A scoping review of Australian nutrition resources for feeding children under 5 years of age.

INTRODUCTION: This review identified and appraised Australian open-access online resources relating to feeding and nutrition during the first 5 years of life. METHODS: Eligible resources were identified by hand searching plus a targeted search of pertinent source websites (government, hospitals and health services, peak bodies, and nutrition organisations) published in English with/without translations to other languages between 2012 and 2022. Search terms relating to the population (children) AND topic (nutrition OR feeding) were entered into Google and Bing. Critical appraisal of each resource was conducted using a modified version of the Centres for Disease Control and Prevention Clear Communication Index. RESULTS: The search identified 1327 nutrition resources, of which 1067 were appraised. Forty-five percent were paper-based resources, 47% were online content only, and 8% audio-visual resources. Almost half of the resources (45%) broadly addressed the 0-5 years age range, and 24% provided information on breast or formula feeding. Limited resources were found specifically addressing growth and development (5%) and introducing solids (8%). Only 10% of resources were culturally tailored and only 3% were translated into a language other than English. Appraisal showed the majority included visual cues and appropriate language, but less included images to support the main message of the resource. DISCUSSION: Although there were a large volume of evidence-based nutrition resources available in Australia for feeding children under 5 years, they were highly dispersed and of varying quality. Collating and presenting these resources in an open-access resource hub would empower families and education and health professionals in the nutritional care of young children.

Exploring the effect of a school-based cluster-randomised controlled trial to increase the scheduling of physical activity for primary school students on teachers' physical activity.

BACKGROUND: To determine if a school-based physical activity (PA) intervention that supported primary school teachers to schedule PA during school hours impacted their own PA. METHODS: A 2x2 factorial group cluster-randomised controlled trial was undertaken in 12 Australian primary schools. The nine-month intervention supported classroom teachers to increase scheduled weekly PA for their class via physical education, sport, Energisers and integrated lessons. Teachers' PA (n = 76) was measured at follow-up only using accelerometers (Actigraph GT3X or GT9X). Linear mixed models were used to estimate between-group differences in teachers' mean minutes of sedentary, light, moderate-to-vigorous-intensity physical activity (MVPA) across the school day and during class-time. RESULTS: At follow-up, there were non-significant between-group differences favouring intervention teachers, compared to controls, for light PA (4.9 minutes, 95% CI: -6.3, 16.0; P = .33) and MVPA (0.4 minutes, 95% CI: -10.9, 11.6; P = .94) across the school day; although not favouring the intervention for sedentary behaviour (5.1 minutes, 95% CI: -11.4, 21.7; P = .48). Similar patterns were seen during class-time for light PA and sedentary time, but not for MVPA. CONCLUSIONS: Supporting teachers with the scheduling of PA for their class may impact on their own PA. Fully powered studies are needed to better understand the impact of the intervention on teachers' PA. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12616001228471 (http://www.anzctr.org.au/).

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.

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.

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.

Development and psychometric testing of an instrument to assess psychosocial determinants of sleep hygiene practice.

This study examined the psychometric properties of a newly developed instrument to assess psychosocial determinants of sleep hygiene. Baseline data (n = 160) from an m-health physical activity and sleep intervention were analyzed to examine scale validity. Additional participants (n = 20) were recruited to compute test-retest reliability. Four of seven constructs correlated significantly with sleep hygiene practice (r = -0.17 to -0.36). The scales generally displayed unidimensional component structures. Internal consistency was good to excellent (α = 0.76-0.92). Test-retest reliability was good to excellent (ICC = 0.61-0.84). Though satisfactory, these findings warrant replication in larger samples.

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.

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.

The Efficacy of Workplace Interventions on Improving the Dietary, Physical Activity and Sleep Behaviours of School and Childcare Staff: A Systematic Review.

There is a need for effective interventions that improve the health and wellbeing of school and childcare staff. This review examined the efficacy of workplace interventions to improve the dietary, physical activity and/or sleep behaviours of school and childcare staff. A secondary aim of the review was to assess changes in staff physical/mental health, productivity, and students' health behaviours. Nine databases were searched for controlled trials including randomised and non-randomised controlled trials and quasi-experimental trials published in English up to October 2019. PRISMA guidelines informed screening and study selection procedures. Data were not suitable for quantitative pooling. Of 12,396 records screened, seven articles (based on six studies) were included. Most studies used multi-component interventions including educational resources, work-based wellness committees and planned group practice (e.g., walking groups). Multiple outcomes were assessed, findings were mixed and on average, there was moderate risk of bias. Between-group differences in dietary and physical activity behaviours (i.e., fruit/vegetable intake, leisure-time physical activity) favoured intervention groups, but were statistically non-significant for most outcomes. Some of the studies also showed differences favouring controls (i.e., nutrient intake, fatty food consumption). Additional robust studies testing the efficacy of workplace interventions to improve the health of educational staff are needed.

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 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.

Feasibility and Preliminary Efficacy of an m-Health Intervention Targeting Physical Activity, Diet, and Sleep Quality in Shift-Workers.

Poor health behaviors are prevalent in shift-workers, but few multiple health-behavior interventions consider their unique needs. This study aimed to (1) evaluate the feasibility and acceptability of an existing app-based intervention to improve physical activity, diet, and sleep quality in a shift-worker population, (2) estimate intervention effect in a four-week pilot randomized controlled trial (RCT) (ACTRN12618001785291). Shift-workers (18-65 years old) were randomized to intervention (n = 20) or wait-list (n = 20) groups. Outcomes included recruitment, engagement, attrition, usefulness ratings, System Usability Scale (SUS), qualitative interviews, and estimation of treatment effect (minutes of physical activity, diet quality, and sleep quality) using mixed model analysis. Recruitment took one week. App-use at week four was 55% (11/20), 85% (34/40) completed the four-week follow-up questionnaire, and 20% (4/20) of the intervention group completed the qualitative interview. The intervention was rated as slightly to moderately useful by 76.9% (10/13) of participants on a five-point scale. The SUS score was 62.7 (12.7) out of 100. Diet quality improved for the intervention (4.5 points; 95% confidence interval (CI) = 0.1, 8.9; p = 0.047) vs. the wait-list group, but not physical activity or sleep quality. Qualitative interviews found that a more tailored intervention, more accessible information, and interactive features were desired. The intervention was feasible in terms of recruitment, but modifications to increase engagement are needed.

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.

Consumer Understanding, Perception and Interpretation of Serving Size Information on Food Labels: A Scoping Review.

The increase in packaged food and beverage portion sizes has been identified as a potential factor implicated in the rise of the prevalence of obesity. In this context, the objective of this systematic scoping review was to investigate how healthy adults perceive and interpret serving size information on food packages and how this influences product perception and consumption. Such knowledge is needed to improve food labelling understanding and guide consumers toward healthier portion size choices. A search of seven databases (2010 to April 2019) provided the records for title and abstract screening, with relevant articles assessed for eligibility in the full-text. Fourteen articles met the inclusion criteria, with relevant data extracted by one reviewer and checked for consistency by a second reviewer. Twelve studies were conducted in North America, where the government regulates serving size information. Several studies reported a poor understanding of serving size labelling. Indeed, consumers interpreted the labelled serving size as a recommended serving for dietary guidelines for healthy eating rather than a typical consumption unit, which is set by the manufacturer or regulated in some countries such as in the U.S. and Canada. Not all studies assessed consumption; however, larger labelled serving sizes resulted in larger self-selected portion sizes in three studies. However, another study performed on confectionary reported the opposite effect, with larger labelled serving sizes leading to reduced consumption. The limited number of included studies showed that labelled serving size affects portion size selection and consumption, and that any labelled serving size format changes may result in increased portion size selection, energy intake and thus contribute to the rise of the prevalence of overweight and obesity. Research to test cross-continentally labelled serving size format changes within experimental and natural settings (e.g., at home) are needed. In addition, tailored, comprehensive and serving-size-specific food literacy initiatives need to be evaluated to provide recommendations for effective serving size labelling. This is required to ensure the correct understanding of nutritional content, as well as informing food choices and consumption, for both core foods and discretionary foods.

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.

Examining the efficacy of a multicomponent m-Health physical activity, diet and sleep intervention for weight loss in overweight and obese adults: randomised controlled trial protocol.

INTRODUCTION: Traditional behavioural weight loss trials targeting improvements in physical activity and diet are modestly effective. It has been suggested that sleep may have a role in weight loss and maintenance. Improving sleep health in combination with physical activity and dietary behaviours may be one strategy to enhance traditional behavioural weight loss trials. Yet the efficacy of a weight loss intervention concurrently targeting improvements in physical activity, dietary and sleep behaviours remains to be tested. METHODS AND ANALYSIS: The primary aim of this three-arm randomised controlled trial is to examine the efficacy of a multicomponent m-Health behaviour change weight loss intervention relative to a waitlist control group. The secondary aims are to compare the relative efficacy of a physical activity, dietary behaviour and sleep intervention (enhanced intervention), compared with a physical activity and dietary behaviour only intervention (traditional intervention), on the primary outcome of weight loss and secondary outcomes of waist circumference, glycated haemoglobin, physical activity, diet quality and intake, sleep health, eating behaviours, depression, anxiety and stress and quality of life. Assessments will be conducted at baseline, 6 months (primary endpoint) and 12 months (follow-up). The multicomponent m-Health intervention will be delivered using a smartphone/tablet 'app', supplemented with email and SMS and individualised in-person dietary counselling. Participants will receive a Fitbit, body weight scales to facilitate self-monitoring, and use the app to access educational material, set goals, self-monitor and receive feedback about behaviours. Generalised linear models using an analysis of covariance (baseline adjusted) approach will be used to identify between-group differences in primary and secondary outcomes, following an intention-to-treat principle. ETHICS AND DISSEMINATION: The Human Research Ethics Committee of The University of Newcastle Australia provided approval: H-2017-0039. Findings will be disseminated via publication in peer-reviewed journals, conference presentations, community presentations and student theses. TRIAL REGISTRATION NUMBER: ACTRN12617000735358; UTN1111-1219-2050.

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.

The effect of the labelled serving size on consumption: A systematic review.

Guidance for food consumption and portion control plays an important role in the global management of overweight and obesity. Carefully conceptualised serving size labelling can contribute to this guidance. However, little is known about the relationship between the information that is provided regarding serving sizes on food packages and levels of actual food consumption. The aim of this systematic review was to investigate how serving size information on food packages influences food consumption. We conducted a systematic review of the evidence published between 1980 and March 2018. Two reviewers screened titles and abstracts for relevance and assessed relevant articles for eligibility in full-text. Five studies were considered eligible for the systematic review. In three of the included studies, changes in serving size labelling resulted in positive health implications for consumers, whereby less discretionary foods were consumed, if serving sizes were smaller or if serving size information was provided alongside contextual information referring to the entire package. One study did not find significant differences between the conditions they tested and one study suggested a potentially negative impact, if the serving size was reduced. The influence of labelled serving size on consumption of non-discretionary foods remains unclear, which is partially due to the absence of studies specifically focusing on non-discretionary food groups. Studies that investigate the impact of serving size labels within the home environment and across a broad demographic cross-section are required.

A systematic review and meta-analysis of cognitive and behavioral interventions to improve sleep health in adults without sleep disorders.

Many adults without a diagnosed sleep disorder report poor sleep health, which is defined by dissatisfactory levels of sleep duration, sleep quality, or the timing of sleep. No previous review has summarized and described interventions targeting poor sleep health in this population. This meta-analysis aimed to quantify the efficacy of behavioral and cognitive sleep interventions in adults with poor sleep health, who do not have a sleep disorder. Electronic databases (Medline, Embase, PsycInfo, Cinahl) were searched with restrictions for age (18-64 y) and English language full-text, resulting in 18,009 records being screened and 592 full-texts being assessed. Eleven studies met inclusion criteria, seven of which reported a measure of overall sleep health (Pittsburgh sleep quality index [PSQI]). Following appraisal for risk of bias, extracted data were meta-analyzed using random-effects models. Meta-analyses showed interventions had a medium effect on sleep quality (Hedge's g = -0.54, [95% confidence interval (CI)] -0.90 to -0.19, p < 0.01). Baseline sleep health was the only significant effect moderator (p = 0.01). The most frequently used intervention components were stress management and relaxation practice, stimulus control, sleep hygiene, and exercise. Interventions targeting cognitive and behavioral self-regulation improve sleep quality in adults without clinical sleep disorder.