Energy Cost Of Physical Activity Research Articles

Sex-related differences in the energy cost of physical activity in seniors

Introduction. The aging of the human body, which is an inevitable and irreversible process, causes changes in the structure and functions of organs and a decrease in intellectual and cognitive functions. Physical activity is essential for the quality of life of seniors. The aim of the study was to compare the energy cost of physical activity of women and men over 65 years of age, living in the Podkarpackie Voivodeship. Material and methods. Cross-sectional study covered seniors at the age of 65-74, from Podkarpackie Province. The research tool was an International Physical Activity Questionnaire (IPAQ). Chi-square and Mann-Whitney U tests were used for the analysis. Results. Energy expenditure related to energy cost of vigorous (p = 0.031), moderate (p = 0.014) and total effort (p = 0.007) job-related, motor vehicle-related effort (p < 0.001), and leisure-time physical activity (p = 0.005) was statistically significantly higher in men. In women, higher values of vigorous physical activities in the garden or yard (p = 0.049) and moderate physical activities at home (p = 0.014) were observed. Conclusions. The energy cost of activities requiring job-related vigorous, moderate and total physical activity, as well as the energy cost of effort related to train, bus, car, tram, or other kind of motor vehicle, as well as recreation, sport, and leisure-time physical activity is higher in men. On the other hand, women are characterized by a higher energy cost of vigorous physical activities in the garden or yard and moderate physical activities inside home. The time spent sitting does not differentiate the surveyed women and men.

Energy cost of physical activities in growing broilers

ABSTRACT 1. The time-energy budget method estimates the energy used for physical activity (PA) by integrating behaviour PA patterns with energy cost for specific PAs. Nevertheless, information about individual energy cost by type of PA are not available and so this study estimated the energy cost of PA for growing broilers. 2. An indirect calorimetry system for single birds was constructed to measure the variation in the rate of O2 consumption (O2, L/min) and rate of CO2 production (CO2, L/min) produced by these PAs. 3. A total of five birds were used in a replicated trial where their body weight (BW) ranged from 1.5 to 2.5 kg to measure the increase in heat production (HP) above resting levels as a result of PA. The procedure in the chamber was divided into five steps: (1) initial baselining, (2) resting metabolic rate, (3) PA such as feeding, drinking and other standing activities, (4) removal of gas exchange produced in step 3, and (5) final baselining. The PA was recorded using a video camera fixed at the chamber’s top (and outside). 4. The area under CO2 and O2 curves was used to calculate the CO2 production (vCO2, L) and O2 consumption (vO2, L). Then, the HP (cal/kg−0.75) was calculated according to the Brouwer equation. Two observers analysed the video records to estimate the time spent for each PA (seconds and frequency). 5. To calculate the energetic coefficients, the HP was regressed with the function of time spent to perform each PA allowing to estimate the energy cost for eating, drinking and stand activities, which were 0.607, 0.352 and 0.938 cal/kg−0.75/s, respectively.

The metabolic cost of physical activity in mice using a physiology-based model of energy expenditure

ObjectivePhysical activity is a major component of total energy expenditure (TEE) that exhibits extreme variability in mice. Our objective was to construct a general, physiology-based model of TEE to accurately quantify the energy cost of physical activity. MethodsSpontaneous home cage physical activity, body temperature, TEE, and energy intake were measured with frequent sampling. The energy cost of activity was modeled considering six contributors to TEE (basal metabolic rate, thermic effect of food, body temperature, cold induced thermogenesis, physical activity, and body weight). An ambient temperature of 35 °C was required to remove the contribution from cold induced thermogenesis. Basal metabolic rate was adjusted for body temperature using a Q10 temperature coefficient. ResultsWe developed a TEE model that robustly explains 70–80% of the variance in TEE at 35 °C while fitting only two parameters, the basal metabolic rate and the mass-specific energy cost per unit of physical activity, which averaged 60 cal/km/g body weight. In Ucp1−/− mice the activity cost was elevated by 60%, indicating inefficiency and increased muscle thermogenesis. The diurnal rhythm in TEE was quantitatively explained by the combined diurnal differences in physical activity, body temperature, and energy intake. Incorporating body temperature into human basal metabolic rate measurements significantly reduced the inter-individual variation. ConclusionsThe physiology-based model of TEE allows quantifying the energy cost of physical activity. While applied here to mice, the model should be generally valid across species. Due to the effect of body temperature, we suggest that basal metabolic rate measurements be corrected to a reference body temperature, including in humans. Having an accurate cost of physical activity allows mechanistic dissection of disorders of energy homeostasis, including obesity.

O66 Energy cost of physical activity (standing and walking) in finishing pigs and sows

O66 Energy cost of physical activity (standing and walking) in finishing pigs and sows

Chinese Compilation of Physical Activities in healthy adults aged 18–64: Categories and metabolic intensities

A Chinese Compilation of Physical Activities was compiled to estimate the energy costs of physical activities (PAs) using data on adults aged 18–64. Data were obtained from published articles and laboratory measurements. Databases, including PubMed, Embase, Scopus, Ebsco, Web of Science, Chinese National Knowledge Infrastructure, Wan Fang Data, National Science and Technology Report Service, Public Health Scientific Data were searched to collect data from inception to January 2022, on energy expenditure associated with PA in the healthy Chinese population. Two reviewers independently screened the literature and extracted, classified, and summarized data. Data were measured for 36 PAs using indirect calorimetry. Detailed descriptions of specific activities and metabolic equivalent values were provided by summarizing 241 physical activities in 13 categories. The first edition of the Chinese Compilation of PAs in Healthy Adults Aged 18–64(CCPA) was created. It provides valuable resources for people who regularly engage in physical exercise, researchers, educators, fitness professionals, and health or commercial sectors to quickly obtain various PA MET intensities. In the future, the energy expenditure of various PAs of different ages within the Chinese population can be measured based on the CCPA.

1399-P: Quantitation of the Energy Cost of Physical Activity in Mice

Mice are widely used for diabetes and obesity research, but the quantitative contribution of physical activity to mouse energy metabolism is poorly understood. The energy cost of activity (PAEE) is typically determined by regression of total energy expenditure (TEE) versus physical activity. Confounding factors are 1) that muscle-produced heat reduces cold induced thermogenesis by brown fat and 2) that core body temperature (Tb) increases during physical activity. Minimizing cold induced thermogenesis addresses the first problem. Prior studies used housing at 30°C, but 30°C is now known to be below thermoneutrality in the dark phase. Furthermore, the Tb increase accompanying physical activity increases energy expenditure by non-activity processes; this was not considered previously. To account for these factors, we studied mice by indirect calorimetry at an ambient temperature of 35 °C while measuring Tb by telemetry and physical activity by beam break. We developed a model, partitioning TEE into PAEE and resting energy expenditure (REE) . Significant features of the model are i) physical activity measurements are aligned to the measured TEE using the time constant of the indirect calorimetry system, ii) the REE term is adjusted for the measured Tb using a Q10 (van’t Hoff coefficient) of 3.0, and iii) the REE term is scaled for body mass. In this model, the within mouse PAEE was robustly fit by linear regression, yielding PAEE of 22.5 ± 0.8 (light) and 21.7 ± 1.0 (dark) cal/1000 beam breaks (n=17) . The correlations between measured and model-calculated TEE were r = 0.888 ± 0.013 (light) and 0.888 ± 0.0 (dark) . Under usual housing conditions (ambient temperature of 23 °C) , the average physical activity was 1390 ± 130 (light) and 4940 ± 390 (dark) beam breaks/h. Based on these data, PAEE accounts for 8.6 ± 0.9 % (light) and 21.7 ± 1.8 % (dark) of TEE. This rigorous determination of PAEE advances understanding the role of physical activity in mouse energy metabolism, improving the predictive value of the mouse as a model for human disorders. Disclosure V.Skop: None. J.Guo: n/a. N.Liu: None. K.D.Hall: None. O.Gavrilova: None. M.L.Reitman: None. Funding Intramural NIDDK

P4385Diaphragm dysfunction following cardiac surgery: role of ultrasound imaging for initial and follow-up assessment during cardiac rehabilitation

Abstract Background Diaphragm dysfunction is a common complication of cardiac surgery, often underdiagnosed. Ultrasonography (US) is a promising technique for diaphragmatic assessment. Few trials have been conducted using US after heart surgery and no clear data exist on the recovery of diaphragm function after cardiovascular rehabilitation (CR). Purpose The aim of this study is to evaluate post-cardiac surgery diaphragm dysfunction using US and to assess the impact of an inpatient CR programme on its functional recovery. Methods In a single-centre prospective cohort study 97 consecutive patients hospitalised in our CR Unit were enrolled. 14 patients underwent aortic valve replacement, 38 mitral valve repair or replacement, 14 coronary artery bypass grafting (CABG), 22 combined surgery, and 9 other surgical interventions. We performed diaphragm US at admission and after 10 rehabilitative sessions. The following parameters were assessed: thickening fraction (TF) in B-mode on the right intercostal projections, and excursion, time of inspiration, time of a respiratory cycle and contraction velocity in M-mode on right anterior subcostal projections. Results After cardiac surgery, the incidence of diaphragm dysfunction and paralysis were 60% and 1%, respectively. Patients with TF <20% at admission showed a significant improvement in TF (13.30%, IQR 8.69–17.39 vs 27.27%, IQR 21.05–31.58; p<0.001), excursion (1.67cm, IQR 1.3–2.1 vs 2.23cm, IQR 1.9–2.7; p<0.001), time of inspiration (0.9s, IQR 0.9–1.07 vs 1.01s, IQR 0.87–1.13; p=0.005), time of a respiratory cycle (2.67s, IQR 2.38–3.05 vs 3.07s, IQR 2.68–3.35; p<0.001) and velocity (1.81cm/s, IQR 1.14–2.33 vs 2.24cm/s, IQR 1.92–2.76; p<0.001). On the contrary, in patients with a TF>20%, no additional improvement was observed. In both groups, there was a significant improvement in the parameters of physical performance. In particular, in the group with a TF<20%, the distance covered during the 6MWT (300m, IQR 205–370 vs 555m, IQR 450–612; p<0.001) and the energy cost of physical activity (2.60, IQR 2.13–2.92 vs 4.09, IQR 3.44–4.50; p<0.001) increased while the perception of exertion (Borg Scale 11, IQR 11–13 vs 13, IQR 12–13; p=0.011) was reduced. At the 10th day assessment, 51.5% of the total population had a recovery of diaphragm function, whilst 48.5% had a failure of recovery (TF relative change between admission and discharge <60%). The multivariate analysis identified CABG as an independent predictor of failure of diaphragm recovery (OR 5.44; CI 1.10–26.84, p=0.037). Conclusion US might be a valuable part of routine clinical practice for initial and follow-up assessment of patients after open-heart surgery. CR showed to be an effective strategy to improve diaphragm parameters in patients with post-surgical dysfunction. Progressive evaluation of diaphragm function may drive personalised rehabilitation programmes.

Quantification of Daily Physical Activity and Sedentary Behavior of Claudicating Patients

Claudication is the most common manifestation of peripheral artery disease (PAD), producing significant ambulatory compromise. Limited information exists on the routine physical activity of claudicating patients. Our objective was to record the intensity/time profiles of physical activity and the timing and duration of sedentary behavior of a sample of community-dwelling claudicating patients. Forty-four claudicating patients referred to our vascular clinic were recruited. Physical activity was recorded using the ActiGraph GT1M activity monitor. The Actigraph monitor is a lightweight instrument designed to measure human movement through changes in acceleration, measured as counts over 1-minute time periods. Data from 7 consecutive days were used for the calculations. We processed the data using the ActiLife software program. The average daily activity of the claudicating patients shows a steady increase beginning approximately 05:30 AM until a peak plateau from approximately 10:00 AM to 01:30 PM followed by a steady decrease until approximately 09:30 PM, when a sustained period of inactivity begins. The average claudicating patient takes 3586 steps per day at an average intensity of 1.77 metabolic equivalents of task (METs, a physiological measure expressing the energy cost of physical activities). Average physical activity intensity and peak intensity fluctuate very little during the day, and they rarely exceed the level of light activity (light = <3 METs maximum effort, such as casual walking or light housework). During awake time, approximately 7 hours are spent in sedentary behaviors (<1.5 METs), and sedentary time is spread throughout the day mostly in short intervals between periods of low-energy activity. Our study objectively demonstrates the reduced physical activity of claudicating patients and documents physical activity/duration profiles throughout the day. The intensity of the physical activity of the average claudicating patient fluctuates very little during the day and rarely exceeds a light intensity level. Claudicating patients spend approximately half of their awake time in sedentary behavior and when they walk they do it in short bursts followed by several minutes of rest. We anticipate that changes in routine physical activity/duration profiles of patients with PAD will provide relevant, sensitive, and direct measures of the effectiveness of therapeutic interventions.

A Youth Compendium of Physical Activities: Activity Codes and Metabolic Intensities.

A Youth Compendium of Physical Activities (Youth Compendium) was developed to estimate the energy costs of physical activities using data on youth only. On the basis of a literature search and pooled data of energy expenditure measurements in youth, the energy costs of 196 activities were compiled in 16 activity categories to form a Youth Compendium of Physical Activities. To estimate the intensity of each activity, measured oxygen consumption (V˙O2) was divided by basal metabolic rate (Schofield age-, sex-, and mass-specific equations) to produce a youth MET (METy). A mixed linear model was developed for each activity category to impute missing values for age ranges with no observations for a specific activity. This Youth Compendium consists of METy values for 196 specific activities classified into 16 major categories for four age-groups, 6-9, 10-12, 13-15, and 16-18 yr. METy values in this Youth Compendium were measured (51%) or imputed (49%) from youth data. This Youth Compendium of Physical Activities uses pediatric data exclusively, addresses the age dependency of METy, and imputes missing METy values and thus represents advancement in physical activity research and practice. This Youth Compendium will be a valuable resource for stakeholders interested in evaluating interventions, programs, and policies designed to assess and encourage physical activity in youth.

Does Pregnancy Affect the Metabolic Equivalent at Rest and During Low Intensity Exercise?

Background: One metabolic equivalent (MET) is the amount of oxygen consumed while sitting at rest and is equal to 3.5 ml O2·kg-1·min-1. METs are often used to provide simple, practical, and easily understood values that reflect the energy cost of physical activity. It is plausible that the increase in body mass and absolute submaximal oxygen uptake during gestation has the potential to affect the MET of pregnant women. Objective: The aim of this study was to measure the MET during the second trimester of pregnancy and to compare this with non-pregnant women. In addition, the measured MET values were compared to those proposed by the Compendium of Physical Activities (CPA). Design: Ten pregnant and ten non-pregnant women participated in this study. Ventilatory variables and heart rate (HR) were measured during four conditions on two different days: Condition 1 - sitting, Condition 2 - lying, Condition 3 - treadmill walking and Condition 4 - cycling. The women performed two conditions on each testing day; one resting condition followed by one exercising condition. The data were analysed using a two-way ANOVA with repeated measures. Bonferroni’s tests were used when significant differences were detected. Results: The MET was not significantly different between pregnant and non-pregnant women either at rest or during exercise (p > 0.05). While cycling, the MET obtained by indirect calorimetry (IC) was significantly higher than the CPA predicted MET, regardless of group (pregnant cycling p = 0.002 and non-pregnant cycling p 0.05). In general, (combined pregnant and non-pregnant data), VE and HR were significantly higher during seated rest, when compared with supine rest and all ventilatory variables, HR and ratings of perceived exertion (RPE) were significantly higher during cycling, when compared with walking (p > 0.05). Conclusion: METs were unaffected by pregnancy at rest or when undertaking either walking or cycling exercise during the second trimester of pregnancy. The MET of cycling was significantly underestimated by the CPA, when compared to IC, in both groups.

Prolonged high altitude exposure exacerbates fat‐free mass and fat mass loss during negative energy balance regardless of dietary protein intake

Protein intake above the recommended dietary allowance attenuates fat‐free mass (FFM) loss during moderate negative energy balance (~40% energy deficit) at sea level (SL). Sustained periods of strenuous physical activity at high altitude (HA) may exacerbate FFM loss, especially during energy deficit. However, increased dietary protein intake has not been evaluated as a countermeasure to FFM loss at HA. This study aimed to determine whether consuming dietary protein at amounts consistent with current recommendations for elevated physical activity (2.0 g protein/kg) attenuates FFM loss during prolonged energy deficit at HA. Seventeen healthy males (mean ± SD, 23.4 ± 5.6y, 81.9± 13.9 kg) participated in a 2‐phase, 43‐d study. During phase 1 (SL), participants were instructed to consume a weight maintenance diet with standard protein intake(1.0 g protein/kg, STD) for 21 d. During phase 2, participants resided at HA (4300 m, Pikes Peak, CO) for 22 d and were randomly assigned to either a STD or high (2.0 g protein/kg, HIGH) protein diet designed to elicit a 40% energy deficit (30% dietary restriction and 10% increase in physical activity, estimated energy deficit was 1074 ± 122 kcal/d based on the total energy requirements necessary to maintain body mass during phase 1) and~3 kg total body mass loss. Diet and physical activity were highly controlled. Total body mass, FFM, and fat mass (FM) were assessed by dual energy x‐ray absorptiometry and resting metabolic rate (RMR) by indirect calorimetry. Volunteers were weight stable during SL and lost −7.9 ± 1.9 kg(P&lt;0.01)during HA, regardless of protein group (P&gt;0.05). Decrements in FFM (−4.0 ± 3.3 vs. −3.2 ± 1.5 kg) and FM (−3.3 ± 1.8 vs. −3.9 ± 0.8 kg) were not statistically different between STD and HIGH (P&gt;0.05). The overall energy deficit was 2306 ± 444kcal/d when calculated based on changes in FFM and FM. The additional energy deficit was attributable, in part, to an increase in RMR, which peaked at 58%above SL on HA day 1 and remained ≥ 25% higher than SL throughout HA(P&lt;0.05), accounting for 27% (634 ± 273 kcal/d) of the total energy deficit at HA. The remaining 598 kcal/d (26% of total deficit) could not be accounted for by estimated energy expenditure of prescribed daily physical activity and measured energy intake, suggesting the energy cost of physical activity may be greater at HA than SL. Prolonged HA exposure exacerbated the catabolic effects of negative energy balance. In this context, consuming a higher versus standard protein diet was equally ineffective at sparing FFM with weight loss. The opinions or assertions contained herein are the private views of the author(s)and are not to be construed as official or reflecting the views of the Army or the Department of Defense.Support or Funding InformationSupported by USAMRMC.

Developmental Trends in the Energy Cost of Physical Activities Performed by Youth.

Published energy cost data for children and adolescents are lacking. The purpose of this study was to measure and describe developmental trends in the energy cost of 12 physical activities commonly performed by youth. A mixed age cohort of 209 participants completed 12 standardized activity trials on 4 occasions over a 3-year period (baseline, 12-months, 24-months, and 36-months) while wearing a portable indirect calorimeter. Bayesian hierarchical regression was used to link growth curves from each age cohort into a single curve describing developmental trends in energy cost from age 6 to 18 years. For sedentary and light-intensity household chores, YOUTH METs (METy) remained stable or declined with age. In contrast, METy values associated with brisk walking, running, basketball, and dance increased with age. The reported energy costs for specific activities will contribute to efforts to update and expand the youth compendium.

Energy Cost of Physical Activities and Sedentary Behaviors in Young Children.

This study reports energy expenditure (EE) data for lifestyle and ambulatory activities in young children. Eleven children aged 3 to 6 years (mean age = 4.8 ± 0.9; 55% boys) completed 12 semistructured activities including sedentary behaviors (SB), light (LPA), and moderate-to-vigorous physical activities (MVPA) over 2 laboratory visits while wearing a portable metabolic system to measure EE. Mean EE values for SB (TV, reading, tablet and toy play) were between 0.9 to 1.1 kcal/min. Standing art had an energy cost that was 1.5 times that of SB (mean = 1.4 kcal/min), whereas bike riding (mean = 2.5 kcal/min) was similar to LPA (cleaning-up, treasure hunt and walking) (mean = 2.3 to 2.5 kcal/min), which had EE that were 2.5 times SB. EE for MVPA (running, active games and obstacle course) was 4.2 times SB (mean = 3.8 to 3.9 kcal/min). EE values reported in this study can contribute to the limited available data on the energy cost of lifestyle and ambulatory activities in young children.

Validity of Accelerometer Methods to Estimate Activity Energy Cost in Adults With and Without Functional Limitations

PURPOSE: The purpose of this study was to evaluate the validity of two published accelerometer analysis methods to estimate energy cost of physical activities in adults with and without functional limitations. METHODS: 62 healthy and functionally limited ambulatory adults underwent measures of strength and functional testing to cluster into 1) no functional limitations [HLTHY], or 2) lower and/or upper body limitations [LIM]. All subjects completed a variety of simulated activities while wearing accelerometers and a portable metabolic system. Estimated METs were derived from a hip-worn accelerometer (Freedson et al.(HIP)), and a wrist-worn accelerometer (Staudenmayer et al.(WRIST)). Model predictions were compared to measured METs and evaluated on the types of activities for which they were developed (HIP=locomotion, WRIST=all activities). Statistical significance was assessed with a linear mixed model. RESULTS: Mean (95% CI) measured METs across all activities were HLTHY (n=17, 48.1 ± 16.7 yrs) 3.17 (1.59) and LIM (n=45, 61.0 ±12.9 yrs) 2.32 (1.08). Fig.1. Accelerometer Model Prediction Performance. Mean (95% CI). Fig.1. shows neither the HIP nor the WRIST methods are significantly biased for the HLTHY group, and both methods are biased for the LIM group. Estimates for the LIM group are significantly different from the HLTHY group for both methods. The HIP and WRIST methods under- and over-estimate respectively for the LIM group. CONCLUSION: Accelerometer energy cost model performance is influenced by whether or not an individual has functional limitations. Future research efforts should examine how to improve accelerometer model performance within individuals with functional limitations. Supported by NIH-1R21HD080828.

Physical Activity and the Missing Calories.

Physical Activity and the Missing Calories.

Overreliance on familiar, manual, one-arm-drive wheelchair technology

International Journal of Therapy and RehabilitationVol. 21, No. 5 OpinionOverreliance on familiar, manual, one-arm-drive wheelchair technologyAnne MandyAnne MandySearch for more papers by this authorAnne MandyPublished Online:9 May 2014https://doi.org/10.12968/ijtr.2014.21.5.208AboutSectionsView articleView Full TextPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareShare onFacebookTwitterLinked InEmail View article References Biotechnology and Biological Sciences Research Council (BBSRC) (2013) Best Practice Guidance Note: www.bbsrc.ac.uk/web/FILES/EmploymentCode/guidance_note_2_disabilities.pdf (accessed 12 March 14) Google ScholarConger SA, Bassett DR (2011) A Compendium of Energy Costs of Physical Activities for Individuals Who use Manual Wheelchairs. Adapt Phys Activ Q 28(4): 310–25 Crossref, Google ScholarFinley MA, Rodgers MM (2004) Prevalence and identification of shoulder pathology in athletic and nonathletic wheelchair users with shoulder pain: a pilot study. J Rehabil Res Dev 41(3b): 395–402 Crossref, Google ScholarHurst A, Tobias J (2011) Empowering individuals with do-it-yourself assistive technology. ASSETS. The proceedings of the 13th international ACM SIGACCESS conference on Computers and accessibility. ACM 11: 24–6 Google ScholarMandy A, Redhead L, McCudden C, Michaelis J (2013) A comparison of vertical reaction forces during propulsion of three different one-arm drive wheelchairs by hemiplegic users. [published online ahead of print 25 March] Disabil Rehabil Assist Technol: 1–6 Google ScholarMandy A, Lesley S (2009) Measures of Energy Expenditure, and Comfort in an ESP wheelchair: A Controlled Trial using Hemiplegic Users. Disabil Rehabil Assist Technol 4(3): 137–42 Crossref, Google ScholarMcLaurin CA Brubaker C (1986) Lever drive system for wheelchairs. J Rehabi Res Dev 23(2): 52–4 Google ScholarMcLaurin CA (1990) Current Directions in Wheelchair Research. J Rehabil Res Dev Clin Suppl 2:88–99 Google ScholarRoberts J, Young H, Andrew K, McAlpine A, Hogg J (2011) The needs of carers who push Wheelchairs. J Integrated Care 20(1): 23–35 Crossref, Google ScholarSarraj AR, Massarelli R (2011) Design History and Advantages of a New Lever-Propelled Wheelchair Prototype. Int J Adv Robotic Sy 8(3): 12–21 Google ScholarSmith C, Kirby RL (2011) Manual wheelchair skills capacity and safety of residents of a long-term-care facility. Arch Phys Med Rehabil 92(4): 663–9 Google Scholar FiguresReferencesRelatedDetails 1 May 2014Volume 21Issue 5ISSN (online): 1759-779X Metrics History Published online 9 May 2014 Published in print 1 May 2014 Information© MA Healthcare LimitedPDF download

Perceived Exertion and Energy Cost of Physical Activity during Pregnancy

Perceived Exertion and Energy Cost of Physical Activity during Pregnancy

Declared and real physical activity in patients with type 2 diabetes mellitus as assessed by the International Physical Activity Questionnaire and Caltrac accelerometer monitor: A potential tool for physical activity assessment in patients with type 2 diabetes mellitus

AimsThe aims of this study were to assess and compare declared and real volume of physical activity (PA), and to evaluate correlations of these measurements with glycemic control (HbA1c) and body mass index (BMI), in patients with type 2 diabetes mellitus (T2DM). Material and methodsA group of 31 (16 women and 15 men) type 2 diabetic patients treated with insulin monotherapy, from (mean age=54±3.6 years, BMI=29.7±4.8kg/m2, T2DM treatment=9±8 years, HbA1c 7±1%) and not professionally active (unemployed or retired) was recruited.An assessment of energy cost (EC) of their weekly PA using International Physical Activity Questionnaire (IPAQ), and an accelerometer assessment was performed. ResultsTotal energy expenditure of the declared weekly PA, calculated from the IPAQ (DPA) was 2513±1349METmin/week, and 2428±1348, for male and female participants, respectively (p>0.05). EC of the real PA (RPA), registered with the accelerometer was 4552±2028kcal/week, and 4032±2288kcal/week, for males, and females, respectively. Patients who demonstrated a high DPA, based on their IPAQ score, showed a significantly higher RPA, as registered by the accelerometer (p<0.05). HbA1c and BMI did not correlate with their PA measurements. ConclusionsOur findings indicate that the IPAQ may serve as a potential tool for physical activity assessment with no further requirement for more sophisticated methods. Our results suggest that habitual physical activity has no impact on glycemic control and BMI in type 2 diabetic patients. However, further studies on a larger population are needed to explore these issues.

Changes in daily physical activity before and after total hip arthroplasty. A pilot study using accelerometry

The present single-centre prospective follow-up study assessed the objective changes in physical activity undertaken before and after total hip arthroplasty (THA) using accelerometry. We enrolled 12 female patients who underwent home-based accelerometry assessment one month before and six months after the THA procedure. We assessed the daily amount of physical activity and energy expenditure related to physical activities. We also recorded the intensity of the physical activity, and pre- and post-operative clinical evaluation with the Harris Hip Score (HHS). At 6 months after surgery, we found a statistically significant increase of the total energy cost of physical activity (DA) (P=0.02), without significant increase of activity time (P>0.05). The energy cost of moderate/vigorous activity was statistically significant increased after surgery (P=0.008). Finally, HHS improved form 53.9±15.3 pre-operatively to 78.1±12.2 post-operatively (P=0.03). In our patients, the improvement was significant only for the total energy cost of daily activity. Thus, although patients did not exhibit a more active lifestyle, as shown by the slight increase of the activity time, they significantly increased the amount of moderate or vigorous activities performed after surgery.

Energy Costs of Physical Activities for Wheelchair Users: A Systematic Review

Energy Costs of Physical Activities for Wheelchair Users: A Systematic Review