Establishing Effectiveness of a Community-based, Physical Activity Program for Fathers and Daughters: A Randomized Controlled Trial.

BACKGROUND: The 'Dads And Daughters Exercising and Empowered' (DADEE) program significantly improved physical activity levels of fathers and their daughters in an efficacy trial. However, the effectiveness of interventions when delivered in real-world settings needs to be established. PURPOSE: To evaluate the effectiveness of the DADEE intervention when delivered in community settings by trained facilitators. METHODS: We conducted a two-arm RCT, (baseline and 3-months post-intervention assessments), in Newcastle, Australia. In 2016, 155 fathers (27-60 years) and 189 primary-school-aged daughters (4-12 years) (n = 344) were randomly allocated to the intervention (78 fathers, 95 daughters) or waitlist-control (77 fathers, 94 daughters) groups. Trained facilitators delivered the 9-week DADEE program (weekly sessions plus home-based tasks). Primary outcomes were fathers' and daughters' physical activity (steps/day). Secondary outcomes included screen-time, weight status, daughters' fundamental movement skill (FMS) proficiency, perceived sports competence, and fathers' parenting practices. Effects were assessed using linear mixed models. RESULTS: Primary outcome follow-up data were collected from 88% of fathers and 89% of daughters. Significant group-by-time differences in mean daily steps were found for fathers' (adjusted difference = +1,638; 95% CI: 833, 2,443, d = 0.7) and daughters' (adjusted difference = +1,023 steps/day; 95% CI: 259, 1,787; d = 0.4) physical activity. Significant effects were observed for daughters' screen-time, FMS, and some parenting practices. No significant effects were identified for weight status, or fathers'screen-time or self-reported MVPA. Program attendance, satisfaction and fidelity were very high. CONCLUSION: This study established the effectiveness of the DADEE intervention when delivered in community settings by trained facilitators. Importantly, the findings were comparable to those of the efficacy RCT delivered by the research team. To maximize public health benefits, a larger-scale dissemination of the program appears warranted.Trial Registration Australian New Zealand Clinical Trial Registry: ACTRN12616001270404 Human Research Ethics Committee: H-2014-0330.

Impact of the 'Healthy Youngsters, Healthy Dads' program on physical activity and other health behaviours: a randomised controlled trial involving fathers and their preschool-aged children.

BACKGROUND: Targeting fathers may be a key strategy to increase physical activity among their preschool-aged children, but limited research exists in this area. The primary study aim was to examine the impact of a lifestyle program for fathers and their preschool-aged children on child physical activity levels. METHODS: A total of 125 fathers (aged: 38 ± 5.4 years, BMI: 28.1 ± 4.9 kg/m2) and 125 preschool-aged children (aged: 3.9 ± 0.8 years, BMI z-score: 0.3 ± 0.9, 39.2% girls) recruited from Newcastle, Australia, NSW were randomised to (i) the Healthy Youngsters, Healthy Dads (HYHD) program, or (ii) wait-list control group. The program included two fathers-only workshops (2 h each) and eight father-child weekly educational and practical sessions (75 min each), plus home-based activities targeting family physical activity and nutrition. Assessments took place at baseline, 10-weeks (post-intervention) and 9-months follow-up. The primary outcome was the children's mean steps/day at 10-weeks. Secondary outcomes included: co-physical activity, fathers' physical activity levels and parenting practices for physical activity and screen time behaviours, children's fundamental movement skill (FMS) proficiency, plus accelerometer based light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA), screen time and adiposity for fathers and children. Process measures included; attendance, satisfaction, fidelity and retention. Linear mixed models estimated the treatment effect at all time-points for all outcomes. RESULTS: Intention-to-treat analyses revealed a significant group-by-time effect for steps per day at 10-weeks (+ 1417, 95%CI: 449, 2384) and 9-months follow-up (+ 1480, 95%CI: 493, 2467) in intervention children compared to control. There were also favourable group-by-time effects for numerous secondary outcomes including fathers' physical activity levels, children's FMS proficiency, and several parenting constructs. No effects were observed for both fathers' and children's accelerometer based LPA or MVPA, co-physical activity, screen-time and adiposity measures. Process evaluation data revealed very high levels of satisfaction, attendance, retention, and intervention fidelity. CONCLUSION: Engaging fathers in a lifestyle program is a promising strategy to increase physical activity among preschool-aged children. Additional benefits to fathers' physical activity levels, children's FMS proficiency and parenting practices further support the importance of engaging fathers to improve family health outcomes. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry: ACTRN12619000105145 . Registered 24/01/2019.

Effect of a physical activity and sleep m-health intervention on a composite activity-sleep behaviour score and mental health: a mediation analysis of two randomised controlled trials.

BACKGROUND: To examine if a composite activity-sleep behaviour index (ASI) mediates the effects of a combined physical activity and sleep intervention on symptoms of depression, anxiety, or stress, quality of life (QOL), energy and fatigue in adults. METHODS: This analysis used data pooled from two studies: Synergy and Refresh. Synergy: Physically inactive adults (18-65 years) who reported poor sleep quality were recruited for a two-arm Randomised Controlled Trial (RCT) (Physical Activity and Sleep Health (PAS; n = 80), or Wait-list Control (CON; n = 80) groups). Refresh: Physically inactive adults (40-65 years) who reported poor sleep quality were recruited for a three-arm RCT (PAS (n = 110), Sleep Health-Only (SO; n = 110) or CON (n = 55) groups). The SO group was omitted from this study. The PAS groups received a pedometer, and accessed a smartphone/tablet "app" using behaviour change strategies (e.g., self-monitoring, goal setting, action planning), with additional email/SMS support. The ASI score comprised self-reported moderate-to-vigorous-intensity physical activity, resistance training, sitting time, sleep duration, efficiency, quality and timing. Outcomes were assessed using DASS-21 (depression, anxiety, stress), SF-12 (QOL-physical, QOL-mental) and SF-36 (Energy & Fatigue). Assessments were conducted at baseline, 3 months (primary time-point), and 6 months. Mediation effects were examined using Structural Equation Modelling and the product of coefficients approach (AB), with significance set at 0.05. RESULTS: At 3 months there were no direct intervention effects on mental health, QOL or energy and fatigue (all p > 0.05), and the intervention significantly improved the ASI (all p < 0.05). A more favourable ASI score was associated with improved symptoms of depression, anxiety, stress, QOL-mental and of energy and fatigue (all p < 0.05). The intervention effects on symptoms of depression ([AB; 95%CI] -0.31; - 0.60,-0.11), anxiety (- 0.11; - 0.27,-0.01), stress (- 0.37; - 0.65,-0.174), QOL-mental (0.53; 0.22, 1.01) and ratings of energy and fatigue (0.85; 0.33, 1.63) were mediated by ASI. At 6 months the magnitude of association was larger although the overall pattern of results remained similar. CONCLUSIONS: Improvements in the overall physical activity and sleep behaviours of adults partially mediated the intervention effects on mental health and quality of life outcomes. This highlights the potential benefit of improving the overall pattern of physical activity and sleep on these outcomes. TRIAL REGISTRATION: Australian New Zealand Clinical Trial Registry: ACTRN12617000680369 ; ACTRN12617000376347 . Universal Trial number: U1111-1194-2680; U1111-1186-6588. Human Research Ethics Committee Approval: H-2016-0267; H-2016-0181.

Behavioural mediators of reduced energy intake in a physical activity, diet, and sleep behaviour weight loss intervention in adults.

Reduced energy intake is a major driver of weight loss and evidence suggests that physical activity, dietary, and sleep behaviours interact to influence energy intake. Energy restriction can be challenging to sustain. Therefore to improve intervention efficacy, evaluation of how changes in physical activity, diet, and sleep behaviours mediate reduced energy intake in adults with overweight/obesity who participated in a six-month multiple-behaviour-change weight loss intervention was undertaken. This was a secondary analysis of a 3-arm randomised controlled trial. Adults with body mass index (BMI) 25-40 kg/m2 were randomised to either: a physical activity and diet intervention; physical activity, diet, and sleep intervention; or wait-list control. Physical activity, dietary intake, and sleep was measured at baseline and six-months using validated measures. The two intervention groups were pooled and compared to the control. Structural equation modelling was used to estimate the mediated effects (AB Coefficient) of the intervention on total energy intake. One hundred and sixteen adults (70% female, 44.5y, BMI 31.7 kg/m2) were enrolled and 70% (n = 81) completed the six-month assessment. The significant intervention effect on energy intake at six-months (-1011 kJ/day, 95% CI -1922, -101) was partially mediated by reduced fat intake (AB = -761.12, 95% CI -1564.25, -53.74) and reduced consumption of energy-dense, nutrient-poor foods (AB = -576.19, 95% CI -1189.23, -97.26). In this study, reducing fat intake and consumption of energy-dense, nutrient-poor foods was an effective strategy for reducing daily energy intake in adults with overweight/obesity at six-months. These strategies should be explicitly targeted in future weight loss interventions.

The Association Between Logging Steps Using a Website, App, or Fitbit and Engaging With the 10,000 Steps Physical Activity Program: Observational Study.

BACKGROUND: Engagement is positively associated with the effectiveness of digital health interventions. It is unclear whether tracking devices that automatically synchronize data (eg, Fitbit) produce different engagement levels compared with manually entering data. OBJECTIVE: This study examines how different step logging methods in the freely available 10,000 Steps physical activity program differ according to age and gender and are associated with program engagement. METHODS: A subsample of users (n=22,142) of the free 10,000 Steps physical activity program were classified into one of the following user groups based on the step-logging method: Website Only (14,617/22,142, 66.01%), App Only (2100/22,142, 9.48%), Fitbit Only (1705/22,142, 7.7%), Web and App (2057/22,142, 9.29%), and Fitbit Combination (combination of web, app, and Fitbit; 1663/22,142, 7.51%). Generalized linear regression and binary logistic regression were used to examine differences between user groups' engagement and participation parameters. The time to nonusage attrition was assessed using Cox proportional hazards regression. RESULTS: App Only users were significantly younger and Fitbit user groups had higher proportions of women compared with other groups. The following outcomes were significant and relative to the Website Only group. The App Only group had fewer website sessions (odds ratio [OR] -6.9, 95% CI -7.6 to -6.2), whereas the Fitbit Only (OR 10.6, 95% CI 8.8-12.3), Web and App (OR 1.5, 95% CI 0.4-2.6), and Fitbit Combination (OR 8.0; 95% CI 6.2-9.7) groups had more sessions. The App Only (OR -0.7, 95% CI -0.9 to -0.4) and Fitbit Only (OR -0.5, 95% CI -0.7 to -0.2) groups spent fewer minutes on the website per session, whereas the Fitbit Combination group (OR 0.2, 95% CI 0.0-0.5) spent more minutes. All groups, except the Fitbit Combination group, viewed fewer website pages per session. The mean daily step count was lower for the App Only (OR -201.9, 95% CI -387.7 to -116.0) and Fitbit Only (OR -492.9, 95% CI -679.9 to -305.8) groups but higher for the Web and App group (OR 258.0, 95% CI 76.9-439.2). The Fitbit Only (OR 5.0, 95% CI 3.4-6.6), Web and App (OR 7.2, 95% CI 5.9-8.6), and Fitbit Combination (OR 15.6, 95% CI 13.7-17.5) groups logged a greater number of step entries. The App Only group was less likely (OR 0.65, 95% CI 0.46-0.94) and other groups were more likely to participate in Challenges. The mean time to nonusage attrition was 35 (SD 26) days and was lower than average in the Website Only and App Only groups and higher than average in the Web and App and Fitbit Combination groups. CONCLUSIONS: Using a Fitbit in combination with the 10,000 Steps app or website enhanced engagement with a real-world physical activity program. Integrating tracking devices that synchronize data automatically into real-world physical activity interventions is one strategy for improving engagement.

Efficacy of an m-Health Physical Activity and Sleep Intervention to Improve Sleep Quality in Middle-Aged Adults: The Refresh Study Randomized Controlled Trial.

BACKGROUND: Poor sleep health is highly prevalent. Physical activity is known to improve sleep quality but not specifically targeted in sleep interventions. PURPOSE: To compare the efficacy of a combined physical activity and sleep intervention with a sleep-only intervention and a wait-list control, for improving sleep quality in middle-aged adults without a diagnosed sleep disorder. METHODS: Three-arm randomized controlled trial (Physical Activity and Sleep Health (PAS), Sleep Health Only (SO), Wait-list Control (CON) groups; 3-month primary time-point, 6-month follow-up) of 275 (PAS = 110, SO = 110, CON = 55) inactive adults (40-65 years) reporting poor sleep quality. The main intervention component was a smartphone/tablet "app" to aid goal setting and self-monitoring physical activity and/or sleep hygiene behaviors (including stress management), and a pedometer for PAS group. Primary outcome was Pittsburgh Sleep Quality Index (PSQI) global score. Secondary outcomes included several self-reported physical activity measures and PSQI subcomponents. Group differences were examined stepwise, first between pooled intervention (PI = PAS + SO) and CON groups, then between PAS and SO groups. RESULTS: Compared with CON, PI groups significantly improved PSQI global and subcomponents scores at 3 and 6 months. There were no differences in sleep quality between PAS and SO groups. The PAS group reported significantly less daily sitting time at 3 months and was significantly more likely to report ≥2 days/week resistance training and meeting physical activity guidelines at 6 months than the SO group. CONCLUSIONS: PIs had statistically significantly improved sleep quality among middle-aged adults with poor sleep quality without a diagnosed sleep disorder. The adjunctive physical activity intervention did not additionally improve sleep quality. CLINICAL TRIAL INFORMATION: Australian New Zealand Clinical Trial Registry: ACTRN12617000680369; Universal Trial number: U1111-1194-2680; Human Research Ethics Committee, Blinded by request of journal: H-2016-0267.

Sleep, diet, activity, and incident poor self-rated health: A population-based cohort study.

OBJECTIVE: The prospective relationships between poor sleep health, poor diet quality, and physical inactivity with self-rated health (SRH) are not well described. The aim of this study was to assess individual and joint associations between high-risk health behaviors and incident poor SRH. METHOD: Participants from the Household Income and Labor Dynamics in Australia longitudinal cohort reporting "good" SRH in 2013 were included (n = 8,853) in 2020 data analysis. Logistic regression was used to assess odds of poor SRH in 2017 associated with (a) individual, (b) count, and (c) unique combinations of high-risk behaviors reported in 2013. RESULTS: In the sample (48% female, Mage = 45.2 years, SD = 16.8), poor sleep health (OR = 1.66, 95% CI [1.38, 2.01]), physical inactivity (OR = 1.18, [1.01, 1.38]), and poor diet quality (OR = 1.38, [1.16, 1.65]) were associated with increased odds of poor SRH. Reporting one (OR = 1.76, [1.27, 2.43]), two (OR = 2.16, [1.57, 2.98]), and three (OR = 2.99, [2.02, 4.41]) high-risk behaviors was associated with increased odds of poor SRH. All unique combinations of high-risk behaviors were significantly associated with greater odds of poor SRH, except "poor sleep health only" (prevalence = 1.3%). Odds of poor SRH associated with high-risk behavior combinations ranged from 1.73 (95% CI [1.21, 2.47]) for "physical inactivity only" to 4.11 ([2.66, 6.35]) for "poor sleep health + poor diet quality." CONCLUSIONS: Reporting ≥ 1 high-risk behavior was associated with increased odds of poor SRH. The combination of poor sleep health with poor diet quality was associated with the greatest odds of poor SRH. Improving multiple high-risk behaviors in combination may be more effective in preventing decline in SRH than improving any behavior alone. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Efficacy of a Multi-Component m-Health Diet, Physical Activity, and Sleep Intervention on Dietary Intake in Adults with Overweight and Obesity: A Randomised Controlled Trial.

This three-arm randomised controlled trial evaluated whether (1) a multi-component weight loss intervention targeting diet, physical activity (PA), and sleep was effective at improving dietary intake over six months and 12 months, compared with a control, and (2) the enhanced diet, PA, and sleep intervention was more effective at improving dietary intake than the traditional diet and PA intervention. A total of 116 adults (70% female, 44.5 years, BMI 31.7 kg/m2) were randomised to either traditional diet and PA intervention; enhanced diet, PA, and sleep intervention; or wait-list control. To examine between-group differences, intervention groups were pooled and compared with the control. Then, the two intervention groups were compared. At six months, the pooled intervention group consumed 1011 fewer kilojoules/day (95% CI -1922, -101), less sodium (-313.2 mg/day; 95% CI -591.3, -35.0), and higher %EI from fruit (+2.1%EI; 95% CI 0.1, 4.1) than the controls. There were no differences in intake between the enhanced and traditional groups at six months. At 12 months, the pooled intervention and control groups reported no significant differences. However, compared to the traditional group, the enhanced reported higher %EI from nutrient-dense foods (+7.4%EI; 95% CI 1.3, 13.5) and protein (+2.4%EI; 95% CI 0.1, 4.6), and reduced %EI from fried/takeaway foods (-3.6%EI; 95% CI -6.5, -0.7), baked sweet products (-2.0%EI; 95% CI -3.6, -0.4), and packaged snacks (-1.1%EI; 95% CI -2.2, -0.3). This weight loss intervention reduced total energy and sodium intakes as well as increased fruit intake in adults at six months. The enhanced intervention group reported improved dietary intake relative to the traditional group at 12 months.

Engaging Fathers to Improve Physical Activity and Nutrition in Themselves and in Their Preschool-Aged Children: The "Healthy Youngsters, Healthy Dads" Feasibility Trial.

BACKGROUND: Few lifestyle programs for young children have targeted fathers. This study examined the feasibility of a lifestyle intervention for fathers and their preschool-aged children. METHOD: A total of 24 father/preschool child dyads were recruited from Newcastle, Australia, into a single-arm, feasibility trial (baseline and 3-mo postbaseline assessments). The 9-session program aimed to improve physical activity and dietary habits of fathers and children. A priori feasibility benchmarks targeted recruitment (15 dyads), eligibility rate (>60%), attendance (80%), retention (≥85%), and program acceptability (≥4 out of 5). Acceptability of data collection procedures, research team program/resource management, home-program compliance, and preliminary intervention outcomes were also assessed. RESULTS: Feasibility benchmarks were surpassed for recruitment (24 dyads), eligibility rate (61.5%), attendance (89%), retention (100%), and program acceptability (4.6 out of 5). Data collection procedures were acceptable. Challenges included mothers reporting their own dietary intake rather than their child's, children moving during body composition measurement, and resetting pedometers. Resource and program management were excellent. Most families met home-program requirements (83%). Preliminary intervention outcomes were encouraging for fathers and children. CONCLUSION: Program feasibility was demonstrated by excellent recruitment, attendance, acceptability, retention, program administration, and promising preliminary intervention outcomes. A few data collection difficulties were identified. A larger scale efficacy trial is warranted.

Dietary Outcomes of the 'Healthy Youngsters, Healthy Dads' Randomised Controlled Trial.

(1) Background: The effect of fathers on dietary intake in preschool-aged children is under-explored. The aims were to: (i) evaluate the efficacy of a family-based lifestyle intervention, Healthy Youngsters, Healthy Dads, on change in dietary intake in fathers and their preschool-aged children post-intervention (10 weeks) and at 9 months follow-up compared to a waitlist control group and (ii) investigate associations in father-child dietary intakes. (2) Methods: Linear mixed models estimated group-by-time effects for all dietary outcomes, measured by food frequency questionnaires. Cohen's d determined effect sizes, while correlation tests determined associations in father-child dietary intakes. (3) Results: For children, medium group-by-time effects sizes were identified at 10 weeks for sodium intake (d = 0.38) and percentage energy from core foods (d = 0.43), energy-dense, nutrient-poor (EDNP) foods (d = 0.43) and prepacked snacks (d = 0.45). These findings were sustained at 9 months follow-up. For fathers, medium to large, group-by-time effect sizes were identified at 10 weeks for energy intake (d = 0.55), sodium intake (d = 0.64) and percentage energy from core foods (d = 0.49), EDNP foods (d = 0.49), and confectionary (d = 0.36). For all of these dietary variables, except sodium, effects were sustained at 9 months. Moderate to strong associations existed in father-child dietary intakes for some of the dietary variables. (4) Conclusions: Although further research is required, this study provides preliminary support for targeting fathers as agents of change to improve dietary intakes in their preschool-aged children.

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.

Examining mediators of intervention efficacy in a randomised controlled m-health trial to improve physical activity and sleep health in adults.

Objectives: Examining mediators of intervention efficacy in an m-health intervention targeting physical activity and sleep in 160 Australian adults.Design: Nationwide randomised controlled trial.Main outcome measures: Moderate- and vigorous-intensity physical activity (MVPA), assessed using the Active Australia Questionnaire; sleep quality (Pittsburgh Sleep Quality Index); and sleep hygiene practices (Sleep Hygiene Index). Hypothesised psychosocial (e.g. self-efficacy) and behavioural (i.e. MVPA, sleep quality, sleep hygiene) mediators were tested on primary endpoint data at 3 months using bias-corrected bootstrapping (PROCESS 2 for SPSS). All outcomes and mediators were assessed using self-report.Results: At three months, the intervention had significantly improved sleep quality (d = 0.48, 95% CI: -2.26, -0.33, p = 0.009) and sleep hygiene (d = 0.40, 95% CI: -3.10, -0.19, p = 0.027). Differences in MVPA were not significant (d = 0.24, 95% CI: -35.53, 254.67, p = 0.139). Changes in MVPA were mediated by self-efficacy, perceived capability, environment, social support, intentions and planning, some of which showed inconsistent mediation (suppression). None of the hypothesised psychosocial factors mediated sleep outcomes. Changes in sleep hygiene mediated changes in sleep quality.Conclusions: Several psychosocial factors mediated changes in physical activity but not in sleep outcomes. Mediation effects of sleep hygiene on sleep quality highlight the importance of providing evidence-based strategies to improve sleep quality.

Efficacy of a Multi-component m-Health Weight-loss Intervention in Overweight and Obese Adults: A Randomised Controlled Trial.

BACKGROUND: This study compared the efficacy of two multi-component m-health interventions with a wait-list control group on body weight (primary outcome), and secondary outcomes of cardiovascular risk factors, lifestyle behaviours, and mental health. METHODS: Three-arm randomised controlled trial (Enhanced: physical activity, diet, sleep, Traditional: physical activity, diet, Control) with assessments conducted at baseline, 6 and 12 months. Participants (n = 116) were overweight or obese adults aged 19-65 (M = 44.5 [SD = 10.5]). The 6-month intervention was delivered via a smartphone app providing educational materials, goal-setting, self-monitoring and feedback, and also included one face-to-face dietary consultation, a Fitbit and scales. The trial was prospectively registered and conducted between May 2017 and September 2018. Group differences on primary and secondary outcomes were examined between the Pooled Intervention groups (Pooled Intervention = Enhanced and Traditional) and Control groups, and then between Enhanced and Traditional groups. RESULTS: Nineteen participants (16.4%) formally withdrew from the trial. Compared with the Control group, average body weight of the Pooled Intervention group did not differ at 6 (between-group difference = -0.92, (95% CI -3.33, 1.48)) or 12 months (0.00, (95% CI -2.62, 2.62)). Compared with the Control group, the Pooled Intervention group significantly increased resistance training (OR = 7.83, (95% CI 1.08, 56.63)) and reduced energy intake at 6 months (-1037.03, (-2028.84, -45.22)), and improved insomnia symptoms at 12 months (-2.59, (-4.79, -0.39)). Compared with the Traditional group, the Enhanced group had increased waist circumferences (2.69, (0.20, 5.18)) and sedentary time at 6 months (105.66, (30.83, 180.48)), and improved bed time variability at 12 months (-1.08, (-1.86, -0.29)). No other significant differences were observed between groups. CONCLUSIONS: Relative to Controls, the Pooled Intervention groups did not differ on body weight but improved resistance training, and reduced energy intake and insomnia symptom severity. No additional weight loss was apparent when targeting improvements in physical activity, diet and sleep in combination compared with physical activity and diet.

Impact of a Social Media Campaign on Reach, Uptake, and Engagement with a Free Web- and App-Based Physical Activity Intervention: The 10,000 Steps Australia Program.

Social media campaigns provide broad-reach and convenience for promoting freely-available health programs. However, their effectiveness and subsequent engagement of new users is unknown. This study aimed to assess the reach and new member registration rates resulting from a dedicated 10,000 Steps social media campaign (SMC) and to compare program engagement and time to non-usage attrition of new users from the SMC with other users. SMC reach (using Facebook, Instagram, and display advertisements engagement metrics), new-user numbers, engagement (usage of the website and its features), and time to non-usage attrition were assessed using generalized linear regression, binary logistic regression, and Cox proportion hazards regression models. During the SMC, Instagram and display advertisement impressions, Facebook reach and new daily registrations were significantly higher compared with six weeks and one year prior. There were no between-group differences in the average usage of most website/program features. Risk of non-usage attrition was higher among new users from the SMC than new users from one year prior. The SMC was effective in promoting awareness of the 10,000 Steps program. Further research to identify long-term engagement strategies and the most effective combination of social media platforms for promotion of, and recruitment to, health programs is warranted.

Sociodemographic and behavioral correlates of insufficient sleep in Australian adults.

OBJECTIVES: Insufficient sleep is being increasingly recognized as a public health issue. There is a need to identify correlates of insufficient sleep to guide future preventative health interventions. This study aims to determine the sociodemographic and behavioral correlates of frequent perceived insufficient sleep in the Australian population. DESIGN: Pooled analyses of two cross-sectional, self-report national telephone surveys were conducted in 2015 (July-August) and 2016 (June-August). SETTING: Adults living in Australia. PARTICIPANTS: Data from participants (age 18 years and over) of both surveys were pooled for analysis (2015 n = 1041; 2016 n = 1170), with 2211 participants being included in the current study. MEASUREMENTS: Participants self-reported their age, gender, education and employment level, language spoken at home, urbanization, chronic disease, and height and weight to calculate BMI. Self-reported physical activity, sitting time, smoking, and consumption of fruit, vegetables, fast food, alcohol and frequency of perceived insufficient sleep were also assessed. Binary logistic regression analysis examined the relationship between insufficient sleep (≥14 days out of 30), sociodemographic and behavioral variables. RESULTS: The overall prevalence of insufficient sleep was 24%. Female gender, obesity, >8 h/d sitting time, smoking, and frequent consumption of fast food were positively associated with frequent insufficient sleep (P < .05). Higher levels of physical activity and being aged 51 years or older were negatively associated with frequent insufficient sleep (P < .05). CONCLUSIONS: The sociodemographic and behavioral characteristics associated with frequent perceived insufficient sleep can be used to guide the development of future interventions to reduce sleep insufficiency.

Efficacy of an m-Health Physical Activity and Sleep Health Intervention for Adults: A Randomized Waitlist-Controlled Trial.

INTRODUCTION: Interventions that improve both physical activity and sleep quality may be more effective in improving overall health. The purpose of the Synergy Study is to test the efficacy of a mobile health combined behavior intervention targeting physical activity and sleep quality. STUDY DESIGN: Randomized, waitlist-controlled trial. SETTING/PARTICIPANTS: This study had an app-based delivery mode, Australia-wide. The participants were 160 adults who reported insufficient physical activity and poor sleep quality in an eligibility survey. INTERVENTION: The intervention was a mobile app providing educational resources, goal setting, self-monitoring, and feedback strategies. It included 12 weeks of personalized support including weekly reports, tool sheets, and prompts. MAIN OUTCOME MEASURES: Outcomes were assessed at baseline, 3 months (primary), and 6 months (secondary endpoint). Self-reported minutes of moderate-to-vigorous intensity physical activity and sleep quality were co-primary outcomes. Resistance training; sitting time; sleep hygiene; sleep timing variability; insomnia severity; daytime sleepiness; quality of life; and depression, anxiety, and stress symptoms were secondary outcomes. Data were collected between June 2017 and February 2018 and analyzed in August 2018. RESULTS: At 3 months, between-group differences in moderate-to-vigorous intensity physical activity were not statistically significant (p=0.139). Significantly more participants in the intervention group engaged in ≥2 days/week (p=0.004) of resistance training. The intervention group reported better overall sleep quality (p=0.009), subjective sleep quality (p=0.017), sleep onset latency (p=0.013), waketime variability (p=0.018), sleep hygiene (p=0.027), insomnia severity (p=0.002), and lower stress symptoms (p=0.032) relative to waitlist controls. At 6 months, group differences were maintained for sleep hygiene (p=0.048), insomnia severity (p=0.002), and stress symptoms (p=0.006). Differences were observed for bedtime variability (p=0.023), sleepiness (p<0.001), daytime dysfunction (p=0.039), and anxiety symptoms (p=0.003) at 6 months, but not 3 months. CONCLUSIONS: This remotely delivered intervention did not produce statistically significant between-group differences in minutes of moderate-to-vigorous intensity physical activity. Significant short-term differences in resistance training and short- and medium-term differences in sleep health in favor of the intervention were observed. TRIAL REGISTRATION: This study is registered at anzctr.org.au ACTRN12617000376347.

Randomised controlled trial using a theory-based m-health intervention to improve physical activity and sleep health in adults: the Synergy Study protocol.

INTRODUCTION: There is a need to reduce physical inactivity and poor sleep health in the adult population to decrease chronic disease rates and the associated burden. Given the high prevalence of these risk behaviours, effective interventions with potential for wide reach are warranted. METHODS AND ANALYSIS: The aim of this two-arm RCT will be to test the effect of a three month personalised mobile app intervention on two main outcomes: minutes of moderate-to-vigorous-intensity physical activity and overall sleep quality. In addition, between-group changes in health-related quality of life and mental health status will be assessed as secondary outcomes. The pre-specified mediators and moderators include social cognitive factors, the neighbourhood environment, health (BMI, depression, anxiety, stress), sociodemographic factors (age, gender, education) and app usage. Assessments will be conducted after three months (primary endpoint) and six months (follow-up). The intervention will provide access to a specifically developed mobile app, through which participants can set goals for active minutes, daily step counts, resistance training, sleep times and sleep hygiene practice. The app also allows participants to log their behaviours daily and view progress bars as well as instant feedback in relation to goals. The personalised support system will consist of weekly summary reports, educational and instructional materials, prompts on disengagement and weekly facts. ETHICS AND DISSEMINATION: The Human Research Ethics Committee of The University of Newcastle, Australia granted full approval: H-2016-0181. This study will assess the efficacy of a combined behaviour intervention, mechanisms of behaviour change and gather high-quality process data, all of which will help refine future trials. Dissemination of findings will include publication in a peer-reviewed journal and presentation at national or international conferences. Participants will receive a plain English summary report of results. TRIAL REGISTRATION NUMBER: ACTRN12617000376347; Pre-results.

Associations between Changes in Activity and Sleep Quality and Duration over Two Years.

PURPOSE: Insufficient physical activity (PA) and inadequate sleep quality (SQ) and sleep duration (SD) are highly prevalent behaviors that increase the risk of developing many chronic health conditions. Evidence regarding bidirectional relationships between PA, SQ, and SD is inconsistent. As changes in one of these behaviors may impact on the other, it is important to understand the nature of the bidirectional relationship between PA and sleep. Therefore, the aim of this study was to examine the relationship between changes in PA, SQ, and SD over a 2-yr period in middle-age adults. METHODS: Participants were adults age 42 to 72 yr from Brisbane, Australia. Mail surveys were used to assess PA, SQ, SD, sociodemographic and health characteristics in 2011 and 2013 (n = 3649). Multinomial logistic regression analyses were conducted to examine the relationships between patterns of change in PA, SQ, and SD over the 2 yr. RESULTS: Improving or maintaining good SQ was associated with increasing or maintaining PA and maintaining PA was associated with maintaining or increasing SQ (P < 0.05). Changes in PA were not associated with changes in SD. CONCLUSIONS: A bidirectional relationship between PA and SQ was identified; however, no evidence of a relationship in any direction between PA and SD was found. Multibehavior interventions targeting both PA and SQ are warranted. Middle-age adults with poor SQ may benefit from increasing PA and improving SQ may promote higher levels of activity.

A randomised controlled trial to test the efficacy of an m-health delivered physical activity and sleep intervention to improve sleep quality in middle-aged adults: The Refresh Study Protocol.

INTRODUCTION: Poor sleep health is common and has a substantial negative health impact. Physical activity has been shown to improve sleep health. Many sleep interventions do not explicitly target physical activity, potentially limiting changes in activity and also sleep. Few intervention target those with poor sleep health but without a diagnosed disorder. This study aims to examine the efficacy of a combined physical activity and sleep intervention to improve sleep quality in middle-aged adults and its effect on physical activity, depression and quality of life. METHODS: A three-arm randomised trial with a three-month primary time-point, will be conducted. Adults (N = 275) aged 40-65 years, who report physical inactivity and poor sleep quality, will be randomly allocated to either a combined Physical Activity and Sleep Health, a Sleep Health-Only or a Wait List Control group. The multi-component m-health intervention will be delivered using a smartphone/tablet "app", supplemented with email and SMS. Participants will use the app to access educational material, set goals, self-monitor and receive feedback about behaviours. Assessments will be conducted at baseline, three-month primary time-point and six-month follow-up. Generalized linear models using an ANCOVA (baseline-adjusted) approach, will be used to identify between-group differences in sleep quality, following an intention-to-treat principle. DISCUSSION: This study will determine whether the addition of a physical activity intervention enhances the effectiveness of a sleep intervention to improve sleep quality, relative to a sleep-only intervention, in physically inactive middle-aged adults who report poor sleep health, but without a sleep disorder.