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OBJECTIVE: This study aimed to examine the prevalence of adolescent active travel to school (ATS) across 31 countries and territories in Asia, overall and by age group, sex and body mass index (BMI) category. DESIGN: Cross-sectional study. SETTING: 31 Asian countries. PARTICIPANTS: 152 368 adolescents aged 13-17 years with complete data for age, sex, measured weight and height and active travel to school from 31 Asian countries from the Global School-based student Health Survey (GSHS). PRIMARY OUTCOME: Self-reported active travel to school categorised into passive (0 days) and active (1-7 days). RESULTS: Overall prevalence of adolescent ATS in Asia based on random-effect meta-analysis was 55%, ranging from 18% (UAE) to 84% (Myanmar). There was limited subregional variation: 47% in the Eastern Mediterranean (EM), 56% in the South East Asia and 64% in the Western Pacific. Summarised by random-effect meta-analysis, being an older adolescent aged 16 years and older (vs younger age below 16 years: OR: 1.08; 95% CI: 1.00 to 1.16) was positively associated with ATS. This association was strongest in EM countries. Summarised by random-effect meta-analysis, females (vs males: OR: 0.79; 95% CI: 0.71 to 0.89) and adolescents with overweight/obesity (vs underweight and normal BMI: OR: 0.92; 95% CI: 0.86 to 0.99) were less likely to use ATS. Association with sex was strongest in EM countries. Heterogeneity was considerable in all meta-analyses. CONCLUSION: The prevalence of adolescent ATS in Asia varies substantially. Overall, older and male adolescents, and adolescents with underweight and normal BMI category are more likely to actively travel to school. However, the main contributor to differences in ATS between and within regions remain unknown. Although there is substantial scope for improving ATS rates in Asia, any policy actions and interventions should be cognisant of local built, social and natural environmental contexts that may influence active travel behaviour. ; RM's doctoral study is supported by Indonesia Endowment Fund for Education (201908220815174). EMFvS and EI are supported by the Medical Research Council [grant number MC_UU_00006/5]. TO is supported by the National Institute for Health Research (NIHR) (16/137/34) using UK aid from the UK Government to support global health research.

Creating an environment capable of responding to its users and organizations in real‐time is a challenging task. However, with the advent of the Internet of Things (IoT) ecosystem, a new perspective about creating an intelligent and interconnected world has become a reality. The goal of the present study aims to explore the relationship between IoT and Knowledge Management (KM) when generating a Smart environment. Herein, we conducted a Systematic Literature Review and present a discussion about the evolution of the IoT concept and the IoT ecosystem. More specifically we focused on the main IoT elements that serve as the foundation of the IoT ecosystem and the relationship between the IoT and KM. Although there is a lack of studies about KM supporting the IoT, our study provides evidence that the IoT is composed of a set of technologies that enable KM and KM processes can facilitate the development of IoT Smart environments. Thus, there is an opportunity to study how to generate more intelligence and connectivity, which will support the players of the ecosystem, promote interactions among objects and people and ultimately add value to organizations and users.

BACKGROUND: Physical activity (PA) declines during childhood. Important sources of PA are active travel, organised sport and physical education (PE), but it is unclear how these domain-specific PA sources contribute to (changes in) daily moderate-to-vigorous PA (MVPA) in young people. This study aimed to examine (1) the cross-sectional association between domain-specific physical activity (i.e., active travel, organised sport and PE) and daily minutes in accelerometer-assessed MVPA; and (2) the longitudinal association between domain-specific physical activity at baseline and change in daily minutes in MVPA. METHODS: Participants (baseline age 11.3 ± .1.2 years) were drawn from three studies in the International Children's Accelerometry Database. The contribution of self-reported standardised active travel, organised sport and PE to accelerometer-measured daily minutes in MVPA was examined using linear regression. In cross-sectional analyses, MVPA was regressed on each PA domain in separate models, adjusted for study, age, sex, maternal education, season, and monitor wear time. In longitudinal analyses, change in MVPA was regressed on each of the baseline PA domains, additionally adjusting for changes in season and wear time, follow-up duration, and baseline MVPA. R-squared was used to compare variance explained by each PA domain. RESULTS: In the cross-sectional analyses (n = 3871), organised sport (standardised β = 3.81, 95% confidence interval [95%CI] = 3.06, 4.56) and active travel (β = 3.46, 95%CI = 2.73, 4.19) contributed more to daily MVPA than PE (β = 0.82, 95%CI = -0.02, 1.66). Compared to the base model which included only covariates (R2 = 21.5%), organised sport (absolute change: + 1.9%) and active travel (+ 1.7%) models explained more of the variance than the PE model (± < 0.1%). Associations followed a similar pattern in the longitudinal analyses (n = 2302), but none of the PA domains predicted change in MVPA (organised sport: standardised β = 0.85, 95%CI = -0.03, 1.72; active travel: β = 0.68, 95%CI = -0.14, 1.50; PE: β = 0.02, 95%CI = -0.87, 0.91). CONCLUSIONS: A multi-sectoral approach covering a wide range of PA domains should be promoted to minimise the age-related decline in MVPA during childhood. ; The ICAD data pooling project and SPEEDY study for the collection of data were funded through grants from the National Prevention Research Initiative (Grant Numbers: G0501294; G0701877) (http://www.mrc.ac.uk/research/initiatives/national-prevention-research-initiative-npri/). The funding partners relevant to this award and role of the funding (i.e., data pooling and collection) are: British Heart Foundation; Cancer Research UK; Department of Health; Diabetes UK; Economic and Social Research Council; Medical Research Council; Research and Development Office for the Northern Ireland Health and Social Services; Chief Scientist Office; Scottish Executive Health Department; The Stroke Association; Welsh Assembly Government and World Cancer Research Fund. The UK Medical Research Council and Wellcome (Grant reference: 217065/Z/19/Z) and the University of Bristol provide core support for the ALSPAC study in the collection of data. The CLAN study was supported by grants from the Financial Markets Foundation for Children and the National Health and Medical Research Council (NHMRC, ID: 274309 and 374241) for the collection of data. This work was additionally supported by the Medical Research Council (Grant numbers: MC_UU_12015/3; MC_UU_12015/6; MC_UU_12015/7), the Research Council of Norway (249932/F20), Bristol University, Loughborough University and Norwegian School of Sport Sciences for the harmonisation of data in the ICAD project. EvS and EI are supported by the Medical Research Council (Grant number: MC_UU_00006/5) in the design of the study, analysis and interpretation of data, and in writing the manuscript. The funding sources had no role in the design of this study, neither during its execution, analyses, interpretation of the data, or decision to submit results.

Background: There is increasing recognition of the need for more comprehensive surveillance data, including information on physical activity of all intensities, sedentary behavior, and sleep. However, meeting this need poses significant challenges for current surveillance systems, which are mainly reliant on self-report. Objective: The primary objective of this project is to develop and evaluate the feasibility of a sensor-based system for use in the surveillance of physical activity, sedentary behavior, and sleep (SurPASS) at a national level in Denmark. Methods: The SurPASS project involves an international, multidisciplinary team of researchers collaborating with an industrial partner. The SurPASS system consists of (1) a thigh-worn accelerometer with Bluetooth connectivity, (2) a smartphone app, (3) an integrated back end, facilitating the automated upload, analysis, storage, and provision of individualized feedback in a manner compliant with European Union regulations on data privacy, and (4) an administrator web interface (web application) to monitor progress. The system development and evaluation will be performed in 3 phases. These phases will include gathering user input and specifications (phase 1), the iterative development, evaluation, and refinement of the system (phase 2), and the feasibility evaluation (phase 3). Results: The project started in September 2020 and completed phase 2 in February 2022. Phase 3 began in March 2022 and results will be made available in 2023. Conclusions: If feasible, the SurPASS system could be a catalyst toward large-scale, sensor-based surveillance of physical activity, sedentary behavior, and sleep. It could also be adapted for cohort and interventional research, thus contributing to the generation of evidence for both interventions and public health policies and recommendations. International Registered Report Identifier (IRRID): DERR1-10.2196/35697

INTRODUCTION: New Zealand children's physical activity, including independent mobility and active travel, has declined markedly over recent decades. The Neighbourhoods for Active Kids (NfAK) study examines how neighbourhood built environments are associated with the independent mobility, active travel, physical activity and neighbourhood experiences of children aged 9-12 years in primary and intermediate schools across Auckland, New Zealand's largest city. METHODS AND ANALYSIS: Child-specific indices of walkability, destination accessibility and traffic exposure will be constructed to measure the built environment in 8 neighbourhoods in Auckland. Interactive online-mapping software will be used to measure children's independent mobility and transport mode to destinations and to derive measures of neighbourhood use and perceptions. Physical activity will be measured using 7-day accelerometry. Height, weight and waist circumference will be objectively measured. Parent telephone interviews will collect sociodemographic information and parent neighbourhood perceptions. Interviews with school representative will capture supports and barriers for healthy activity and nutrition behaviours at the school level. Multilevel modelling approaches will be used to understand how differing built environment variables are associated with activity, neighbourhood experiences and health outcomes. DISCUSSION: We anticipate that children who reside in neighbourhoods considered highly walkable will be more physically active, accumulate more independent mobility and active travel, and be more likely to have a healthy body size. This research is timely as cities throughout New Zealand develop and implement plans to improve the liveability of intensifying urban neighbourhoods. Results will be disseminated to participants, local government agencies and through conventional academic avenues.

Introduction New Zealand children's physical activity, including independent mobility and active travel, has declined markedly over recent decades. The Neighbourhoods for Active Kids (NfAK) study examines how neighbourhood built environments are associated with the independent mobility, active travel, physical activity and neighbourhood experiences of children aged 9–12 years in primary and intermediate schools across Auckland, New Zealand's largest city. Methods and analysis Child-specific indices of walkability, destination accessibility and traffic exposure will be constructed to measure the built environment in 8 neighbourhoods in Auckland. Interactive online-mapping software will be used to measure children's independent mobility and transport mode to destinations and to derive measures of neighbourhood use and perceptions. Physical activity will be measured using 7-day accelerometry. Height, weight and waist circumference will be objectively measured. Parent telephone interviews will collect sociodemographic information and parent neighbourhood perceptions. Interviews with school representative will capture supports and barriers for healthy activity and nutrition behaviours at the school level. Multilevel modelling approaches will be used to understand how differing built environment variables are associated with activity, neighbourhood experiences and health outcomes. Discussion We anticipate that children who reside in neighbourhoods considered highly walkable will be more physically active, accumulate more independent mobility and active travel, and be more likely to have a healthy body size. This research is timely as cities throughout New Zealand develop and implement plans to improve the liveability of intensifying urban neighbourhoods. Results will be disseminated to participants, local government agencies and through conventional academic avenues. ; Peer reviewed