Estimating nitrate intake in the Australian diet: Design and validation of a food frequency questionnaire.

BACKGROUND: Dietary nitrates may play a role in mediating several key physiological processes impacting health and/or exercise performance. However, current methods for assessing dietary nitrate (NO3 - ) consumption are inadequate. The present study aimed to examine the dietary nitrate intake in a sample of 50 healthy adults, as well as test the validity of a purposefully developed food frequency questionnaire (FFQ). METHODS: Dietary nitrate intake was estimated over a week using (i) three 24-h dietary recalls; (ii) a short-term (7-day) FFQ; and (iii) a biomarker (urinary nitrate), in conjunction with a nitrate reference database. RESULTS: Daily dietary nitrate intake estimates were 130.94 mg (average of three 24-h recalls) and 180.62 mg (FFQ). The mean urinary NO3 - excretion was 1974.79 µmol day-1 (or 917.9 µmol L-1 ). Despite the difference between the two dietary assessment methods, there was a moderate positive correlation (r = 0.736, ρ < 0.001) between the two tools. There was also a positive correlation between urinary NO3 - and 24-h recall data (r = 0.632, ρ < 0.001), as well as between urinary NO3 - and FFQ (r = 0.579, ρ < 0.001). CONCLUSIONS: The ability to accurately estimate nitrate intakes depends on having suitable reference methods to estimate the concentrations of nitrate in the food supply, coupled with valid and reliable dietary assessment tools. Based on the findings from the present study, at an individual level, dietary recalls or records may be more accurate in estimating intakes of NO3 - . However, given the lower cost and time needed for administration relative to recalls, the FFQ has merit for estimating NO3 - intakes in health interventions, dietary surveys and surveillance programs.

Evidence that heat acclimation training may alter sleep and incidental activity.

This randomized cross-over study tested the hypothesis that heat acclimation training would detrimentally affect sleep variables and alter incidental physical activity compared to a thermoneutral training control condition. Eight recreationally trained males (V̇O2peak 49±4.9 mL.kg-1.min-1) completed two separate interventions separated by at least 31 days: 5 consecutive day training blocks of moderate-intensity cycling (60 min·day-1 at 50% peak power output) in a hot (34.9±0.7 °C and 53±4 % relative humidity) and a temperate (22.2±2.6 °C; 65±8 % relative humidity) environment. Wrist-mounted accelerometers were worn continuously for the length of the training blocks and recorded physical activity, sleep quality and quantity. Data were analysed in a Bayesian framework, with the results presented as the posterior probability that a coefficient was greater or less than zero. Compared to the temperate training environment, heat acclimation impaired sleep efficiency (Pr ß<0 = .979) and wake on sleep onset (Pr ß>0 = .917). Daily sedentary time was, on average, 35 min longer (Pr ß>0 = .973) and light physical activity time 18 min shorter (Pr ß>0 = .960) during the heat acclimation period. No differences were observed between conditions in sleep duration, subjective sleep quality, or moderate or vigorous physical activity. These findings may suggest that athletes and coaches need to be cognisant that heat acclimation training may alter sleep quality and increase sedentary behaviour.HighlightsFive consecutive days of heat training negatively affected some objective measures of sleep quality and incidental physical activity in recreationally trained athletes.Athletes and coaches need to be aware of the potential unintended consequences of using heat acclimation on sleep behaviours.

Nitrate, nitrite and nitrosamines in the global food supply.

Inorganic nitrate provided by either nitrate salts or food supplements may improve cardiometabolic health. However, current methods to assess dietary nitrate, nitrite and nitrosamine consumption are inadequate. The purpose of this study was to develop a reference database to estimate the levels of nitrate, nitrite and nitrosamines in the global food supply. A systematic literature search was undertaken; of the 5,747 articles screened, 448 met the inclusion criteria. The final database included data for 1,980 food and beverages from 65 different countries. There were 5,105 unique records for nitrate, 2,707 for nitrite, and 954 for nitrosamine. For ease of use, data were sorted into 12 categories; regarding nitrate and nitrite concentrations in food and beverages, 'vegetables and herbs' were most reported in the literature (n = 3,268 and n = 1,200, respectively). For nitrosamines, 'protein foods of animal origin' were most reported (n = 398 records). This database will allow researchers and practitioners to confidently estimate dietary intake of nitrate, nitrite and nitrosamines. When paired with health data, our database can be used to investigate associations between nitrate intake and health outcomes, and/or exercise performance and could support the development of key dietary nitrate intake guidelines.

Evolving the validity of a mental toughness measure: Refined versions of the Mental Toughness Questionnaire-48.

The Mental Toughness Questionnaire-48 (MTQ48) is a 48-item self-report instrument to measure one's level of mental toughness. Despite its wide popularity in psychological studies, the questionnaire has been criticized due to its factorial validity. The present study aimed to re-assess the factorial validity of the instrument and propose alternative models to provide researchers with theoretically and practically useful instruments to measure mental toughness. Two studies were conducted using large samples of university students (Study 1: n = 2186; Study 2: n = 3209). In Study 1, none of one-, four- and six-factor models with 48 items satisfactorily fit the data set. Instead, two refined 18- and 6-item versions of the questionnaire, covering six aspects of mental toughness, were proposed: the Short MTQ and Very Short MTQ. Both measures demonstrated excellent fit to the data. These results were replicated with a larger independent sample in Study 2. With the Short MTQ, it is possible to represent mental toughness as a multidimensional construct consisting of a global mental toughness factor and six specific factors. The Very Short MTQ is a practical tool for occasions where constraints prevent use of the Short MTQ. The refined questionnaires are promising options to measure and understand individuals' mental toughness with the MTQ.

Machine Learning Models for Classifying Physical Activity in Free-Living Preschool Children.

Machine learning (ML) activity classification models trained on laboratory-based activity trials exhibit low accuracy under free-living conditions. Training new models on free-living accelerometer data, reducing the number of prediction windows comprised of multiple activity types by using shorter windows, including temporal features such as standard deviation in lag and lead windows, and using multiple sensors may improve the classification accuracy under free-living conditions. The objective of this study was to evaluate the accuracy of Random Forest (RF) activity classification models for preschool-aged children trained on free-living accelerometer data. Thirty-one children (mean age = 4.0 ± 0.9 years) completed a 20 min free-play session while wearing an accelerometer on their right hip and non-dominant wrist. Video-based direct observation was used to categorize the children's movement behaviors into five activity classes. The models were trained using prediction windows of 1, 5, 10, and 15 s, with and without temporal features. The models were evaluated using leave-one-subject-out-cross-validation. The F-scores improved as the window size increased from 1 to 15 s (62.6%-86.4%), with only minimal improvements beyond the 10 s windows. The inclusion of temporal features increased the accuracy, mainly for the wrist classification models, by an average of 6.2 percentage points. The hip and combined hip and wrist classification models provided comparable accuracy; however, both the models outperformed the models trained on wrist data by 7.9 to 8.2 percentage points. RF activity classification models trained with free-living accelerometer data provide accurate recognition of young children's movement behaviors under real-world conditions.

Effectiveness of Tailored Dietary Counseling in Treating Malnourished Outpatients with Chronic Obstructive Pulmonary Disease: A Randomized Controlled Trial.

BACKGROUND: Malnutrition in patients with chronic obstructive pulmonary disease (COPD) is common and associated with poor prognosis. Nutrition interventions are necessary, but there is a lack of evidence regarding the effectiveness of tailored nutrition advice. OBJECTIVE: This study investigated whether tailored nutrition counseling could improve dietary intake, nutritional status, functional outcomes, and health-related quality of life (QoL) of malnourished outpatients with COPD. DESIGN: We conducted a randomized controlled trial in which participants were randomly assigned to either the intervention group (IG) or the control group (CG). PARTICIPANTS/SETTING: One hundred and twenty malnourished outpatients with COPD participated in the study between May and November 2017 at the National Lung Hospital, Hanoi, Vietnam. INTERVENTION: The IG received tailored nutrition counseling once per month for 3 months based on a specifically developed written nutrition resource for COPD. The CG received the same educational resource at baseline without any discussion. MAIN OUTCOME MEASURES: The main outcome measures were energy and protein intakes, body weight change, nutritional status (Subjective Global Assessment score), muscle strength, and QoL. STATISTICAL ANALYSES: Differences between groups before and after the intervention were assessed using two-way repeated measures analysis of variance. Generalized estimating equation modeling was used to investigate the differences between groups over time. RESULTS: At baseline, there were no significant differences in outcomes of interest between the two groups. After 3 months of intervention, time-intervention interactions for energy intake, protein intake, and body weight change were significant (945 kcal/day, 95% CI 792 to 1,099 kcal/day, P<0.001; 50.0 g protein/day, 95% CI 43.9 to 56.1 g protein/day, P<0.001; and 1.0 kg, 95% CI 0.5 to 1.5 kg, P<0.001, respectively). Subjective Global Assessment scores improved in the IG and worsened in the CG. Significant improvements were found in inspiratory muscle strength in the IG (5.4 cmH2O, 95% CI 2.3 to 8.6 cmH2O, P=0.001) and significant decreases in handgrip strength were found in the CG after 3 months of the intervention (1.4 kg, 95% CI 0.4 to 2.4 kg, P=0.007). There was a significant interaction effect for all QoL scores (analysis of variance two-way repeated, P≤0.003). The IG also significantly improved all QoL scores from baseline to 3 months (P<0.004). CONCLUSIONS: Tailored nutritional counseling has the potential to improve dietary intakes, nutritional status, functional outcomes, and QoL in malnourished outpatients with COPD.

Nutritional status, dietary intake, and health-related quality of life in outpatients with COPD.

BACKGROUND: Malnutrition is common in patients with COPD; however, little is known about its impacts on health-related quality of life (QoL) among patients with COPD. This study aimed to explore the nutritional status and dietary intake among outpatients with COPD in Vietnam and its possible associations with QoL. METHODS: A cross-sectional study was carried out in COPD outpatients visiting the COPD management unit at the National Lung Hospital, Hanoi, Vietnam between May 2017 and July 2017. Consecutive outpatients with a confirmed diagnosis of COPD were recruited with written inform consent. The nutritional status of participants was assessed using Subjective Global Assessment (SGA), and dietary intake via a 24-hour recall interview. The St George Respiratory Questionnaire (SGRQ) for COPD was used to investigate the participants' QoL. Sociodemographic and clinical data were extracted from hospital records. RESULTS: Of 168 COPD outpatients involved in the study, three-quarters (74.4%) were diagnosed as malnourished (SGA B/C) and 81.5% reported unintentional weight loss. Most of the patients did not meet their estimated energy and protein requirements (85.7% and 89.9%, respectively). Malnutrition was significantly associated with disease severity (P=0.039) and ratio of protein intake to estimated requirement (P=0.005). QoL was low for all levels of malnutrition or disease severity, with well-nourished participants and those with less disease severity having better QoL (P=0.006 and P<0.001, respectively). With an extra meal per day, the odds of having malnutrition decreased 5.6 times (P<0.05) and the total SGRQ reduced 3.61 scores (P<0.05) indicating a better QoL. CONCLUSION: Malnutrition and weight loss are prevalent among COPD outpatients. Most of the patients had inadequate dietary intake and low QoL. Nutrition counselling including increasing the number of meals per day with a focus on energy- and protein-rich foods may help improving nutritional status and QoL of patients with COPD in Vietnam.

Which Women are Highly Active Over a 12-Year Period? A Prospective Analysis of Data from the Australian Longitudinal Study on Women's Health.

INTRODUCTION: Current Australian physical activity (PA) guidelines encourage adults to accumulate 150-300 min of moderate to vigorous PA each week. Some critics assert that 300 min is unachievable. OBJECTIVES: The aims of this study were to identify the proportion of younger and mid-aged women who met the 300-min recommendation over a 12-year period, examine how the "highly active" women achieved this level of activity (in terms of walking, moderate activity, and vigorous activity), and to identify the sociodemographic, biological, lifestyle, and work-related determinants of being "highly active". METHODS: Younger (n = 7843) and mid-aged (n = 8043) participants in the Australian Longitudinal Study on Women's Health completed triennial surveys between 2000 and 2013, when their ages were 24.6-36.3 and 52.5-64.5 years, respectively. Self-reported PA was assessed as time spent in walking, moderate activity, and vigorous activity in the previous week; an index of MET.min/week was derived and dichotomized as <1000 MET.min/week (<300 min; not highly active) or ≥1000 MET.min/week (≥300 min; highly active). Generalized estimating equations were used to examine univariable and multivariable associations between a number of sociodemographic, lifestyle, and health variables with PA status (measured at every survey). RESULTS: In the younger cohort, the proportion who were highly active decreased from 40% in 2000 to 31% in 2012. High levels of activity were achieved through a combination of walking (39.1-45.1% of total activity) and vigorous PA (41.8-47.7%). In the mid-age cohort, the proportion of women who were highly active increased from 32% in 2001 to 47% in 2013; this was achieved predominantly through walking (55.8-59.7%). In multi-variable models, the highest odds for being in the high PA category (odds ratios [ORs] ≥ 1.20; p < 0.001) were for younger women who were single, those who worked long full-time hours, those who drank any quantity of alcohol, and those who sat for less than 8 h/day. In the mid-age cohort, the highest odds for being in the high PA category (ORs ≥1.20; p < 0.001) were for women with post-school education, those who were retired, those who were low-risk drinkers (compared with non-drinkers), those who sat for less than 8 h/day, and those with lower levels of stress. DISCUSSION: Our findings clearly indicate that the upper limit of the Australian PA guidelines is achievable for large numbers of women. Factors associated with being highly active were different for younger and mid-age women, but healthy weight, high education, and paid work (full-time in the younger women, part-time in mid-age) were common characteristics of highly active women in both cohorts.

The impact of an m-Health financial incentives program on the physical activity and diet of Australian truck drivers.

BACKGROUND: Chronic diseases are high in truck drivers and have been linked to work routines that promote inactivity and poor diets. This feasibility study examined the extent to which an m-Health financial incentives program facilitated physical activity and healthy dietary choices in Australian truck drivers. METHODS: Nineteen men (mean [SD] age = 47.5 [9.8] years; BMI = 31.2 [4.6] kg/m2) completed the 20-week program, and used an activity tracker and smartphone application (Jawbone UP™) to regulate small positive changes in occupational physical activity, and fruit, vegetable, saturated fat and processed/refined sugar food/beverage choices. Measures (baseline, end-program, 2-months follow-up; April-December 2014) were accelerometer-determined proportions of work time spent physically active, and a workday dietary questionnaire. Statistical (repeated measures ANOVA) and thematic (interviews) analyses assessed program impact. RESULTS: Non-significant increases in the mean proportions of work time spent physically active were found at end-program and follow-up (+1%; 7 mins/day). Fruit (p = 0.023) and vegetable (p = 0.024) consumption significantly increased by one serve/day at end-program. Non-significant improvements in saturated fat (5%) and processed/refined sugar (1%) food/beverage choices were found at end-program and follow-up. Overall, 65% (n = 11) of drivers demonstrated positive changes in physical activity, and at least one dietary choice (e.g. saturated fat) at follow-up. Drivers found the financial incentives component of the program to be a less effective facilitator of change than the activity tracker and smartphone application, although this technology was easier to use for monitoring of physical activity than healthy dietary choices. CONCLUSIONS: Not all drivers benefitted from the program. However, positive changes for different health behaviours were observed in the majority of participants. Outcomes from this feasibility study inform future intervention development for studies with larger samples. TRIAL REGISTRATION: ANZCTR12616001513404 . Registered November 2nd, 2016 (retrospectively registered).

Field evaluation of a random forest activity classifier for wrist-worn accelerometer data.

OBJECTIVES: Wrist-worn accelerometers are convenient to wear and associated with greater wear-time compliance. Previous work has generally relied on choreographed activity trials to train and test classification models. However, validity in free-living contexts is starting to emerge. Study aims were: (1) train and test a random forest activity classifier for wrist accelerometer data; and (2) determine if models trained on laboratory data perform well under free-living conditions. DESIGN: Twenty-one participants (mean age=27.6±6.2) completed seven lab-based activity trials and a 24h free-living trial (N=16). METHODS: Participants wore a GENEActiv monitor on the non-dominant wrist. Classification models recognising four activity classes (sedentary, stationary+, walking, and running) were trained using time and frequency domain features extracted from 10-s non-overlapping windows. Model performance was evaluated using leave-one-out-cross-validation. Models were implemented using the randomForest package within R. Classifier accuracy during the 24h free living trial was evaluated by calculating agreement with concurrently worn activPAL monitors. RESULTS: Overall classification accuracy for the random forest algorithm was 92.7%. Recognition accuracy for sedentary, stationary+, walking, and running was 80.1%, 95.7%, 91.7%, and 93.7%, respectively for the laboratory protocol. Agreement with the activPAL data (stepping vs. non-stepping) during the 24h free-living trial was excellent and, on average, exceeded 90%. The ICC for stepping time was 0.92 (95% CI=0.75-0.97). However, sensitivity and positive predictive values were modest. Mean bias was 10.3min/d (95% LOA=-46.0 to 25.4min/d). CONCLUSIONS: The random forest classifier for wrist accelerometer data yielded accurate group-level predictions under controlled conditions, but was less accurate at identifying stepping verse non-stepping behaviour in free living conditions Future studies should conduct more rigorous field-based evaluations using observation as a criterion measure.

The Effect of Dietary Nitrate Supplementation on Endurance Exercise Performance in Healthy Adults: A Systematic Review and Meta-Analysis.

BACKGROUND: Recent research into the use of dietary nitrates and their role in vascular function has led to it becoming progressively more popular amongst athletes attempting to enhance performance. OBJECTIVE: The objective of this review was to perform a systematic review and meta-analysis of the literature to evaluate the effect of dietary nitrate (NO3-) supplementation on endurance exercise performance. An additional aim was to determine whether the performance outcomes are affected by potential moderator variables. DATA SOURCES: Relevant databases such as Cochrane Library, Embase, PubMed, Ovid, Scopus and Web of Science were searched for the following search terms 'nitrates OR nitrate OR beetroot OR table beet OR garden beet OR red beet AND exercise AND performance' from inception to October 2015. STUDY SELECTION: Studies were included if a placebo versus dietary nitrate-only supplementation protocol was able to be compared, and if a quantifiable measure of exercise performance was ≥30 s (for a single bout of exercise or the combined total for multiple bouts). STUDY APPRAISAL AND SYNTHESIS: The literature search identified 1038 studies, with 47 (76 trials) meeting the inclusion criteria. Data from the 76 trials were extracted for inclusion in the meta-analysis. A fixed-effects meta-analysis was conducted for time trial (TT) (n = 28), time to exhaustion (TTE) (n = 22) and graded-exercise test (GXT) (n = 8) protocols. Univariate meta-regression was used to assess potential moderator variables (exercise type, dose duration, NO3- type, study quality, fitness level and percentage nitrite change). RESULTS: Pooled analysis identified a trivial but non-significant effect in favour of dietary NO3- supplementation [effect size (ES) = -0.10, 95 % Cl = -0.27 to 0.06, p > 0.05]. TTE trials had a small to moderate statistically significant effect in favour of dietary NO3- supplementation (ES = 0.33, 95 % Cl = 0.15-0.50, p < 0.01). GXT trials had a small but non-significant effect in favour of dietary NO3- supplementation in GXT performance measures (ES = 0.25, 95 % Cl = -0.06 to 0.56, p > 0.05). No significant heterogeneity was detected in the meta-analysis. No statistically significant effects were observed from the meta-regression analysis. CONCLUSION: Dietary NO3- supplementation is likely to elicit a positive outcome when testing endurance exercise capacity, whereas dietary NO3- supplementation is less likely to be effective for time-trial performance. Further work is needed to understand the optimal dosing strategies, which population is most likely to benefit, and under which conditions dietary nitrates are likely to be most effective for performance.

Objectively Quantified Physical Activity and Sedentary Behavior in Predicting Visceral Adiposity and Liver Fat.

Objective. Epidemiologic studies suggest an inverse relationship between nonalcoholic fatty liver disease (NAFLD), visceral adipose tissue (VAT), and self-reported physical activity levels. However, subjective measurements can be inaccurate and prone to reporter bias. We investigated whether objectively quantified physical activity levels predicted liver fat and VAT in overweight/obese adults. Methods. Habitual physical activity was measured by triaxial accelerometry for four days (n = 82). Time spent in sedentary behavior (MET < 1.6) and light (MET 1.6 < 3), moderate (MET 3 < 6), and vigorous (MET 6 < 9) physical activity was quantified. Magnetic resonance imaging and spectroscopy were used to quantify visceral and liver fat. Bivariate correlations and hierarchical multiple regression analyses were performed. Results. There were no associations between physical activity or sedentary behavior and liver lipid. Sedentary behavior and moderate and vigorous physical activity accounted for just 3% of variance for VAT (p = 0.14) and 0.003% for liver fat (p = 0.96). Higher levels of VAT were associated with time spent in moderate activity (r = 0.294, p = 0.007), but there was no association with sedentary behavior. Known risk factors for obesity-related NAFLD accounted for 62% and 40% of variance in VAT and liver fat, respectively (p < 0.01). Conclusion. Objectively measured levels of habitual physical activity and sedentary behavior did not influence VAT or liver fat.

Estimating Physical Activity and Sedentary Behavior in a Free-Living Context: A Pragmatic Comparison of Consumer-Based Activity Trackers and ActiGraph Accelerometry.

BACKGROUND: Activity trackers are increasingly popular with both consumers and researchers for monitoring activity and for promoting positive behavior change. However, there is a lack of research investigating the performance of these devices in free-living contexts, for which findings are likely to vary from studies conducted in well-controlled laboratory settings. OBJECTIVE: The aim was to compare Fitbit One and Jawbone UP estimates of steps, moderate-to-vigorous physical activity (MVPA), and sedentary behavior with data from the ActiGraph GT3X+ accelerometer in a free-living context. METHODS: Thirty-two participants were recruited using convenience sampling; 29 provided valid data for this study (female: 90%, 26/29; age: mean 39.6, SD 11.0 years). On two occasions for 7 days each, participants wore an ActiGraph GT3X+ accelerometer on their right hip and either a hip-worn Fitbit One (n=14) or wrist-worn Jawbone UP (n=15) activity tracker. Daily estimates of steps and very active minutes were derived from the Fitbit One (n=135 days) and steps, active time, and longest idle time from the Jawbone UP (n=154 days). Daily estimates of steps, MVPA, and longest sedentary bout were derived from the corresponding days of ActiGraph data. Correlation coefficients and Bland-Altman plots with examination of systematic bias were used to assess convergent validity and agreement between the devices and the ActiGraph. Cohen's kappa was used to assess the agreement between each device and the ActiGraph for classification of active versus inactive (≥10,000 steps per day and ≥30 min/day of MVPA) comparable with public health guidelines. RESULTS: Correlations with ActiGraph estimates of steps and MVPA ranged between .72 and .90 for Fitbit One and .56 and .75 for Jawbone UP. Compared with ActiGraph estimates, both devices overestimated daily steps by 8% (Fitbit One) and 14% (Jawbone UP). However, mean differences were larger for daily MVPA (Fitbit One: underestimated by 46%; Jawbone UP: overestimated by 50%). There was systematic bias across all outcomes for both devices. Correlations with ActiGraph data for longest idle time (Jawbone UP) ranged from .08 to .19. Agreement for classifying days as active or inactive using the ≥10,000 steps/day criterion was substantial (Fitbit One: κ=.68; Jawbone UP: κ=.52) and slight-fair using the criterion of ≥30 min/day of MVPA (Fitbit One: κ=.40; Jawbone UP: κ=.14). CONCLUSIONS: There was moderate-strong agreement between the ActiGraph and both Fitbit One and Jawbone UP for the estimation of daily steps. However, due to modest accuracy and systematic bias, they are better suited for consumer-based self-monitoring (eg, for the public consumer or in behavior change interventions) rather than to evaluate research outcomes. The outcomes that relate to health-enhancing MVPA (eg, "very active minutes" for Fitbit One or "active time" for Jawbone UP) and sedentary behavior ("idle time" for Jawbone UP) should be used with caution by consumers and researchers alike.

Safety, adherence and efficacy of exercise training in solid-organ transplant candidates: A systematic review.

BACKGROUND: Patients awaiting solid-organ transplantation may be encouraged to undertake exercise training to improve pre- and post-transplant outcomes. However, the safety, adherence and efficacy of exercise training in this population remain unclear. METHODS: All randomized, non-randomized and non-controlled trials of exercise training interventions in solid-organ transplant candidates were included. The Cochrane risk of bias tool and a modified Newcastle-Ottawa scale were used to assess procedural quality. Safety was defined as the number of reported adverse events during exercise training. Adherence was evaluated from session attendance, and efficacy as changes in cardiorespiratory fitness (CRF), exercise capacity, muscular strength, health-related quality of life (HR-QoL) and lung function. RESULTS: Eleven studies involving 874 patients were included: four randomized controlled, one non-randomized controlled and six non-controlled trials. Six studies included heart transplant candidates and five involved patients awaiting lung transplantation. Three trials included aerobic-only training, one incorporated resistance-only exercise and seven combined modalities. Twelve adverse events were reported with four due to exercise, although methods to collect these data were often omitted. Exercise adherence ranged from 82.5% to 100%, but was poorly described. No significant between-group changes attributable to exercise training were demonstrated. However, significant within-group improvements in CRF, exercise capacity, muscular strength, lung function and HR-QoL were observed. CONCLUSIONS: Patients awaiting heart or lung transplant appear to tolerate exercise training despite the larger number of adverse events compared to other high-risk populations. Exercise training demonstrated within-group benefits for several outcomes, with no significant between-group differences. Randomized controlled trials with sufficient statistical power are required for all solid-organ transplant candidates.

Long-term Effects of Physical Activity Level on Changes in Healthy Body Mass Index Over 12 Years in Young Adult Women.

OBJECTIVES: To examine the effects of overall level and timing of physical activity (PA) on changes from a healthy body mass index (BMI) category over 12 years in young adult women. PATIENTS AND METHODS: Participants in the Australian Longitudinal Study on Women's Health (younger cohort, born 1973-1978) completed surveys between 2000 (age 22-27 years) and 2012 (age 34-39 years). Physical activity was measured in 2000, 2003, 2006, and 2009 and was categorized as very low, low, active, or very active at each survey, and a cumulative PA score for this 9-year period was created. Logistic regression was used to examine relationships between PA accumulated across all surveys (cumulative PA model) and PA at each survey (critical periods PA model), with change in BMI category (from healthy to overweight or healthy to obese) from 2000 to 2012. RESULTS: In women with a healthy BMI in 2000, there were clear dose-response relationships between accumulated PA and transition to overweight (P=.03) and obesity (P<.01) between 2000 and 2012. The critical periods analysis indicated that very active levels of PA at the 2006 survey (when the women were 28-33 years old) and active or very active PA at the 2009 survey (age 31-36 years) were most protective against transitioning to overweight and obesity. CONCLUSION: These findings confirm that maintenance of very high PA levels throughout young adulthood will significantly reduce the risk of becoming overweight or obese. There seems to be a critical period for maintaining high levels of activity at the life stage when many women face competing demands of caring for infants and young children.

Project Energise: Using participatory approaches and real time computer prompts to reduce occupational sitting and increase work time physical activity in office workers.

OBJECTIVES: This efficacy study assessed the added impact real time computer prompts had on a participatory approach to reduce occupational sedentary exposure and increase physical activity. DESIGN: Quasi-experimental. METHODS: 57 Australian office workers (mean [SD]; age=47 [11] years; BMI=28 [5]kg/m2; 46 men) generated a menu of 20 occupational 'sit less and move more' strategies through participatory workshops, and were then tasked with implementing strategies for five months (July-November 2014). During implementation, a sub-sample of workers (n=24) used a chair sensor/software package (Sitting Pad) that gave real time prompts to interrupt desk sitting. Baseline and intervention sedentary behaviour and physical activity (GENEActiv accelerometer; mean work time percentages), and minutes spent sitting at desks (Sitting Pad; mean total time and longest bout) were compared between non-prompt and prompt workers using a two-way ANOVA. RESULTS: Workers spent close to three quarters of their work time sedentary, mostly sitting at desks (mean [SD]; total desk sitting time=371 [71]min/day; longest bout spent desk sitting=104 [43]min/day). Intervention effects were four times greater in workers who used real time computer prompts (8% decrease in work time sedentary behaviour and increase in light intensity physical activity; p<0.01). Respective mean differences between baseline and intervention total time spent sitting at desks, and the longest bout spent desk sitting, were 23 and 32min/day lower in prompt than in non-prompt workers (p<0.01). CONCLUSIONS: In this sample of office workers, real time computer prompts facilitated the impact of a participatory approach on reductions in occupational sedentary exposure, and increases in physical activity.

Chronic disease risks and use of a smartphone application during a physical activity and dietary intervention in Australian truck drivers.

OBJECTIVE: This study examined chronic disease risks and the use of a smartphone activity tracking application during an intervention in Australian truck drivers (April-October 2014). METHODS: Forty-four men (mean age=47.5 [SD 9.8] years) completed baseline health measures, and were subsequently offered access to a free wrist-worn activity tracker and smartphone application (Jawbone UP) to monitor step counts and dietary choices during a 20-week intervention. Chronic disease risks were evaluated against guidelines; weekly step count and dietary logs registered by drivers in the application were analysed to evaluate use of the Jawbone UP. RESULTS: Chronic disease risks were high (e.g. 97% high waist circumference [≥ 94 cm]). Eighteen drivers (41%) did not start the intervention; smartphone technical barriers were the main reason for drop out. Across 20-weeks, drivers who used the Jawbone UP logged step counts for an average of 6 [SD 1] days/week; mean step counts remained consistent across the intervention (weeks 1-4=8,743[SD 2,867] steps/day; weeks 17-20=8,994[SD 3,478] steps/day). The median number of dietary logs significantly decreased from start (17 [IQR 38] logs/weeks) to end of the intervention (0 [IQR 23] logs/week; p<0.01); the median proportion of healthy diet choices relative to total diet choices logged increased across the intervention (weeks 1-4=38[IQR 21]%; weeks 17-20=58[IQR 18]%). CONCLUSIONS: Step counts were more successfully monitored than dietary choices in those drivers who used the Jawbone UP. IMPLICATIONS: Smartphone technology facilitated active living and healthy dietary choices, but also prohibited intervention engagement in a number of these high-risk Australian truck drivers.

Past-day recall of sedentary time: Validity of a self-reported measure of sedentary time in a university population.

OBJECTIVES: To assess the validity of the Past-day Adults' Sedentary Time-University (PAST-U) questionnaire, modified for a university population, compared with activPAL. DESIGN: Participants (n=57, age=18-55 years, 47% female, 65% students) were recruited from the University of Queensland (students and staff). METHODS: Participants answered the PAST-U questionnaire, which asked about time spent sitting or lying down for work, study, travel, television viewing, leisure-time computer use, reading, eating, socialising and other purposes, during the previous day. Times reported for these questions were summed to provide a measure of total sedentary time. Participants also wore an activPAL device for the full day prior to completing the questionnaire and recorded their wake and sleep times in an activity log. Total waking sedentary time derived from the activPAL was used as the criterion measure. Correlation (intraclass correlation coefficient, ICC) and agreement (Bland-Altman plots) between PAST-U and activPAL sedentary time were examined. RESULTS: Participants were sedentary (activPAL-determined) for 66% of waking hours. The correlation between PAST-U and activPAL sedentary time for the whole sample was ICC=0.64 [95% confidence interval (CI)=0.45, 0.77]; and higher for non-students (ICC=0.78, 95%CI 0.52, 0.91) than students (ICC=0.59, 95%CI 0.33, 0.77). Bland-Altman plots revealed that the mean difference between the two measures was 5min although limits of agreement were wide (95% limits of agreement: -3.9 to 4.1h). CONCLUSIONS: The PAST-U provides an acceptable measure of sedentary time in this population, which included students and adults with high workplace sitting time.