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The descriptive epidemiology of total physical activity, muscle-strengthening exercises and sedentary behaviour among Australian adults--results from the National Nutrition and Physical Activity Survey.

ABSTRACT: The current Australia's Physical Activity and Sedentary Behaviour Guidelines recommend that adults engage in regular moderate-to-vigorous-intensity physical activity (MVPA) and strength training (ST), and minimise time spent in sedentary behaviours (SB). However, evidence about the specific individual and concurrent distribution of these behaviours in Australia is scarce. Therefore, the aim of this study was to determine the prevalence and sociodemographic correlates of MVPA, ST and SB in a national-representative sample of Australian adults.Data were collected using face-to-face interviews, as part of the National Nutrition and Physical Activity Survey 2011-12. The population-weighted proportions meeting the MVPA (≥ 150 min/week), ST (≥ 2 sessions/week) and combined MVPA-ST guidelines, and proportions classified as having 'low levels of SB' (< 480 min/day) were calculated, and their associations with selected sociodemographic and health-related variables were assessed using multiple logistic regression analyses. This was also done for those at potentially 'high-risk', defined as insufficient MVPA-ST and 'high-sedentary' behaviour.Out of 9345 participants (response rate = 77.0 %), aged 18-85 years, 52.6 % (95 % CI: 51.2 %-54.0 %), 18.6 % (95 % CI: 17.5 %-19.7 %) and 15.0 % (95 % CI: 13.9 %-16.1 %) met the MVPA, ST and combined MVPA-ST guidelines, respectively. Female gender, older age, low/medium education, poorer self-rated health, being classified as underweight or obese, and being a current smoker were independently associated with lower odds of meeting the MVPA, ST and combined MVPA-ST guidelines. A total of 78.9 % (95 % CI: 77.9 %-80.0 %) were classified as having low levels of SB. Females, older adults and those with lower education were more likely to report lower levels of SB, whilst those with poor self-rated health and obese individuals were less likely to report lower levels of SB (i.e. SB = ≥ 480 min/day). A total of 8.9 % (95 % CI: 8.1 %-9.6 %) were categorised as individuals at potentially 'high-risk'. Those with poorer self-rated health, obese individuals, those aged 25-44, and current smokers were more likely to be in the 'high risk' group.The large majority of Australian adults do not meet the full physical activity guidelines and/or report excessive SB. Our results call for public health interventions to reduce physical inactivity and SB in Australia, particularly among the subgroups at the highest risk of these unhealthy behaviours.

SUBMITTER: Bennie JA

PROVIDER: S-EPMC4727339 | biostudies-other | 2016

REPOSITORIES: biostudies-other

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Project description:BackgroundLittle is known regarding the patterning and socio-demographic distribution of multiple sedentary behaviours in children. The aims of this study were to: 1) describe the leisure-time sedentary behaviour of 9-10 year old British children, and 2) establish associations with objectively-measured sedentary time.MethodsCross-sectional analysis in the SPEEDY study (Sport, Physical activity and Eating behaviour: Environmental Determinants in Young people) (N=1513, 44.3% boys). Twelve leisure-time sedentary behaviours were assessed by questionnaire. Objectively-measured leisure-time sedentary time (Actigraph GT1M, <100 counts/minute) was assessed over 7 days. Differences by sex and socioeconomic status (SES) in self-reported sedentary behaviours were tested using Kruskal-Wallis tests. The association between objectively-measured sedentary time and the separate sedentary behaviours (continuous (minutes) and categorised into 'none' 'low' or 'high' participation) was assessed using multi-level linear regression.ResultsSex differences were observed for time spent in most sedentary behaviours (all p ≤ 0.02), except computer use. Girls spent more time in combined non-screen sedentary behaviour (median, interquartile range: girls: 770.0 minutes, 390.0-1230.0; boys: 725.0, 365.0 - 1182.5; p = 0.003), whereas boys spent more time in screen-based behaviours (girls: 540.0, 273.0 - 1050.0; boys: 885.0, 502.5 - 1665.0; p < 0.001). Time spent in five non-screen behaviours differed by SES, with higher values in those of higher SES (all p ≤ 0.001). Regression analyses with continuous exposures indicated that reading (β = 0.1, p < 0.001) and watching television (β = 0.04, p < 0.01) were positively associated with objectively-measured sedentary time, whilst playing board games (β = -0.12, p < 0.05) was negatively associated. Analysed in categorical form, sitting and talking (vs. none: 'low' β = 26.1,ns; 'high' 30.9, p < 0.05), playing video games (vs. none: 'low' β = 49.1, p < 0.01; 'high' 60.2, p < 0.01) and watching television (vs. lowest tertile: middle β = 22.2,ns; highest β = 31.9, p < 0.05) were positively associated with objectively-measured sedentary time whereas talking on the phone (vs. none: 'low' β = -38.5, p < 0.01; 'high' -60.2, p < 0.01) and using a computer/internet (vs. none: 'low' β = -30.7, p < 0.05; 'high' -4.2,ns) were negatively associated.ConclusionsBoys and girls and children of different socioeconomic backgrounds engage in different leisure-time sedentary behaviours. Whilst a number of behaviours may be predictive of total sedentary time, collectively they explain little overall variance. Future studies should consider a wide range of sedentary behaviours and incorporate objective measures to quantify sedentary time where possible.

Project description:Lower levels of physical activity (PA) and sedentary behaviour (SB) have been associated with increased cardiometabolic risk among children. However, little is known about the independent and combined associations of PA and SB as well as different types of these behaviours with cardiometabolic risk in children. We therefore investigated these relationships among children.The subjects were a population sample of 468 children 6-8 years of age. PA and SB were assessed by a questionnaire administered by parents and validated by a monitor combining heart rate and accelerometry measurements. We assessed body fat percentage, waist circumference, blood glucose, serum insulin, plasma lipids and lipoproteins and blood pressure and calculated a cardiometabolic risk score using population-specific Z-scores and a formula waist circumference?+?insulin?+?glucose?+?triglycerides - HDL cholesterol?+?mean of systolic and diastolic blood pressure. We analysed data using multivariate linear regression models.Total PA was inversely associated with the cardiometabolic risk score (??=?-0.135, p?=?0.004), body fat percentage (??=?-0.155, p?<?0.001), insulin (??=?-0.099, p?=?0.034), triglycerides (??=?-0.166, p?<?0.001), VLDL triglycerides (??=?-0.230, p?<?0.001), VLDL cholesterol (??=?-0.168, p?=?0.001), LDL cholesterol (??=?-0.094, p?=?0.046) and HDL triglycerides (??=?-0.149, p?=?0.004) and directly related to HDL cholesterol (??=?0.144, p?=?0.002) adjusted for age and gender. Unstructured PA was inversely associated with the cardiometabolic risk score (??=?-0.123, p?=?0.010), body fat percentage (??=?-0.099, p?=?0.027), insulin (??=?-0.108, p?=?0.021), triglycerides (??=?-0.144, p?=?0.002), VLDL triglycerides (??=?-0.233, p?<?0.001) and VLDL cholesterol (??=?-0.199, p?<?0.001) and directly related to HDL cholesterol (??=?0.126, p?=?0.008). Watching TV and videos was directly related to the cardiometabolic risk score (??=?0.135, p?=?0.003), body fat percentage (??=?0.090, p?=?0.039), waist circumference (??=?0.097, p?=?0.033) and systolic blood pressure (??=?0.096, p?=?0.039). Resting was directly associated with the cardiometabolic risk score (??=?0.092, p?=?0.049), triglycerides (??=?0.131, p?=?0.005), VLDL triglycerides (??=?0.134, p?=?0.009), VLDL cholesterol (??=?0.147, p?=?0.004) and LDL cholesterol (??=?0.105, p?=?0.023). Other types of PA and SB had less consistent associations with cardiometabolic risk factors.The results of our study emphasise increasing total and unstructured PA and decreasing watching TV and videos and other sedentary behaviours to reduce cardiometabolic risk among children.ClinicalTrials.gov Identifier: NCT01803776.

Project description:BackgroundShorter gestation or smaller birth size are indicators of a suboptimal fetal environment and negatively impact short- and long-term offspring health. Understanding how modifiable maternal behaviours, such as moderate-to-vigorous intensity physical activity (MVPA) or sedentary behaviour (SED), improve fetal outcomes could inform strategies to improve health across the lifespan.ObjectivesThe objective of this study was to examine the association of MVPA and SED across pregnancy trimesters on gestational age at delivery and newborn anthropometrics.MethodsThe MoM Health Study measured SED (thigh-mounted activPAL3 micro) and MVPA (waist-worn Actigraph GTX3) in each trimester of pregnancy. Birth outcomes (gestational age at delivery, birthweight, birth length, and head circumference) were abstracted from medical records and used to calculate ponderal index (grams*100/cm3 ) and size-for-gestational age percentiles. Associations of group-based trajectories and trimester-specific SED and MVPA with birth outcomes were analysed using regression models.ResultsLow, medium, and high trajectory groups were generated SED and MVPA in 103 and 99 pregnant women, respectively. High vs low SED trajectory was associated with earlier gestational age at delivery (β -1.03 weeks, 95% CI -2.01, -0.06), larger head circumference (β 0.83 cm, 95% CI 0.24, 1.63), longer birth length (β 1.37 cm, 95% CI 0.09, 2.64), and lower ponderal index (β -0.24 g*100/cm3 , 95% CI -0.42, -0.06), after adjustment for demographics, pre-pregnancy BMI, and (for newborn anthropometric outcomes) gestational age. The association of high SED with lower ponderal index was the most robust across progressively adjusted models (β -0.25 g*100/cm3 , 95% CI -0.44, -0.07). SED trajectory was not associated with birthweight or size-for-gestational age. High vs low MVPA trajectory was only associated with smaller head circumference (β -0.86 cm, 95% CI -1.70, -0.02).ConclusionsHigher SED during pregnancy may result in shorter gestation and inhibited fetal growth. Further research evaluating the effect of reducing SED during pregnancy on birth outcomes is warranted.

Project description:The impact of bronchiectasis on sedentary behaviour and physical activity is unknown. It is important to explore this to identify the need for physical activity interventions and how to tailor interventions to this patient population. We aimed to explore the patterns and correlates of sedentary behaviour and physical activity in bronchiectasis.Physical activity was assessed in 63 patients with bronchiectasis using an ActiGraph GT3X+ accelerometer over seven days. Patients completed: questionnaires on health-related quality-of-life and attitudes to physical activity (questions based on an adaption of the transtheoretical model (TTM) of behaviour change); spirometry; and the modified shuttle test (MST). Multiple linear regression analysis using forward selection based on likelihood ratio statistics explored the correlates of sedentary behaviour and physical activity dimensions. Between-group analysis using independent sample t-tests were used to explore differences for selected variables.Fifty-five patients had complete datasets. Average daily time, mean(standard deviation) spent in sedentary behaviour was 634(77)mins, light-lifestyle physical activity was 207(63)mins and moderate-vigorous physical activity (MVPA) was 25(20)mins. Only 11% of patients met recommended guidelines. Forced expiratory volume in one-second percentage predicted (FEV1% predicted) and disease severity were not correlates of sedentary behaviour or physical activity. For sedentary behaviour, decisional balance 'pros' score was the only correlate. Performance on the MST was the strongest correlate of physical activity. In addition to the MST, there were other important correlate variables for MVPA accumulated in ?10-minute bouts (QOL-B Social Functioning) and for activity energy expenditure (Body Mass Index and QOL-B Respiratory Symptoms).Patients with bronchiectasis demonstrated a largely inactive lifestyle and few met the recommended physical activity guidelines. Exercise capacity was the strongest correlate of physical activity, and dimensions of the QOL-B were also important. FEV1% predicted and disease severity were not correlates of sedentary behaviour or physical activity. The inclusion of a range of physical activity dimensions could facilitate in-depth exploration of patterns of physical activity. This study demonstrates the need for interventions targeted at reducing sedentary behaviour and increasing physical activity, and provides information to tailor interventions to the bronchiectasis population.NCT01569009 ("Physical Activity in Bronchiectasis").

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The descriptive epidemiology of total physical activity, muscle-strengthening exercises and sedentary behaviour among Australian adults--results from the National Nutrition and Physical Activity Survey.

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