Non-exercise Physical Activity Research Articles

Age-Related Olfactory Decline Is Associated With Levels of Exercise and Non-exercise Physical Activities.

Objective: This cross-sectional study evaluates the impact of active or non-active lifestyle in terms of physical, cognitive and social activity on the olfactory function in Elderly Subjects (ES) and aims at looking for a correlation between the time devoted to life activities and the score obtained during the olfactory tests by each individual.Methods: One hundred and twenty-two elderly volunteers were recruited in Sardinia (Italy) and divided into active ES (n = 60; 17 men, 43 women; age 67.8 ± 1.12 years) and inactive ES (n = 62; 21 men, 41 women, age 71.1 ± 1.14 years) based on their daily physical activities. The olfactory function was evaluated using the “Sniffin’s Sticks” battery test, while the assessment of daily activities was made by means of personal interviews.Results: A significant effect of active or inactive lifestyle was found on the olfactory function of ES (F(1,120) > 10.16; p < 0.005). A positive correlation was found between the olfactory scores and the number of hours per week dedicated to physical activities (Pearson’s r > 0.32, p ≤ 0.014) in both active and inactive ES.Conclusions: High levels of exercise and non-exercise physical activity are strongly associated with the olfactory function and, consequently, with the quality of life of the elderly. Given the limited physical exercise of elderly people, they can benefit from a more active lifestyle by increasing non-exercise physical activities.

Examining the Role of Exercise Timing in Weight Management: A Review.

Many adults cite exercise as a primary strategy for losing weight, yet exercise alone is modestly effective for weight loss and results in variable weight loss responses. It is possible that some of the variability in weight loss may be explained by the time of day that exercise is performed. Few studies have directly compared the effects of exercise performed at different times of the day (i. e., morning versus evening exercise). Results from these existing studies are mixed with some studies demonstrating superior weight and fat mass loss from morning exercise, while other studies have found that evening exercise may be better for weight management. Exercise timing may alter modifiable lifestyle behaviors involved in weight management, such as non-exercise physical activity, energy intake, and sleep. The purpose of this review is to summarize evidence for and against time-of-day dependent effects of exercise on weight management. Although limited, we also review studies that have examined the effect of exercise timing on other lifestyle behaviors linked to body weight regulation. While exercise at any time of day is beneficial for health, understanding whether there is an optimal time of day to exercise may advance personalized treatment paradigms for weight management.

The Impact of Low Energy Availability on Nonexercise Activity Thermogenesis and Physical Activity Behavior in Recreationally Trained Adults.

Energy availability describes the amount of dietary energy remaining for physiological functionality after the energy cost of exercise is deducted. The physiological and hormonal consequences of low energy availability (LEA) are well established, but the impact of LEA on physical activity behavior outside of exercise and, specifically, nonexercise activity thermogenesis (NEAT) has not been systematically examined. The authors conducted a secondary analysis of a repeated-measures crossover study in which recreationally trained young men (n = 6, 25 ± 1.0years) underwent two 4-day conditions of LEA (15kcal·kg fat-free mass-1 ·day-1) with and without endurance exercise (LEA + EX and LEA EX) and two energy-balanced control conditions (CON + EX and CON EX). The duration and intensity of physical activity outside of prescribed exercise were assessed using the SenseWear Pro3 armband. LEA did not alter NEAT (p = .41), nor time spent in moderate to vigorous (p = .20) and low-intensity physical activity (p = .17). However, time spent in low-intensity physical activity was lower in LEA + EX than LEA - EX (13.7 ± 0.3 vs. 15.2 ± 0.3hr/day; p = .002). Short-term LEA does not seem to impact NEAT per se, but the way it is attained may impact physical activity behavior outside of exercise. As the participants expended similar amounts of energy during NEAT (900-1,300kcal/day = 12.5-18.0kcal·kg fat-free mass-1·day-1) and prescribed exercise bouts (15.0kcal·kg fat-free mass-1·day-1), excluding it as a component of energy expenditure may skew the true energy available for physiological functionality in active populations.

The Effect of Aerobic Training and Increasing Nonexercise Physical Activity on Cardiometabolic Risk Factors.

Epidemiological studies suggest that sedentary behavior is an independent risk factor for cardiovascular mortality independent of meeting physical activity guidelines. However, limited evidence of this relationship is available from prospective interventions. The purpose of the present study is to evaluate the combined effect of aerobic training and increasing nonexercise physical activity on body composition and cardiometabolic risk factors. Obese adults (N = 45) were randomized to 6 months of aerobic training (AERO), aerobic training and increasing nonexercise physical activity (~3000 steps above baseline levels; AERO-PA), or a control (CON) group. The AERO and AERO-PA groups performed supervised aerobic training (3-4 times per week). The AERO-PA group wore Fitbit One accelerometers and received behavioral coaching to increase nonexercise physical activity. There was a larger increase in fitness in the AERO-PA group (0.27 L·min-1; confidence interval (CI), 0.16 to 0.40 L·min-1) compared with the AERO group (0.09 L·min-1; CI, -0.04 to 0.22 L·min-1) and the CON group (0.01; CI, -0.11 to 0.12 L·min-1). Although significant findings were not observed in the entire study sample, when the analysis was restricted to participants compliant to the intervention (n = 33), we observed significant reductions in waist circumference, percent weight loss, body fat, 2-h glucose, and 2-h insulin in comparison to the CON group (P < 0.05), but not the AERO group. Furthermore, linear regression models showed that change in steps was associated with 21% and 26% of the variation in percent weight loss and percent fat loss, respectively. Increasing nonexercise physical activity with aerobic training may represent a viable strategy to augment the fitness response in comparison to aerobic training alone and has promise for other health indicators.

Morning fatigue and structured exercise interact to affect non-exercise physical activity of fit and healthy older adults

BackgroundExercise training is crucial for maintaining physical and mental health in aging populations. However, as people participate in structured exercise training, they tend to behaviorally compensate by decreasing their non-exercise physical activity, thus potentially blunting the benefits of the training program. Furthermore, physical activity of older adults is substantially influenced by physical feelings such as fatigue. Nevertheless, how older people react to day-to-day fluctuations of fatigue and whether fatigue plays a role in non-exercise physical activity compensation is not known. Thus, the purpose of this study was twofold: (1) To explore whether the volume and intensity of habitual physical activity in older adults were affected by morning fatigue. (2) To investigate the effect of attending power and resistance exercise sessions on the levels of non-exercise physical activity later that day and the following day.MethodsTwenty-eight older adults wore an accelerometer during a 4-week low-volume, low-intensity resistance and power training program with three exercise sessions per week and for 3 weeks preceding and 1 week following the program. During the same period, the participants were prompted every morning, using text messages, to rate their momentary fatigue on a scale from 0 to 10.ResultsGreater morning fatigue was associated with lower volume (p = 0.002) and intensity (p = 0.017) of daily physical activity. Specifically, one point greater on the fatigue scale was associated with 3.2 min (SE 1.0) less moderate-to-vigorous physical activity. Furthermore, attending an exercise session was associated with less moderate-to-vigorous physical activity later that day by 3.7 min (SE 1.9, p = 0.049) compared to days without an exercise session. During the next day, the volume of physical activity was greater, but only in participants with a body mass index up to 23 (p = 0.008).ConclusionsFollowing low-volume exercise sessions, fit and healthy older adults decreased their non-exercise physical activity later that day, but this compensation did not carry over into the next day. As momentary morning fatigue negatively affects daily physical activity, we suggest that the state level of fatigue should be monitored during intensive exercise programs, especially in less fit older adults with increased fatigability.

Adherence to walking exercise prescription during pulmonary rehabilitation in COPD with a commercial activity monitor: a feasibility trial

BackgroundRegular exercise is important in the management of COPD. Pulmonary rehabilitation (PR) facilitates a more physically active lifestyle through exercise participation, ideally without compromising non-exercise physical activity (PA). During PR patients are advised to perform exercise defined by duration and intensity. The extent to which PR attendees participate in unsupervised exercise bouts and their adherence to the exercise prescription provided during PR is unclear. Commercially available devices have the potential to support patients to exercise at their individually prescribed intensity. Study aims were to (1) assess how adherent patients are to their prescribed walking intensity; (2) examine the pattern of overall PA and walking exercise during the course of PR; (3) determine the feasibility of prescribing exercise to PR attendees using an activity monitor; and (4) explore the relationship between exercise and non-exercise PA with routine PR outcome measures.Methods19 patients wore an activity monitor during routine walking tests and 6 weeks of PR, recording in a diary when they exercised. Exercise intensity (cadence) was prescribed from the Endurance Shuttle Walk Test. Patients completed questionnaires, walking tests and a lower limb strength test before and after PR. Repeated ANOVA compared changes in outcomes between weeks 1–6.ResultsPatients wore the monitor every day during PR (median 42 days). Exercise steps increased by 56% (Δ332 [95% CI 54–611] steps/day, p = 0.009) between weeks 1 and 6, with no significant change in non-exercise steps (Δ79 [95% CI − 22 to − 179] steps/day, p = 0.13). Patients reported exercising on 70% of days. Adherence to prescribed cadence was achieved 55% of time spent exercising, and did not change across the 6 weeks (p = 0.907). Change in total daily steps was associated with improved dyspnea (p = 0.027), Chronic Respiratory Questionnaire (CRQ) Dyspnea domain (p = 0.019), CRQ Emotional Functioning domain (p = 0.001) and CRQ Mastery domain scores (p = 0.001) but not with exercise capacity or lower limb muscle strength.ConclusionsImprovements in exercise participation, not at the expense of non-exercise PA, throughout a PR course was observed in attendees provided with a commercially available activity monitor. Wearable technology may be able to support effective remote walking exercise prescription and participation during PR.Trial registration (retrospectively registered): http://www.isrctn.com/ISRCTN15892972.

A Cross-Sectional Study On Practise Of Physical Activity Among Medical Students In Chennai

As defined by the World Health Organisation (WHO), physical activity is any bodily movement produced by skeletal muscles that require energy expenditure. Physical activity is split into exercise and non-exercise physical activity. Physical inactivity is associated with many chronic and non-communicable diseases such as hypertension, type II diabetes mellitus, carcinoma and mental health problems. According to the global statistical report of WHO, around 1.6 million deaths occur annually, and these deaths can be attributed to insufficient physical activity­­. This study would aim to assess the practice of physical activity among medical students and to study the factors associated with physical activity. A cross-sectional study was conducted in a private medical college between January 2020 and March 2020, 444 undergraduate students were included in the study, among which 401 responses were considered valid. A standard international physical activity questionnaire (IPAQ) was used. The data were entered in Microsoft Excel and analysed using Pearson’s chi-square test. The students belonged to 1st year 125(31.2%), 2nd year 128(31.9%), 3rd year 133(33.2%) and 4th year 15(3.7%). Majority of these students 233(58.1%) had an average Body Mass Index (BMI) and 184(45.9%) practised low level of physical activity. In comparison with the level of physical activity, batches(1st year, 2nd year,3rd year, 4th year) and gender(males, females) were significant at p&amp;lt;0.05, but BMI was not significant at p&amp;lt;0.05. Comparing the level of physical activity with the BMI of the students, it can be concluded that the level of physical activity is not associated with BMI.

Effects Of Moderate Versus Vigorous Intensity Exercise Training In Older Adults With Prediabetes

PURPOSE: Aerobic exercise is recommended to improve glycemic control; however, the optimal intensity of exercise for older adults with prediabetes is unknown. The objective of this pilot study was to compare the effects of moderate vs. vigorous intensity aerobic exercise on glycemic control and non-exercise physical activity (NEPA). METHODS: 19 older adults (14F; 68.1 ± 5.8 yrs) with prediabetes (HbA1c 5.7-6.4% or fasting glucose 100-125 mg/dl) were randomized to 12-weeks of supervised aerobic exercise (45-min sessions 4 days/wk) at either moderate (MOD: 60-65% HRmax) or vigorous (VIG: 80-85% HRmax) intensity. Free-living glycemic control (24h mean; percent of day ≥140 mg/dL) was measured using continuous glucose monitors (CGM, Dexcom). NEPA (>1.5 METs, excluding exercise sessions) was assessed using a thigh worn accelerometer (ActivPAL v4). A 3h Oral glucose tolerance test (OGTT, 75g) was performed at baseline and following the exercise intervention (72-96h following the last exercise bout) to compare to free-living CGM and as measure of insulin sensitivity (Matsuda Index). Data are presented as mean±SE. RESULTS: Adherence rates to the exercise interventions were 85±9% and 89±3% in MOD and VIG with mean heart rates during exercise of 99±1 bpm (65% HRmax) and 123±4 bpm (79% HRmax), respectively. Mean 24h glucose (-8.4±6.4 vs. -2.2±6.7 mg/dl) and percent of day >140 mg/dL (-9.7±11.0% vs. 0.7±4.6%) did not significantly change in MOD or VIG, respectively. However, there was a significant group by time interaction (p=0.05) for change in insulin sensitivity in MOD (+2.4±1.1) and VIG (-0.6±0.8).There were no differences between groups for change in NEPA, fasting glucose, or 2h glucose. Changes in free-living CGM were not significantly correlated with changes in OGTT outcomes. CONCLUSION: In older men and women with prediabetes, both MOD and VIG had minimal effects on free-living glycemic control, but MOD induced greater improvements in insulin sensitivity. These preliminary results suggest that a more comprehensive lifestyle intervention combining dietary intervention and exercise may be needed to improve glycemic control in this population.

Non-exercise Activity During Dietary Restriction Or Aerobic Exercise Interventions In Individuals With Overweight Or Obesity

PURPOSE: Reduced non-exercise physical activity (PA) may contribute to attenuated weight loss during behavioral interventions. Our objective was to compare PA and sedentary behavior (SB) before and after dietary restriction (DIET) versus aerobic exercise intervention (EX). METHODS: Adults with overweight or obesity were randomized to undergo 12 weeks of DIET or EX, both aimed at 2000 kcal/week reduction in energy balance. Average steps and time spent sitting, standing, stepping, light activity, and moderate-to-vigorous activity (MVPA) were measured using ActivPAL accelerometers at baseline and for approximately 7 days within the last 2 weeks of the intervention. PA and SB variables were assessed with and without removal of exercise sessions. Data were analyzed using mixed methods analysis of variance with time (baseline vs. follow-up) as the within-subjects factor and group (diet vs. exercise) as the between-subjects factor. In post-hoc analyses, dependent samples t-tests assessed changes within groups. RESULTS: 26 individuals (n=15 DIET, n=11 EX) had valid accelerometry data at both time points (age: 36±8 years, body mass index: 30.3±3.0 kg/m2, n=19 [73%] women). The DIET group trended towards greater weight loss (DIET -7.2±6.4 kg; EX: -3.5±6.3 kg, p=0.071). Without removing exercise sessions, MVPA increased within the EX group (baseline: 60±11, follow-up: 73±15 min, p=0.011), but not in the DIET group (baseline: 63±15, follow-up: 62±16 min, p=0.847). However, after removing exercise session data, no significant interactions, within-subject effects, or between-subject effects were observed for steps or time spent sitting, standing, stepping, light activity, or MVPA, Table 1. CONCLUSION: PA and SB were not differentially affected by DIET and EX interventions, suggesting that these strategies may not result in compensatory reduction in PA. Supported by the American Diabetes Association and NIH Grants: UL1 TR000154, T32 DK007658-29, K01 DK100445.

Feasibility and behavioral effects of prolonged static and dynamic standing as compared to sitting in older adults with type 2 diabetes mellitus

BackgroundPhysical inactivity is prevalent in older adults with type 2 diabetes mellitus (T2DM) and may exacerbate their clinical symptoms. The aim of this study was to examine the feasibility of 4-h regular versus more dynamic standing sessions while performing routine desktop activities as a non-exercise physical activity intervention in older adults with T2DM to increase non-exercise activity.MethodsTwelve older adult patients with T2DM (3 female; age 71 ± 4 years; Body mass index 34 ± 5 kg/m2) completed three sessions (baseline sitting followed by “static” or “dynamic” desktop standing sessions). Participants stood behind a regular height-adjustable desk in the “static” standing session. An upright dynamic standing desk, which provides cues to make small weight-shifting movements, was used for the “dynamic” standing session. Oxygen consumption, cognitive performance, as well as net standing duration, total movement activity, and musculoskeletal discomfort were assessed during all three sessions.ResultsAll participants were able to complete all sessions. Oxygen consumption and overall movements progressively increased from sitting to static and dynamic standing, respectively (p < 0.001). The duration of breaks during standing (p = 0.024) and rate of total musculoskeletal discomfort development (p = 0.043) were lower in the dynamic standing compared to static standing sessions. There was no evidence of executive cognitive worsening during either standing session compared to sitting.ConclusionsProlonged 4-h standing as a simple non-exercise physical intervention is feasible in older adults with T2DM and may have metabolic (oxygen consumption) benefits. Increasing movement during desktop standing may offer incremental benefits compared to regular standing. Prolonged desktop standing might provide an effective intervention in T2DM older participants to target sedentariness.Trial registrationClinicalTrials.gov (NCT04410055), retrospectively registered May 27, 2020.

Wearable Technology To Reduce Sedentary Behavior And CVD Risk In Older Adults: A Pilot Randomized Clinical Trial.

BackgroundPhysical exercise is associated with decreased cardiovascular disease (CVD) risk, but recent large-scale trials suggest that exercise alone is insufficient to reduce CVD events in high-risk older adults.PurposeThis pilot randomized clinical trial aimed to collect critical data on feasibility, safety, and protocol integrity necessary to design a fully powered randomized controlled trial (RCT) and evaluate the impact of combining structured exercise with an intervention designed to enhance non-exercise physical activity (EX+NEPA) compared to EX alone.MethodsForty participants aged ≥60 years with moderate-to-high risk of coronary heart disease events were randomly assigned to either the EX+NEPA or EX groups and followed for 20 weeks. Both groups underwent a twice-weekly, 8-week center-based exercise intervention with aerobic and resistance exercises. EX+NEPA group also received a wearable activity tracking device along with behavioral monitoring and feedback throughout the study. Study outcomes were evaluated at 8 and 20 weeks.ResultsData are presented as adjusted mean change of the differences over time with 95% confidence intervals at 20 weeks. Relative to EX, the change in steps/day at 20 weeks was 1994 (−40.27, 4028) higher for EX+NEPA. For sedentary time at close-out, the EX+NEPA group was −6.8 (−45.2, 31.6) min/day relative to EX. The between-group differences for systolic and diastolic blood pressure were −9.9 (−19.6, −0.3) and −1.8 (−6.9, 3.3) mmHg, respectively.ConclusionThe addition of wearable technology intervention appeared to positively influence daily activity patterns and changes in blood pressure – potentially improving risk factors for CVD. A fully powered randomized trial is needed to ultimately test this hypothesis.

Effect of different doses of supervised exercise on food intake, metabolism, and non-exercise physical activity: The E-MECHANIC randomized controlled trial

Exercise is recommended for weight management, yet exercise produces less weight loss than expected, which is called weight compensation. The mechanisms for weight compensation are unclear. The aim of this study was to identify the mechanisms responsible for compensation. In a randomized controlled trial conducted at an academic research center, adults (n=198) with overweight or obesity were randomized for 24 wk to a no-exercise control group or 1 of 2 supervised exercise groups: 8 kcal/kg of body weight/wk (KKW) or 20 KKW. Outcome assessment occurred at weeks 0 and 24. Energy intake, activity, and resting metabolic rate (RMR) were measured with doubly labeled water (DLW; with and without adjustments for change in RMR), armband accelerometers, and indirect calorimetry, respectively. Appetite and compensatory health beliefs were measured by self-report. A per-protocol analysis included 171 participants (72.5% women; mean±SD baseline body mass index: 31.5±4.7 kg/m2). Significant (P<0.01) compensation occurred in the 8 KKW (mean: 1.5 kg; 95% CI: 0.9, 2.2 kg) and 20 KKW (mean: 2.7 kg; 95% CI: 2.0, 3.5 kg) groups, and compensation differed significantly between the exercise groups (P=0.01). Energy intake by adjusted DLW increased significantly (P<0.05) in the 8 KKW (mean: 90.7 kcal/d; 95% CI: 35.1, 146.4 kcal/d) and 20 KKW (mean: 123.6 kcal/d; 95% CI: 64.5, 182.7 kcal/d) groups compared with control (mean: -2.3 kcal/d; 95% CI: -58.0, 53.5 kcal/d). Results were similar without DLW adjustment. RMR and physical activity (excluding structured exercise) did not differentially change among the 3 groups. Participants with higher compared with lower compensation reported increased appetite ratings and beliefs that healthy behaviors can compensate for unhealthy behaviors. Furthermore, they increased craving for sweet foods, increased sleep disturbance, and had worsening bodily pain. Compensation resulted from increased energy intake and concomitant increases in appetite, which can be treated with dietary or pharmacological interventions. Compensation was not due to activity or metabolic changes. This trial was registered at clinicaltrials.gov as NCT01264406.

The effects of exercise session timing on weight loss and components of energy balance: midwest exercise trial 2

Background/objectivesCircadian physiology has been linked to body weight regulation and obesity. To date, few studies have assessed the association between exercise timing and weight related outcomes. The aim of this secondary analysis was to explore the impact of exercise timing (i.e., 24 h clock time of exercise session) on weight loss and components of energy balance.Subjects/methodsOverweight/obese (BMI 25.0–39.9 kg/m2), physically inactive, young adults (~51% female) completed a 10-month supervised exercise program (400 or 600 kcal/session for 5 days/week) or served as non-exercise controls (CON). Participants were categorized based on the time of day in which they completed exercise sessions (Early-Ex: >50% of sessions completed between 7:00 and 11:59 am; (n = 21), Late-Ex: >50% of sessions completed between 3:00 and 7:00 pm; (n = 25), Sporadic-Ex: <50% of sessions completed in any time category; (n = 24), and CON; (n = 18)). Body weight, energy intake (EI; digital photography), and non-exercise physical activity (NEPA; accelerometer) were assessed at baseline, 3.5, 7, and 10 months. Total daily energy expenditure (TDEE; doubly labeled water), was assessed at baseline and 10 months.ResultsAt month 10, weight loss was significantly greater in both Early-EX (−7.2 ± 1.2%; p < 0.001) and Sporadic-EX (− 5.5 ± 1.2%; p = 0.01) vs CON (+0.5 ± 1.0%), and Early-EX vs Late-EX (−2.1 ± 1.0%; p < 0.001). There were no between group differences for change in TDEE, EI, and non-exercise energy expenditure (P > 0.05). A significant group × time interaction (p = 0.02) was observed for NEPA (counts/min), however, after adjusting for multiple comparisons, group effects were no longer significant.ConclusionsDespite minimal differences in components of energy balance, Early-EX lost significantly more weight compared with Late-Ex. Although the mechanisms are unclear, the timing of exercise may be important for body weight regulation.

Changes On Non-exercise Physical Activity Are Related To Improvements In Mitochondrial Function Independently Of Structured Intentional Exercise

Whether exercise interventions increase or reduce non-exercise physical activity (NEPA) is controversial. Few studies have examined this potential effect on relevant physiological outcomes, particularly in the context of randomized controlled trials. PURPOSE: To determine the effects of a structured exercise program on NEPA, and the independent association between NEPA and both cardiorespiratory fitness (VO2max) and mitochondrial capacity within skeletal muscle. METHODS Thirty-seven older (age=69±5yrs) obese (BMI=35±3kg/m2) adults were randomized to one of the following 6-month interventions: Health education (CON: n=12), diet induced weight-loss (DIWL: n=12, or Weight-loss and exercise (WLEX: n=15). CRWL and WLEX participants had a goal of 10% weight-loss through calorie restriction. Subjects in the WLEX group completed a supervised combined aerobic and resistance exercise program. We quantified components of PA by a multisensory device. VO2max was determined by cycle ergometry. Maximal oxidative phosphorylation (OXPHOS) and maximal uncoupled respiration (ETS) of permeabilized myofibers from biopsies was evaluated by high-resolution respirometry. Repeated measures analysis was performed to compare differences between the three groups pre and post intervention. Adjusted correlations to weight loss (WL) between NEPA and VO2max, ETS and OXPHOS were performed. RESULTS: After the intervention WLEX increased significantly NEPA compared with the other groups (NEPA: WLEX= 89.6±84.5 min/day; DIWL= 3.7±42.4 min/day; CON= -10.5±63.6 min/day; F= 8.87 for time x group interaction, P<0.001). Change in NEPA was positively correlated with change in mitochondrial capacity (OXPHOS, r = 0.453 and r= 0.468; P<0.05 for both) and absolute VO2max (r= 0.453, P<0.05). Both DIWL and WLEX experimented a significant WL (WLEX= -10.1±5.0 min/day and DIWL= -7.2±5.5 min/day; P<0.05). CONCLUSIONS: In addition to the beneficial effects of structured intentional exercise on cardiorespiratory fitness and mitochondrial capacity within muscle, exercise programs in older obese adults may also increase non-exercise physical activity, which in turn appears to independently correlate with improved aerobic capacity. These results highlight the concurrent effect of exercise and NEPA to improve health outcomes.

Increasing Non-Exercise Physical Activity With Training Reduces Chance Of Non-Response To Exercise

Evidence of cardiorespiratory fitness (CRF) non-response is growing in both clinical and exercise training studies. Along with aerobic training, an increase in non-exercise physical activity may reduce CRF non-response contingency. PURPOSE: To determine if increases in non-exercise physical activity mitigates CRF non-response to exercise training among sedentary, overweight/obese adults. METHODS: Thirty-six adults (age: 54.19±7.14 years; BMI: 35.83±4.66 kg/m2; 77.8% female) were assessed from a previous exercise study (>70% adherence to 4 weekly sessions across 24 weeks). Participants were randomized to an aerobic training group or an aerobic training and increasing non-exercise physical activity group (increase 1,000 to 3,000 steps per day from baseline). Both groups performed the same supervised aerobic training (50-75% VO2 max) for 24 weeks at a dose of 12 kcals per kg per week. CRF non-response was determined via calculated delta (∆) values (follow-up minus baseline values) for absolute VO2 max (L/min) and participants were categorized as non-responders via technical error (TE) (∆<0.71 L/min) and classical measures (∆<0 L/min). Pearson Chi-square test of independence was conducted for categorical variables (i.e. responders vs. non-responders) in TE and classical non-responders, separately. A binary multivariable logistic regression was used to estimate odds of CRF non-response based on baseline demographic factors (age, race, BMI, fitness, waist circumference). RESULTS: Participants increasing non-exercise physical activity with aerobic training were significantly more likely to increase CRF based on TE analysis, X2 (2, N=36) =10.99, p=.004, compared to aerobic training alone. Whereas, classic non-response did not show a significant relationship X2 (2, N=36) =2.77, p=.251. Baseline age (p<.05) was a significant predictor of TE response, while baseline BMI (p<.05) was a significant predictor for classic response. CONCLUSION: Increasing non-exercise physical activity concurrent with aerobic training may improve likeliness of increasing CRF and, thus, reduce risk of cardiovascular disease and mortality. Supported by a grant from the American Heart Association (13SDG17140091).

Development And Testing Of An Integrated Score For Physical Behaviors

There is expanding interest in the 24-hr activity cycle in relation to health outcomes, creating a need for new statistical approaches to analyze the joint effects of distinct but inter-related physical behaviors (e.g., exercise, sitting time, sleep). PURPOSE: To develop and test an integrated physical behavior score (PBS) in relation to all-cause and cause specific mortality. METHODS: NIH-AARP Diet and Health Study participants (N=163,016) completed a questionnaire (2004-2006) asking about time spent in five exercise and non-exercise physical activities, two sedentary behaviors (television and non-television), and sleep. In half of the sample, we used shape constrained additive regression to model the relationship between each behavior and survival. Maximum logit scores from each of the eight behavior-survival functions were summed to produce a PBS that was proportionally rescaled to range from 0-100. We examined predictive validity of the PBS in the other half-sample using Cox Proportional Hazards models after adjustment for covariates for all-cause and cause-specific mortality. RESULTS: In the testing sample, over an average of 6.6y of follow-up, 8,732 deaths occurred. We found a strong graded decline in risk of all-cause mortality across quintiles of PBS (Q5 vs Q1 hazard ratio [95%CI] = 0.53 [0.49, 0.57]). Risk estimates for the PBS were higher than any of the components in isolation. Results were similar but stronger for cardiovascular disease (Q5 vs Q1 = 0.42 [0.39, 0.48]) and other mortality (Q5 vs Q1 = 0.42 [0.36, 0.48]). The relationship between PBS and mortality was observed in stratified analyses by median age, sex, BMI and health status. CONCLUSIONS: Although widespread in other areas of epidemiology, this is one of the first attempts to characterize integrate multiple distinct physical behaviors into a single composite score. In a large sample of US adults, we showed this score has strong predictive validity for both men and women. Future research is needed to test this approach in an independent sample. Supported by the National Institutes of Health U01-CA057030 and the Intramural Research Program.

The Effect Of Exercise Training And Increasing Non-exercise Physical Activity On Glyca Levels

The Effect Of Exercise Training And Increasing Non-exercise Physical Activity On Glyca Levels

Study on practice of physical activity among medical interns in a private medical college hospital in Chennai

Background: Physical inactivity is one of the leading risk factors for death worldwide. It is a key risk factor for non-communicable diseases (NCDs) such as cardiovascular diseases, cancer and diabetes. Physical activity has significant health benefits and contributes to prevent NCDs. Globally, 1 in 4 adults are not active enough. More than 80% of the world's adolescent population is insufficiently physically active. So the aim of this study is to assess the practice of physical activity among the medical interns, as they are the future doctors.Methods: A cross sectional study was conducted among 124 medical interns. A pre-tested, semi-structured questionnaire was used to collect the data. Microsoft Excel 2010 spread sheet version 14.1.3 and statistical package for social sciences (SPSS) version 21 were used for data entry and analysis. The results are expressed as percentages and proportions.Results: In our study majority of the interns 66 (64.1%) had normal body mass index (BMI). The practice of non-exercise physical activity is more in female than male interns whereas the exercise physical activity is more in males comparing to female interns.Conclusions: Physical inactivity is an urgent public health priority, so long-term follow-up is needed to identify the factors promoting for the practice of physical activity among medical interns.

Association of non-exercise physical activity in mid- and late-life with cognitive trajectories and the impact of APOE \u03b54 genotype status: the Mayo Clinic Study of Aging

In this study derived from the population-based Mayo Clinic Study of Aging, we investigated whether non-exercise physical activity (PA) was associated with global and domain-specific cognitive trajectories (memory, language, visuospatial skills, attention) and whether the association differed by apolipoprotein E (APOE) ε4 genotype status. We included 2061 community-dwelling individuals aged ≥ 70 years (50.5% males, 26.7% APOE ε4 carriers) who were cognitively unimpaired at baseline and on whom serial cognitive data and self-reported information on non-exercise PA were available. We specifically inquired about non-exercise PA carried out at two time points, i.e., midlife (between 50 and 65 years of age) and late-life (within 1 year prior to assessment) and three intensity levels, i.e., light (e.g., laundry), moderate (e.g., scrubbing floors) and heavy (e.g., hard manual labor). Linear mixed-effect models revealed that engaging in midlife PA of moderate or heavy intensity was associated with significantly less-pronounced decline of z-scores in all cognitive domains. Similarly, participants that engaged in late-life moderate or heavy PA had less decline in visuospatial, attention and global z-scores than non-active peers. These associations varied depending on APOE ε4 carrier status, i.e., APOE ε4 non-carriers but not APOE ε4 carriers that engaged in late-life PA had less decline in cognitive z-scores. In contrast, engaging in midlife PA, irrespective of intensity, was significantly associated with less decline in memory function only among APOE ε4 carriers.

Development and Testing of an Integrated Score for Physical Behaviors.

Interest in a variety of physical behaviors (e.g., exercise, sitting time, sleep) in relation to health outcomes creates a need for new statistical approaches to analyze the joint effects of these distinct but inter-related physical behaviors. We developed and tested an integrated physical behavior score (PBS). National Institutes of Health-American Association of Retired Persons Diet and Health Study participants (N = 163,016) completed a questionnaire (2004-2006) asking about time spent in five exercise and nonexercise physical activities, two sedentary behaviors (television and nontelevision), and sleep. In half of the sample, we used shape-constrained additive regression to model the relationship between each behavior and survival. Maximum logit scores from each of the eight behavior-survival functions were summed to produce a PBS that was proportionally rescaled to range from 0 to 100. We examined predictive validity of the PBS in the other half-sample using Cox Proportional Hazards models after adjustment for covariates for all-cause and cause-specific mortality. In the testing sample, over an average of 6.6 yr of follow-up, 8732 deaths occurred. We found a strong graded decline in risk of all-cause mortality across quintiles of PBS (Q5 vs Q1 hazard ratio [95% CI] = 0.53 [0.49, 0.57]). Risk estimates for the PBS were higher than any of the components in isolation. Results were similar but stronger for cardiovascular disease (Q5 vs Q1 = 0.42 [0.39, 0.48]) and other mortality (Q5 vs Q1 = 0.42 [0.36, 0.48]). The relationship between PBS and mortality was observed in stratified analyses by median age, sex, body mass index, and health status. We developed a novel statistical method generated a composite physical behavior that is predictive of mortality outcomes. Future research is needed to test this approach in an independent sample.