Socioeconomic disadvantage and polygenic risk for high BMI magnify obesity risk across childhood: a longitudinal, population, cohort study.

BACKGROUND: Across the life course, socioeconomic disadvantage disproportionately afflicts those with genetic predispositions to inflammatory diseases. We describe how socioeconomic disadvantage and polygenic risk for high BMI magnify the risk of obesity across childhood, and using causal analyses, explore the hypothetical impact of intervening on socioeconomic disadvantage to reduce adolescent obesity. METHODS: Data were drawn from a nationally representative Australian birth cohort, with biennial data collection between 2004 and 2018 (research and ethics committee approved). We generated a polygenic risk score for BMI using published genome-wide association studies. We measured early-childhood disadvantage (age 2-3 years) with a neighbourhood census-based measure and a family-level composite of parent income, occupation, and education. We used generalised linear regression (Poisson-log link) to estimate the risk of overweight or obesity (BMI ≥85th percentile) at age 14-15 years for children with early-childhood disadvantage (quintiles 4-5) versus average (quintile 3) and least disadvantage (quintiles 1-2), for those with high and low polygenic risk separately. FINDINGS: For 1607 children (n=796 female, n=811 male; 31% of the original cohort [N=5107]), polygenic risk and disadvantage were both associated with overweight or obesity; effects of disadvantage were more marked as polygenic risk increased. Of children with polygenic risk higher than the median (n=805), 37% of children living in disadvantage at age 2-3 years had an overweight or obese BMI by adolescence, compared with 26% of those with least disadvantage. For genetically vulnerable children, causal analyses indicated that early neighbourhood intervention to lessen disadvantage (to quintile 1-2) would reduce risk of adolescent overweight or obesity by 23% (risk ratio 0·77; 95% CI 0·57-1·04); estimates for improving family environments were similar (0·59; 0·43-0·80). INTERPRETATION: Actions addressing socioeconomic disadvantage could mitigate polygenic risk for developing obesity. This study benefits from population-representative longitudinal data but is limited by sample size. FUNDING: Australian National Health and Medical Research Council.

Insights into adolescent well-being from computerised analysis of written language.

AIM: To examine associations between patterns of language use and early adolescent well-being. METHODS: Participants were 1763 Australian 11- to 12-year-olds in the Child Health CheckPoint. Six patterns of language use were identified from a writing activity using Linguistic Inquiry and Word Count and factor analysis: Acting in the present and future, Positive emotion, Gender and relationships, Self-aware, Inquisitive and time focused, and Confident. Well-being measures represented a spectrum from negatively to positively framed psychosocial health. Associations between language use and well-being were estimated using linear regression adjusted for age, sex and social disadvantage. RESULTS: Positive emotion (high emotional tone, positive emotion) was associated with better general well-being (standardised regression coefficient (SRC) 0.05; 95% confidence interval 0.00 to 0.11; p = 0.04), life satisfaction (0.06; 0.01 to 0.11; p = 0.03), psychosocial health (0.07; 0.02 to 0.12; p = 0.01) and quality of life (QoL) (0.06; 0.01 to 0.11; p = 0.02). Similarly, Self-aware (high first person singular pronouns, authentic, low clout) was associated with better general well-being, life satisfaction and psychosocial health (SRC 0.05, 0.09, 0.08), but Confident (high clout, first person plural pronouns, affiliation) was associated with worse life satisfaction, psychosocial health and QoL (SRC -0.06, -0.09, -0.06). CONCLUSION: If replicated in 'real-world' settings (e.g., social media), language patterns could provide naturalistic insights into early adolescents' well-being.

A Social Networking and Gamified App to Increase Physical Activity: Cluster RCT.

INTRODUCTION: Appealing approaches to increasing physical activity levels are needed. This study evaluated whether a social and gamified smartphone app (Active Team) could be one such approach. STUDY DESIGN: A 3-group cluster RCT compared the efficacy of Active Team with a basic self-monitoring app and waitlist control group. SETTING/PARTICIPANTS: Australian adults (N=444, mean age of 41 years, 74% female) were recruited in teams (n=121) and randomly assigned (1:1:1) to the Active Team (n=141, 39 teams), self-monitoring app (n=160, 42 teams), or waitlist group (n=143, 40 teams). Data were collected in 2016-2017, and analysis was conducted in 2018-2019. INTERVENTION: Active Team is a 100-day app-based, gamified, online social networking physical activity intervention. MAIN OUTCOME MEASURES: The primary outcome was change in objective physical activity from baseline to 3-month follow-up. Secondary outcomes included objective physical activity at 9 months and self-reported physical activity, quality of life, depression, anxiety and stress, well-being, and engagement. RESULTS: Mixed models indicated no significant differences in objective physical activity between groups at 3 (F=0.17, p=0.84; Cohen's d=0.03, 95% CI= -0.21, 0.26) or 9 months (F=0.23, p=0.92; d=0.06, 95% CI= -0.17, 0.29) and no significant differences for secondary outcomes of quality of life, depression, anxiety and stress, or well-being. Self-reported moderate-to-vigorous physical activity was significantly higher in the Active Team group at the 9-month follow-up (F=3.05, p=0.02; d=0.50, 95% CI=0.26, 0.73). Engagement was high; the Active Team group logged steps on an average of 72 (SD=35) days and used the social and gamified features an average of 89 (SD=118) times. CONCLUSIONS: A gamified, online social networking physical activity intervention did not change objective moderate-to-vigorous physical activity, though it did increase self-reported moderate-to-vigorous physical activity and achieve high levels of engagement. Future work is needed to understand if gamification, online social networks, and app-based approaches can be leveraged to achieve positive behavior change. TRIAL REGISTRATION: This study is registered at Australian and New Zealand Clinical Trial Registry (protocol: ANZCTR12617000113358).

Child and adult snack food intake in response to manipulated pre-packaged snack item quantity/variety and snack box size: a population-based randomized trial.

OBJECTIVES: Snacks contribute to overconsumption of energy-dense foods and thence obesity. Previous studies in this area are limited by self-reported data and small samples. In a large population-based cohort of parent-child dyads, we investigated how modification of pre-packaged snack food, i.e. (a) item quantity and variety, and (b) dishware (boxed container) size affected intake. METHODS: Design: Randomized trial nested within the cross-sectional Child Health CheckPoint of the Longitudinal Study of Australian Children, clustered by day of visit. SAMPLE: 1299 11-12 year olds, 1274 parents. EXPOSURE: 2 × 2 manipulation of snack box container size and item quantity/variety: (1) small box, few items, (2) large box, few items, (3) small box, more items, (4) large box, more items. PROCEDURE: Participants received a snack box during a 15 min break within their 3.5 h visit; any snacks remaining were weighed. OUTCOMES: Consumed quantity (grams) and energy intake (kilojoules). ANALYSES: Unadjusted linear regression. RESULTS: Children who were offered a greater quantity and variety of snack items consumed considerably more energy and a slightly higher food mass (main effect for energy intake: 349 kJ, 95% CI 282-416, standardized mean difference (effect size) 0.66; main effect for mass: 10 g, 95% CI 3-17, effect size 0.17). In contrast, manipulating box size had little effect on child consumption, and neither box size nor quantity/variety of items consistently affected adults' consumption. CONCLUSION: In children, reducing the number and variety of snack food items available may be a more fruitful intervention than focusing on container or dishware size. Effects observed among adults were small, although we could not exclude social desirability bias in adults aware of observation.

A source of systematic bias in self-reported physical activity: The cutpoint bias hypothesis.

OBJECTIVES: Estimates of adults' moderate-to-vigorous physical activity (MVPA) based on self-report are generally higher than estimates derived from criterion measures. This study examines a possible explanation for part of this discrepancy: the cutpoint bias hypothesis. This hypothesis proposes that inter- and intra-individual variability in energy expenditure, combined with the fact that adults perform a high proportion of daily activities at or just above the traditional 3 MET cutpoint, result in systematic over-estimates of MVPA. DESIGN: Cross-sectional. METHODS: Time-use recalls (n = 6862) were collected using the Multimedia Activity Recall for Children and Adults from 2210 adults (1215 female, age 16-93 years) from 16 studies conducted in Australia and New Zealand between 2008-2017. Minutes spent in MVPA were estimated using models with varying levels of intra- and inter-individual (total variability) Unadjusted (0% total variability), Low (11.9%), Best Guess (20.7%), and High (30.0%). RESULTS: In the Unadjusted model, participants accumulated an average of 129 (standard deviation 127) min/day of MVPA. Estimated MVPA was 98 (110), 99 (107) and 108 (107) min/day in the Low, Best Guess and High variability models, respectively, with intra-class correlation coefficients with the Unadjusted model ranging from 0.78 to 0.83. CONCLUSIONS: These findings support the hypothesis of a cutpoint bias, which probably contributes to the large disparities seen between self-reported and criterion measures of MVPA. Future studies are needed to confirm these findings using other self-report instruments and in other populations.

Converting between estimates of moderate-to-vigorous physical activity derived from raw accelerations measured at the wrist and from ActiGraph counts measured at the hip: the Rosetta Stone.

The ability to compare published group-level estimates of objectively measured moderate-to-vigorous physical activity (MVPA) across studies continues to increase in difficulty. The objective of this study was to develop conversion equations and demonstrate their utility to compare estimates of MVPA derived from the wrist and hip. Three studies of youth (N = 232, 9-12yrs, 50% boys) concurrently wore a hip-worn ActiGraph and a wrist-worn GENEActiv for 7-days. ActiGraph hip count data were reduced using four established cutpoints. Wrist accelerations were reduced using the Hildebrand MVPA 200 mg threshold. Conversion equations were developed on a randomly selected subsample of 132 youth. Equations were cross-validated and absolute error, absolute percent error, and modified Bland-Altman plots were evaluated for conversion accuracy. Across equations R2adj was 0.51-0.56 with individual-level absolute error in minutes ranging from 7 (wrist-to-hip Puyau) to 14.5 minutes (wrist-to-hip Freedson 3MET) and absolute percent differences ranging from 13.9%-24.5%. Group-level cross-validation to convert hip-to-wrist MVPA resulted in average absolute percent errors ranging from 3.1%-4.9%. Conversion of wrist-to-hip MVPA resulted in average absolute percent errors ranging from 3.0%-10.0%. We recommend the use of these equations to compare published estimates of MVPA between the wear-site cut-point combinations presented.

Accelerometer wear-site detection: When one site does not suit all, all of the time.

OBJECTIVES: Choice of accelerometer wear-site may facilitate greater compliance in research studies. We aimed to test whether a simple method could automatically discriminate whether an accelerometer was worn on the hip or wrist from free-living data. DESIGN: Cross-sectional. METHODS: Twenty-two 10-12y old children wore a GENEActiv at the wrist and at the hip for 7-days. The angle between the forearm and the total acceleration vector for the wrist-worn monitor and between the pelvis and the total acceleration vector for the hip-worn monitor (i.e. the angle between the Y-axis component of the acceleration and the total acceleration vector) was calculated for each 5s epoch. The standard deviation of this angle (SDangle) was calculated over time for the wrist-worn and hip-worn monitor for windows of varying lengths. We hypothesised that the wrist angle would be more variable than the hip angle. RESULTS: Wear site could be discriminated based on SDangle; the shorter the time window the lower the optimal threshold and Area under the Receiver-Operating-Characteristic curve (AUROC) for discrimination of wear-site (AUROC=0.833 (1min) - 0.952 (12h)). Classification accuracy was good for windows of 8min (sensitivity=90%, specificity=87%, AUROC=0.92) and plateaued for windows of ≥60min (sensitivity and specificity >90%, AUROC=0.95-0.96). CONCLUSIONS: We have presented a robust, computationally simple method that detects whether an accelerometer is being worn on the hip or wrist from 8 to 60min of data. This facilitates the use of wear-site specific algorithms to analyse accelerometer data.

Everybody's working for the weekend: changes in enjoyment of everyday activities across the retirement threshold.

BACKGROUND: the aim of this study was to explore the associations between use of time and momentary hedonic affect ('enjoyment') in adults in the peri-retirement period. METHODS: a total of 124 adults [61 males, 63 females; age 62 (4) years] completed a computerised use-of-time recall on 4 days at each of four time points (3-6 months pre-, 3, 6 and 12 months post-retirement), as well as surveys regarding self-reported health, well-being, sleep quality and loneliness. They reported how much they enjoyed each activity on a 0-10 scale. An individual Enjoyment Index was calculated as the time-weighted average of each participant's enjoyment ratings. Time-weighted enjoyment ratings were also calculated for nine mutually exclusive and exhaustive activity domains (Sleep, Chores, Work, Social, Screen Time, Self-care, Quiet Time, Transport, Physical Activity) and sub-domains. RESULTS: the mean (±SD) Enjoyment Index was 7.43 ± 0.61, and was significantly and positively associated with well-being (P = 0.003 to P < 0.0001) and sleep quality (P = 0.03 to P < 0.0001), and negatively associated with loneliness (P = 0.003 to P < 0.0001). Mean Enjoyment Index values increased significantly (P < 0.0001) from pre-retirement (7.19 ± 0.82) to post-retirement (7.46 ± 0.89, 7.42 ± 0.91 and 7.49 ± 0.89 at 3, 6 and 12 months post-retirement). There were significant differences in enjoyment across domains, with Physical Activity (7.86 ± 1.11) and Social (7.66 ± 0.85) being the most enjoyable, and Work (7.10 ± 0.89) and Chores (7.09 ± 0.85) the least enjoyable. CONCLUSION: enjoyment of everyday activities increased after retirement and remained elevated for at least 12 months. Work appears to constitute a relative hedonic deficit.

Moving Forward with Backward Compatibility: Translating Wrist Accelerometer Data.

PURPOSE: This study aimed to provide a means for calibrating raw acceleration data from wrist-worn accelerometers in relation to past estimates of children's moderate-to-vigorous physical activity (MVPA) from a range of cut points applied to hip-worn ActiGraph data. METHODS: This is a secondary analysis of three studies with concurrent 7-d accelerometer wear at the wrist (GENEActiv) and hip (ActiGraph) in 238 children age 9-12 yr. The time spent above acceleration (ENMO) thresholds of 100, 150, 200, 250, 300, 350, and 400 mg from wrist acceleration data (≤5-s epoch) was calculated for comparison with MVPA estimated from widely used children's hip-worn ActiGraph MVPA cut points (Freedson/Trost, 1100 counts per minute; Pate, 1680 counts per minute; Evenson, 2296 counts per minute; Puyau, 3200 counts per minute) with epochs of ≤5, 15, and 60 s. RESULTS: The optimal ENMO thresholds for alignment with MVPA estimates from ActiGraph cut points determined from 70% of the sample and cross validated with the remaining 30% were as follows: Freedson/Trost = ENMO 150+ mg, irrespective of ActiGraph epoch (intraclass correlation [ICC] ≥ 0.65); Pate = ENMO 200+ mg, irrespective of ActiGraph epoch (ICC ≥ 0.67); Evenson = ENMO 250+ mg for ≤5- and 15-s epochs (ICC ≥ 0.69) and ENMO 300+ mg for 60-s epochs (ICC = 0.73); Puyau = ENMO 300+ mg for ≤5-s epochs (ICC = 0.73), ENMO 350+ mg for 15-s epochs (ICC = 0.73), and ENMO 400+ mg for 60-s epochs (ICC = 0.65). Agreement was robust with cross-validation ICC = 0.62-0.71 and means within ∣7.8∣% ± 4.9% of MVPA estimates from ActiGraph cut points, except Puyau 60-s epochs (ICC = 0.42). CONCLUSION: Incremental ENMO thresholds enable children's acceleration data measured at the wrist to be simply and directly compared, at a group level, with past estimates of MVPA from hip-worn ActiGraphs across a range of cut points.

Wrist-Worn Accelerometer-Brand Independent Posture Classification.

INTRODUCTION: Access to raw acceleration data should facilitate comparisons between accelerometer outputs regardless of monitor brand. PURPOSE: To evaluate the accuracy of posture classification using the Sedentary Sphere in data from two widely used wrist-worn triaxial accelerometers. METHODS: Laboratory: Thirty-four adults wore a GENEActiv and an ActiGraph GT3X+ on their nondominant wrist while performing four lying, seven sitting, and five upright activities. Free-living: The same participants wore both accelerometers on their nondominant wrist and an activPAL3 on their right thigh during waking hours for 2 d. RESULTS: Laboratory: Using the Sedentary Sphere with 15-s epoch GENEActiv data, sedentary and upright postures were correctly identified 74% and 91% of the time, respectively. Corresponding values for the ActiGraph data were 75% and 90%. Free-living: Total sedentary time was estimated at 534 ± 144, 523 ± 143, and 528 ± 137 min by the activPAL, the Sedentary Sphere with GENEActiv data and with ActiGraph data, respectively. The mean bias, relative to the activPAL, was small with moderate limits of agreement (LoA) for both the GENEActiv (mean bias = -12.5 min, LoA = -117 to 92 min) and ActiGraph (mean bias = -8 min, LoA = -103 to 88 min). Strong intraclass correlations (ICC) were evident for the activPAL with the GENEActiv (0.93, 0.84-0.97 (95% confidence interval) and the ActiGraph (0.94, 0.86-0.97). Agreement between the GENEActiv and ActiGraph posture classifications was very high (ICC = 0.98 (0.94-0.99), mean bias = +3 min, LoA = -58 to 63 min). CONCLUSIONS: These data support the efficacy of the Sedentary Sphere for classification of posture from a wrist-worn accelerometer in adults. The approach is equally valid with data from both the GENEActiv and ActiGraph accelerometers.

Multiple components of fitness improved among overweight and obese adolescents following a community-based lifestyle intervention.

Fitness is an important component of health, and obese adolescents regularly have poor fitness. Unfortunately, few have assessed the impact of community-based lifestyle interventions on multiple components of fitness. The purpose of this study was to assess the impact of participation in a community-based intervention involving adolescents and parents on multiple components of fitness of obese adolescents. In a within-subject, waitlist controlled clinical trial with 12 months follow-up in Western Australia, participants (n = 56) completed multiple fitness measures at baseline, immediately prior to beginning an 8-week intervention and at 3, 6 and 12 months during a maintenance period. Performance on the shuttle walk was improved immediately post-intervention (increase of 42.8 m, 95% CI: 7.5, 78.2) and at 12 months post-intervention (increase of 44.6 m, 95% CI: 1.3, 87.8) compared with pre-intervention. Muscle performance of quadriceps and deltoids were improved post-intervention (increase of 1.1 (95% CI: 0.1, 2.1) kg · F and 1.0 (0.02, 2.1) kg · F, respectively) and all muscle performance measures were improved at 12 months following the intervention. There were no changes in waist circumference. A community-based lifestyle programme such as Curtin University's Activity, Food and Attitudes Program (CAFAP) may be a viable strategy for improving fitness in overweight adolescents.

The Canadian Assessment of Physical Literacy: Development of a Model of Children's Capacity for a Healthy, Active Lifestyle Through a Delphi Process.

BACKGROUND: The Canadian Assessment of Physical Literacy (CAPL) was conceptualized as a tool to monitor children's physical literacy. The original model (fitness, activity behavior, knowledge, motor skill) required revision and relative weights for calculating/interpreting scores were required. METHODS: Nineteen childhood physical activity/fitness experts completed a 3-round Delphi process. Round 1 was open-ended questions. Subsequent rounds rated statements using a 5-point Likert scale. Recommendations were sought regarding protocol inclusion, relative importance within composite scores and score interpretation. RESULTS: Delphi participant consensus was achieved for 64% (47/73) of statement topics, including a revised conceptual model, specific assessment protocols, the importance of longitudinal tracking, and the relative importance of individual protocols and composite scores. Divergent opinions remained regarding the inclusion of sleep time, assessment/ scoring of the obstacle course assessment of motor skill, and the need for an overall physical literacy classification. CONCLUSIONS: The revised CAPL model (overlapping domains of physical competence, motivation, and knowledge, encompassed by daily behavior) is appropriate for monitoring the physical literacy of children aged 8 to 12 years. Objectively measured domains (daily behavior, physical competence) have higher relative importance. The interpretation of CAPL results should be reevaluated as more data become available.

Sedentary Behavior in People with and without a Chronic Health Condition: How Much, What and When?

PURPOSE: To describe sedentary behaviors (duration, bouts and context) in people with and without a chronic health condition. METHODS: Design: Secondary analysis of two cross-sectional studies. Participants: People with stable chronic obstructive pulmonary disease (COPD) (n = 24, male:female 18:6) and their spousal carers (n = 24, 6:18); stroke survivors (n = 24, 16:8) and age- and sex-matched healthy adults (n = 19, 11:8). Level of physiological impairment was measured with post-bronchodilator spirometry (FEV1 %predicted) for people with COPD, and walking speed for people with stroke. Outcomes: Participants were monitored over seven days (triaxial accelerometer, Sensewear armband) to obtain objective data on daily sedentary time, and prolonged sedentary bouts (≥ 30 min). During the monitoring period, a 24-hour use of time recall instrument was administered by telephone interview to explore the context of sedentary activities (e.g. television, computer or reading). Sedentary time was quantified using accelerometry and recall data, and group differences were explored. Linear regression examined associations between physiological impairment and sedentary time. RESULTS: Participant groups were similar in terms of age (COPD 75 ± 8, carers 70 ± 11, stroke 69 ± 10, healthy 73 ± 7 years) and body mass index (COPD 28 ± 4, carers 27 ± 4, stroke 31 ± 4, healthy 26 ± 4 kg.m-2). The healthy group had the lowest sedentary time (45% of waking hours), followed by the carer (54%), stroke (60%) and COPD (62%) groups (p < 0.0001). Level of physiological impairment was an independent predictor of waking sedentary time (p = 0.001). CONCLUSIONS: People with a chronic health condition spent more time sedentary than those without a chronic condition, and there were small but clear differences between groups in the types of activities undertaken during sedentary periods. The study findings may aid in the design of targeted interventions to decrease sedentary time in people with chronic health conditions.

In search of lost time: When people undertake a new exercise program, where does the time come from? A randomized controlled trial.

OBJECTIVES: The objective of this study was to investigate changes in use of time when undertaking a structured exercise program. DESIGN: This study used a randomized, multi-arm, controlled trial design. METHODS: A total of 129 insufficiently active adults aged 18-60 years were recruited and randomly allocated to one of three groups, a Moderate or Extensive six-week exercise group (150 and 300 additional minutes of exercise per week, respectively) or a Control group. Prescribed exercise was accumulated through both group and individual sessions. Use of time was measured at baseline and end-program using the Multimedia Activity Recall for Children and Adults, a computerized 24-h recall instrument. Daily minutes of activity in activity domains and energy expenditure zones were determined. RESULTS: Relative to changes in the control group, daily time spent in the physical activity [F (2, 108)=20.21, p<0.001] and Active Transport [F (2, 108)=3.71, p=0.03] time use domains significantly increased in the intervention groups by 21-45 min/day. Comparatively, the intervention groups spent significantly less time watching television [F (2, 108)=5.02, p=0.008; -50-52 min/day], relative to Controls. Additionally, time spent in the moderate to vigorous energy expenditure zone had significantly increased in the intervention groups by end-program [F (2, 108)=6.35, p=0.002; 48-50 min/day], relative to Controls. CONCLUSIONS: This study is the first to comprehensively map changes in time use across an exercise program. The results suggest that exercise interventions should be mindful not only of compliance but also of "isotemporal displacement" of behaviors.

Comparability of measured acceleration from accelerometry-based activity monitors.

BACKGROUND: Accelerometers that provide triaxial measured acceleration data are now available. However, equivalence of output between brands cannot be assumed and testing is necessary to determine whether features of the acceleration signal are interchangeable. PURPOSE: This study aimed to establish the equivalence of output between two brands of monitor in a laboratory and in a free-living environment. METHODS: For part 1, 38 adults performed nine laboratory-based activities while wearing an ActiGraph GT3X+ and GENEActiv (Gravity Estimator of Normal Everyday Activity) at the hip. For part 2, 58 children age 10-12 yr wore a GT3X+ and GENEActiv at the hip for 7 d in a free-living setting. RESULTS: For part 1, the magnitude of time domain features from the GENEActiv was greater than that from the GT3X+. However, frequency domain features compared well, with perfect agreement of the dominant frequency for 97%-100% of participants for most activities. For part 2, mean daily acceleration measured by the two brands was correlated (r = 0.93, P < 0.001, respectively) but the magnitude was approximately 15% lower for the GT3X+ than that for the GENEActiv at the hip. CONCLUSIONS: Frequency domain-based classification algorithms should be transferable between monitors, and it should be possible to apply time domain-based classification algorithms developed for one device to the other by applying an affine conversion on the measured acceleration values. The strong relation between accelerations measured by the two brands suggests that habitual activity level and activity patterns assessed by the GENE and GT3X+ may compare well if analyzed appropriately.

Introducing novel approaches for examining the variability of individuals' physical activity.

Tudor-Locke and colleagues previously assessed steps/day for 1 year. The aim of this study was to use this data set to introduce a novel approach for the investigation of whether individual's physical activity exhibits periodicity fluctuating round a mean and, if so, the degree of fluctuation and whether the mean changes over time. Twenty-three participants wore a pedometer for 365 days, recorded steps/day and whether the day was a workday. Fourier transform of each participant's daily steps data showed the physical activity had a periodicity of 7 days in half of the participants, matching the periodicity of the workday pattern. Activity level remained stable in half of the participants, decreased in ten participants and increased in two. In conclusion, the 7-day periodicity of activity in half of the participants and correspondence with the workday pattern suggest a social or environmental influence. The novel analytical approach introduced herein allows the determination of the periodicity of activity, the degree of variability in activity that is tolerated during day-to-day life and whether the activity level is stable. Results from the use of these methodologies in larger data sets may enable a more focused approach to the design of interventions that aim to increase activity.

Use of time in people with chronic obstructive pulmonary disease--a systematic review.

"Physical inactivity" and "sedentary lifestyles" are phrases often used when describing lifestyles of people with chronic obstructive pulmonary disease (COPD). Evidence suggests activity types, independent of energy expenditure, influence health outcomes, so understanding patterns of time use is important, particularly in chronic disease. We aimed to identify reports of time use in people with COPD. Predefined search strategies were used with six electronic databases to identify individual activity reports (including frequencies and/or durations) in which community-dwelling people with COPD engaged. Eligible studies were assessed independently against predefined criteria and data were extracted by two reviewers. Data synthesis was achieved by aggregating activity reports into activity domains (sports/exercise, screen time, transport, quiet time, self-care, sociocultural, work/study, chores, and sleep). Twenty-six publications reported 37 specific daily activities. People with COPD were found to spend extended periods in sedentary behaviors (eg, standing [194 min/day]; sitting [359 min/day]; lying [88 min/day]), have limited engagement in physical activity (eg, walking [51 min/day]; exercising [1.2 episodes per week {ep/w}, 13 min/day]), have high health care needs (medical appointments [1.0 ep/w]), and experience difficulties associated with activities of daily living (eg, showering [2.5 ep/w, 60 minutes per episode]; preparing meals [4.7 ep/w]). Little data could be found describing how people with COPD use their time, and data synthesis was problematic because of variations in methodologies, population differences, and research emphases. Identified data largely referred to posture and were skewed according to country, assessment methods, and disease severity. Comparisons with age-matched population data showed people with COPD spent less time engaged in personal-care activities (self-care and sleeping) and chores than people in similar age groups. The incorporation of time-use outcomes in future research designs should be encouraged. Ideally, these tools should use consistent frameworks and comparable outcome measures in order to provide clearer descriptions of time use in chronic disease.

The impact of Curtin University's activity, food and attitudes program on physical activity, sedentary time and fruit, vegetable and junk food consumption among overweight and obese adolescents: a waitlist controlled trial.

BACKGROUND: To determine the effects of participation in Curtin University's Activity, Food and Attitudes Program (CAFAP), a community-based, family-centered behavioural intervention, on the physical activity, sedentary time, and healthy eating behaviours of overweight and obese adolescents. METHODS: In this waitlist controlled clinical trial in Western Australia, adolescents (n = 69, 71% female, mean age 14.1 (SD 1.6) years) and parents completed an 8-week intervention followed by 12 months of telephone and text message support. Assessments were completed at baseline, before beginning the intervention, immediately following the intervention, and at 3-, 6-, and 12- months follow-up. The primary outcomes were physical activity and sedentary time assessed by accelerometers and servings of fruit, vegetables and junk food assessed by 3-day food records. RESULTS: During the intensive 8-week intervention sedentary time decreased by -5.1 min/day/month (95% CI: -11.0, 0.8) which was significantly greater than the rate of change during the waitlist period (p = .014). Moderate physical activity increased by 1.8 min/day/month (95% CI: -0.04, 3.6) during the intervention period, which was significantly greater than the rate of change during the waitlist period (p = .041). Fruit consumption increased during the intervention period (monthly incidence rate ratio (IRR) 1.3, 95% CI: 1.10, 1.56) and junk food consumption decreased (monthly IRR 0.8, 95% CI: 0.74, 0.94) and these changes were different to those seen during the waitlist period (p = .004 and p = .020 respectively). CONCLUSIONS: Participating in CAFAP appeared to have a positive influence on the physical activity, sedentary and healthy eating behaviours of overweight and obese adolescents and many of these changes were maintained for one year following the intensive intervention. TRIAL REGISTRATION: Australia and New Zealand Clinical Trials Registry ACTRN12611001187932.

Children's physical activity assessed with wrist- and hip-worn accelerometers.

BACKGROUND: Recently, triaxial raw acceleration accelerometers have become available from GENEActiv and ActiGraph; both are designed for wrist and hip wear. It is important to determine whether the output from these monitors is comparable with the wealth of data already collected from the hip-worn, epoch-based, uniaxial ActiGraph. PURPOSE: This study aimed to assess the concurrent validity of measures of total activity and time spent at different activity intensities from the GENEActiv relative to the ActiGraph GT3X+. METHODS: Fifty-eight children age 10-12 yr wore two accelerometers at the hip (ActiGraph GT3X+ and GENEActiv) and one at the wrist (GENEActiv) for 7 d. Wear time was matched for all monitors before analysis. RESULTS: Mean daily accelerometer output, time spent sedentary, and time in moderate-to-vigorous physical activity (MVPA) from the hip- or wrist-worn GENEActiv were strongly correlated with the corresponding output from the hip-worn ActiGraph (r > 0.83, P < 0.001). However, less time was estimated to be sedentary and more time was estimated to be MVPA using the hip- or wrist-worn GENEActiv (Phillips cut points) than that when using the Evenson vertical axis cut points with the hip-worn ActiGraph. Output from the vertical axis ActiGraph cut points could be predicted with 95% limits of agreement, equating to 23%-28% and 33%-35% of the mean value, by the hip- and wrist-worn GENEActiv, respectively. CONCLUSIONS: The assessment of children's activity level, time spent sedentary, and time in MVPA estimated from the hip- or wrist-worn GENEActiv seems to be comparable with that of the uniaxial ActiGraph. On the basis of the strong linear correlations, ActiGraph output can be predicted from the hip- or wrist-worn GENEActiv for comparative purposes at the group level. However, because of relatively wide limits of agreement, individual-level comparisons are not recommended.

Validating the multimedia activity recall for children and adolescents in a large New Zealand sample.

The aim of the study was to validate the self-report Multimedia Activity Recall for Children and Adolescents (MARCA) against accelerometry for the assessment of physical activity in New Zealand children. Participants (n = 716, 10-18 years) recalled 3-4 days of activity using the MARCA and underwent a partially overlapping 7-day accelerometry protocol during a national survey. Spearman correlation coefficients (ρ) assessed the association between accelerometer-derived counts per minute and MARCA-derived physical activity level and time in locomotion. Both data sources estimated time spent in light and moderate-vigorous physical activity. Association and agreement between methods for light physical activity and moderate-vigorous physical activity was assessed using correlations and Bland-Altman plots respectively, and paired t-tests conducted. Accelerometer-derived activity counts were moderately correlated with both MARCA-derived physical activity level and locomotion (ρ = 0.38, P < 0.0001). The correlation between methods was -0.14 for light physical activity and 0.28 for moderate-vigorous physical activity (P < 0.0001). The MARCA overestimated moderate-vigorous physical activity compared with accelerometry (120 min, P < 0.0001), which increased as moderate-vigorous physical activity time increased. Some sex and ethnicity (Maori [indigenous] versus non-Maori) differences were observed. Overall, the MARCA indicated moderate validity for assessment of physical activity level, locomotion and moderate-vigorous physical activity and poor validity for assessment of light physical activity. This was comparable to other self-report tools. The MARCA has utility for future large-scale research.