BACKGROUND: Between-person differences in sedentary patterns should be considered to understand the role of sedentary behavior (SB) in the development of childhood obesity. This study took a novel approach based on compositional data analysis to examine associations between SB patterns and adiposity and investigate differences in adiposity associated with time reallocation between time spent in sedentary bouts of different duration and physical activity. METHODS: An analysis of cross-sectional data was performed in 425 children aged 7-12 years (58% girls). Waking behaviors were assessed using ActiGraph GT3X accelerometer for seven consecutive days. Multi-frequency bioimpedance measurement was used to determine adiposity. Compositional regression models with robust estimators were used to analyze associations between sedentary patterns and adiposity markers. To examine differences in adiposity associated with time reallocation, we used the compositional isotemporal substitution model. RESULTS: Significantly higher fat mass percentage (FM%; βilr1 = 0.18; 95% CI: 0.01, 0.34; p = 0.040) and visceral adipose tissue (VAT; βilr1 = 0.37; 95% CI: 0.03, 0.71; p = 0.034) were associated with time spent in middle sedentary bouts in duration of 10-29 min (relative to remaining behaviors). No significant associations were found for short (< 10 min) and long sedentary bouts (≥30 min). Substituting the time spent in total SB with moderate-to-vigorous physical activity (MVPA) was associated with a decrease in VAT. Substituting 1 h/week of the time spent in middle sedentary bouts with MVPA was associated with 2.9% (95% CI: 1.2, 4.6), 3.4% (95% CI: 1.2, 5.5), and 6.1% (95% CI: 2.9, 9.2) lower FM%, fat mass index, and VAT, respectively. Moreover, substituting 2 h/week of time spent in middle sedentary bouts with short sedentary bouts was associated with 3.5% (95% CI: 0.02, 6.9) lower FM%. CONCLUSIONS: Our findings suggest that adiposity status could be improved by increasing MVPA at the expense of time spent in middle sedentary bouts. Some benefits to adiposity may also be expected from replacing middle sedentary bouts with short sedentary bouts, that is, by taking standing or activity breaks more often. These findings may help design more effective interventions to prevent and control childhood obesity.
- MeSH
- Adiposity * MeSH
- Accelerometry MeSH
- Data Analysis MeSH
- Child MeSH
- Body Mass Index MeSH
- Humans MeSH
- Cross-Sectional Studies MeSH
- Sedentary Behavior * MeSH
- Check Tag
- Child MeSH
- Humans MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
The health effects of daily activity behaviours (physical activity, sedentary time and sleep) are widely studied. While previous research has largely examined activity behaviours in isolation, recent studies have adjusted for multiple behaviours. However, the inclusion of all activity behaviours in traditional multivariate analyses has not been possible due to the perfect multicollinearity of 24-h time budget data. The ensuing lack of adjustment for known effects on the outcome undermines the validity of study findings. We describe a statistical approach that enables the inclusion of all daily activity behaviours, based on the principles of compositional data analysis. Using data from the International Study of Childhood Obesity, Lifestyle and the Environment, we demonstrate the application of compositional multiple linear regression to estimate adiposity from children's daily activity behaviours expressed as isometric log-ratio coordinates. We present a novel method for predicting change in a continuous outcome based on relative changes within a composition, and for calculating associated confidence intervals to allow for statistical inference. The compositional data analysis presented overcomes the lack of adjustment that has plagued traditional statistical methods in the field, and provides robust and reliable insights into the health effects of daily activity behaviours.
- MeSH
- Exercise * MeSH
- Child MeSH
- Data Interpretation, Statistical * MeSH
- Humans MeSH
- Pediatric Obesity * MeSH
- Sedentary Behavior * MeSH
- Sleep * MeSH
- Check Tag
- Child MeSH
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
INTRODUCTION: It is unclear whether adiposity leads to changes in movement behaviors, and there is a lack of compositional analyses of longitudinal data which focus on these associations. Using a compositional approach, this study aimed to examine the associations between baseline adiposity and 7-year changes in physical activity (PA) and sedentary behavior (SB) among elderly women. We also explored the longitudinal associations between change in adiposity and change in movement-behavior composition. METHODS: This longitudinal study included 176 older women (mean baseline age 62.8 (4.1) years) from Central Europe. Movement behavior was assessed by accelerometers and adiposity was measured by bioelectrical impedance analysis at baseline and follow-up. A set of multivariate least-squares regression analyses was used to examine the associations of baseline adiposity and longitudinal changes in adiposity as explanatory variables with longitudinal changes in a 3-part movement-behavior composition consisting of SB, light PA (LPA) and moderate-to-vigorous PA (MVPA) as outcome variables. RESULTS: No significant associations were found between baseline adiposity and longitudinal changes in the movement-behavior composition (p > 0.05). We found significant associations of changes in body mass index (BMI) and fat mass percentage (FM%) with changes in the movement-behavior composition. An increase in BMI was associated with an increase of SB at the expense of LPA and MVPA (β = 0.042, p = 0.009) and with a decrease of MVPA in favor of SB and LPA (β = - 0.059, p = 0.037). An increase in FM% was significantly associated only with an increase of SB at the expense of LPA and MVPA (β = 0.019, p = 0.031). CONCLUSIONS: This study did not support the assumption that baseline adiposity is associated with longitudinal changes in movement behaviors among elderly women, but we found evidence for change-to-change associations, suggesting that a 7-year increase in adiposity is associated with a concurrent increase of SB at the expense of LPA and MVPA and with a concurrent decrease of MVPA in favor of LPA and SB. Public health interventions are needed to simultaneously prevent weight gain and promote physically active lifestyle among elderly women.
- MeSH
- Adiposity * MeSH
- Accelerometry MeSH
- Data Analysis * MeSH
- Body Mass Index MeSH
- Humans MeSH
- Longitudinal Studies MeSH
- Prospective Studies MeSH
- Cross-Sectional Studies MeSH
- Aged MeSH
- Check Tag
- Humans MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Geographicals
- Europe MeSH
... about Change 7 -- 1.3 Three Important Features of a Study of Change 9 -- 2 Exploring Longitudinal Data ... ... on Change 16 -- 2.1 Creating a Longitudinal Data Set 17 -- 2.2 Descriptive Analysis of Individual Change ... ... Systematic Interindividual Differences in Change 57 -- 3.4 Fitting the Multilevel Model for Change to Data ... ... Examining Estimated Fixed Effects 68 -- 3.6 Examining Estimated Variance Components 72 -- 4 Doing Data ... ... for Characterizing the Distribution of Discrete-Time -- Event Occurrence Data 339 -- 10.3 Developing ...
xx, 644 s. : il, tab. ; 24 cm
- MeSH
- Longitudinal Studies MeSH
- Social Sciences methods MeSH
- Research MeSH
- Research Design MeSH
- Publication type
- Monograph MeSH
- Conspectus
- Sociologie
- NML Fields
- sociologie
BACKGROUND: To date, no longitudinal study using a compositional approach has examined sedentary behavior (SB) patterns in relation to adiposity in the pediatric population. Therefore, our aims were to (1) investigate the changes in SB patterns and adiposity from childhood to adolescence, (2) analyze the prospective compositional associations between changes in SB patterns and adiposity, and (3) estimate the changes in adiposity associated with substituting SB with physical activity (PA) of different intensities. METHODS: The study presents a longitudinal design with a 5-year follow-up. A total of 88 participants (61% girls) were included in the analysis. PA and SB were monitored for seven consecutive days using a hip-worn accelerometer. Adiposity markers (fat mass percentage [FM%], fat mass index [FMI], and visceral adiposity tissue [VAT]) were assessed using the multi-frequency bioimpedance analysis. The prospective associations were examined using compositional data analysis. RESULTS: Over the follow-up period, the proportion of time spent in total SB increased by 154.8 min/day (p < 0.001). The increase in total SB was caused mainly by an increase in middle and long sedentary bouts, as these SB periods increased by 79.8 min/day and 62.0 min/day (p < 0.001 for both), respectively. FM%, FMI, and VAT increased by 2.4% points, 1.0 kg/m2, and 31.5 cm2 (p < 0.001 for all), respectively. Relative to the remaining movement behaviors, the increase in time spent in middle sedentary bouts was significantly associated with higher FM% (βilr1 = 0.27, 95% confidence interval [CI]: 0.02 to 0.53) at follow-up. Lower VAT by 3.3% (95% CI: 0.8 to 5.7), 3.8% (95% CI: 0.03 to 7.4), 3.9% (95% CI: 0.8 to 6.9), and 3.8% (95% CI: 0.7 to 6.9) was associated with substituting 15 min/week spent in total SB and in short, middle, and long sedentary bouts, respectively, with an equivalent amount of time spent in vigorous PA. CONCLUSIONS: This study showed unfavorable changes in SB patterns and adiposity status in the transition from childhood to adolescence. Incorporating high-intensity PA at the expense of SB appears to be an appropriate approach to reduce the risk of excess adiposity in the pediatric population.
- Publication type
- Journal Article MeSH
OBJECTIVES: Growing evidence supports the important role of 24-hour movement behaviours (MB) in preventing childhood obesity. However, research to understand the heterogeneity and variability of MB among individuals and what kind of typologies of individuals are at risk of developing obesity is lacking. To bridge this gap, this study identified typologies of 24-hour MB in children and adolescents and investigated their associations with adiposity indicators. METHODS: In this cross-sectional study, 374 children and 317 adolescents from the Czech Republic wore wrist-worn accelerometers for seven consecutive days. Time spent in moderate-to-vigorous physical activity (MVPA), light physical activity (LPA), sedentary behaviour (SB), and sleep was quantified using raw accelerometery data. Adiposity indicators included body mass index (BMI) z-score, fat mass percentage (FM%), fat mass index (FMI), and visceral adipose tissue (VAT). Bias-adjusted latent profile analysis was used on the 24-hour MB data to identify MB typologies and their associations with adiposity indicators. The models were adjusted for potential confounders. The identified typologies were labelled to reflect the behavioural profiles of bees to aid interpretability for the general public. RESULTS: Two typologies were identified in children: highly active Workers characterised by high levels of MVPA and LPA, and inactive Queens characterised by low levels of MVPA and LPA, high levels of SB and longer sleep duration compared to Workers. In adolescents, an additional typology labelled as Drones was characterised by median levels of MVPA, LPA, SB and longest sleep duration. After controlling for covariates, we found that children labelled as Queens were associated with 1.38 times higher FM%, 1.43 times higher FMI, and 1.67 times higher VAT than Workers. In adolescents, Drones had 1.14 times higher FM% and Queens had 1.36 higher VAT in comparison with Workers, respectively. CONCLUSION: Our study highlights the importance of promoting active lifestyles in children and adolescents to potentially reduce adiposity. These findings can provide insights for interventions aimed at promoting healthy MB and preventing childhood obesity.
- MeSH
- Adiposity * physiology MeSH
- Accelerometry MeSH
- Exercise * MeSH
- Child MeSH
- Body Mass Index MeSH
- Humans MeSH
- Adolescent MeSH
- Pediatric Obesity * epidemiology MeSH
- Cross-Sectional Studies MeSH
- Sedentary Behavior * MeSH
- Sleep physiology MeSH
- Check Tag
- Child MeSH
- Humans MeSH
- Adolescent MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Geographicals
- Czech Republic MeSH
Eight phenolic acids (vanillic, gentisic, protocatechuic, syringic, gallic, coumaric, ferulic and caffeic) were quantitatively determined in 30 commercially available wines from South Moravia by gas chromatography-mass spectrometry. Raw (untransformed) and centered log-ratio transformed data were evaluated by classical and robust version of principal component analysis (PCA). A robust compositional biplot of the centered log-ratio transformed data gives the best resolution of particular categories of wines. Vanillic, syringic and gallic acids were identified as presumed markers occurring in relatively higher concentrations in red wines. Gentisic and caffeic acid were tentatively suggested as prospective technological markers, reflecting presumably some kinds of technological aspects of wine making.
In recent years, the focus of activity behavior research has shifted away from univariate paradigms (e.g., physical activity, sedentary behavior and sleep) to a 24-h time-use paradigm that integrates all daily activity behaviors. Behaviors are analyzed relative to each other, rather than as individual entities. Compositional data analysis (CoDA) is increasingly used for the analysis of time-use data because it is intended for data that convey relative information. While CoDA has brought new understanding of how time use is associated with health, it has also raised challenges in how this methodology is applied, and how the findings are interpreted. In this paper we provide a brief overview of CoDA for time-use data, summarize current CoDA research in time-use epidemiology and discuss challenges and future directions. We use 24-h time-use diary data from Wave 6 of the Longitudinal Study of Australian Children (birth cohort, n = 3228, aged 10.9 ± 0.3 years) to demonstrate descriptive analyses of time-use compositions and how to explore the relationship between daily time use (sleep, sedentary behavior and physical activity) and a health outcome (in this example, adiposity). We illustrate how to comprehensively interpret the CoDA findings in a meaningful way.
- MeSH
- Adiposity MeSH
- Data Analysis * MeSH
- Activities of Daily Living MeSH
- Exercise * MeSH
- Child MeSH
- Cohort Studies MeSH
- Humans MeSH
- Longitudinal Studies MeSH
- Sedentary Behavior * MeSH
- Sleep MeSH
- Check Tag
- Child MeSH
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Geographicals
- Australia MeSH
... Project: purpose and initial steps 14 -- General methods for the indicator set of the HCQI Project 16 -- DATA ... ... COMPARABILITY ISSUES 20 -- “INITIAL” (2003-2005) INDICATORS: 2006 SPECIFICATIONS AND DATA RESULTS 24 ... ... Composition and evolution of the HCQI set of indicators 19 -- Table 3. 2004 Admission based ischemic ... ... Availability of data for ‘Initial’ (2003-2005) Indicators presented in this section.25 -- Table 5. ... ... Findings on differences between administrative and survey data for cancer screening 21 -- 13 ...
OECD health working papers ; No. 29
157 stran : ilustrace, tabulky ; 30 cm
- MeSH
- Evaluation Studies as Topic MeSH
- Data Collection MeSH
- Quality Indicators, Health Care MeSH
- Quality Assurance, Health Care MeSH
- Geographicals
- Europe MeSH
- Conspectus
- Veřejné zdraví a hygiena
- NML Fields
- veřejné zdravotnictví
- management, organizace a řízení zdravotnictví
- NML Publication type
- výzkumné zprávy
BACKGROUND & AIMS: The aims of this study were to examine the prospective compositional associations between sedentary behaviour (SB) patterns and longitudinal changes in body composition parameters, and to use compositional isotemporal substitution modelling to analyse the longitudinal changes in body composition parameters associated with time reallocation from SB to physical activity (PA) in older women. METHODS: The study included women aged 60 years and older (n = 182) with valid data at baseline and at the subsequent 7-year follow-up. For both time points, the ActiGraph GT1M accelerometer was used for SB and PA assessments and multi-frequency bioimpedance analysis was used to assess the body composition parameters related to adiposity and muscle mass. Compositional regression models were used to analyse the associations between proportion of time spent in sedentary bouts of different duration and longitudinal changes in body composition parameters. A compositional isotemporal substitution model was created to estimate the differences in body composition parameters associated with one-to-one time reallocations between baseline SB and PA. RESULTS: A significant increase in fat mass index (βilr1 = 0.61, 95% confidence interval [CI]: 0.18, 1.04) and visceral adipose tissue (βilr1 = 6.01, 95% CI: 1.52, 10.5) was associated with a higher baseline proportion of time spent in long sedentary bouts (i.e. sedentary bout of ≥30 min). Reallocating 1 h/week and 3.5 h/week from the time spent in long sedentary bouts in favour of light PA was associated with a significant decrease in fat mass index by 0.78% (95% CI: 0.24, 1.32) and 3.13% (95% CI: 0.97, 5.29), respectively. No association was found for indicators of muscle mass. CONCLUSIONS: This study suggests that long-term adiposity status could be improved by increasing the proportion of time spent in light PA at the expense of time spent in prolonged SB. This finding may help in designing more effective and feasible interventions for the maintenance of healthy body composition in advanced age.
- MeSH
- Adiposity MeSH
- Exercise MeSH
- Muscle, Skeletal physiology MeSH
- Middle Aged MeSH
- Humans MeSH
- Intra-Abdominal Fat MeSH
- Prospective Studies MeSH
- Sedentary Behavior * MeSH
- Aged MeSH
- Body Composition * MeSH
- Adipose Tissue MeSH
- Check Tag
- Middle Aged MeSH
- Humans MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH