Sleep quantity and quality during consecutive day heat training with the inclusion of cold-water immersion recovery.

Exercise in the heat is a common occurrence among athletes and often is intentional in order to gain heat acclimation benefits, however, little is known about how such training may affect sleep. Therefore, this study investigated five days of training in the heat of varying intensity and duration and inclusion of cold-water immersion (CWI) recovery on sleep quantity and quality. Thirty recreationally-trained male participants completed five days of heat training (HT) and were randomised into three interventions including (i) 90 min cycling at 40% power at maximal aerobic capacity (Pmax) with 15 min passive recovery (90HT); (ii) 90 min cycling at 40% Pmax with 15 min CWI recovery (90CWI); or (iii) 30 min cycling alternating between 40% and 70% Pmax, with 15 min passive recovery (30HT). Sleep quality and quantity were assessed using Actigraphy and sleep diaries during five baseline nights (BASE) and five nights of HT which included subjective sleep quality and objective assessments of sleep quantity and quality. Total time asleep and perceived sleep quality were reduced, while awake duration and wake after sleep onset (WASO) were increased (p = 0.001-0.01) during HT compared to BASE. Latency was shorter for 30HT compared to 90HT during HT (p = 0.02), however, no differences between interventions for all other sleep variables (p > 0.05). The reduction in total sleep time due to increases in average wake duration during HT may be due to the unaccustomed increased in training frequency. Of note, reducing training in the heat duration per day improved sleep latency and sleep quality with no effect on total sleep time, while the addition of CWI has minimal effect on sleep quality or quantity.

Walking with Diabetes (WW-DIAB) programme a walking programme for Indonesian type 2 diabetes mellitus patients: A pilot randomised controlled trial.

OBJECTIVES: This pilot study aimed to examine the feasibility and effectiveness of a pedometer-based walking programme in Indonesian type 2 diabetes mellitus patients. METHODS: Feasibility was assessed by monitoring participant recruitment, retention, and adherence to the step-monitoring and recording instructions. Effectiveness was assessed in a pilot randomised controlled trial. Participants were type 2 diabetes mellitus patients randomly assigned to a pedometer-only (PED-only) group (n = 22) and a pedometer with text message support (PED+) group (n = 21). Outcomes were step counts, self-reported physical activity, social cognitive constructs, glycaemic parameters, and health-related quality of life. These were assessed at baseline, 12-week intervention, and 12 weeks later. Longitudinal analyses using generalised estimating equations were carried out to assess treatment and time effects on study outcomes. RESULTS: All but one participant (98%) attended 12- and 24-week data collection follow-ups. Throughout the study period, 82% of PED+ participants submitted their daily steps log. Daily steps increased in both groups (p < 0.001) but more in the PED+ group (2064 more steps at week 24, 95% confidence interval: 200-3925, p = 0.03). Self-reported physical activity levels and glycaemic parameters increased similarly in the two groups over time (p < 0.05). Improvements in social cognitive processes were seen only in the PED+ group (p < 0.05). There were no significant improvements in health-related quality of life. CONCLUSION: This study provides preliminary evidence that a pedometer-based walking programme, with or without additional support, is feasible and improves physical activity and glucose levels in Indonesian type 2 diabetes mellitus patients. Greater increases in step counts can result from the provision of text message support and education materials than from the provision of a pedometer only.

Adolescent's perceptions of parental influences on physical activity.

BACKGROUND: Youth physical activity engagement is a key component of contemporary health promotion strategies. Parents have potential to influence the physical activity behaviours of their children. The purpose of this study was to explore associations between adolescent self-reported physical activity, parent physical activity and perceptions of parental influence as measured by the Children's Physical Activity Correlates (CPAC) questionnaire. METHODS: This investigation included a total of 146 adolescents and their parents. Self-reported measures of physical activity were obtained using the International Physical Activity Questionnaire for Adolescents and International Physical Activity Questionnaire for adolescents and their parents respectively. Adolescent perceptions of parental role modelling, support, and encouragement were measured with the parental influences scales of the CPAC. RESULTS: Ordinary least squares regression indicated that perceptions of parental role modelling (ß=197.41, 95% CI 34.33-360.49, p=0.031) was positively associated with adolescent self-reported moderate-to-vigorous physical activity with the overall model accounting for a small amount of the variance (R2=0.076). CONCLUSION: These results are in agreement with previous research indicating that parents play a small, albeit vital role in the physical activity engagement of their children. Public health campaigns with the aim of promoting youth physical activity should endeavour to incorporate parents into their interventions.

Adolescent Self-Reported Physical Activity and Autonomy: A Case for Constrained and Structured Environments?

The provision of autonomy supportive environments that promote physical activity engagement have become popular in contemporary youth settings. However, questions remain about whether adolescent perceptions of their autonomy have implications for physical activity. The purpose of this investigation was to examine the association between adolescents' self-reported physical activity and their perceived autonomy. Participants (n = 384 adolescents) aged between 12 and 15 years were recruited from six secondary schools in metropolitan Brisbane, Australia. Self-reported measures of physical activity and autonomy were obtained. Logistic regression with inverse probability weights were used to examine the association between autonomy and the odds of meeting youth physical activity guidelines. Autonomy (OR 0.61, 95% CI 0.49-0.76) and gender (OR 0.62, 95% CI 0.46-0.83) were negatively associated with meeting physical activity guidelines. However, the model explained only a small amount of the variation in whether youth in this sample met physical activity guidelines (R(2) = 0.023). For every 1 unit decrease in autonomy (on an index from 1 to 5), participants were 1.64 times more likely to meet physical activity guidelines. The findings, which are at odds with several previous studies, suggest that interventions designed to facilitate youth physical activity should limit opportunities for youth to make independent decisions about their engagement. However, the small amount of variation explained by the predictors in the model is a caveat, and should be considered prior to applying such suggestions in practical settings. Future research should continue to examine a larger age range, longitudinal observational or intervention studies to examine assertions of causality, as well as objective measurement of physical activity. Key pointsAutonomy was negatively associated with meeting physical activity recommendationsThe findings suggest that more structured environments would facilitate physical activityThe small amount of variation explained by the predictors in the model is a caveat.

Reliability of a wellness inventory for use among adolescent females aged 12-14 years.

BACKGROUND: The wellness construct has application in a number of fields including education, healthcare and counseling, particularly with regard to female adolescents. The effective measurement of wellness in adolescents can assist researchers and practitioners in determining lifestyle behaviors in which they are lacking. Behavior change interventions can then be designed which directly aid in the promotion of these areas. METHODS: The 5-Factor Wellness Inventory (designed to measure the Indivisible Self model of wellness) is a popular instrument for measuring the broad aspects of wellness amongst adolescents. The instrument comprises 97 items contributing to 17 subscales, five dimension scores, four context scores, total wellness score, and a life satisfaction index. This investigation evaluated the test-retest (intra-rater) reliability of the 5F-Wel instrument in repeated assessments (seven days apart) among adolescent females aged 12-14 years. Percentages of exact agreement for individual items, and the number of respondents who scored within ±5, ±7.5 and ±10 points for total wellness and the five summary dimension scores were calculated. RESULTS: Overall, 46 (95.8%) participants responded with complete data and were included in the analysis. Item agreement ranged from 47.8% to 100% across the 97 items (median 69.9%, interquartile range 60.9%-73.9%). The percentage of respondents who scored within ±5, ±7.5 and ±10 points for total wellness at the re-assessment was 87.0%, 97.8% and 97.8% respectively. The percentage of respondents who scored within ±5, ±7.5 and ±10 for the domain scores at the reassessment ranged between 54.3-76.1%, 78.3-95.7% and 89.1-95.7% respectively across the five dimensions. CONCLUSIONS: These findings suggest there was considerable variation in agreement between the two assessments on some individual items. However, the total wellness score and the five dimension summary scores remained comparatively stable between assessments.

The association between adolescent self-reported physical activity and wellness: the missing piece for youth wellness programs.

PURPOSE: Potential positive associations between youth physical activity and wellness scores could emphasize the value of youth physical activity engagement and promotion interventions, beyond the many established physiological and psychological benefits of increased physical activity. The purpose of this study was to explore the associations between adolescents' self-reported physical activity and wellness. METHODS: This investigation included 493 adolescents (165 males and 328 females) aged between 12 and 15 years. The participants were recruited from six secondary schools of varying socioeconomic status within a metropolitan area. Students were administered the Five-Factor Wellness Inventory and the International Physical Activity Questionnaire for Adolescents to assess both wellness and physical activity, respectively. RESULTS: Data indicated that significant associations between physical activity and wellness existed. Self-reported physical activity was shown to be positively associated with four dimensions including friendship, gender identity, spirituality, and exercise-the higher order factor physical self and total wellness, and negatively associated with self-care, self-worth, love, and cultural identity. CONCLUSION: This study suggests that relationships exist between self-reported physical activity and various elements of wellness. Future research should use controlled trials of physical activity and wellness to establish causal links among youth populations. Understanding the nature of these relationships, including causality, has implications for the justification of youth physical activity promotion interventions and the development of youth physical activity engagement programs.

Practical physical activity measurement in youth: a review of contemporary approaches.

BACKGROUND: The accurate evaluation of physical activity levels amongst youth is critical for quantifying physical activity behaviors and evaluating the effect of physical activity interventions. The purpose of this review is to evaluate contemporary approaches to physical activity evaluation amongst youth. DATA SOURCES: The literature from a range of sources was reviewed and synthesized to provide an overview of contemporary approaches for measuring youth physical activity. RESULTS: Five broad categories are described: self-report, instrumental movement detection, biological approaches, direct observation, and combined methods. Emerging technologies and priorities for future research are also identified. CONCLUSIONS: There will always be a trade-off between accuracy and available resources when choosing the best approach for measuring physical activity amongst youth. Unfortunately, cost and logistical challenges may prohibit the use of "gold standard" physical activity measurement approaches such as doubly labelled water. Other objective methods such as heart rate monitoring, accelerometry, pedometry, indirect calorimetry, or a combination of measures have the potential to better capture the duration and intensity of physical activity, while self-reported measures are useful for capturing the type and context of activity.

Assigning metabolic equivalent values to the 2002 census occupational classification system.

BACKGROUND: The Current Population Survey (CPS) and the American Time Use Survey (ATUS) use the 2002 census occupation system to classify workers into 509 separate occupations arranged into 22 major occupational categories. METHODS: We describe the methods and rationale for assigning detailed Metabolic Equivalent (MET) estimates to occupations and present population estimates (comparing outputs generated by analysis of previously published summary MET estimates to the detailed MET estimates) of intensities of occupational activity using the 2003 ATUS data comprised of 20,720 respondents, 5323 (2917 males and 2406 females) of whom reported working 6+ hours at their primary occupation on their assigned reporting day. RESULTS: Analysis using the summary MET estimates resulted in 4% more workers in sedentary occupations, 6% more in light, 7% less in moderate, and 3% less in vigorous compared with using the detailed MET estimates. The detailed estimates are more sensitive to identifying individuals who do any occupational activity that is moderate or vigorous in intensity resulting in fewer workers in sedentary and light intensity occupations. CONCLUSIONS: Since CPS/ATUS regularly captures occupation data it will be possible to track prevalence of the different intensity levels of occupations. Updates will be required with inevitable adjustments to future occupational classification systems.

Correction: Expected values for pedometer-determined physical activity in older populations.

Correction to Tudor-Locke C, Hart TL, Washington TL: Expected values for pedometer-determined physical activity in older populations. International Journal of Behavioral Nutrition and Physical Activity 2009, 6:59.

Expected values for pedometer-determined physical activity in older populations.

The purpose of this review is to update expected values for pedometer-determined physical activity in free-living healthy older populations. A search of the literature published since 2001 began with a keyword (pedometer, "step counter," "step activity monitor" or "accelerometer AND steps/day") search of PubMed, Cumulative Index to Nursing & Allied Health Literature (CINAHL), SportDiscus, and PsychInfo. An iterative process was then undertaken to abstract and verify studies of pedometer-determined physical activity (captured in terms of steps taken; distance only was not accepted) in free-living adult populations described as >/= 50 years of age (studies that included samples which spanned this threshold were not included unless they provided at least some appropriately age-stratified data) and not specifically recruited based on any chronic disease or disability. We identified 28 studies representing at least 1,343 males and 3,098 females ranging in age from 50-94 years. Eighteen (or 64%) of the studies clearly identified using a Yamax pedometer model. Monitoring frames ranged from 3 days to 1 year; the modal length of time was 7 days (17 studies, or 61%). Mean pedometer-determined physical activity ranged from 2,015 steps/day to 8,938 steps/day. In those studies reporting such data, consistent patterns emerged: males generally took more steps/day than similarly aged females, steps/day decreased across study-specific age groupings, and BMI-defined normal weight individuals took more steps/day than overweight/obese older adults. The range of 2,000-9,000 steps/day likely reflects the true variability of physical activity behaviors in older populations. More explicit patterns, for example sex- and age-specific relationships, remain to be informed by future research endeavors.

Expected values for pedometer-determined physical activity in youth.

This review assembles pedometry literature focused on youth, with particular attention to expected values for habitual, school day, physical education class, recess, lunch break, out-of-school, weekend, and vacation activity. From 31 studies published since 1999, we constructed a youth habitual activity step-curve that indicates: (a) from ages 6 to 18 years, boys typically take more steps per day than girls; (b) for both sexes the youngest age groups appear to take fewer steps per day than those immediately older; and (c) from a young age, boys decline more in steps per day to become more consistent with girls at older ages. Additional studies revealed that boys take approximately 42-49% of daily steps during the school day; girls take 41-47%. Steps taken during physical education class contribute to total steps per day by 8.7-23.7% in boys and 11.4-17.2% in girls. Recess represents 8-11% and lunch break represents 15-16% of total steps per day. After-school activity contributes approximately 47-56% of total steps per day for boys and 47-59% for girls. Weekdays range from approximately 12,000 to 16,000 steps per day in boys and 10,000 to 14,000 steps perday in girls. The corresponding values for weekend days are 12,000-13,000 steps per day in boys and 10,000-12,000 steps per day in girls.

Pedometry methods for assessing free-living youth.

The purpose of this review is to integrate and summarize specific measurement topics (instrument and metric choice, validity, reliability, how many and what types of days, reactivity, and data treatment) appropriate to the study of youth physical activity. Research quality pedometers are necessary to aid interpretation of steps per day collected in a range ofyoung populations under a variety of circumstances. Steps per day is the most appropriate metric choice, but steps per minute can be used to interpret time-in-intensity in specifically delimited time periods (e.g., physical education class). Reported intraclass correlations (ICC) have ranged from .65 over 2 days (although higher values also have been reported for 2 days) to .87 over 8 days (although higher values have been reported for fewer days). Reported ICCs are lower on weekend days (.59) versus weekdays (.75) and lower over vacation days (.69) versus school days (.74). There is no objective evidence of reactivity at this time. Data treatment includes (a) identifying and addressing missing values, (b) identijfying outliers and reducing data appropriately if necessary, and (c) transforming the data as required in preparation for inferential analysis. As more pedometry studies in young populations are published, these preliminary methodological recommendations should be modified and refined.

Linking the American Time Use Survey (ATUS) and the Compendium of Physical Activities: methods and rationale.

BACKGROUND: The 2003 Bureau of Labor Statistics American Time Use Survey (ATUS) contains 438 distinct primary activity variables that can be analyzed with regard to how time is spent by Americans. The Compendium of Physical Activities is used to code physical activities derived from various surveys, logs, diaries, etc to facilitate comparison of coded intensity levels across studies. METHODS: This article describes the methods, challenges, and rationale for linking Compendium estimates of physical activity intensity (METs, metabolic equivalents) with all activities reported in the 2003 ATUS. RESULTS: The assigned ATUS intensity levels are not intended to compute the energy costs of physical activity in individuals. Instead, they are intended to be used to identify time spent in activities broadly classified by type and intensity. This function will complement public health surveillance systems and aid in policy and health-promotion activities. For example, at least one of the future projects of this process is the descriptive epidemiology of time spent in common physical activity intensity categories. CONCLUSIONS: The process of metabolic coding of the ATUS by linking it with the Compendium of Physical Activities can make important contributions to our understanding of American's time spent in health-related physical activity.

Expected values for steps/day in special populations.

OBJECTIVE: To assemble expected values for free-living steps/day in special populations living with chronic illnesses and disabilities. METHOD: Studies identified since 2000 were categorized into similar illnesses and disabilities, capturing the original reference, sample descriptions, descriptions of instruments used (i.e., pedometers, piezoelectric pedometers, accelerometers), number of days worn, and mean and standard deviation of steps/day. RESULTS: Sixty unique studies represented: 1) heart and vascular diseases, 2) chronic obstructive lung disease, 3) diabetes and dialysis, 4) breast cancer, 5) neuromuscular diseases, 6) arthritis, joint replacement, and fibromyalgia, 7) disability (including mental retardation/intellectual difficulties), and 8) other special populations. A median steps/day was calculated for each category. Waist-mounted and ankle-mounted instruments were considered separately due to fundamental differences in assessment properties. For waist-mounted instruments, the lowest median values for steps/day are found in disabled older adults (1214 steps/day) followed by people living with COPD (2237 steps/day). The highest values were seen in individuals with Type 1 diabetes (8008 steps/day), mental retardation/intellectual disability (7787 steps/day), and HIV (7545 steps/day). CONCLUSION: This review will be useful to researchers/practitioners who work with individuals living with chronic illness and disability and require such information for surveillance, screening, intervention, and program evaluation purposes.

Comparison of Kenz Lifecorder EX and ActiGraph accelerometers in 10-yr-old children.

UNLABELLED: A new accelerometer, the Kenz Lifecorder EX (LC; Suzuken Co. Ltd, Nagoya, Japan), offers promise as a feasible monitor alternative to the commonly used Actigraph (AG: Actigraph LLC, Fort Walton Beach, FL). PURPOSE: This study compared the LC and AG accelerometers and the Yamax SW-200 pedometer (DW) under free-living conditions with regard to children's steps taken and time in light-intensity physical activity (PA) and moderate to vigorous PA (MVPA). METHODS: Participants (N=31, age=10.2 +/- 0.4 yr) wore LC, AG, and DW monitors from arrival at school (7:45 a.m.) until they went to bed. Time in light and MVPA intensities were calculated using two separate intensity classifications for the LC (LC_4 and LC_5) and four classifications for the AG (AG_Treuth, AG_Puyau, AG_Trost, and AG_Freedson). Both accelerometers provided steps as outputs. DW steps were self-recorded. Repeated-measures ANOVA was used to assess overlapping monitor outputs. RESULTS: There was no difference between DW and LC steps (Delta=200 steps), but a nonsignificant trend was observed in the pairwise comparison between DW and AG steps (Delta=1001 steps, P=0.058). AG detected significantly greater steps than the LC (Delta=801 steps, P=0.001). Estimates of light-intensity activity minutes ranged from a low of 75.6 +/- 18.4 min (LC_4) to a high of 309 +/- 69.2 min (AG_Treuth). Estimates of MVPA minutes ranged from a low of 25.9 +/- 9.4 min (LC_5) to a high of 112.2 +/- 34.5 min (AG_Freedson). No significant differences in MVPA were seen between LC_5 and AG_Treuth (Delta=4.9 min) or AG_Puyau (Delta=1.7 min). CONCLUSION: The LC detected a comparable number of steps as the DW but significantly fewer steps than the AG in children. Current results indicate that the LC_5 and either AG_Treuth or AG_Puyau intensity derivations provide similar mean estimates of time in MVPA during-free living activity in 10-yr-old children.