T S. Church’s research while affiliated with Pennington Biomedical Research Center and other places

PURPOSE: Some evidence shows greater peak oxygen uptake (VO2peak) is associated with greater resting metabolic rate, but the relationship between VO2peak and food intake has not been systematically examined using gold standard assessments of energy intake. This analysis aimed to examine the association between VO2peak and energy intake, macronutrient intake, and appetite. METHODS: In all, 198 sedentary adults with overweight or obesity (mean ± SD body mass index: 31.7 ± 4.7 kg/m2) enrolled into the Examination of Mechanisms of Exercise-induced Weight Compensation (E-MECHANIC) trial were studied. Participants completed a graded treadmill test to determine VO2peak Free-living energy intake was determined by doubly labelled water; further, food intake was assessed through laboratory-based test meals, and energy intake and percent energy consumed from macronutrients were calculated. Appetite was examined through retrospective visual analogue scales. Multiple linear regression analyses examined the association between VO2peak (L/min) and outcomes, adjusting for body composition, age, sex, and race (significance: P < 0.05). RESULTS: A positive association between VO2peak and free-living energy intake was observed (P < 0.01), with each 1 L/min increase in VO2peak associated with a 246 (95% CI: 131, 361) kcal/day increase in free-living energy intake. Energy intake (β = 73 kcal, 95% CI:-209, 356; P = 0.61), percent energy from fat (β = 0.9%, 95% CI:-1.9, 3.7; P = 0.53), and percent energy from protein (β =-0.3%, 95% CI:-2.6, 2.0; P = 0.79) at the laboratory test meals were not related to VO2peak; yet a higher VO2peak was associated with reduced percent energy from carbohydrate (β =-4.9%, 95% CI:-9.0,-0.8; P = 0.02). There was a positive association between VO2peak and prospective food consumption (β = 9 mm, 95% CI: 1, 17; P = 0.02), though other appetite constructs were not significantly related to VO2peak (P ≥ 0.15). CONCLUSION: In individuals with overweight and obesity, a higher VO2peak was associated with increased free-living energy intake, lower percent carbohydrate intake at test meals, and greater subjective prospective food consumption. Work is thus needed to examine if VO2peak influences energy intake, appetite, and eating behaviors during weight loss regimens and exercise training.

INTRODUCTION: Our primary aim was to investigate the association between initial weight change and longer-term changes in weight and compensation (predicted weight loss - observed weight loss) during exercise. As secondary aims, we investigated if initial weight change was related to change in cardiometabolic risk markers and energy balance modulators. METHODS: Two 6-month randomized controlled exercise trials conducted in individuals with overweight or obesity were analyzed (Study one: N=312; Study two: N=102). In both studies, participants in an exercise condition (4 kcals·kg-1·week-1 [KKW], 8 KKW, 12 KKW, or 20 KKW) were split into tertiles based on percent weight change from baseline to week 4. Tertiles 1 and 3 exhibited the least and most initial weight loss, respectively. Changes in endpoints were compared between tertiles. RESULTS: At month 6, weight loss was lower in tertile 1 than tertile 3 (Study one: -3.6%, 95% CI -4.6 to -2.6; Study two: -1.8%, 95% CI -3.1 to -0.4; P≤0.034). Tertile 1 also showed greater compensation than tertile 3 in studies one (3.0 kg, 95% CI 2.2 to 3.9) and two (1.5 kg, 95% CI 0.3 to 2.6; P≤0.048). Changes in triglycerides and, in study one, high-density lipoprotein cholesterol were less favorable in tertile 1 versus tertile 3 (P≤0.043); however, changes in other cardiometabolic markers were similar (P≥0.209). In study two, tertile 1 increased energy intake and exhibited maladaptive changes in eating behaviors relative to tertile 3 (P≤0.041). No between-tertile differences in cumulative exercise energy expenditure and physical activity were evident (P≥0.321). CONCLUSIONS: Less initial weight loss was associated with longer-term attenuated weight loss and greater compensation during aerobic exercise training. Individuals who display less initial weight loss during exercise may require early interventions to decrease compensation and facilitate weight loss.

Objective: To examine the joint association of birth weight and physical activity/sedentary time with childhood obesity in 12 countries. Methods: A cross-sectional study of 5,088 children aged 9 to 11 years was conducted. Birth weight was recalled by parents or guardians. Moderate-to-vigorous physical activity (MVPA) and sedentary behavior were objectively measured using accelerometry. Results: The association of birth weight with the odds of obesity, central obesity, and high body fat was significant among children with either low MVPA or high sedentary time but not among children with either high MVPA or low sedentary time. In comparison with children with normal birth weight and high MVPA, children with high birth weight and low MVPA showed 4.48- to 5.18-fold higher odds of obesity, central obesity, and high body fat; children with normal birth weight and low MVPA showed 3.00- to 3.30-fold higher odds of obesity, central obesity, and high body fat, and children with high birth weight and high MVPA showed 1.16- to 1.68-fold higher odds of obesity, central obesity, and high body fat. Conclusions: High MVPA is more important than high birth weight as a correlate of obesity in children.

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.

Objectives: Few studies have investigated the association between the full range of birth weight and the risk of childhood obesity in high-, middle- and low-income countries. The aim of the present study is to assess the association between different levels of birth weight and the risk of obesity among children aged 9-11 years in 12 countries. Methods: A multinational, cross-sectional study of 5141 children aged 9-11 years was conducted in 12 countries. Height and weight were obtained using standardized methods. Time spent in moderate-to-vigorous physical activity (MVPA), sedentary and sleeping were objectively measured using 24-h, waist-worn accelerometer (Actigraph GT3X+) monitored for 7 days. Birth weight and other factors (regions, parental education, maternal history of gestational diabetes, children age, gender, breast feeding, gestational age, unhealthy diet scores and healthy diet scores) were collected by parental and children's questionnaires. Multilevel modeling was used to account for the nested nature of the data. Results: The overall prevalence of obesity (BMI z-score>+2 s.d.) was 15.4% for boys and 10.0% for girls. There was a positive association between birth weight and BMI z-scores. The multivariable-adjusted odds ratios (ORs) of childhood obesity were significantly higher among children whose birth weights were 3500-3999 g (OR 1.45; 95% confidence interval (CI): 1.10-1.92), and >4000 g (OR 2.08; 95% CI: 1.47-2.93), compared with the reference group (2500-2999 g). The positive association between birth weight and the odds of childhood obesity was seen in girls, whereas a U-shaped association appeared in boys. Conclusions: High levels of birth weight, defined as birth weight ⩾3500 g, were associated with increased odds of obesity among 9-11-year-old children in 12 countries. However, sex differences in the association between birth weight and the risk of obesity need to be considered when planning interventions to reduce childhood obesity.

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.

Objectives: We describe the process of identifying and defining nocturnal sleep-related variables (for example, movement/non-movement indicators of sleep efficiency, waking episodes, midpoint and so on) using the unique 24-h waist-worn free-living accelerometer data collected in the International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE). Methods: Seven consecutive days of 24-h waist-worn accelerometer (GT3X+, ActiGraph LLC) data were collected from over 500 children at each site. An expert subgroup of the research team with accelerometry expertize, frontline data collectors and data managers met on several occasions to categorize and operationally define nocturnal accelerometer signal data patterns. The iterative process was informed by the raw data drawn from a sub set of the US data, and culminated in a refined and replicable delineated definition for each identified nocturnal sleep-related variable. Ultimately based on 6318 participants from all 12 ISCOLE sites with valid total sleep episode time (TSET), we report average clock times for nocturnal sleep onset, offset and midpoint in addition to sleep period time, TSET and restful sleep efficiency (among other derived variables). Results: Nocturnal sleep onset occurred at 2218 hours and nocturnal sleep offset at 0707 hours. The mean midpoint was 0243 hours. The sleep period time of 529.6 min (8.8 h) was typically accumulated in a single episode, making the average TSET very similar in duration (529.0 min). The mean restful sleep efficiency ranged from 86.8% (based on absolute non-movement of 0 counts per minute) to 96.0% (based on relative non-movement of <100 counts per minute). Conclusions: These variables extend the potential of field-based 24-h waist-worn accelerometry to distinguish and categorize the underlying robust patterns of movement/non-movement signals conveying magnitude, duration, frequency and periodicity during the nocturnal sleep period.

Objectives: The International Study of Childhood Obesity, Lifestyle and the Environment (ISCOLE) provides robust, multi-national information on physical activity, diet and weight status in 9-11-year-old children around the world. The purpose of this analysis was to examine the similarities and differences between participant characteristics from ISCOLE sites and data from nationally representative surveys from ISCOLE countries (Australia, Brazil, Canada, China, Colombia, Finland, Kenya, India, Portugal, South Africa, the United Kingdom and the United States). Methods: Distributions of characteristics were assessed within each ISCOLE country-level database, and compared with published data from national or regional surveys, where available. Variables of comparison were identified a priori and included body mass index (BMI), physical activity (accelerometer-determined steps per day) and screen time (child-report). Results: Of 12 countries, data on weight status (BMI) were available in 8 countries, data on measured physical activity (steps per day) were available in 5 countries and data on self-reported screen time were available in 9 countries. The five ISCOLE countries that were part of the Health Behaviour in School-aged Children Survey (that is, Canada, Finland, Portugal, the United Kingdom (England) and the United States) also provided comparable data on self-reported physical activity. Available country-specific data often used different measurement tools or cut-points, making direct comparisons difficult. Where possible, ISCOLE data were re-analyzed to match country-level data, but this step limited between-country comparisons. Conclusions: From the analyses performed, the ISCOLE data do not seem to be systematically biased; however, owing to limitations in data availability, data from ISCOLE should be used with appropriate caution when planning country-level population health interventions. This work highlights the need for harmonized measurement tools around the world while accounting for culturally specific characteristics, and the need for collaboration across study centers and research groups.

The purpose was to assess associations between body mass index (BMI) and body fat in a multinational sample of 9–11-year-old children. The sample included 7265 children from countries ranging in human development. Total body fat (TBF) and percentage body fat (PBF) were measured with a Tanita SC-240 scale and BMI z-scores (BMIz) and percentiles were computed using reference data from the World Health Organization and the U.S. Centers for Disease Control and Prevention, respectively. Mean PBF at BMIz values of −1, 0 and +1 were estimated using multilevel models. Correlations between BMI and TBF were >0.90 in all countries, and correlations between BMI and PBF ranged from 0.76 to 0.96. Boys from India had higher PBF than boys from several other countries at all levels of BMIz. Kenyan girls had lower levels of PBF than girls from several other countries at all levels of BMIz. Boys and girls from Colombia had higher values of PBF at BMIz=−1, whereas Colombian boys at BMIz 0 and +1 also had higher values of PBF than boys in other countries. Our results show a consistently high correlation between BMI and adiposity in children from countries representing a wide range of human development.