Patterns of physical activity and sedentary behavior in child and adolescent cancer survivors assessed using wrist accelerometry: A cluster analysis approach.

Physical activity levels among childhood cancer survivors are typically quantified as a total amount using time spent in various intensities. Yet, most analyses do not consider the transitory nature of children's behaviors and a more detailed approach could provide complimentary information. We aimed to explore various behavior profiles of survivors' daily and hourly physical activity patterns. We measured 8-18-year-old survivors' activity levels over 7 days using wrist accelerometry and cluster analysis. Of the 37 participant datasets, survivors engaged in mean (SD) 36.3 (19.0) min/day of MVPA and 4.1 (1.9) hrs/day of sedentary activity. The cluster analysis revealed five daily movement patterns: 'most active' (prevalence 11%), 'active' (22%), 'moderately active + moderately sedentary' (35%), 'moderately active + high sedentary' (5%) and 'least active' (27%). Younger survivors and those with less time since treatment completion were more likely to be in the active clusters. Hourly behaviors were characterized by short bursts of MVPA and moderate bouts of sedentary activity. Our approach provides an insightful analysis into the nature and timing of childhood cancer survivors' movement behaviours. Our findings may assist in the development of targeted interventions to improve physical activity levels.

Mining Sensor Data to Assess Changes in Physical Activity Behaviors in Health Interventions: Systematic Review.

BACKGROUND: Sensors are increasingly used in health interventions to unobtrusively and continuously capture participants' physical activity in free-living conditions. The rich granularity of sensor data offers great potential for analyzing patterns and changes in physical activity behaviors. The use of specialized machine learning and data mining techniques to detect, extract, and analyze these patterns has increased, helping to better understand how participants' physical activity evolves. OBJECTIVE: The aim of this systematic review was to identify and present the various data mining techniques employed to analyze changes in physical activity behaviors from sensors-derived data in health education and health promotion intervention studies. We addressed two main research questions: (1) What are the current techniques used for mining physical activity sensor data to detect behavior changes in health education or health promotion contexts? (2) What are the challenges and opportunities in mining physical activity sensor data for detecting physical activity behavior changes? METHODS: The systematic review was performed in May 2021 using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We queried the Association for Computing Machinery (ACM), IEEE Xplore, ProQuest, Scopus, Web of Science, Education Resources Information Center (ERIC), and Springer literature databases for peer-reviewed references related to wearable machine learning to detect physical activity changes in health education. A total of 4388 references were initially retrieved from the databases. After removing duplicates and screening titles and abstracts, 285 references were subjected to full-text review, resulting in 19 articles included for analysis. RESULTS: All studies used accelerometers, sometimes in combination with another sensor (37%). Data were collected over a period ranging from 4 days to 1 year (median 10 weeks) from a cohort size ranging between 10 and 11615 (median 74). Data preprocessing was mainly carried out using proprietary software, generally resulting in step counts and time spent in physical activity aggregated predominantly at the daily or minute level. The main features used as input for the data mining models were descriptive statistics of the preprocessed data. The most common data mining methods were classifiers, clusters, and decision-making algorithms, and these focused on personalization (58%) and analysis of physical activity behaviors (42%). CONCLUSIONS: Mining sensor data offers great opportunities to analyze physical activity behavior changes, build models to better detect and interpret behavior changes, and allow for personalized feedback and support for participants, especially where larger sample sizes and longer recording times are available. Exploring different data aggregation levels can help detect subtle and sustained behavior changes. However, the literature suggests that there is still work remaining to improve the transparency, explicitness, and standardization of the data preprocessing and mining processes to establish best practices and make the detection methods easier to understand, scrutinize, and reproduce.

Unsupervised Early Detection of Physical Activity Behaviour Changes from Wearable Accelerometer Data.

Wearable accelerometers record physical activity with high resolution, potentially capturing the rich details of behaviour changes and habits. Detecting these changes as they emerge is valuable information for any strategy that promotes physical activity and teaches healthy behaviours or habits. Indeed, this offers the opportunity to provide timely feedback and to tailor programmes to each participant's needs, thus helping to promote the adherence to and the effectiveness of the intervention. This article presents and illustrates U-BEHAVED, an unsupervised algorithm that periodically scans step data streamed from activity trackers to detect physical activity behaviour changes to assess whether they may become habitual patterns. Using rolling time windows, current behaviours are compared with recent previous ones, identifying any significant change. If sustained over time, these new behaviours are classified as potentially new habits. We validated this detection algorithm using a physical activity tracker step dataset (N = 12,798) from 79 users. The algorithm detected 80% of behaviour changes of at least 400 steps within the same hour in users with low variability in physical activity, and of 1600 steps in those with high variability. Based on a threshold cadence of approximately 100 steps per minute for standard walking pace, this number of steps would suggest approximately 4 and 16 min of physical activity at moderate-to-vigorous intensity, respectively. The detection rate for new habits was 80% with a minimum threshold of 500 or 1600 steps within the same hour in users with low or high variability, respectively.

iEngage: A digital health education program designed to enhance physical activity in young adolescents.

iEngage is a modular health education and behavioural change program designed to help adolescents increase moderate to vigorous physical activity (MVPA). The program is delivered through the iEngage app which integrates activity trackers data (Misfit Ray©) within 10 interactive learning modules. Key features include guidance to set goals, self-monitor and assess achievements, and experiential learning via the connected activity trackers which allows for continuous steps recording during the program. iEngage was implemented in two schools over 5 weeks with 10-12 years old adolescents (n = 57) and PA outcomes compared to control group (n = 26). Results show that adolescents successfully set goals and self-assessed achievements during the program, progressing toward higher physical activity (PA) levels as shown by the 30% increase in daily steps through the program (+ 2647 steps/day, P < .001) with boys increasing goals and achievements faster than girls. The consistency in days totalling at least 11,000 steps/day increased from 35% at the start to 48% at the end of the program. The increase in PA is confirmed through the assessment of MVPA during schooldays pre- and post- program via research grade wrist accelerometers in both iEngage and control participants. Contrasting with the control group, MVPA was increased in the week following the program (~+5 min/day, P = .023) in short bouts, particularly during lunch time, recess and after school. This study shows that a digital program integrating activity trackers data, health education, goals setting and self-monitoring of PA, helped young adolescents enhance PA goals, improve achievements and increase MVPA.

The Contribution of Nutrients of Concern to the Diets of 18-to-30-Year-Old Australians from Food Prepared Outside Home Differs by Food Outlet Types: The MYMeals Cross-Sectional Study.

Young adults are frequent consumers of food prepared outside the home (FOH). In a cross-sectional survey, the MYMeals study, we showed FOH provided one-third of meals and snacks for young Australian adults, yet it contributed higher proportions of energy and nutrients of concern, such as saturated fat and sodium. This study aimed to determine the detailed proportional contribution of nutrients of concern from the nine food outlet types captured in the MYMeals study. Young adults residing in New South Wales (NSW), Australia, (n = 1001) used a validated smartphone app to report all types and amounts of food and beverages consumed for three consecutive days, as well as their preparation location. The proportions of daily energy, macronutrients, sodium, total sugars, and saturated fat were calculated for each of the nine following outlet types: bakeries or patisseries, coffee chains, cold-drink chains, fast-food chains, ice creamery or frozen yoghurt outlets, independent cafes or restaurants, pubs (hotels) and clubs, service stations or convenience stores, and others not fitting the above categories. Of all FOH outlet types, independent cafes or restaurants contributed the most energy (17.5%), sodium (20.0%) and saturated fat (17.8%) to the total diet, followed by fast-food chains (12.0% energy, 15.8% sodium, and 12.0% saturated fat) and other outlets, with smaller proportions. For males, the proportion of energy and nutrients contributed by fast-food outlets was higher than for females (14.8% versus 9.8% energy). Menu labelling at independent cafes and restaurants is recommended, comprising, in addition to the energy labels already in use in fast-food restaurants, the labelling of nutrients of concern. The feasibility of this recommendation warrants further exploration.

A Digital Educational Intervention With Wearable Activity Trackers to Support Health Behaviors Among Childhood Cancer Survivors: Pilot Feasibility and Acceptability Study.

BACKGROUND: Childhood cancer survivors are at increased risk of cardiometabolic complications that are exacerbated by poor health behaviors. Critically, many survivors do not meet physical activity guidelines. OBJECTIVE: The primary aim was to evaluate the feasibility and acceptability of iBounce, a digital health intervention for educating and engaging survivors in physical activity. Our secondary aims were to assess the change in survivors' physical activity levels and behaviors, aerobic fitness, and health-related quality of life (HRQoL) after participating in the iBounce program. METHODS: We recruited survivors aged 8 to 13 years who were ≥12 months post cancer treatment completion. The app-based program involved 10 educational modules, goal setting, and home-based physical activities monitored using an activity tracker. We assessed objective physical activity levels and behaviors using cluster analysis, aerobic fitness, and HRQoL at baseline and after the intervention (week 12). Parents were trained to reassess aerobic fitness at home at follow-up (week 24). RESULTS: In total, 30 participants opted in, of whom 27 (90%) completed baseline assessments, and 23 (77%) commenced iBounce. Our opt-in rate was 59% (30/51), and most (19/23, 83%) of the survivors completed the intervention. More than half (13/23, 57%) of the survivors completed all 10 modules (median 10, IQR 4-10). We achieved a high retention rate (19/27, 70%) and activity tracker compliance (15/19, 79%), and there were no intervention-related adverse events. Survivors reported high satisfaction with iBounce (median enjoyment score 75%; ease-of-use score 86%), but lower satisfaction with the activity tracker (median enjoyment score 60%). Parents reported the program activities to be acceptable (median score 70%), and their overall satisfaction was 60%, potentially because of technological difficulties that resulted in the program becoming disjointed. We did not observe any significant changes in physical activity levels or HRQoL at week 12. Our subgroup analysis for changes in physical activity behaviors in participants (n=11) revealed five cluster groups: most active, active, moderately active, occasionally active, and least active. Of these 11 survivors, 3 (27%) moved to a more active cluster group, highlighting their engagement in more frequent and sustained bouts of moderate-to-vigorous physical activity; 6 (56%) stayed in the same cluster; and 2 (18%) moved to a less active cluster. The survivors' mean aerobic fitness percentiles increased after completing iBounce (change +17, 95% CI 1.7-32.1; P=.03) but not at follow-up (P=.39). CONCLUSIONS: We demonstrated iBounce to be feasible for delivery and acceptable among survivors, despite some technical difficulties. The distance-delivered format provides an opportunity to engage survivors in physical activity at home and may address barriers to care, particularly for regional or remote families. We will use these pilot findings to evaluate an updated version of iBounce. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12621000259842; https://anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=ACTRN12621000259842.

The Contribution of Foods Prepared Outside the Home to the Diets of 18- to 30-Year-Old Australians: The MYMeals Study.

Young adults are the highest consumers of food prepared outside home (FOH) and gain most weight among Australian adults. One strategy to address the obesogenic food environment is menu labelling legislation whereby outlets with >20 stores in one state and >50 Australia-wide must display energy content in kJ. The aim of this study was to assess the contribution of FOH to the energy and macronutrients, saturated fat, total sugars and sodium intakes of young Australians. One thousand and one 18 to 30-year-olds (57% female) residing in Australia's most populous state recorded all foods and beverages consumed and the location of preparation for three consecutive days using a purpose-designed smartphone application. Group means for the daily consumption of energy, percentage energy (%E) for protein, carbohydrate, total sugars, total and saturated fats, and sodium density (mg/1000 kJ) and proportions of nutrients from FOH from menu labelling and independent outlets were compared. Overall, participants consumed 42.4% of their energy intake from FOH with other nutrients ranging from 39.8% (sugars) to 47.3% (sodium). Independent outlets not required to label menus, contributed a greater percentage of energy (23.6%) than menu labelling outlets (18.7%, p < 0.001). Public health policy responses such as public education campaigns, extended menu labelling, more detailed nutrition information and reformulation targets are suggested to facilitate healthier choices.

Body image, body dissatisfaction and weight status of Pacific adolescents from different ethnic communities: a cross-sectional study in New Caledonia.

Objective(s): The prevalence of adolescent obesity is high among the various ethnic groups native to the Pacific region (European, Melanesian and Polynesian). An important factor of weight gain or loss is body size satisfaction; however, little is known about adolescent body self-perception in the Pacific region.Design: Body dissatisfaction was evaluated using the Stunkard Figure Rating Scale in a sample of 699 adolescents from rural and urban areas of New Caledonia. The socio-demographic factors associated with higher body dissatisfaction were determined by multiple linear regression modeling.Results: Our results showed a high rate of body dissatisfaction (over 70%) in the adolescents. Body dissatisfaction was strongly related to the body mass index z-score. Melanesians boys had higher body dissatisfaction scores when they felt 'too thin' while Melanesian girls showed lower body dissatisfaction when they felt 'too fat.'.Conclusion: These results showed that social pressure for thinness or musculature may be different among adolescents living in New Caledonia. These results should be taken into account in education overweight prevention programs.

Improving Pacific Adolescents' Physical Activity Toward International Recommendations: Exploratory Study of a Digital Education App Coupled With Activity Trackers.

BACKGROUND: The prevalence of overweight and obesity in children and adolescents has dramatically increased in the Pacific Island countries and territories over the last decade. Childhood overweight and obesity not only have short-term consequences but are also likely to lead to noncommunicable diseases in adulthood. A major factor contributing to the rising prevalence is an insufficient amount of daily moderate-to-vigorous physical activity (MVPA). In the Pacific region, less than 50% of children and adolescents meet the international recommendations of 11,000 steps and 60 min of MVPA per day. Although studies have shown the potential of digital technologies to change behaviors, none has been proposed to guide adolescents toward achieving these recommendations. OBJECTIVE: The aims of this study were (1) to investigate whether a technology-based educational program that combines education, objective measures of physical activity (PA), and self-assessment of goal achievement would be well received by Pacific adolescents and help change their PA behaviors toward the international PA recommendations and (2) to create more insightful data analysis methods to better understand PA behavior change. METHODS: A total of 24 adolescents, aged 12 to 14 years, participated in a 4-week program comprising 8 1-hour modules designed to develop health literacy and physical skills. This self-paced user-centered program was delivered via an app and provided health-related learning content as well as goal setting and self-assessment tasks. PA performed during the 4-week program was captured by an activity tracker to support learning and help the adolescents self-assess their achievements against personal goals. The data were analyzed using a consistency rate and daily behavior clustering to reveal any PA changes, particularly regarding adherence to international recommendations. RESULTS: The consistency rate of daily steps revealed that the adolescents reached 11,000 steps per day 48% (approximately 3.4 days per week) of the time in the first week of the program, and this peaked at 59% (approximately 4.1 days per week) toward the end of the program. PA data showed an overall increase during the program, particularly in the less active adolescents, who increased their daily steps by 15% and ultimately reached 11,000 steps more frequently. The consistency of daily behavior clustering showed a 27% increase in adherence to international recommendations in the least active adolescents. CONCLUSIONS: Technology-supported educational programs that include self-monitored PA via activity trackers can be successfully delivered to adolescents in schools in remote Pacific areas. New data mining techniques enable innovative analyses of PA engagement based on the international recommendations.

Nutrition behaviors and sociodemographic factors associated with overweight in the multi-ethnic adolescents of New Caledonia.

Objectives: New Caledonia is a multi-ethnic French territory in the Pacific, characterized by communities with widely varying nutritional habits. Little is currently known about adolescent food behaviors and habits and their association with overweight. This study therefore determined the sociodemographic factors and food behaviors associated with overweight and underweight in this population, as well as the factors associated with skipping breakfast. Methods: A cross-sectional survey was conducted among New Caledonian adolescents using a self-administered questionnaire; anthropometric measurements were also taken. Weight status was determined using international cutoffs, and the factors associated with overweight and underweight were identified with multiple logistic regression analysis. The factors associated with breakfast skipping were also determined. Results: Skipping breakfast, being Melanesian, living in a rural area and having low economic status were positively associated with overweight in these adolescents. Skipping breakfast was relatively infrequent, reported by 18% and 13% of the males and females, respectively. Logistic regression models found that the main factors associated with breakfast consumption habits were gender, weight status and ethnicity. Conclusions: Several factors are associated with overweight status in New Caledonian adolescents. Breakfast education should be improved for adolescents living in rural areas and from low socioeconomic status.

Examining the Frequency and Contribution of Foods Eaten Away From Home in the Diets of 18- to 30-Year-Old Australians Using Smartphone Dietary Assessment (MYMeals): Protocol for a Cross-Sectional Study.

BACKGROUND: Young Australians aged between 18 and 30 years have experienced the largest increase in the body mass index and spend the largest proportion of their food budget on fast food and eating out. Frequent consumption of foods purchased and eaten away from home has been linked to poorer diet quality and weight gain. There has been no Australian research regarding quantities, type, or the frequency of consumption of food prepared outside the home by young adults and its impact on their energy and nutrient intakes. OBJECTIVES: The objective of this study was to determine the relative contributions of different food outlets (eg, fast food chain, independent takeaway food store, coffee shop, etc) to the overall food and beverage intake of young adults; to assess the extent to which food and beverages consumed away from home contribute to young adults' total energy and deleterious nutrient intakes; and to study social and physical environmental interactions with consumption patterns of young adults. METHODS: A cross-sectional study of 1008 young adults will be conducted. Individuals are eligible to participate if they: (1) are aged between 18 and 30 years; (2) reside in New South Wales, Australia; (3) own or have access to a smartphone; (4) are English-literate; and (5) consume at least one meal, snack, or drink purchased outside the home per week. An even spread of gender, age groups (18 to 24 years and 25 to 30 years), metropolitan or regional geographical areas, and high and low socioeconomic status areas will be included. Participants will record all food and drink consumed over 3 consecutive days, together with location purchased and consumed in our customized smartphone app named Eat and Track (EaT). Participants will then complete an extensive demographics questionnaire. Mean intakes of energy, nutrients, and food groups will be calculated along with the relative contribution of foods purchased and eaten away from home. A subsample of 19.84% (200/1008) of the participants will complete three 24-hour recall interviews to compare with the data collected using EaT. Data mining techniques such as clustering, decision trees, neural networks, and support vector machines will be used to build predictive models and identify important patterns. RESULTS: Recruitment is underway, and results will be available in 2018. CONCLUSIONS: The contribution of foods prepared away from home, in terms of energy, nutrients, deleterious nutrients, and food groups to young people's diets will be determined, as will the impact on meeting national recommendations. Foods and consumption behaviors that should be targeted in future health promotion efforts for young adults will be identified.

Misperception of weight status in the pacific: preliminary findings in rural and urban 11- to 16-year-olds of New Caledonia.

BACKGROUND: Adolescent obesity is prevalent in Pacific region ethnic groups (European, Melanesian and Polynesian) living in both urban and rural areas. Although body perception is an important factor of weight gain or loss, little is known about the body self-perceptions of Pacific region adolescents. This study therefore evaluated adolescent perceptions of body weight according to ethnicity (European, Melanesian or Polynesian), socioeconomic status (low, intermediate or high) and living area (rural or urban) in New Caledonia. METHODS: Sociodemographic and anthropomorphic data from 737 adolescents (351 boys and 386 girls) with ages ranging from 11 to 16 years were collected and analysed. The International Obesity Task Force (IOTF) standards were used to define weight status as normal-weight, underweight or overweight/obese. Weight perception was assessed from detailed questionnaires, with adolescents rating their own weight with the following descriptors: 'about the right weight', 'too heavy', or 'too light'. RESULTS: Results showed that only 8.5% of normal-weight adolescents (7% boys and 10% girls) identifying themselves as 'too heavy'. Normal-weight Melanesian adolescents were less likely than their European counterparts to assess themselves as too heavy (OR = 0.357). However, half the overweight/obese adolescents underestimated their weight status (53% boys and 48% girls). Weight misperception was associated with ethnicity, socioeconomic status and living area, with gender-specific differences. CONCLUSIONS: The results of this study suggest that these sociodemographic factors should be taken into account when designing public health policies and health education school programmes in New Caledonia and, more broadly, the Pacific region.