽  
Specific Behavior ◽  
School Day

Abstract Study Objectives Studies examining time-use activity behaviors (sleep, sedentary behavior, and physical activity) on school days compared with nonschool days have examined these behaviors independently, ignoring their interrelated nature, limiting our ability to optimize the health benefits of these behaviors. This study examines the associations of school-day (vs. nonschool day) with time-use activity behaviors. Methods Time series data (6,642 days) from Fitbits (Charge-2) were collected (n = 196, 53% female, 5–10 years). We used a variable-centered dynamic structural equation modeling approach to estimate day-to-day associations of time-use activity behaviors on school days for each child. We then used person-centered cluster analyses to group individuals based on these estimates. Results Within-participant analysis showed that on school days (vs. nonschool days), children (1) slept less (β = −0.17, 95% CI = −0.21, −0.13), (2) were less sedentary (β = −0.05, 95% CI = −0.09, −0.02), and (3) had comparable moderate-to-vigorous physical activity (MVPA; β = −0.05, 95% CI = −0.11, 0.00). Between-participant analysis showed that, on school days, children with higher sleep carryover experienced greater decreases in sleep (β = 0.44, 95% CI = 0.08, 0.71), children with higher body mass index z-score decreased sedentary behavior more (β = −0.41, 95% CI = −0.64, −0.13), and children with lower MVPA increased MVPA more (β = −0.41, 95% CI −0.64, −0.13). Cluster analysis demonstrated four distinct patterns of connections between time-use activity behaviors and school (High Activity, Sleep Resilient, High Sedentary, and Dysregulated Sleep). Conclusions Using a combination of person-centered and more traditional variable-centered approaches, we identified patterns of interrelated behaviors that differed on school, and nonschool days. Findings can inform targeted intervention strategies tailored to children’s specific behavior patterns.

scholarly journals Correlates of Adiposity Among Latino Preschool Children

2014 ◽  
Vol 11 (1) ◽  
pp. 195-198 ◽  
Author(s):  
Jason A. Mendoza ◽  
Jessica McLeod ◽  
Tzu-An Chen ◽  
Theresa A. Nicklas ◽  
Tom Baranowski
Keyword(s):  
Physical Activity ◽  
Parent Education ◽  
Vigorous Physical Activity ◽  
Neighborhood Disorder ◽  
Z Score ◽  
Neighborhood Safety ◽  
Tv Viewing ◽  
Related Risk ◽  
Z Scores ◽  
Obesity Interventions

Background:Childhood obesity is at record high levels in the US and disproportionately affects Latino children; however, studies examining Latino preschool children’s obesity-related risk factors are sparse. This study determined correlates of Latino preschoolers’ (ages 3–5 years) adiposity to inform future obesity interventions and policies.Methods:Latino preschoolers (n = 96) from 4 Head Start centers in Houston, Texas were recruited. Parents reported acculturation and neighborhood safety. Children’s and parents’ height and weight were measured. Children’s television (TV) viewing was measured by TV diaries and physical activity by accelerometers. Linear regression was used with body mass index (BMI) z-score as the dependent variable and covariates sequentially added and retained in 4 blocks: 1) child age, gender, parent education, and BMI; 2) neighborhood safety and parent and child acculturation; 3) TV viewing; and 4) moderate-to-vigorous physical activity (MVPA).Results:In the final model (n = 96), only neighborhood disorder (β = 0.30, P = .005) and MVPA (β = –0.21, P = .049) were significantly associated with BMI z-score.Conclusions:Among Latino preschoolers, higher neighborhood disorder and lower MVPA were associated with greater children’s BMI z-scores.

scholarly journals Variables independently associated with self-reported obesity in the European Union

1999 ◽  
Vol 2 (1a) ◽  
pp. 125-133 ◽  
Author(s):  
JA Martínez ◽  
JM Kearney ◽  
A Kafatos ◽  
S Paquet ◽  
MA Martínez-Gonzélez
Keyword(s):  
Physical Activity ◽  
Social Class ◽  
Smoking Status ◽  
Adult Population ◽  
Cluster Sampling ◽  
The European Union ◽  
Obesity Prevalence ◽  
Men And Women ◽  
Prevalence Of Obesity ◽  
The Eu

AbstractObjectiveThe rapid increase in obesity rates over recent years suggest that cultural and societal influences are affecting the adjustment in the energy balance equation in addition to other physiopathological or genetic determinants. Therefore, a pan-EU study was carried out to explore the influence of sociodemographic factors as well as some attitudes (smoking and exercise) on the prevalence of obesity in the adult population of all 15 member states of the EU.DesignOverall, a sample of 15 239 individuals aged 15 years and upwards in the EU completed the questionnaire. Subject selection was quota-controlled to make the sample nationally representative following a multistage stratified cluster sampling. Self-reported height and weight were used to calculate body mass index (BMI).ResultsFrom the EU average results, it can be seen that only about half of the EU population (48%) is within the normal weight range, while the obesity (BMI > ≥ 30 kg m−2) prevalence was about 10% in the EU and the overweight prevalence was 36.6% and 25.6% among men and women, respectively. UK subjects had the highest prevalence of obesity (12%), while Italians, French and Swedes had the lowest levels of obesity (about 7%). Concerning age and social class interactions, logistic regression analysis showed that high social class and younger individuals in all groups had a lower odds ratio for obesity prevalence. People with a higher level of education are less likely to be obese, while the interaction between educational levels and obesity was different for men and women. A low participation in various leisure-time physical activities, the lack of interest (precontemplation) in being involved in exercise/physical activity and the increasing number of hours sitting down at work appear to be predictors of obesity. Single individuals were less prone to become obese than couples or widowed/divorced people. Finally, smoking status was statistically linked to the prevalence of obesity, since non-smokers or ex-smokers for more than 1 year presented a higher tendency for a BMI > 30.ConclusionsThis survey confirms that a priority area for health intervention aimed at preventing the development of obesity should be to increase levels of physical activity, although the approach will depend on the population, especially with respect to educational and socioeconomic aspects.

Variables Associated With Active and Inactive Behavior During the After-School Period

2013 ◽  
Vol 25 (2) ◽  
pp. 288-299 ◽  
Author(s):  
Eric Wickel
Keyword(s):  
Physical Activity ◽  
Time Use ◽  
Screen Time ◽  
Vigorous Physical Activity ◽  
Peer Groups ◽  
Fourth Grade ◽  
After School ◽  
Light Physical Activity ◽  
Children's Behavior ◽  
School Period

This study analyzed time-use interviews to report levels of active and inactive behavior during the after-school period (3–6 pm). Interviews were conducted on random days from three separate seasons during third and fourth grade. Youth with at least two interviews during third (356 completed 2 interviews; 506 completed 3 interviews [9 yrs; 50% boys]) and fourth (186 completed 2 interviews; 768 completed 3 interviews [10 yrs; 50% boys]) grade were included to report levels of moderate-to-vigorous physical activity (MVPA), light physical activity, inactive screen time, inactive nonscreen time, and travel by location and who the activity was undertaken with. Reporting time outside the home and with peers (single or group) was related to higher levels of MVPA. While inside the home, screen and nonscreen proportions were comparable (38% and 40%, respectively), despite unique patterns (screen: boys > girls; nonscreen: girls > boys). Reporting time with both parents was associated with more nonscreen time; whereas reporting time with peer groups was associated with lower screen time. Understanding active and inactive patterns of children’s behavior outside of school hours can be very important in contributing toward the development of innovative interventions for increasing physical activity.

scholarly journals Relationship Between Metabolic Syndrome and Moderate-to-Vigorous Physical Activity in Youth

2015 ◽  
Vol 12 (1) ◽  
pp. 13-19 ◽  
Author(s):  
Aristides M. Machado-Rodrigues ◽  
Neiva Leite ◽  
Manuel J. Coelho e Silva ◽  
João Valente-dos-Santos ◽  
Raul A. Martins ◽  
...  
Keyword(s):  
Physical Activity ◽  
Risk Factors ◽  
Metabolic Syndrome ◽  
Vigorous Physical Activity ◽  
Density Lipoprotein ◽  
Metabolic Risk Factors ◽  
Metabolic Risk ◽  
Lifestyle Behaviors ◽  
Increased Risk ◽  
Run Test

Background:Associations of metabolic syndrome (MetS) with lifestyle behaviors in youth is potentially important for identifying subgroups at risk and encourage interventions. This study evaluates the associations among the clustering of metabolic risk factors and moderate-to-vigorous physical activity (MVPA) in youth.Methods:The sample comprised 522 girls and 402 boys (N = 924) aged 11 to 17 years. Height, weight, waist circumference (WC), fasting glucose, high-density lipoprotein cholesterol, triglycerides, and blood pressures were measured. Cardiorespiratory fitness (CRF) was assessed using the 20-m shuttle run test. MVPA was estimated with a 3-day diary. Outcome variables were statistically normalized and expressed as z scores. A clustered metabolic risk score was computed as the mean of z scores. Multiple linear regression was used to test associations between metabolic risk and MVPA by sex, adjusted for age, WC, and CRF.Results:After adjustment for potential confounders, MVPA was inversely associated with the clustering of metabolic risk factors in girls, but not in boys; in addition, after adjusting for WC, the statistical model of that relationship was substantially improved in girls.Conclusion:MVPA was independently associated with increased risk of MetS in girls. Additional efforts are needed to encourage research with different analytical approach and standardization of criteria for MetS in youth.

scholarly journals Body Mass Index of children and adolescent participants in a voucher program designed to incentivise participation in sport and physical activity

2020 ◽  
Author(s):  
Katherine Owen ◽  
B Bellew ◽  
Bridget C Foley ◽  
Adrian Bauman ◽  
Lindsey J Reece
Keyword(s):  
Physical Activity ◽  
Children And Adolescents ◽  
Large Scale ◽  
Sport Participation ◽  
Overweight And Obesity ◽  
Obesity Prevalence ◽  
Multinomial Regression ◽  
Disadvantaged Area ◽  
Activity Promotion ◽  
Increased Risk

Abstract Background There has been limited population-level success in tackling overweight and obesity. The Active Kids program is a state-wide intervention that aims to increase participation in organised physical activity and sport among children and adolescents in NSW, Australia. This study profiled children and adolescents who registered for the Active Kids program by examining the prevalence of overweight and obesity across subgroups and by social disadvantage in this sample. MethodsFor participating children, each parent or carer was required to complete an online registration form with information about the child’s height, weight, physical activity, sport participation, age, sex, primary language spoken at home, Aboriginality, disability status and postcode. Descriptive statistics were used to profile children and adolescents who registered in the program and multinomial regression models were used to determine which demographic characteristics were associated with an increased risk of overweight and obesity. Results In 2018, 671,375 parents registered a child or adolescent for the Active Kids Program. Among these children and adolescents, the prevalence of overweight and obesity was 17.2% and 7.6%, respectively. A large number of children and adolescents who lived in the most disadvantaged area (n = 99,583; 14.8%) registered for the program. There was a clear socio-economic gradient for obesity prevalence across areas of increasing disadvantage, with children and adolescents living in the most disadvantaged area being 1.87 (95% CIs 1.82, 1.93) times more likely to be overweight or obese compared with children and adolescents living in the least disadvantaged area. Conclusions The Active Kids program successfully reached a substantial proportion of overweight and obese children from socially disadvantaged backgrounds, providing financial support and opportunities for these children to participate in organised sport and physical activity. However, the program did not reach all children, and additional physical activity promotion strategies may be needed in a comprehensive approach. Nonetheless, these findings support government investment in reaching childhood overweight and obesity with large-scale programs.

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