supplemental_material_S2 – Supplemental material for Development and psychometric testing of an instrument to assess psychosocial determinants of sleep hygiene practice

Supplemental material, supplemental_material_S2 for Development and psychometric testing of an instrument to assess psychosocial determinants of sleep hygiene practice by Beatrice Murawski, Ronald C Plotnikoff and Mitch J Duncan in Journal of Health Psychology</p

supplemental_material_S1 – Supplemental material for Development and psychometric testing of an instrument to assess psychosocial determinants of sleep hygiene practice

Supplemental material, supplemental_material_S1 for Development and psychometric testing of an instrument to assess psychosocial determinants of sleep hygiene practice by Beatrice Murawski, Ronald C Plotnikoff and Mitch J Duncan in Journal of Health Psychology</p

Impact of COVID-19 on physical activity of 10,000 Steps members and engagement with the program in Australia: Prospective study

BACKGROUND: Background: Physical activity is an important health behavior due to its association with many physical and mental health conditions. During distressing events such as the COVID-19 pandemic, there is a concern that physical activity levels may be negatively impacted. However, recent studies have shown inconsistent results. Additionally, there is a lack of studies in Australia on this topic. OBJECTIVE: Objective: To investigate changes in physical activity reported through the 10,000 Steps program and changes in engagement with the program during the COVID-19 pandemic. METHODS: Methods: Data between 01/01/2018 and 30/06/2020 from registered members of the 10,000 Steps program, which included 3,548,825 days with steps data, were used. The number of daily steps was logged manually by the members or synced automatically from the activity trackers connected to the program. Measures on the program usage were the number of new registered members per day, the number of newly registered organisations per day, the number of steps logged per day, and the number of step entries per day. Key dates used for comparison were: first case with symptoms in Wuhan; first case in Australia reported; a 14-day ban for non-citizens arriving to Australia from China implemented; lockdown starts in Australia; and Australian Government starts relaxing restrictions. Wilcoxon signed-rank tests were used to test for significant differences in steps between subgroups, engagement measures in 2019 vs. 2020, and before and after an event. RESULTS: Results: A decrease in steps was observed after the first case in Australia (1.5%, p9,000 step entries/day with nearly 100 million steps/day logged; and >450 new users and >15 new organizations registering per day although the numbers decreased quickly when restrictions were relaxed. On average per day, there were about 55 new registered users (p<0.001) and two new organisations (p<0.001), 25.6 million steps (p<0.001), and 2672 log entries (p<0.001) more in 2020 compared to the same period in 2019. CONCLUSIONS: Conclusion: The pandemic has had negative effects on steps among Australians across age groups and gender. However, the effect was relatively small with steps recovering quickly after the lockdown. There was a large increase in the program usage during the pandemic that might help minimize the health impact of the lockdown and confirms the important role of physical activity programs during times of distress and lockdowns. CLINICALTRIAL

The associations between physical activity, sedentary behaviour, and sleep with mortality and incident cardiovascular disease, cancer, diabetes and mental health in adults: a systematic review and meta-analysis of prospective cohort studies

Background Physical activity, sedentary behaviour and sleep are interrelated and may have a synergistic impact on health. This systematic review and meta-analysis of prospective cohort studies aimed to evaluate the combined influence of different combinations of these behaviours on mortality risk and incidence of cardiovascular disease (CVD), cancer, diabetes, and mental health. Methods Four online databases were used to identify studies from database inception to May 2023. Prospective cohort studies that examined how different combinations of physical activity, sedentary and sleep behaviours were associated with mortality and incident cardiovascular disease, cancer, diabetes and mental health in adults were included. Random effects meta-analyses using the Der Simonian and Laird method were conducted. Results Assessment of 4583 records resulted in twelve studies being included. Studies were qualitatively summarised and a sub-group of studies (n = 5) were meta-analysed. The most frequent combination of behaviours was duration of leisure time physical activity and sleep (n = 9), with all-cause mortality (n = 16), CVD mortality (n = 9) and cancer mortality (n = 7) the most frequently examined outcomes. Meta-analysis revealed that relative to High physical activity & Mid sleep, High physical activity and Short sleep was not associated with risk of all-cause mortality (RR = 1.05, 95% CI = 0.97, 1.14), however Low physical activity and Short Sleep (RR = 1.42, 95% CI = 1.24, 1.63), Low physical activity and Mid Sleep (RR = 1.30, 95% CI = 1.12, 1.52), High physical activity and Long Sleep (RR = 1.16, 95% CI = 1.01, 1.32), and Low physical activity and Long Sleep were associated with risk of all-cause mortality (RR = 1.63, 95% CI = 1.21, 2.20). Conclusions High levels of physical activity may offset all-cause mortality risks associated with short sleep duration. Low levels of physical activity combined with short sleep duration and any level of physical activity in combination with long sleep duration appear to increase mortality risk. Currently there is limited evidence regarding how dimensions of physical activity, sedentary and sleep behaviours other than duration (e.g., quality, timing, type) are associated with future health status

Patterns of physical activity, sitting time, and sleep in Australian adults: A latent class analysis

Objective: To identify the patterns of activity, sitting and sleep that adults engage in, the demographic and biological correlates of activity-sleep patterns and the relationship between identified patterns and self-rated health. Design and Setting: Online panel of randomly selected Australian adults (n = 2034) completing a cross-sectional survey in October-November 2013. Participants: Panel members who provided complete data on all variables were included (n = 1532). Measurements: Participants self-reported their demographic characteristics, height, weight, self-rated health, duration of physical activity, frequency of resistance training, sitting time, sleep duration, sleep quality, and variability in bed and wake times. Activity-sleep patterns were determined using latent class analysis. Latent class regression was used to examine the relationships between identified patterns, demographic and biological characteristics, and self-rated health. Results: A 4-class model fit the data best, characterized by very active good sleepers, inactive good sleepers, inactive poor sleepers, moderately active good sleepers, representing 38.2%, 22.2%, 21.2%, and 18.4% of the sample, respectively. Relative to the very active good sleepers, the inactive poor sleepers, and inactive good sleepers were more likely to report being female, lower education, higher body mass index, and lower self-rated health, the moderately active good sleepers were more likely to be older, report lower education, higher body mass index and lower self-rated health. Associations between activity-sleep pattern and self-rated health were the largest in the inactive poor sleepers. Conclusions: The 4 activity-sleep patterns identified had distinct behavioral profiles, sociodemographic correlates, and relationships with self-rated health. Many adults could benefit from behavioral interventions targeting improvements in physical activity and sleep. © 2020 National Sleep Foundatio

Objectively measured waist circumference is most strongly associated in father–boy and mother–girl dyads in a large nationally representative sample of New Zealanders

Background: The prevalence of children with elevated weight or obesity is concerning for public health due to associated comorbidities. This study investigates associations between parental adiposity, physical activity (PA), fruit and vegetable consumption, and child adiposity and moderation by both child and parent gender. Methods: Cross-sectional nationally representative data from the New Zealand Health Survey were pooled for the years 2013/14–2016/17. Parent and child surveys were matched resulting in 13,039 child (2–14 years) and parent (15–70 years) dyads. Parent and child, height (cm), weight (kg) and waist circumference (WC) were measured objectively. Height and weight were used to calculate BMI. Linear regression, accounting for clustered samples (b [95% CI]) investigated associations between parental characteristics and child BMI z-score and WC. Interactions and stratification were used to investigate effect moderation by parent gender, child gender, and parent adiposity. Results: Parental PA and fruit and vegetable consumption were unrelated to child adiposity. Overall, higher parent BMI was related to a higher child BMI z-score (b = 0.047 [0.042, 0.052]) and higher parental WC was related to a higher child WC (0.15 [0.12, 0.17]). A three-way interaction revealed no moderation by parent gender, child gender, and parent BMI for child BMI z-score ((b = 0.005 [−0.017, 0.027], p = 0.318). However, a three-way interaction revealed moderation by parent gender, child gender, and parent WC for child WC (b = 0.13 [0.05, 0.22]). The slightly stronger associations were seen between father–son WC (b = 0.20 [0.15, 0.24]) and mother–daughter WC (b = 0.19 [0.15, 0.22]). Conclusions: The findings are highly relevant for those wishing to understand the complex relationships between child-parent obesity factors. Findings suggest that family environments should be a key target for obesity intervention efforts and show how future public health interventions should be differentiated to account for both maternal and paternal influences on child adiposity. © 2020, The Author(s), under exclusive licence to Springer Nature Limited

sj-sps-2-hpq-10.1177_13591053241241840 – Supplemental material for The moderating effect of social support on the effectiveness of a web-based, computer-tailored physical activity intervention for older adults

Supplemental material, sj-sps-2-hpq-10.1177_13591053241241840 for The moderating effect of social support on the effectiveness of a web-based, computer-tailored physical activity intervention for older adults by Stephanie J Alley, Stephanie Schoeppe, Hayley Moore, Quyen G To, Jannique van Uffelen, Felix Parker, Mitch J Duncan, Anthony Schneiders and Corneel Vandelanotte in Journal of Health Psychology</p

sj-sav-1-hpq-10.1177_13591053221137184 – for Does matching a personally tailored physical activity intervention to participants’ learning style improve intervention effectiveness and engagement?

sj-sav-1-hpq-10.1177_13591053221137184 for Does matching a personally tailored physical activity intervention to participants’ learning style improve intervention effectiveness and engagement? by Stephanie Alley, Ronald C Plotnikoff, Mitch J Duncan, Camille E Short, Kerry Mummery, Quyen G To, Stephanie Schoeppe, Amanda Rebar and Corneel Vandelanotte in Journal of Health Psychology</p

The discrepancy between knowledge of sleep recommendations and the actual sleep behaviour of Australian adults

Introduction: Inadequate sleep is a major public health concern, with large economic, health, and operational costs to Australia. Despite the implementation of public sleep health campaigns, approximately 40% of Australian adults do not obtain the recommended 7–9 hours of sleep. Thus, while people may know how much sleep is required, this knowledge may not be adequately translated to actual sleep behavior. Consequently, this study aims to examine the discrepancy between knowledge of sleep recommendations and self-reported sleep behaviors. Methods: A sample of 1265 Australian adults (54% female, aged 18–65) completed a phone interview as part of the 2017 National Social Survey and were asked questions about their knowledge of sleep guidelines and their actual sleep behavior. Binary logistic regression was used to determine the factors associated with awareness of sleep recommendations and whether this corresponded with reported sleep duration. Results: The final sample size was 998. Although 94% of the sample were aware of current sleep recommendations, 23% of participants did not self-report regularly obtaining 7–9 h sleep per night. These participants were less likely to want to obtain more sleep, less likely to view sleep as a priority before stressful events, and less likely to self-report good health. Conclusion: Although a majority of the sample were aware of sleep recommendations, almost a quarter of the participants’ behavior did not align with their knowledge. Future sleep health campaigns should consider options beyond education, including emphasis on practical strategies and modifiable lifestyle factors to assist individuals to obtain the recommended amount of sleep

sj-sps-4-hpq-10.1177_13591053221137184 – for Does matching a personally tailored physical activity intervention to participants’ learning style improve intervention effectiveness and engagement?

sj-sps-4-hpq-10.1177_13591053221137184 for Does matching a personally tailored physical activity intervention to participants’ learning style improve intervention effectiveness and engagement? by Stephanie Alley, Ronald C Plotnikoff, Mitch J Duncan, Camille E Short, Kerry Mummery, Quyen G To, Stephanie Schoeppe, Amanda Rebar and Corneel Vandelanotte in Journal of Health Psychology</p