Sources of variability in childhood obesity indicators and related behaviors.

The purpose of this study was to describe sources of variability in obesity-related variables in 6022 children aged 9-11 years from 12 countries. The study design involved recruitment of students, nested within schools, which were nested within study sites. Height, weight and waist circumference (WC) were measured and body mass index (BMI) was calculated; sleep duration and total and in-school moderate-to-vigorous physical activity (MVPA) and sedentary time were measured by accelerometry; and diet scores were obtained by questionnaire. Variance in most variables was largely explained at the student level: BMI (91.9%), WC (93.5%), sleep (75.3%), MVPA (72.5%), sedentary time (76.9%), healthy diet score (88.3%), unhealthy diet score (66.2%), with the exception of in-school MVPA (53.8%) and in-school sedentary time (25.1%). Variance explained at the school level ranged from 3.3% for BMI to 29.8% for in-school MVPA, and variance explained at the site level ranged from 3.2% for WC to 54.2% for in-school sedentary time. In general, more variance was explained at the school and site levels for behaviors than for anthropometric traits. Given the variance in obesity-related behaviors in primary school children explained at school and site levels, interventions that target policy and environmental changes may enhance obesity intervention efforts.

Does compliance with healthy lifestyle behaviours cluster within individuals in Australian primary school-aged children?

BACKGROUND: The 3 "movement behaviours" of sleep, screen time, and physical activity are associated with a wide range of health outcomes in children. This study examined whether these behaviours cluster together within individuals in Australian primary school children. METHODS: Three datasets including 4,449 9- to 11-year-old children were interrogated-(a) Obesity Prevention and Lifestyle (OPAL), (b) the International Study of Children, Obesity, Lifestyle and Environment (ISCOLE), and (c) the National Children's Nutrition and Physical Activity Survey (NCNPAS). The surveys measured movement behaviours using different instruments (accelerometry, use of time recall, and questionnaires) and different operationalizations of compliance. Observed frequencies of compliance with various combinations of guidelines were compared with expected frequencies based on the assumption of independence, using chi-square tests. RESULTS: Compliance with the sleep guidelines was relatively high (72%, 75%, and 79% in the OPAL, ISCOLE, and NCNPAS datasets, respectively), and compliance with the screen (18%, 35%, and 22%) and physical activity (33%, 57%, and 87%) guidelines was generally lower. Against expectation, there was no evidence of clustering in any of the datasets (p > .99). CONCLUSIONS: Compliance with movement behaviour guidelines does not cluster within individuals in 9- to 11-year-old Australian children. It may be unlikely that fostering compliance with one guideline will have a flow-on effect to the others. Temporal trade-offs (i.e., the need to choose one movement behaviour above another) in the 24-hr day may contribute to the lack of clustering.

Associations between meeting combinations of 24-h movement guidelines and health-related quality of life in children from 12 countries.

OBJECTIVES: To examine whether meeting vs not meeting movement/non-movement guidelines (moderate-to-vigorous physical activity [MVPA], screen time, sleep duration), and combinations of these recommendations, are associated with health-related quality of life (HRQoL) in children from 12 countries in five major geographic regions of the world and explore whether the associations vary by study site. STUDY DESIGN: Observational, multinational cross-sectional study. METHODS: This study included 6106 children aged 9-11 years from sites in Australia, Brazil, Canada, China, Colombia, Finland, India, Kenya, Portugal, South Africa, the United Kingdom, and the United States. Participants completed the KIDSCREEN-10 to provide a global measure of their HRQoL. Sleep duration and MVPA were assessed using 24-h accelerometry. Screen time was assessed through self-report. Meeting the recommendations was defined as ≥60 min/day for MVPA, ≤2 h/day for screen time, and between 9 and 11 h/night for sleep duration. Age, sex, highest parental education, unhealthy diet pattern score, and body mass index z-score were included as covariates in statistical models. RESULTS: In the full sample, children meeting the screen time recommendation, the screen time + sleep recommendation, and all three recommendations had significantly better HRQoL than children not meeting any of these guidelines. Differences in HRQoL scores between sites were also found within combinations of movement/non-movement behaviors. For example, while children in Australia, Canada, and USA self-reported better HRQoL when meeting all three recommendations, children in Kenya and Portugal reported significantly lower HRQoL when meeting all three recommendations (relative to not meeting any). CONCLUSIONS: Self-reported HRQoL is generally higher when children meet established movement/non-movement recommendations. However, differences between study sites also suggest that interventions aimed at improving lifestyle behaviors and HRQoL should be locally and culturally adapted.

Testing the activitystat hypothesis: a randomised controlled trial.

BACKGROUND: It has been hypothesised that an 'activitystat' may biologically regulate energy expenditure or physical activity levels, thereby limiting the effectiveness of physical activity interventions. Using a randomised controlled trial design, the aim of this study was to investigate the effect of a six-week exercise stimulus on energy expenditure and physical activity, in order to empirically test this hypothesis. METHODS: Previously inactive adults (n = 129) [age (mean ± SD) 41 ± 11 year; body mass index 26.1 ± 5.2 kg/m(2)] were randomly allocated to a Control group (n = 43) or a 6-week Moderate (150 min/week) (n = 43) or Extensive (300 min/week) (n = 43) exercise intervention group. Energy expenditure and physical activity were measured using a combination of accelerometry (total counts, minutes spent in moderate to vigorous physical activity) and detailed time use recalls using the Multimedia Activity Recall for Children and Adults (total daily energy expenditure, minutes spent in moderate to vigorous physical activity) at baseline, mid- and end-intervention and 3- and 6-month follow up. Resting metabolic rate was measured at baseline and end-intervention using indirect calorimetry. Analysis was conducted using random effects mixed modeling. RESULTS: At end-intervention, there were statistically significant increases in all energy expenditure and physical activity variables according to both accelerometry and time use recalls (p < 0.001) in the Moderate and Extensive groups, relative to Controls. There was no significant change in resting metabolic rate (p = 0.78). CONCLUSION: Taken together, these results show no evidence of an "activitystat" effect. In the current study, imposed exercise stimuli of 150-300 min/week resulted in commensurate increases in overall energy expenditure and physical activity, with no sign of compensation in either of these constructs. TRIAL REGISTRATION NUMBER: ACTRN12610000248066  (registered prospectively 24 March 2010).

Prevalence and socio-economic distribution of eating, physical activity and sedentary behaviour among South Australian children in urban and rural communities: baseline findings from the OPAL evaluation.

OBJECTIVE: To identify current prevalence and sociodemographic distribution of adherence to national diet and physical activity and sedentary behaviour guidelines among Australian primary school children. STUDY DESIGN: Cross-sectional survey of children (n = 4637, 9-11 years) participating at baseline in the South Australian Obesity Prevention and Lifestyle (OPAL) programme evaluation. METHODS: Self-reported diet, physical activity (PA) and screen time (ST) behaviours were assessed via questionnaire. Children were classified as meeting or not meeting each guideline (two or more serves of fruit, five or more serves of vegetables, two or less serves of discretionary food, ≥60 min of PA, and ≤2 h of ST per day). RESULTS: Although 65% of children met fruit recommendations, only 22% met vegetable recommendations (17% consumed no vegetables). Approximately one-quarter (28%) of children met discretionary food recommendations. Only 17% of children met the ST recommendations and 33% met PA recommendations. Less than 1% of children met all five recommendations. Rural children were more likely to meet both PA (OR = 1.45, 95% CI: 1.21-1.74, P < 0.001) and ST (OR = 1.37, 95% CI: 1.14-1.66, P < 0.01) recommendations than urban counterparts. Children at least socio-economic disadvantage performed better than those at greatest disadvantage for most behaviours. CONCLUSION: Improvement in Australian children's diet and physical activity and sedentary behaviours, particularly urban children and those at greatest socio-economic disadvantage, is urgently warranted.

The evolution of quantitative traits in complex environments.

Species inhabit complex environments and respond to selection imposed by numerous abiotic and biotic conditions that vary in both space and time. Environmental heterogeneity strongly influences trait evolution and patterns of adaptive population differentiation. For example, heterogeneity can favor local adaptation, or can promote the evolution of plastic genotypes that alter their phenotypes based on the conditions they encounter. Different abiotic and biotic agents of selection can act synergistically to either accelerate or constrain trait evolution. The environmental context has profound effects on quantitative genetic parameters. For instance, heritabilities measured in controlled conditions often exceed those measured in the field; thus, laboratory experiments could overestimate the potential for a population to respond to selection. Nevertheless, most studies of the genetic basis of ecologically relevant traits are conducted in simplified laboratory environments, which do not reflect the complexity of nature. Here, we advocate for manipulative field experiments in the native ranges of plant species that differ in mating system, life-history strategy and growth form. Field studies are vital to evaluate the roles of disparate agents of selection, to elucidate the targets of selection and to develop a nuanced perspective on the evolution of quantitative traits. Quantitative genetics field studies will also shed light on the potential for natural populations to adapt to novel climates in highly fragmented landscapes. Drawing from our experience with the ecological model system Boechera (Brassicaceae), we discuss advancements possible through dedicated field studies, highlight future research directions and examine the challenges associated with field studies.

Sleep duration or bedtime? Exploring the association between sleep timing behaviour, diet and BMI in children and adolescents.

OBJECTIVE: To determine whether sleep timing behaviour is associated with energy intake and diet quality in children and adolescents. DESIGN: Cross-sectional analysis of nationally representative survey data. SAMPLE: A total of 2200 participants of the 2007 Australian National Children's Nutrition and Physical Activity Survey aged 9-16 years with 2 days of food intake data, 4 days of use of time data and complete anthropometry. Participants were grouped into one of four sleep-wake behaviour categories: early bed-early rise (EE); early bed-late rise (EL); late bed-early rise (LE) and late bed-late rise (LL). The four categories were compared for body mass index (BMI) z-score, energy intake and diet quality assessed using the Dietary Guideline Index for Children and Adolescents. Analyses were adjusted for survey design, sociodemographic characteristics, sleep duration and physical activity level (PAL). RESULTS: In adjusted multivariate regression models with sleep timing behaviour group as the independent variable, the 'LL' category compared with the 'EE' category had a higher BMI z-score (ß=0.20, 95% confidence interval (CI) 0.06 to 0.34, P=0.007), and lower diet quality (ß=-4.0, 95% CI -5.7 to -2.3, P<0.001). Children and adolescents who went to bed late also had a higher intake of extra foods (that is, energy-dense, nutrient-poor foods) while those whom went to bed early consumed more fruit and vegetables. Energy intake was associated with sleep duration (ß=-4.5 kJ, 95% CI -6.7 to -2.4, P<0.001), but not sleep timing behaviour. CONCLUSION: Late bedtimes and late wake up times are associated with poorer diet quality, independent of sleep duration, PAL and child and sociodemographic characteristics.

Time use patterns in ambulatory adolescents with cerebral palsy.

BACKGROUND: No studies to date have examined the daily time spent across a variety of activity types (sleep, screen time, physical activity, domestic and school-related) in children with cerebral palsy (CP). AIM: To investigate the activity patterns of adolescents with CP and contrast them with those of typically developing (TD) adolescents, using a use-of-time approach. METHODS: Forty-one Australian adolescents with CP and 82 TD adolescents matched for age, sex, weight status and socio-economic status undertook structured interviews using a validated computerized use of time recall administered over 4 days. Time devoted to sleep, screen time, physical activity, domestic and school-related activity were compared using anova and Mann-Whitney tests. RESULTS: Adolescents with CP spent less time in physical activity (91 vs. 147 min/day, P= 0.0003), and in particular, its sub-components of active transport (28 vs. 52 min/day, P= 0.0013) and team sports (25 vs. 39 min/day, P= 0.04). They experienced significantly more quiet time (116 vs. 80 min/day, P= 0.0025) but spent less time in social interaction (6 vs. 22 min/day, P= 0.0016). There were no significant differences in sleep, screen time, domestic activities or school-related time. CONCLUSIONS: By and large, the activity patterns of ambulatory adolescents with CP were similar to their TD peers. Results highlight physical activity in younger adolescents (11-13 years) as an area for targeted interventions.

The calmodulin-binding transcription factor SIGNAL RESPONSIVE1 is a novel regulator of glucosinolate metabolism and herbivory tolerance in Arabidopsis.

The Arabidopsis Ca(2+)/calmodulin (CaM)-binding transcription factor SIGNAL RESPONSIVE1 (AtSR1/CAMTA3) was previously identified as a key negative regulator of plant immune responses. Here, we report a new role for AtSR1 as a critical component of plant defense against insect herbivory. Loss of AtSR1 function impairs tolerance to feeding by the generalist herbivore Trichoplusia ni as well as wound-induced jasmonate accumulation. The susceptibility of the atsr1 mutant is associated with decreased total glucosinolate (GS) levels. The two key herbivory deterrents, indol-3-ylmethyl (I3M) and 4-methylsulfinylbutyl (4MSOB), showed the most significant reductions in atsr1 plants. Further, changes in AtSR1 transcript levels led to altered expression of several genes involved in GS metabolism including IQD1, MYB51 and AtST5a. Overall, our results establish AtSR1 as an important component of plant resistance to insect herbivory as well as one of only three described proteins involved in Ca(2+)/CaM-dependent signaling to function in the regulation of GS metabolism, providing a novel avenue for future investigations of plant-insect interactions.

Analysing body composition as compositional data: An exploration of the relationship between body composition, body mass and bone strength.

Human body composition is made up of mutually exclusive and exhaustive parts (e.g. %truncal fat, %non-truncal fat and %fat-free mass) which are constrained to sum to the same total (100%). In statistical analyses, individual parts of body composition (e.g. %truncal fat or %fat-free mass) have traditionally been used as proxies for body composition, and have been linked with a range of health outcomes. But analysis of individual parts omits information about the other parts, which are intrinsically co-dependent because of the constant sum constraint of 100%. Further, body mass may be associated with health outcomes. We describe a statistical approach for body composition based on compositional data analysis. The body composition data are expressed as logratios to allow relative information about all the compositional parts to be explored simultaneously in relation to health outcomes. We describe a recent extension to the logratio approach to compositional data analysis which allows absolute information about the total of the compositional parts (body mass) to be considered alongside relative information about body composition. The statistical approach is illustrated by an example that explores the relationships between adults' body composition, body mass and bone strength.

Trends in the prevalence of childhood overweight and obesity in Australia between 1985 and 2008.

BACKGROUND: Popular media, health experts and researchers talk about a paediatric 'obesity epidemic' with exponentially increasing rates of obesity and overweight. However, some recent reports suggest that prevalence may have plateaued. This study examined trends in the prevalence of Australian childhood overweight and obesity since 1985. Specifically, it aimed to determine whether there have been (a) overall increases in average body mass index (BMI), (b) differential patterns of change within age groups and (c) increases in BMI within each weight-status category. METHOD: Forty-one Australian studies of childhood weight status conducted between 1985 and 2008 were reviewed. The studies included data on 264 905 Australians aged 2-18 years, with raw data being available on 70 758 children (27%). Children were classified as overweight or obese based on BMI using the criteria of Cole et al. (BMJ, 2000). The prevalence estimates were adjusted for age and sex, and plotted against measurement year using Lowess plots and two-linear-segment models. Where raw data were available, BMI z-scores (UK 1990 standard) were plotted against measurement year for all children and children in various age groups. Lowess plots and two-linear-segment models were used to assess secular trends in BMI z-scores pre- and post-1996 within age, gender and weight-status categories. RESULTS: There has been a plateau, or only slight increase, in the percentage of boys and girls classified as overweight or obese, with almost no change over the last 10 years. In boys and girls, prevalence rates have settled around 21-25% for overweight and obesity together, and 5-6% for obesity alone. Similar trends were found for BMI z-scores. These patterns were fairly consistent across the age span. Within each weight-status category, average BMI has not increased. CONCLUSIONS: Although levels of Australian paediatric overweight remain high, the prevalence of overweight and obesity seems to have flattened and has not followed the anticipated exponential trajectory.

Children's conceptualization of the term 'satisfaction': relevance for measuring health outcomes.

BACKGROUND: Health outcomes measurement is integral to planning and evaluating paediatric health care. Recent outcome measures have been developed to capture children's participation in everyday activities, a core component of which is the child's perceived satisfaction. Satisfaction, however, is a complex concept and it is not known how children conceptualize satisfaction and hence how it should best be measured. The purpose of this study was to explore children's conceptualization of the term 'satisfaction' and compare this with the description of satisfaction given in the literature to inform how satisfaction can be assessed in children. METHODS: Forty children aged between 10 and 15 years participated in eight focus groups, guided by a descriptive qualitative approach, to describe how they conceptualize 'satisfaction'. Children with disabilities were excluded as it was considered important to first ascertain how children without disabilities conceptualize satisfaction. Recruitment occurred through seven urban and rural public schools. Data were analysed using qualitative content analysis. RESULTS: Participants identified three methods by which a person may determine their level of satisfaction (i) making comparisons with previous experiences, and other's and self-expectations; (ii) evaluating one's emotions; and (iii) receiving positive external feedback. Participants described drawing upon one of these methods in isolation, rather than integrating outcomes from each method into one judgement of satisfaction. Participants also demonstrated confusion between the terms 'satisfaction' and 'satisfactory'. CONCLUSIONS: Partial congruence between children's conceptualization of satisfaction and that reported in the literature was observed in this study. Not all children between the ages of 10 and 15, however, have a full understanding of satisfaction. Caution must therefore be taken when using the term satisfaction in children's assessments to minimize the potential for varying interpretations of the question. Further studies are required to explore how children with disabilities view the term satisfaction and if their understanding differs to that of typically developing children.

Long-Chain Omega-3 Fatty Acid Intake Is Associated with Age but not Cognitive Performance in an Older Australian Sample.

BACKGROUND: Long-chain omega-3 polyunsaturated fatty acids (LCn-3 PUFA) are essential nutrients and may be capable of delaying age-related cognitive decline. However, previous studies indicate that Australians are not meeting recommendations for LCn-3 PUFA intake. The current study therefore examined LCn-3 PUFA intake in an older Australia sample, as well as associations between LCn-3 PUFA intake and cognitive function. METHODS: Cross-sectional data were collected from 90 adults aged 50 to 80 years. LCn-3 PUFA intake was assessed using a food frequency questionnaire and red blood cell fatty acid profiles were used to calculate the Omega-3 Index (RBC n-3 index). Cognitive function was measured using Addenbrooke's Cognitive Examination-III. RESULTS: Positive associations were observed between age and RBC n-3 index (b=0.06, 95% CI: 0.01 - 0.10, P=0.01), and age and LCn-3 PUFA intake from fish oil capsules (b=17.5, 95% CI: 2.4 - 32.5 mg/day, P=0.02). When adjusting for LCn-3 PUFA from fish oil capsules, the association between age and RBC n-3 index was no longer significant. No associations were observed between LCn-3 PUFA intake and cognitive function. CONCLUSION: LCn-3 PUFA and fish oil consumption increased with age in this sample of older Australians, particularly due to supplement intake. However, LCn-3 PUFA intake was not associated with cognitive function.

Health-related quality of life in obese children and adolescents.

OBJECTIVE: This review addresses the effect of overweight and obese weight status on pediatric health-related quality of life (HRQOL). METHOD: Web of Science, Medline, CINAHL, Cochrane Library, EMBASE, AMED and PubMed were searched for peer-reviewed studies in English reporting HRQOL and weight status in youth (<21 years), published before March 2008. RESULTS: Twenty-eight articles were identified. Regression of HRQOL against body mass index (BMI) using pooled data from 13 studies utilizing the Pediatric Quality of Life Inventory identified an inverse relationship between BMI and pediatric HRQOL (r=-0.7, P=0.008), with impairments in physical and social functioning consistently reported. HRQOL seemed to improve with weight loss, but randomized controlled trials were few and lacked long-term follow-up. CONCLUSIONS: Little is known about the factors associated with reduced HRQOL among overweight or obese youth, although gender, age and obesity-related co-morbidities may play a role. Few studies have examined the differences in HRQOL between community and treatment-seeking samples. Pooled regressions suggest pediatric self-reported HRQOL can be predicted from parent proxy reports, although parents of obese youths tend to perceive worse HRQOL than children do about themselves. Thus, future research should include both pediatric and parent proxy perspectives.

Ecological genomics of Boechera stricta: identification of a QTL controlling the allocation of methionine- vs branched-chain amino acid-derived glucosinolates and levels of insect herbivory.

In the Brassicaceae, glucosinolates influence the feeding, reproduction and development of many insect herbivores. Glucosinolate production and effects on herbivore feeding have been extensively studied in the model species, Arabidopsis thaliana and Brassica crops, both of which constitutively produce leaf glucosinolates mostly derived from the amino acid, methionine. Much less is known about the regulation or role in defense of glucosinolates derived from other aliphatic amino acids, such as the branched-chain amino acids (BCAA), valine and isoleucine. We have identified a glucosinolate polymorphism in Boechera stricta controlling the allocation to BCAA- vs methionine-derived glucosinolates in both leaves and seeds. B. stricta is a perennial species that grows in mostly undisturbed habitats of western North America. We have measured glucosinolate profiles and concentrations in 192 F(2) lines that have earlier been used for genetic map construction. We also performed herbivory assays on six F(3) replicates per F(2) line using the generalist lepidopteran, Trichoplusia ni. Quantitative trait locus (QTL) analysis identified a single locus controlling both glucosinolate profile and levels of herbivory, the branched chain-methionine allocation or BCMA QTL. We have delimited this QTL to a small genomic region with a 1.0 LOD confidence interval just 1.9 cm wide, which, in A. thaliana, contains approximately 100 genes. We also found that methionine-derived glucosinolates provided significantly greater defense than the BCAA-derived glucosinolates against feeding by this generalist insect herbivore. The future positional cloning of this locus will allow for testing various adaptive explanations.

Interindividual and intraindividual variability in adolescent sleep patterns across an entire school term: A pilot study.

OBJECTIVES: This study aimed to investigate sleep patterns in adolescent males over a 12-week period (a 10-week school term and pre and post term holidays). DESIGN: Intensive longitudinal design, with sleep data collected daily via actigraphy for 81 consecutive days. SETTING: Five Secondary Schools in Adelaide, South Australia. PARTICIPANTS: Convenience sample of 47 adolescent males aged 14 to 17 years. MEASUREMENTS: Daily sleep duration, bedtimes, rise times, and sleep efficiency were collected via actigraphy with all (except sleep efficiency) also measured by sleep diary. Mood was measured weekly with Depression Anxiety Stress Scale-21 (DASS-21) and weekly wellbeing with the Satisfaction with Life Scale (SWLS). Age, body mass index, self-reported mood, life satisfaction, and chronotype preference assessed at baseline (pre-term holiday week) were included as covariates. RESULTS: Dynamic Structural Equation Modeling indicated significant but small fixed-effect and random-effect auto-regressions for all sleep variables. Collectively, these findings demonstrate day-to-day fluctuations in sleep patterns, the magnitude of which varied between individuals. Age, morningness, and mood predicted some of the temporal dynamics in sleep over time but other factors (BMI, life satisfaction) were not associated with sleep dynamics. CONCLUSIONS: Using intensive longitudinal data, this study demonstrated inter-individual and intra-individual variation in sleep patterns over 81 consecutive days. These findings provide important and novel insights into the nature of adolescent sleep and require further examination in future studies.

Relationships between older adults' use of time and cardio-respiratory fitness, obesity and cardio-metabolic risk: A compositional isotemporal substitution analysis.

OBJECTIVE: Older adults' health has been linked with time in moderate-to-vigorous physical activity (MVPA), and recent studies suggest time in sedentary behaviour may also be important. Time-use behaviours (MVPA, light physical activity, sedentary time and sleep) are co-dependent, and therefore their associations with health should be examined in an integrated manner. This is the first study to investigate the relationship between older adults' reallocation of time among these time-use behaviours and markers of cardio-respiratory fitness, obesity and cardio-metabolic risk. STUDY DESIGN: Cross-sectional study of 122 Australians (65 ±â€¯3 y, 61% female). MAIN OUTCOME MEASURES: Daily time use: average daily minutes spent in MVPA, light physical activity, sedentary time and sleep derived from 24-h, 7-day accelerometry, were conceptualised as a time-use composition. Cardio-respiratory fitness: graded submaximal cycle ergometer test. Obesity: objectively measured body mass index (BMI) and waist-to-hip ratio (WHR). Cardio-metabolic risk: sphygmomanometer-measured resting blood pressure and fingertip blood sampling for fasting total cholesterol and glucose. RESULTS: Time-use composition was significantly associated with obesity markers (BMI, p = 0.001; WHR, p < 0.001). The reallocation of 15 min to MVPA from any of the other behaviours was associated with approximately +1.1 (95% confidence interval 0.2; 1.9) ml/kg-1 min-1 VO2max, -0.7 (-1.0; -0.3) BMI units and -1.2 (-1.8; -0.7) WHR percentage points, while the opposite reallocation (15 min from MVPA to other behaviours) was associated with larger difference estimates of -1.8 (-3.2; -0.4) ml/kg-1 min-1 VO2max, +1.2 (0.5; 1.9) BMI units and +2.1 (1.2; 3.1) WHR percentage points. CONCLUSION: These findings reinforce the importance of MVPA for health among older adults. Interventions to maintain MVPA, even without increasing it, may be valuable.

Inequality in physical activity, sedentary behaviour, sleep duration and risk of obesity in children: a 12-country study.

OBJECTIVE: Studies examining associations between movement behaviours (i.e. physical activity, sedentary behaviour and sleep duration) and obesity focus on average values of these movement behaviours, despite important within-country and between-country variability. A better understanding of movement behaviour inequalities is important for developing public health policies and behaviour-change interventions. The objective of this ecologic analysis at the country level was to determine if inequality in movement behaviours is a better correlate of obesity than average movement behaviour volume in children from all inhabited continents of the world. METHODS: This multinational, cross-sectional study included 6,128 children 9-11 years of age. Moderate-to-vigorous physical activity (MVPA), total sedentary time (SED) and sleep period time were monitored over 7 consecutive days using waist-worn accelerometry. Screen time was self-reported. Inequality in movement behaviours was determined using Gini coefficients (ranging from 0 [complete equality] to 1 [complete inequality]). RESULTS: The largest inequality in movement behaviours was observed for screen time (Gini of 0.32; medium inequality), followed by MVPA (Gini of 0.21; low inequality), SED (Gini of 0.07; low inequality) and sleep period time (Gini of 0.05; low inequality). Average MVPA (h d-1) was a better correlate of obesity than MVPA inequality (r = -0.77 vs. r = 0.00, p = 0.03). Average SED (h d-1) was also a better correlate of obesity than SED inequality (r = 0.52 vs. r = -0.32, p = 0.05). Differences in associations for screen time and sleep period time were not statistically significant. MVPA in girls was found to be disproportionally lower in countries with more MVPA inequality. CONCLUSIONS: Findings from this study show that average MVPA and SED should continue to be used in population health studies of children as they are better correlates of obesity than inequality in these behaviours. Moreover, the findings suggest that MVPA inequality could be greatly reduced through increases in girls' MVPA alone.

Thresholds of physical activity associated with obesity by level of sedentary behaviour in children.

BACKGROUND: It is unknown whether moderate-to-vigorous physical activity (MVPA) thresholds for obesity should be adapted depending on level of sedentary behaviour in children. OBJECTIVE: The objective of the study is to determine the MVPA thresholds that best discriminate between obese and non-obese children, by level of screen time and total sedentary time in 12 countries. METHODS: This multinational, cross-sectional study included 6522 children 9-11 years of age. MVPA and sedentary time were assessed using waist-worn accelerometry, while screen time was self-reported. Obesity was defined according to the World Health Organization reference data. RESULTS: Receiver operating characteristic curve analyses showed that the best thresholds of MVPA to predict obesity ranged from 53.8 to 73.9 min d-1 in boys and from 41.7 to 58.7 min d-1 in girls, depending on the level of screen time. The MVPA cut-offs to predict obesity ranged from 37.9 to 75.9 min d-1 in boys and from 32.5 to 62.7 min d-1 in girls, depending on the level of sedentary behaviour. The areas under the curve ranged from 0.57 to 0.73 ('fail' to 'fair' accuracy), and most sensitivity and specificity values were below 85%, similar to MVPA alone. Country-specific analyses provided similar findings. CONCLUSIONS: The addition of sedentary behaviour levels to MVPA did not result in a better predictive ability to classify children as obese/non-obese compared with MVPA alone.

The adiposity of children is associated with their lifestyle behaviours: a cluster analysis of school-aged children from 12 nations.

BACKGROUND: The relationship between children's adiposity and lifestyle behaviour patterns is an area of growing interest. OBJECTIVES: The objectives of this study are to identify clusters of children based on lifestyle behaviours and compare children's adiposity among clusters. METHODS: Cross-sectional data from the International Study of Childhood Obesity, Lifestyle and the Environment were used. PARTICIPANTS: the participants were children (9-11 years) from 12 nations (n = 5710). MEASURES: 24-h accelerometry and self-reported diet and screen time were clustering input variables. Objectively measured adiposity indicators were waist-to-height ratio, percent body fat and body mass index z-scores. ANALYSIS: sex-stratified analyses were performed on the global sample and repeated on a site-wise basis. Cluster analysis (using isometric log ratios for compositional data) was used to identify common lifestyle behaviour patterns. Site representation and adiposity were compared across clusters using linear models. RESULTS: Four clusters emerged: (1) Junk Food Screenies, (2) Actives, (3) Sitters and (4) All-Rounders. Countries were represented differently among clusters. Chinese children were over-represented in Sitters and Colombian children in Actives. Adiposity varied across clusters, being highest in Sitters and lowest in Actives. CONCLUSIONS: Children from different sites clustered into groups of similar lifestyle behaviours. Cluster membership was linked with differing adiposity. Findings support the implementation of activity interventions in all countries, targeting both physical activity and sedentary time.