Does home equipment contribute to socioeconomic gradients in Australian children’s physical activity, sedentary time and screen time?

Abstract Background Activity behaviours (physical activity, sedentary time and screen time) have been linked to health outcomes in childhood. Furthermore, socioeconomic disparities have been observed in both children’s activity behaviours and health outcomes. Children’s physical home environments may play a role in these relationships. This study aimed to examine the associations and interactions between children’s physical home environment, socioeconomic status and moderate-to-vigorous physical activity, sedentary time and screen time. Methods Australian children (n = 528) aged 9–11 years from randomly selected schools participated in the cross-sectional International Study of Childhood Obesity, Lifestyle and the Environment. Children’s physical home environment (access to equipment), socioeconomic status (household income and parental education) and demographic variables (gender and family structure) were determined by parental questionnaire. Moderate-to-vigorous physical activity and sedentary time were measured objectively by 7-day 24-h accelerometry. Screen time was obtained from child survey. The associations between the physical home environment, socioeconomic status and moderate-to-vigorous physical activity, sedentary time and screen time were examined for 427 children, using analysis of covariance, and linear and logistic regression, with adjustment for gender and family structure. Results The presence of TVs (p < 0.01) and video game consoles (p < 0.01) in children’s bedrooms, and child possession of handheld video games (p = 0.04), cell phones (p < 0.01) and music devices (p = 0.04) was significantly and positively associated with screen time. Ownership of these devices (with the exception of music devices) was inversely related to socioeconomic status (parental education). Children’s moderate-to-vigorous intensity physical activity (p = 0.04) and possession of active play equipment (p = 0.04) were both positively associated with socioeconomic status (household income), but were not related to each other (with the exception of bicycle ownership). Conclusions Children with less electronic devices, particularly in their bedrooms, participated in less screen time, regardless of socioeconomic status. Socioeconomic disparities were identified in children’s moderate-to-vigorous physical activity, however socioeconomic status was inconsistently related to possession of active play equipment. Home active play equipment was therefore not a clear contributor to the socioeconomic gradients in Australian children’s moderate-to-vigorous physical activity

Joint profiles of sedentary time and physical activity in adults and their associations with cardiometabolic health

Purpose: This study aimed to identify and characterize joint profiles of sedentary time and physical activity among adults and investigate how these profiles are associated with markers of cardiometabolic health. Methods: The participants included 3,702 of the Northern Finland Birth Cohort 1966 at age 46 years, who wore a hip-worn accelerometer during waking hours and provided 7 consecutive days of valid data. Sedentary time, LPA, and MVPA on each valid day were obtained, and a data-driven clustering approach ("KmL3D") was used to characterize distinct joint profiles of sedentary time and physical activity intensities. Participants self-reported their sleep duration and performed a submaximal step test with continuous heart rate measurement to estimate their cardiorespiratory fitness (peak heart rate). Linear regression was used to determine the association between joint profiles of sedentary time and physical activities with cardiometabolic health markers, including adiposity markers and blood lipid, glucose, and insulin levels. Results: Four distinct groups were identified: "Active couch potatoes" (n = 1,173), "Sedentary light movers" (n = 1,199), "Sedentary exercisers" (n = 694), and " Movers " (n = 636). Although sufficiently active, Active couch potatoes had the highest daily sedentary time (>10 hours) and lowest LPA. Compared to Active couch potatoes, Sedentary light movers, Sedentary exercisers, and Movers spent less time in sedentary by performing more physical activity at light-intensity upward and had favorable differences in their cardiometabolic health markers after accounting for potential confounders (1.1%-25.0% lower values depending on the health marker and profile). Conclusions: After accounting for sleep duration and cardiorespiratory fitness, waking activity profiles characterized by performing more physical activity at light-intensity upward, resulting in less time spent in sedentary, were associated with better cardiometabolic health

Parent wellbeing, family screen time and socioeconomic status during early childhood predict physical activity of Aboriginal and Torres Strait Islander children at ages 8–13

Objectives: Physical activity is holistically linked to culture and wellbeing among Aboriginal and Torres Strait Islander peoples, the First Nation Peoples of Australia. Socioecological correlates of high physical activity among Indigenous children include living in a remote area and low screen time but little is known about early life determinants of physical activity. This paper examines sociodemographic, family, community, cultural, parent social and emotional wellbeing determinants of physical activity among Aboriginal and Torres Strait Islander children. Design: Longitudinal cohort study. Methods: The Longitudinal Study of Indigenous Children, the largest First Nations child cohort study in the world, primarily collects data through parental report. Multiple logistic regression analyses examined Wave 1 (age 0–5 years) predictors of achieving ≥1 h/day of physical activity at Wave 9 (aged 8–13 years). Results: Of the 1181 children, 596 (50.5 %) achieved ≥1 h of physical activity every day. Achieving ≥1 h/day of physical activity at Wave 9 was associated with the following Wave 1 determinants: high parent social and emotional wellbeing (resilience; adjusted odds ratio 1.87 (95 % confidence interval: 1.32–2.65)), living in remote (odds ratio 3.66 (2.42–5.54)), regional (odds ratio 2.98 (2.13–4.18)) or low socioeconomic areas (odds ratio 1.85 (1.08–3.17)), main source of family income not wages/salaries (odds ratio 0.66 (0.46–0.97)), and if families played electronic games (odds ratio 0.72 (0.55–0.94)). Conclusions: To achieve high physical activity levels among Aboriginal and Torres Strait Islander children, high parental culture specific social and emotional wellbeing and low family screen time in early life may compensate for apparently low socio-economic circumstances, including living in remote areas

Systematic review and meta-analysis of the effectiveness of chatbots on lifestyle behaviours

Abstract Chatbots (also known as conversational agents and virtual assistants) offer the potential to deliver healthcare in an efficient, appealing and personalised manner. The purpose of this systematic review and meta-analysis was to evaluate the efficacy of chatbot interventions designed to improve physical activity, diet and sleep. Electronic databases were searched for randomised and non-randomised controlled trials, and pre-post trials that evaluated chatbot interventions targeting physical activity, diet and/or sleep, published before 1 September 2022. Outcomes were total physical activity, steps, moderate-to-vigorous physical activity (MVPA), fruit and vegetable consumption, sleep quality and sleep duration. Standardised mean differences (SMD) were calculated to compare intervention effects. Subgroup analyses were conducted to assess chatbot type, intervention type, duration, output and use of artificial intelligence. Risk of bias was assessed using the Effective Public Health Practice Project Quality Assessment tool. Nineteen trials were included. Sample sizes ranged between 25–958, and mean participant age ranged between 9–71 years. Most interventions (n = 15, 79%) targeted physical activity, and most trials had a low-quality rating (n = 14, 74%). Meta-analysis results showed significant effects (all p < 0.05) of chatbots for increasing total physical activity (SMD = 0.28 [95% CI = 0.16, 0.40]), daily steps (SMD = 0.28 [95% CI = 0.17, 0.39]), MVPA (SMD = 0.53 [95% CI = 0.24, 0.83]), fruit and vegetable consumption (SMD = 0.59 [95% CI = 0.25, 0.93]), sleep duration (SMD = 0.44 [95% CI = 0.32, 0.55]) and sleep quality (SMD = 0.50 [95% CI = 0.09, 0.90]). Subgroup analyses showed that text-based, and artificial intelligence chatbots were more efficacious than speech/voice chatbots for fruit and vegetable consumption, and multicomponent interventions were more efficacious than chatbot-only interventions for sleep duration and sleep quality (all p < 0.05). Findings from this systematic review and meta-analysis indicate that chatbot interventions are efficacious for increasing physical activity, fruit and vegetable consumption, sleep duration and sleep quality. Chatbot interventions were efficacious across a range of populations and age groups, with both short- and longer-term interventions, and chatbot only and multicomponent interventions being efficacious