Patterns of diet, physical activity, sitting and sleep are associated with socio-demographic, behavioural, and health-risk indicators in adults

Vandelanotte, CL ORCiD: 0000-0002-4445-8094Our 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. © 2019 by the authors. Licensee MDPI, Basel, Switzerland

Associations between multiple positive health behaviours and cardiometabolic risk using three alternative measures of physical activity: NHANES 2005–2006

Purpose: The study aimed to investigate the association between clustered cardiometabolic risk (CCMR) and health-behavior indices comprising three different measures of physical activity, screen time, diet and sleep in NHANES 2005-2006. Methods: 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. Results: 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 (β [95%CI]) for zero vs. six 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]). Conclusion: Irrespective of the measure of physical activity, engaging in fewer positive health behaviors was associated with greater CCMR. Novelty bullets • 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.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Associations between aerobic and muscle-strengthening physical activity, sleep duration, and risk of all-cause mortality

Objective 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 US 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 (HRs) 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% female) 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 (HR = 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 aerobic 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

A systematic review of the clinimetric properties of measures of habitual physical activity in primary school aged children with cerebral palsy

Regular participation in physical activity is an important determinant of health for children and adolescents with cerebral palsy (CP). However, there is little consensus on the most valid or reliable method to measure physical activity in this population. This study aimed to systematically review the psychometric properties of habitual physical activity (HPA) measures in primary school-aged children with CP. Databases were systematically searched for measures assessing physical activity over more than one day and had evidence of validity, reliability and/or clinical utility in children aged 6-12 years with CP. Ten measures met inclusion criteria and their quality was assessed in twelve studies. Quality of the included studies was appraised using the consensus-based standards for the selection of health measurement instruments (COSMIN) checklist. Measures were moderately to strongly correlated to criterion measures, with study quality rated as Fair (+) to Poor (0). Only four measures had evidence of reliability. Accelerometers provide a valid measure of HPA with good clinical utility; however they do not have documented reliability in this population. No one measure appears ideal to record HPA in primary school-age children with CP and further research is necessary to determine the psychometric properties of HPA measurement instruments in this population. (C) 2013 Elsevier Ltd. All rights reserved

PREPRINT: The associations between physical activity, sleep and sedentary behaviour, with mortality and health outcomes: A systematic review and meta-analysis of prospective cohort studies

Background: Physical activity, sedentary behaviour and sleep are interrelated and may have a synergistic impact on health. This systematic review and meta-analysis of prospective cohort studies aimed to evaluate the combined influence of different combinations of these behaviours on mortality risk and incidence of cardiovascular disease (CVD), cancer, diabetes, and mental health. Methods: Four online databases were used to identify studies from database inception to 2022. Prospective cohort studies that examined how different combinations of physical activity, sedentary and sleep behaviours were associated with mortality and health outcomes were included. Random effects meta-analyses using the Der Simonian and Laird method were conducted. Results: Assessment of 4490 records result in twelve studies being included. Studies were qualitatively summarised and a sub-group of studies (n=5) were meta-analysed. The most frequent combination of behaviours was duration of leisure time physical activity and sleep (n=9), with all-cause mortality (n=16), CVD mortality (n=9) and cancer mortality (n=7) the most frequently examined outcomes. Meta-analysis revealed that relative to High physical activity & Mid sleep, High physical activity and Short sleep was not associated with risk of all-cause mortality (RR=1.05, 95% CI=0.97, 1.14), however Low physical activity and Short Sleep (RR = 1.42, 95% CI = 1.24, 1.63), Low physical activity and Mid Sleep (RR = 1.30, 95% CI = 1.12, 1.52), High physical activity and Long Sleep (RR = 1.16, 95% CI = 1.01, 1.32), and Low physical activity and Long Sleep were associated with risk of all-cause mortality (RR = 1.63, 95% CI = 1.21, 2.20). Conclusions: High levels of physical activity may offset all-cause mortality risks associated with short sleep duration. Low levels of physical activity combined with short sleep duration and any level of physical activity with long sleep duration appear to increase mortality risk. Currently there is limited evidence regarding how dimensions of physical activity, sedentary and sleep behaviours other than duration (e.g., quality, timing, type) are associated with future health status

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

Vandelanotte, CL ORCiD: 0000-0002-4445-8094The 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 ± 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. © 2019 Elsevier Inc

A systematic review of the clinimetric properties of habitual physical activity measures in young children with a motor disability

Aim. To identify and systematically review the clinimetric properties of habitual physical activity (HPA) measures in young children with a motor disability. Method. Five databases were searched for measures of HPA including: children age

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

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