Efficacy of Early Intervention for Infants With Cerebral Palsy in an LMIC: An RCT.

OBJECTIVE: To test efficacy of a parent-delivered multidomain early intervention (Learning through Everyday Activities with Parents [LEAP-CP]) for infants with cerebral palsy (CP) compared with equal-dose of health advice (HA), on (1) infant development; and (2) caregiver mental health. It was hypothesized that infants receiving LEAP-CP would have better motor function, and caregivers better mental health. METHODS: This was a multisite single-blind randomized control trial of infants aged 12 to 40 weeks corrected age (CA) at risk for CP (General Movements or Hammersmith Infant Neurologic Examination). Both LEAP-CP and HA groups received 15 fortnightly home-visits by a peer trainer. LEAP-CP is a multidomain active goal-directed intervention. HA is based on Key Family Practices, World Health Organization. Primary outcomes: (1) infants at 18 months CA: Pediatric Evaluation of Disability Inventory-Computer Adaptive Test (PEDI-CAT mobility); and (2) caregiver: Depression Anxiety and Stress Scale. RESULTS: Of eligible infants, 153 of 165 (92.7%) were recruited (86 males, mean age 7.1±2.7 months CA, Gross Motor Function Classification System at 18 m CA: I = 12, II = 25, III = 9, IV = 18, V = 32). Final data were available for 118 (77.1%). Primary (PEDI-CAT mobility mean difference = 0.8 (95% CI -1.9 to 3.6) P = .54) and secondary outcomes were similar between-groups. Modified-Intention-To-Treat analysis on n = 96 infants with confirmed CP showed Gross Motor Function Classification System I and IIs allocated to LEAP-CP had significantly better scores on PEDI-CAT mobility domain (mean difference 4.0 (95% CI = 1.4 to 6.5), P = .003) compared with HA. CONCLUSIONS: Although there was no overall effect of LEAP-CP compared with dose-matched HA, LEAP-CP lead to superior improvements in motor skills in ambulant children with CP, consistent with what is known about targeted goal-directed training.

The evolution of nutrition management in children with severe neurological impairment with a focus on cerebral palsy.

Nutritional management of children with severe neurological impairment (SNI) is highly complex, and the profile of this population is changing. The aim of this narrative review was to give the reader a broad description of evolution of the nutritional management of children with SNI in a high resource setting. In the last decade, there has been an emphasis on using multiple anthropometric measures to monitor nutritional status in children with SNI, and several attempts at standardising the approach have been made. Tools such as the Feeding and Nutrition Screening Tool, the Subjective Global Nutrition Assessment, the Eating and Drinking Ability Classification System and the Focus on Early Eating and Drinking Swallowing (FEEDS) toolkit have become available. There has been an increased understanding of how the gut microbiome influences gastrointestinal symptoms common in children with SNI, and the use of fibre in the management of these has received attention. A new diagnosis, 'gastrointestinal dystonia', has been defined. The increased use and acceptance of blended food tube feeds has been a major development in the nutritional management of children with SNI, with reported benefits in managing gastrointestinal symptoms. New interventions to support eating and drinking skill development in children with SNI show promise. In conclusion, as the life expectancy of people with SNI increases due to advances in medical and nutrition care, our approach necessitates a view to long-term health and quality of life. This involves balancing adequate nutrition to support growth, development and well-being while avoiding overnutrition and its associated detrimental long-term effects.

Construct Validity of the Both Hands Assessment Using Wrist-Worn Accelerometers.

AIM: The aim of this study was to evaluate the construct validity of the Both Hands Assessment (BoHA) using activity of the upper limbs as detected by accelerometry in children with bilateral cerebral palsy (CP). METHODS: Observational study of children with CP (n = 44, n = 27 boys, aged 9.1 ± 1.6 years; Manual Ability Classification Scale I: n = 15, II: n = 22, III: n = 7) completing a BoHA assessment while wearing a triaxial accelerometer on each wrist. BoHA Each-Hand sub-scores, BoHA percentage difference between hands, BoHA Units, mean activity for each hand, mean activity asymmetry index and total mean activity were calculated. Linear regressions were used to analyze associations between measures. RESULTS: There were significant, positive associations between BoHA Units and total mean activity (B = 0.86, 95%CI: 0.32, 1.40), BoHA Percentage difference between hands and mean activity asymmetry index (B = 0.95, 95%CI: 0.75,1.15), and BoHA Each-Hand sub-score and mean activity for the non-dominant hand (B = 1.71, 95%CI: 1.16, 2.28), but not the dominant hand (B = 0.50, 95%CI: -0.45, 1.45). CONCLUSIONS: This study provides further evidence for the construct validity of the BoHA as a measure of upper limb performance. Wearable wrist sensors such as accelerometers capture and quantify gross upper limb movement in children with CP but cannot measure fine finger movements captured by the BoHA. CLINICAL TRIALS REGISTRATION: Australian New Zealand Clinical Trials Registry (ACTRN12616001488493 and ACTRN12618000164291).

Changes in physical activity, diet, sleep, and mental well-being when starting university: A qualitative exploration of Australian student experiences.

Objective: To explore young adult's experiences of how starting university influenced their physical activity, diet, sleep, and mental well-being, and barriers and enablers to health behavior change. Participants: University students aged 18-25 years. Methods: Three focus groups were conducted in November 2019. Inductive thematic approach was utilized to identify themes. Results: Students (female: n = 13, male: n = 2, other gender identity: n = 1, 21.2 (1.6) years) reported mental well-being, physical activity levels, diet quality and sleep health were negatively affected. Stress, study demands, university timetabling, not prioritizing physical activity, cost and availability of healthy foods, and difficulty falling asleep were key barriers. Health behavior change interventions aiming to support mental well-being need to include both information and support features. Conclusions: There is a significant opportunity to improve the transition to university for young adults. Findings highlight areas to target in future interventions to improve physical activity, diet, and sleep of university students.

School readiness of children at high risk of cerebral palsy randomised to early neuroprotection and neurorehabilitation: protocol for a follow-up study of participants from four randomised clinical trials.

INTRODUCTION: School readiness includes cognitive, socio-emotional, language and physical growth and development domains which share strong associations with life-course opportunities. Children with cerebral palsy (CP) are at increased risk of poor school readiness compared with their typically developing peers. Recently, earlier diagnosis of CP has allowed interventions to commence sooner, harnessing neuroplasticity. First, we hypothesise that early referral to intervention for children at-risk of CP will lead to improved school readiness at 4-6 years relative to placebo or care as usual. Second, we hypothesise that receipt of early diagnosis and early intervention will lead to cost-savings in the form of reduced healthcare utilisation. METHODS AND ANALYSIS: Infants identified as at-risk of CP ≤6 months corrected age (n=425) recruited to four randomised trials of neuroprotectants (n=1), early neurorehabilitation (n=2) or early parenting support (n=1) will be re-recruited to one overarching follow-up study at age 4-6 years 3 months. A comprehensive battery of standardised assessments and questionnaires will be administered to assess all domains of school readiness and associated risk factors. Participants will be compared with a historical control group of children (n=245) who were diagnosed with CP in their second year of life. Mixed-effects regression models will be used to compare school readiness outcomes between those referred for early intervention versus placebo/care-as-usual. We will also compare health-resource use associated with early diagnosis and intervention versus later diagnosis and intervention. ETHICS AND DISSEMINATION: The Children's Health Queensland Hospital and Health Service, The University of Queensland, University of Sydney, Monash University and Curtin University Human Research Ethics Committees have approved this study. Informed consent will be sought from the parent or legal guardian of every child invited to participate. Results will be disseminated in peer-reviewed journals, scientific conferences and professional organisations, and to people with lived experience of CP and their families. TRIAL REGISTRATION NUMBER: ACTRN12621001253897.

Associations between aerobic and muscle-strengthening physical activity, sleep duration, and risk of all-cause mortality: A prospective cohort study of 282,473 U.S. adults.

PURPOSE: To examine the joint associations between meeting guidelines for physical activity (PA) and sleep duration and all-cause mortality risk among adults. METHODS: Participants were adults (n = 282,473) aged 18-84 years who participated in the 2004-2014 U.S. National Health Interview Survey. Mortality status was ascertained using the National Death Index through December 2015. Self-reported PA (Active: meeting both aerobic (AER) and muscle-strengthening (MSA) guidelines, AER only (AER), MSA only (MSA), or not meeting either AER or MSA (Inactive)) and sleep duration (Short, recommended (Rec), or Long) were classified according to guidelines, and 12 PA-sleep categories were derived. Adjusted hazard ratios and 95% confidence intervals (95%CIs) for all-cause mortality risk were estimated using Cox proportional hazards regression models. RESULTS: A total of 282,473 participants (55% females) were included; 18,793 deaths (6.7%) occurred over an average follow-up of 5.4 years. Relative to the Active-Rec group, all other PA-sleep groups were associated with increased mortality risk except for the Active-Short group (hazard ratio = 1.08; 95%CI: 0.92-1.26). The combination of long sleep with either MSA or Inactive appeared to be synergistic. For a given sleep duration, mortality risk progressively increased among participants classified as AER, MSA, and Inactive. Within each activity level, the mortality risk was greatest among adults with long sleep. CONCLUSION: Relative to adults meeting guidelines for both PA and sleep duration, adults who failed to meet guidelines for both AER and muscle strengthening PA and who also failed to meet sleep duration guidelines had elevated all-cause mortality risks. These results support interventions targeting both PA and sleep duration to reduce mortality risk.

Prospective associations between joint categories of physical activity and insomnia symptoms with onset of poor mental health in a population-based cohort.

BACKGROUND: Physical inactivity and insomnia symptoms are independently associated with increased risk of depression and anxiety; however, few studies jointly examine these risk factors. This study aimed to prospectively examine the joint association of physical activity (PA) and insomnia symptoms with onset of poor mental health in adults. METHODS: Participants from the 2013 to 2018 annual waves of the Household Income and Labour Dynamics in Australia panel study who had good mental health (Mental Health Inventory-5 >54) in 2013, and who completed at least 1 follow-up survey (2014-2018), were included (n = 10,977). Poor mental health (Mental Health Inventory-5 ≤ 54) was assessed annually. Baseline (2013) PA was classified as high/moderate/low, and insomnia symptoms (i.e., trouble sleeping) were classified as no insomnia symptoms/insomnia symptoms, with 6 mutually exclusive PA-insomnia symptom groups derived. Associations of PA-insomnia symptom groups with onset of poor mental health were examined using discrete-time proportional-hazards logit-hazard models. RESULTS: There were 2322 new cases of poor mental health (21.2%). Relative to the high PA/no insomnia symptoms group, there were higher odds (odds ratio and 95% confidence interval (95%CI)) of poor mental health among the high PA/insomnia symptoms (OR = 1.87, 95%CI: 1.57-2.23), moderate PA/insomnia symptoms (OR = 1.93, 95%CI: 1.61-2.31), low PA/insomnia symptoms (OR = 2.33, 95%CI: 1.96-2.78), and low PA/no insomnia symptoms (OR = 1.14, 95%CI: 1.01-1.29) groups. Any level of PA combined with insomnia symptoms was associated with increased odds of poor mental health, with the odds increasing as PA decreased. CONCLUSION: These findings highlight the potential benefit of interventions targeting both PA and insomnia symptoms for promoting mental health.

Prevalence, Trends, and Correlates of Joint Patterns of Aerobic and Muscle-Strengthening Activity and Sleep Duration: A Pooled Analysis of 359,019 Adults in the National Health Interview Survey 2004-2018.

BACKGROUND: Physical activity (PA) and sleep duration have established associations with health outcomes individually but tend to co-occur and may be better targeted jointly. This study aimed to describe the cross-sectional prevalence, trends, and population characteristic correlates of activity-sleep patterns in a population-representative sample of US adults from the National Health Interview Survey (2004-2018). METHODS: Participants (N = 359,019) self-reported aerobic and muscle-strengthening activity and sleep duration. They were categorized as "meeting both"/"meeting PA only"/"meeting sleep only"/"meeting neither" of the 2018 US PA guidelines and age-based sleep duration recommendations. Trends in activity-sleep patterns were analyzed using weighted multinomial logistic regression, and correlates were identified using weighted binary Poisson regressions, with P ≤ .001 considered significant. RESULTS: "Meet sleep only" was most prevalent (46.4%) by 2018, followed by "meet neither" (30.3%), "meet both" (15.6%), and "meet PA only" (7.7%). Many significant sociodemographic, biological, and health-behavior correlates of the activity-sleep groups were identified, and the direction and magnitude of these associations differed between groups. CONCLUSIONS: Public health campaigns should emphasize the importance of both sufficient PA and sleep; target women and older adults, current smokers, and those with lower education and poorer physical and mental health; and consider specific barriers experienced by minority ethnic groups.

The Prospective Association Between Physical Activity, Insomnia Symptoms, and Productivity in an Australian Population-Based Cohort.

OBJECTIVES: To investigate the joint, prospective associations of physical inactivity and insomnia symptoms and productivity using the 2013 and 2014 household income and labor dynamics in Australia Survey panel data. METHODS: The association between (i) presenteeism (yes/no, n = 5864) and (ii) absenteeism (sick leave days, n = 4324) and the mutually exclusive groups "active without insomnia," "active with insomnia," "inactive without insomnia," and "inactive with insomnia" was assessed. RESULTS: Participants "active with insomnia" or "inactive with insomnia" had greater odds of presenteeism than those "active without insomnia" (odds ratio [OR] = 1.41, 95% confidence interval [CI]: 1.07 to 1.85 and OR = 1.44, 95% CI: 1.14 to 1.83, respectively). Participants "inactive with insomnia" had a greater incidence of absenteeism than participants "active without insomnia" (incidence rate ratio [IRR] = 1.28, 95% CI: 1.07 to 1.54). CONCLUSIONS: Findings suggest improving physical activity levels and insomnia symptoms concurrently may improve productivity by reducing presenteeism and sick leave.

Joint association of physical activity and sleep difficulties with the incidence of hypertension in mid-age Australian women.

INTRODUCTION: Little is known about the joint effects of physical activity and sleep difficulties on hypertension. The aim of this study was to examine the joint associations of physical activity and sleep difficulties with the incidence of hypertension in mid-aged women. STUDY DESIGN: Prospective cohort study. MAIN OUTCOME MEASURES: Mid-aged participants (n = 5,300) in the Australian Longitudinal Study on Women's Health completed four triennial surveys starting in 2004, when they had a mean age of 55 years. The presence of hypertension, physical activity and the number of sleep difficulties (range 0-4) were reported at each survey. Total MET.min/week of physical activity was assessed, and dichotomised as inactive (<500 MET.min/wk) or active (≥500 MET.min/wk). Joint categories of physical activity and sleep difficulties were created using six mutually exclusive groups. Associations of joint physical activity and sleep difficulty groups with incident hypertension were examined via discrete-time survival analysis using logit-hazard models. RESULTS: There were 1,175 cases of incident hypertension (22.2%). Compared with the Active and No Difficulties group, women in the Inactive and 1 Difficulty (Odds Ratio (95% confidence interval) (1.31 (1.06, 1.62)) and Inactive and 2-4 Difficulties (1.44 (1.16, 1.78)) groups were more likely to develop hypertension. Sleep difficulties were not associated with hypertension among active women. CONCLUSIONS: Mid-aged inactive women with sleep difficulties were more likely to develop hypertension. Physical activity appeared to protect against the increased risk of hypertension in women with sleeping difficulties.

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).

Latent Class Analysis of Multiple Health Risk Behaviors among Australian University Students and Associations with Psychological Distress.

University students have high rates of health risk behaviors and psychological distress. This study explores patterns of health behaviors among a sample of Australian university students, and determines whether patterns of health behaviors are associated with psychological distress and demographic characteristics. Cross-sectional data from the University of Newcastle Student Healthy Lifestyle Survey 2019 were analyzed. Fruit and vegetable intake, sugar-sweetened beverage intake, physical activity, sitting time, smoking, alcohol intake, drug use, sleep and psychological distress were assessed. Latent class analysis (LCA) was used to identify patterns of health risk behaviors, and latent class regression to explore associations between psychological distress and demographic characteristics with health behavior classes. Analysis included 1965 students (mean age 25.8 ± 8.6 years, 70.7% female). Three patterns of health behaviors were identified: healthier (48.6%), moderate (40.2%) and unhealthy (11.2%) lifestyle classes. Students in the moderate and unhealthy lifestyle classes had higher odds of moderate (OR 1.43 and 2.37) and high/very high psychological distress risk (OR 2.71 and 11.69). Students in the unhealthy and moderate lifestyle classes had a higher odds of being male, younger, enrolled in transition to university and English language courses, Aboriginal or Torres Strait Islander descent and to report some financial difficulty. Study findings may be used to inform the design of mental health interventions for university students that target key health risk behaviors.

Associations between multiple positive health behaviors and cardiometabolic risk using 3 alternative measures of physical activity: NHANES 2005-2006.

The study aimed to investigate the association between clustered cardiometabolic risk (CCMR) and health-behavior indices comprising 3 different measures of physical activity, screen time, diet and sleep in NHANES 2005-2006. CCMR was calculated by standardizing and summarizing measures of blood pressure, fasting glucose, triglycerides, insulin, high-density lipoprotein and waist circumference to create a z score. Three health behavior indices were constructed with a single point allocated to each of the following lower risk behaviors: muscle strengthening activity, healthy eating score, sleep disorder/disruption, sleep duration, screen time and physical activity (self-reported moderate-to-vigorous physical activity [MVPA] (Index Score-SR), accelerometer-measured MVPA (Index Score-MVPA) or accelerometer-measured steps Index Score-Steps). Linear regression models explored associations between index scores and CCMR. In the sample (n = 1537, 52% male, aged 45.5 [SE: 0.9] years), reporting 0-5 vs. 6 health behaviors using Index Score-SR and Index Score-MVPA, and 0-4 vs. 6 health behaviors using Index Score-Steps, were associated with a significantly higher CCMR. The beta (ß [95% CI]) for zero vs. 6 behaviors were Index Score-SR (2.86 [2.02, 3.69], Index Score-MVPA (2.41 [1.49, 3.33] and Index Score-Steps (2.41 [1.68, 3.15]). Irrespective of the measure of physical activity, engaging in fewer positive health behaviors was associated with greater CCMR. Novelty: Physical activity, screen time, diet and sleep may exert synergistic/cumulative effects on clustered cardiometabolic risk. A greater number of positive health behaviors was associated with a lower clustered cardiometabolic risk factor score. The reduction in cardiometabolic risk was similar irrespective of which physical activity measure was used.

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.

Diet quality and depressive symptoms. Assessing the direction of the association in a population-based cohort study.

BACKGROUND: Emerging evidence links a poor diet with mental ill-health although the direction of this association is unclear. The aim was to examine the bidirectional prospective relationships between core (and non-core food consumption, and symptoms of depression. METHODS: Depressive symptoms (Mental Health Index-5, MHI-5), current/prior depression and consumption of core (recommended food groups) and non-core (discretionary) foods were assessed in the population-based 2013 and 2017 Household Income and Labour Dynamics in Australia cohort study. Three cross-lagged linear models assessed associations between all three baseline variables in 2013, alternating 2017 variables as outcomes. RESULTS: In the population (n = 10,003; 48.3% women; 48.5[15.7] years), core food score in 2013 was associated with MHI-5 (ß:0.102, 95%CI: 0.010,0.193) in 2017, while the non-core food score was not (ß:-0.030, 95%CI:-0.099,0.160). Depressive symptom score in 2013 was not associated with either food score in 2017. Current/prior diagnosis of depression in 2013 was associated with core (ß:-0.198, 95%CI:-0.329,-0.067) but not non-core (ß:-0.036, 95%CI: -0.151,0.080) food score in 2017. LIMITATIONS: Results may not be generalizable to the whole population due to some selection bias, self-report depression diagnosis may have led to misclassification of previous mental illness, and core and non-core food scores are not validated measures of diet quality. CONCLUSIONS: There is a prospective association between core food consumption and depressive symptoms. This association is of small magnitude and we cannot discount insufficient core food consumption reflecting an effect of prior mental illness. Our results suggest that, for depression, public health focus should be on improving core food intake.

Daily steps and diet, but not sleep, are related to mortality in older Australians.

OBJECTIVES: Supporting healthy ageing is a key priority worldwide. Physical activity, diet quality and sleep are all associated with health outcomes, but few studies have explored their independent associations with all-cause mortality in an older population in the same model. The study aim was to examine associations between step-count, self-reported diet quality, restless sleep, and all-cause mortality in adults aged 55-85 years. DESIGN: A prospective cohort study of adults in Newcastle, New South Wales, Australia. METHOD: Data were from 1697 participants (49.3% women; baseline mean age 65.4 ±â€¯7.1 years). Daily steps (measured by pedometer), diet quality (from a modified Australian Recommended Food Score), and frequency of restless sleep (by self-report) were assessed in relation to all-cause mortality using Cox proportional hazard regression with adjustment for sex, age, household income and smoking. Baseline data were collected between January 2005 and April 2008, and last follow-up was in March 2017 (median follow-up 9.6 years). RESULTS: Higher step count (HR: 0.93, 95%CI: 0.88-0.98 per 1000-step increment) and higher diet quality (HR: 0.86, 95%CI: 0.74-0.99 per 8-point increment in diet quality score) were associated with reduced mortality risk. Restless sleep for ≥3 nights/week was not associated with mortality risk (HR: 1.03, 95%CI: 0.78-1.39). Sensitivity analyses, adjusting for chronic disease and excluding deaths <1 year after baseline, did not change these estimates. CONCLUSIONS: Increased daily steps and consumption of a greater variety of nutrient-dense foods every week would result in substantial health benefits for older people. Future research should include a greater variety of sleep measures.

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.

Resistance training in addition to aerobic activity is associated with lower likelihood of depression and comorbid depression and anxiety symptoms: A cross sectional analysis of Australian women.

The mental health benefits of resistance training (RT) alone or beyond those provided by aerobic physical activity (PA) are unclear. This study aimed to determine the association between meeting recommendations for aerobic PA and/or RT, and symptoms of depression and/or anxiety. Participants were Australian female members of the 10,000 Steps project (n = 5180, 50.0 ±â€¯11.5 years). Symptoms of depression and anxiety were determined using the Depression Anxiety Stress Score. Participants were grouped as 'depression only', 'anxiety only', 'co-occurring depression and anxiety' or 'neither depression nor anxiety' based on relevant subscale score (cut-points: depression≥14 points, anxiety≥10 points). The International Physical Activity Questionnaire-Long Form questionnaire was used to determine PA with an additional item to specify RT frequency. Participants were classified as adhering to 'aerobic PA only' (≥150 min PA/week), 'RT only' (RT ≥ 2 days/week), 'aerobic PA + RT' (≥150 min PA/week+RT ≥ 2 days/week), or 'neither aerobic PA nor RT' (<150 min PA/week+RT < 2 days/week). Adjusted relative risk ratios (RRR [95%CI]) were estimated using multinomial logistic regression models. Relative to the 'neither PA nor RT' (n = 2215), the probabilities of 'depression only' (n = 317) and 'co-occurring depression and anxiety' (n = 417) were lower for the 'aerobic PA only' (n = 1590) (RRR = 0.74 [0.56-0.97] and RRR = 0.76 [0.59-0.97] respectively), and 'both PA + RT' (n = 974) groups (RRR = 0.61 [0.43-0.86] and RRR = 0.47 [0.33-0.67] respectively). There were no associations between adhering to one or both recommendations and 'anxiety only' (n = 317), or between 'RT only' (n = 401) and depression and/or anxiety. Prevention and treatment strategies including both aerobic PA and RT may provide additional benefits for depression with or without comorbid anxiety.

Patterns of Diet, Physical Activity, Sitting and Sleep Are Associated with Socio-Demographic, Behavioural, and Health-Risk Indicators in Adults.

Our understanding of how multiple health-behaviours co-occur is in its infancy. This study aimed to: (1) identify patterns of physical activity, diet, sitting, and sleep; and (2) examine the association between sociodemographic and health-risk indicators. Pooled data from annual cross-sectional telephone surveys of Australian adults (2015-2017, n = 3374, 51.4% women) were used. Participants self-reported physical activity, diet, sitting-time, sleep/rest insufficiency, sociodemographic characteristics, smoking, alcohol use, height and weight to calculate body mass index (BMI), and mental distress frequency. Latent class analysis identified health-behaviour classes. Latent class regression determined the associations between health-behaviour patterns, sociodemographic, and health-risk indicators. Three latent classes were identified. Relative to a 'moderate lifestyle' pattern (men: 43.2%, women: 38.1%), a 'poor lifestyle' pattern (men: 19.9%, women: 30.5%) was associated with increased odds of a younger age, smoking, BMI ≥ 30.0 kg/m2, frequent mental distress (men and women), non-partnered status (men only), a lower Socioeconomic Index for Areas centile, primary/secondary education only, and BMI = 25.0-29.9 kg/m2 (women only). An 'active poor sleeper' pattern (men: 37.0%, women: 31.4%) was associated with increased odds of a younger age (men and women), working and frequent mental distress (women only), relative to a 'moderate lifestyle' pattern. Better understanding of how health-behaviour patterns influence future health status is needed. Targeted interventions jointly addressing these behaviours are a public health priority.

Associations of health-behavior patterns, mental health and self-rated health.

Diet quality, physical activity, alcohol use, smoking, sleep and sitting-time are behaviors known to influence health. The aims of this study were to identify how these behaviors co-occur to form distinct health-behavior patterns, and to investigate the relationship between these patterns, and mental and self-rated health. Members of the Australian 10,000 Steps project were invited to participate in an online survey in November-December 2011. The participants self-reported demographic and behavioral characteristics (fruit and vegetable intake, fast food, soft drink and alcohol consumption, smoking, physical activity, sitting-time and sleep), frequency of mental distress and self-rated health. Latent Class Analysis was used to identify health-behavior patterns. Latent class regression was used to examine relationships between behavior patterns, mental and self-rated health, and socio-demographic and economic factors. Data were analyzed in October 2017. Complete datasets were obtained from 10,638 participants. Four latent classes were identified, characterized by 'Low-Risk Behavior', 'Poor Sleep, Low-Risk Daytime Behavior', 'Sound Sleep, High-Risk Daytime Behavior' and 'High-Risk Behavior'. The latter two classes, both characterized by high-risk daytime behaviors, were associated with poor self-rated health. Participants in classes with high-risk daytime behaviors were more likely to be younger, non-partnered, non-university educated, from lower income households and work longer hours. Classes characterized by poor sleep quality were associated with higher frequency of mental distress. Findings suggest that experiencing poor sleep is partly independent of daytime behaviors, demographic and socioeconomic factors, but has a strong association with mental health.