Levels and Correlates of Objectively Measured Sedentary Behaviour In Young Children: Sunrise Pilot Study Results from 19 Countries

Background: There is a paucity of data from low- and middle-income countries on sedentary behaviour (SB) levels and patterns during early childhood. The purpose of this study was to examine how device-measured SB in young children differed across geographically, economically, and socio-demographically diverse populations, in an international sample.Methods: This multinational, cross-sectional pilot study included data from 1071 3–5-year-old children from 19 countries, collected between 2018 and 2020 (pre-COIVID). SB was measured for three consecutive days using activPAL accelerometers. Sedentary time, sedentary fragmentation and seated transport duration were calculated using PAL Analysis Algorithms and a custom-made analysis program. Linear mixed models were used to examine the differences in SB variables between sex, country-level income groups, caregiver education levels, urban/rural settings, and population density.Findings: Children spent 56% (7.4 hrs) of their waking time sedentary, and 42% accrued at least one sedentary bout/day lasting ≥60 min. The longest average bout duration was 81.1±45.4 min, and an average of 61.1±50.1 min/day was spent in seated transport. Children from upper-middle-income and high-income countries spent a greater proportion of the day sedentary, accrued more sedentary bouts, had shorter breaks between sedentary bouts, and spent significantly more time in seated transport, than children from low- and lower-middle-income countries. Few differences were found in SB patterns between urban/rural settings and caregiver education levels within each country-level income group, while multiple significant differences were found when comparing between country-level income groups. Higher population density was correlated with several higher SB measures.Interpretation: These data advance our understanding of young children’s SB patterns globally and the influences of country income, urban/rural setting, caregiver education levels, and population density. Country income levels and population density appear to be stronger drivers of the observed differences, than sex, rural or urban residential setting or caregiver educational attainment.Funding: American Council on Exercise, USA Beijing Health System High Level Talents Training Project, China 13 Biomedical Research Foundation, Dhaka, Bangladesh Canadian Institutes of Health Research Planning and Dissemination Grant Conselho Nacional de Pesquisa e Desenvolvimento Cientıfico e Tecnologico - CNPq Research Department of National Planning and Monitoring, PNG Government Early Start, University of Wollongong, Australia Faculty of Health Sciences at the University of the Witwatersrand, Johannesburg, South Africa Global Challenges Program, University of Wollongong, Australia Harry Crossley Foundation, South Africa National Health and Medical Research Council, Australia NIH - International Research Training Grant Pham Ngoc Thach University of Medicine, Vietnam Research University Grant (GUP), Universiti Kebangsaan Malaysia Sasakawa Sports Research Grant, Sasakawa Sports Foundation, Japan Stella de Silva Research Grant, Sri Lanka College of Paediatricians, Sri Lanka The DST-NRF Centre for Excellence in Human Development at the University of Witwatersrand, Johannesburg, South Africa The International Society of Behavioral Nutrition and Physical Activity, Pioneers ProgramDeclaration of Interest: The authors have no competing financial or personal interests to declare.Ethical Approval: Ethical approval was obtained from the University of Wollongong, Australia (ref: 2018/044) and the appropriate ethics committee(s) in each country.