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.

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.

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.

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.

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.

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.

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.

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.

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.

Mid-upper arm circumference as a screening tool for identifying children with obesity: a 12-country study.

BACKGROUND: No studies have examined if mid-upper arm circumference (MUAC) can be an alternative screening tool for obesity in an international sample of children differing widely in levels of human development. OBJECTIVE: Our aim is to determine whether MUAC could be used to identify obesity in children from 12 countries in five major geographic regions of the world. METHODS: This observational, multinational cross-sectional study included 7337 children aged 9-11 years. Anthropometric measurements were objectively assessed, and obesity was defined according to the World Health Organization reference data. RESULTS: In the total sample, MUAC was strongly correlated with adiposity indicators in both boys and girls (r > 0.86, p < 0.001). The accuracy level of MUAC for identifying obesity was high in both sexes and across study sites (overall area under the curve of 0.97, sensitivity of 95% and specificity of 90%). The MUAC cut-off value to identify obesity was ~25 cm for both boys and girls. In country-specific analyses, the cut-off value to identify obesity ranged from 23.2 cm (boys in South Africa) to 26.2 cm (girls in the UK). CONCLUSIONS: Results from this 12-country study suggest that MUAC is a simple and accurate measurement that may be used to identify obesity in children aged 9-11 years. MUAC may be a promising screening tool for obesity in resource-limited settings.

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.

Small Steps: Preliminary effectiveness and feasibility of an incremental goal-setting intervention to reduce sitting time in older adults.

OBJECTIVE: This study aimed to evaluate the preliminary effectiveness and feasibility of a theory-informed program to reduce sitting time in older adults. DESIGN: Pre-experimental (pre-post) study. Thirty non-working adult (≥ 60 years) participants attended a one hour face-to-face intervention session and were guided through: a review of their sitting time; normative feedback on sitting time; and setting goals to reduce total sitting time and bouts of prolonged sitting. Participants chose six goals and integrated one per week incrementally for six weeks. Participants received weekly phone calls. OUTCOME MEASURES: Sitting time and bouts of prolonged sitting (≥ 30 min) were measured objectively for seven days (activPAL3c inclinometer) pre- and post-intervention. During these periods, a 24-h time recall instrument was administered by computer-assisted telephone interview. Participants completed a post-intervention project evaluation questionnaire. Paired t tests with sequential Bonferroni corrections and Cohen's d effect sizes were calculated for all outcomes. RESULTS: Twenty-seven participants completed the assessments (71.7 ± 6.5 years). Post-intervention, objectively-measured total sitting time was significantly reduced by 51.5 min per day (p=0.006; d=-0.58) and number of bouts of prolonged sitting by 0.8 per day (p=0.002; d=-0.70). Objectively-measured standing increased by 39 min per day (p=0.006; d=0.58). Participants self-reported spending 96 min less per day sitting (p<0.001; d=-0.77) and 32 min less per day watching television (p=0.005; d=-0.59). Participants were highly satisfied with the program. CONCLUSION: The 'Small Steps' program is a feasible and promising avenue for behavioral modification to reduce sitting time in older adults.

Active school transport and weekday physical activity in 9-11-year-old children from 12 countries.

OBJECTIVES: Active school transport (AST) may increase the time that children spend in physical activity (PA). This study examined relationships between AST and weekday moderate-to-vigorous physical activity (MVPA), light physical activity (LPA), sedentary time (SED) and total activity during naturally organized time periods (daily, before school, during school and after school) in a sample of children from 12 countries. METHODS: The sample included 6224 children aged 9-11 years. PA and sedentary time were objectively measured using Actigraph accelerometers. AST was self-reported by participants. Multilevel generalized linear and logistic regression statistical models were used to determine associations between PA, SED and AST across and within study sites. RESULTS: After adjustment for age, highest parental educational attainment, BMI z-score and accelerometer wear time, children who engaged in AST accumulated significantly more weekday MVPA during all studied time periods and significantly less time in LPA before school compared with children who used motorized transport to school. AST was unrelated to time spent in sedentary behaviors. Across all study sites, AST was associated with 6.0 min (95% confidence interval (CI): 4.7-7.3; P<0.0001) more of weekday MVPA; however, there was some evidence that this differed across study sites (P for interaction=0.06). Significant positive associations were identified within 7 of 12 study sites, with differences ranging from 4.6 min (95% CI: 0.3-8.9; P=0.04, in Canada) to 10.2 min (95% CI: 5.9-14.4; P<0.0001, in Brazil) more of daily MVPA among children who engaged in AST compared with motorized transport. CONCLUSIONS: The present study demonstrated that AST was associated with children spending more time engaged in MVPA throughout the day and less time in LPA before school. AST represents a good behavioral target to increase levels of PA in children.

Relationships between active school transport and adiposity indicators in school-age children from low-, middle- and high-income countries.

OBJECTIVES: Within the global context of the nutrition and physical activity transition it is important to determine the relationship between adiposity and active school transport (AST) across different environmental and socio-cultural settings. The present study assessed the association between adiposity (that is, body mass index z-score (BMIz), obesity, percentage body fat (PBF), waist circumference) and AST in 12 country sites, in the International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE). METHODS: The analytical sample included 6797 children aged 9-11 years. Adiposity indicators included, BMIz calculated using reference data from the World Health Organization, obesity (BMIz ⩾+2 s.d.), PBF measured using bioelectrical impedance and waist circumference. School travel mode was assessed by questionnaire and categorized as active travel versus motorized travel. Multilevel linear and non-linear models were used to estimate the magnitude of the associations between adiposity indicators and AST by country site and sex. RESULTS: After adjusting for age, sex, parental education and motorized vehicle availability, children who reported AST were less likely to be obese (odds ratio=0.72, 95% confidence interval (0.60-0.87), P<0.001) and had a lower BMIz (-0.09, s.e.m.=0.04, P=0.013), PBF (least square means (LSM) 20.57 versus 21.23% difference -0.66, s.e.m.=0.22, P=0.002) and waist circumference (LSM 63.73 cm versus 64.63 cm difference -0.90, s.e.m.=0.26, P=0.001) compared with those who reported motorized travel. Overall, associations between obesity and AST did not differ by country (P=0.279) or by sex (P=0.571). CONCLUSIONS: AST was associated with lower measures of adiposity in this multinational sample of children. Such findings could inform global efforts to prevent obesity among school-age children.

An international comparison of dietary patterns in 9-11-year-old children.

OBJECTIVES: Dietary pattern is defined as a combination of foods and drinks and the frequency of consumption within a population. Dietary patterns are changing on a global level, which may be linked to an increased incidence of chronic diseases. The aim of this study was to identify and compare the dietary patterns among 9-11-year-old children living in urban regions in different parts of the world. METHODS: Participants were 7199 children (54% girls), aged 9-11 years, from 12 countries situated in all major world regions. Food consumption was assessed using a 23-item Food Frequency Questionnaire (FFQ). To identify dietary patterns, principal components analyses (PCA) were carried out using weekly portions as input variables. RESULTS: Both site-specific and pooled PCA resulted in two strong components. Component 1 ('unhealthy diet pattern') included fast foods, ice cream, fried food, French fries, potato chips, cakes and sugar-sweetened sodas with >0.6 loadings. The loadings for component 2 ('healthy diet pattern') were slightly weaker with only dark-green vegetables, orange vegetables, vegetables in general, and fruits and berries reaching a >0.6 loading. The site-specific diet pattern scores had very strong correlations with the pattern scores from the pooled data: r=0.82 and 0.94 for components 1 and 2, respectively. CONCULSIONS: The results suggest that the same 'healthier' and 'unhealthier' foods tend to be consumed in similar combinations among 9-11-year-old children in different countries, despite variation in food culture, geographical location, ethnic background and economic development.

Reliability of accelerometer-determined physical activity and sedentary behavior in school-aged children: a 12-country study.

OBJECTIVES: Focused on the accelerometer-determined physical activity and sedentary time metrics in 9-11-year-old children, we sought to determine the following: (i) number of days that are necessary to achieve reliable estimates (G⩾0.8); (ii) proportion of variance attributed to different facets (participants and days) of reliability estimates; and (iii) actual reliability of data as collected in The International Study of Childhood Obesity, Lifestyle and Environment (ISCOLE). METHODS: The analytical sample consisted of 6025 children (55% girls) from sites in 12 countries. Physical activity and sedentary time metrics measures were assessed for up to 7 consecutive days for 24 h per day with a waist-worn ActiGraph GT3X+. Generalizability theory using R software was used to investigate the objectives i and ii. Intra-class correlation coefficients (ICC) were computed using SAS PROC GLM to inform objective iii. RESULTS: The estimated minimum number of days required to achieve a reliability estimate of G⩾0.8 ranged from 5 to 9 for boys and 3 to 11 for girls for light physical activity (LPA); 5 to 9 and 3 to 10, for moderate-to-vigorous physical activity (MVPA); 5 to 10 and 4 to 10 for total activity counts; and 7 to 11 and 6 to 11 for sedentary time, respectively. For all variables investigated, the 'participant' facet accounted for 30-50% of the variability, whereas the 'days' facet accounted for ⩽5%, and the interaction (P × D) accounted for 50-70% of the variability. The actual reliability for boys in ISCOLE ranged from ICCs of 0.78 to 0.86, 0.73 to 0.85 and 0.72 to 0.86 for LPA, MVPA and total activity counts, respectively, and 0.67 to 0.79 for sedentary time. The corresponding values for girls were 0.80-0.88, 0.70-0.89, 0.74-0.86 and 0.64-0.80. CONCLUSIONS: It was rare that only 4 days from all participants would be enough to achieve desirable reliability estimates. However, asking participants to wear the device for 7 days and requiring ⩾4 days of data to include the participant in the analysis might be an appropriate approach to achieve reliable estimates for most accelerometer-derived metrics.

The epidemiological transition and the global childhood obesity epidemic.

OBJECTIVES: Childhood obesity is now recognized as a global public health issue. Social patterning of obesity, consistent with the theory of epidemiologic transition, has not been well described in children, and the limited research has focused on developed settings. The aim of this study was to describe the relationship between childhood obesity and household income using objective measures of adiposity and to explore how this relationship differs across levels of country human development. METHODS: The International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE) was a multi-national cross-sectional study conducted in 12 urban/suburban study sites that represented all inhabited continents and wide ranges of development. ISCOLE collected objectively measured height, body mass and percentage body fat in 7341 10-year-old children. Multi-level random-effects models were used to examine income gradients in several obesity measures. RESULTS: The mean age of the children was 10.4 years, and 12.6% were obese, ranging from 5.4% (Finland) to 23.8% (China). For both boys and girls, obesity prevalence, body fat percentage and body mass index (BMI) z-score increased linearly with higher income at lower levels of development (all P for trend ⩽0.0012), but decreased linearly with higher income at higher levels of development (all P for trend ⩽0.0003). Country human development explained 75% of the variation in the country-specific income-obesity relationships (r=-0.87, P=0.0003). CONCLUSIONS: Results are consistent with the theory of epidemiologic transition. Global efforts to control obesity must account for socioeconomic factors within a country's context. Future research should seek to understand global socioeconomic patterns in obesity-related lifestyle behaviors.