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Background/Objectives:: Easy-to-use and accurate methods to assess free-living activity energy expenditure (AEE) in preschool children are required. The aims of this study in healthy preschool children were to (a) evaluate the ability of the wrist-worn ActiGraph wGT3x-BT to predict free-living AEE and (b) assess wear compliance using a 7-day, 24-h protocol. Subjects/Methods:: Participants were 40 Swedish children (5.5±0.2 years) in the Mobile-based intervention intended to stop obesity in preschoolers (MINISTOP) obesity prevention trial. Total energy expenditure (TEE) was assessed using the doubly labeled water method during 14 days. AEE was calculated as (TEEx0.9) minus predicted basal metabolic rate. The ActiGraph accelerometer was worn on the wrist for 7 days and outputs used were mean of the daily and awake filtered vector magnitude (mean VM total and mean VM waking). Results:: The ActiGraph was worn for 7 (n=34, 85%), 6 (n=4, 10%), 5 (n=1, 2.5%) and 4 (n=1, 2.5%) days (a valid day was ⩾600 awake minutes). Alone, mean VM total and mean VM waking were able to explain 14% (P=0.009) and 24% (P=0.001) of the variation in AEE, respectively. By incorporating fat and fat-free mass in the models 58% (mean VM total) and 62% (mean VM waking) in the variation of AEE was explained (P<0.001). Conclusions:: The wrist-worn ActiGraph wGT3x-BT in combination with body composition variables explained up to the 62% of the variation in AEE. Given the high wear compliance, the wrist-worn ActiGraph has the potential to provide useful information in studies where physical activity in preschool children is measured.

Background/Objectives:: To examine the association between parental body mass index (BMI) and their offspring’s body composition, physical fitness and lifestyle factors (that is, sedentary time, physical activity and diet). Subjects/Methods:: A total of 307 preschoolers (4.5±0.1 years) and their parents (fathers: 38.1±5.1 years and mothers: 35.6±4.2 years) participated in this study. Parental BMI was calculated using self-reported weight and height. Preschoolers body composition was assessed using: BMI, fat mass percentage, fat mass index, fat-free mass index (measured via air-displacement plethysmography) and waist circumference. Physical fitness was assessed by the PREFIT fitness battery. Lifestyle factors were assessed using the ActiGraph wGT3x-BT (sedentary time and physical activity), and the mobile-phone based tool for energy balance in children (diet). Results:: Parental BMI were positively associated with their offspring’s BMI (paternal BMI: standardised beta, β=0.233, P<0.001; maternal BMI: β=0.186, P=0.001), fat mass index (paternal BMI: β=0.130, P=0.026; maternal BMI: β=0.163, P=0.005), fat-free mass index (paternal BMI: β=0.214, P<0.001; maternal BMI: β=0.119, P=0.036) and waist circumference (paternal BMI: β=0.178, P=0.001; maternal BMI: β=0.179, P=0.001). A negative association was found between maternal BMI and their offspring’s standing long jump test (β=−0.132, P=0.022). Paternal BMI was associated with their offspring’s sedentary time (β=0.100, P=0.026), whereas parental BMI was not associated with neither physical activity nor diet (all P⩾0.104). Conclusions:: Parental BMI was positively associated with their offspring’s BMI, fat as well as fat-free mass index and waist circumference. Moreover, a higher paternal and maternal BMI were related to higher levels of sedentary time and a lower performance in the standing long jump test of their offspring, respectively.

Background:: Existing knowledge on associations of physical activity (PA) and sedentary behavior (SB) with body composition and physical fitness in preschoolers is limited. Objective:: To examine associations of PA and SB with body composition and physical fitness in healthy Swedish 4-year-old children. Methods:: We utilized baseline data collected in 2014 for the population-based MINISTOP trial (n=307). Light-intensity PA (LPA), moderate-intensity PA (MPA), vigorous-intensity PA (VPA), moderate-to-vigorous PA (MVPA) and SB were measured using accelerometry (ActiGraph-wGT3x-BT). Body composition was measured using air-displacement plethysmography, and physical fitness (that is, cardiorespiratory fitness, lower and upper body muscular strength and motor fitness) was measured using the PREFIT fitness test battery. Multiple linear regression models adjusted for relevant confounders, and in addition, isotemporal substitution models were applied. Results:: Greater MVPA was associated with lower fat mass percent (%FM, P=0.015), and greater VPA and MVPA were associated with higher fat-free mass index (FFMI, P=0.002 and P=0.011). In addition, greater VPA and MVPA were associated with higher scores for all physical fitness tests (P=0.042 to P<0.001). The results for MVPA were primarily due to VPA. SB was associated with weaker handgrip strength (P=0.031) when PA was not adjusted, but after adjusting also for VPA, the significant association disappeared (P=0.25). Substituting 5?min per day of SB, LPA or MPA with 5?min per day of VPA was associated with higher FFMI and better scores for cardiorespiratory fitness and motor fitness. Correspondingly, substituting 5?min per day of VPA with SB or LPA was associated with weaker performance for lower muscular strength. Conclusions:: Time spent on VPA was associated with higher FFMI and better physical fitness. The results suggest that promoting VPA may be important to improve childhood body composition and physical fitness already at an early age.

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Copyright of Nuova Secondaria is the property of Edizioni Studium S.r.l and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article discusses the development of an intelligent wearable device called the e-physiotherapist, which aims to measure physical activity (PA), blood pressure, and energy consumption. The device utilizes multiple sensors to collect data on various aspects of PA and cardiovascular health indicators. The goal is to develop and validate AI-based algorithms that can accurately measure these parameters in both laboratory and everyday conditions. The article highlights the limitations of current wearables on the market and emphasizes the need for a transparent and evidence-based wearable for healthcare use. The document discusses the use of wearable technology, specifically open-source wearables, to assess physical activity (PA) and health-related variables in real-time. The project aims to develop and validate algorithms using artificial intelligence and machine learning to analyze data collected from accelerometers and optical sensors in the wearables. The goal is to create a self-learning system that can accurately measure PA intensity, energy expenditure, and even blood pressure at an individual level. The project will involve recruiting apparently healthy adults to test the wearables and algorithms in controlled laboratory conditions and real-world settings. The document discusses the use of wearable technology and machine learning techniques to assess physical activity and energy expenditure. The goal is to develop a wearable device that can accurately measure and predict physical activity levels and provide personalized advice for healthy levels of activity. The document references several studies that have used machine learning to classify different types and intensities of physical activity with high accuracy. The authors also mention the use of reinforcement learning to handle unlabelled data [Extracted from the article]

The article reports that mental fitness is as important as physical fitness and should be neither neglected nor ignored as it is an integral part of maintaining mental wellbeing and making progress. It notes that high achievers understand that doing something when one does not feel like it is viewed as discipline, commitment, dedication and excellence rather than a burden to be undergone. It adds that high achievers do not necessarily exert themselves physically from the fitness point of view.

New research findings suggest that boys who participate in sports and stay physically active during early childhood may be less prone to generalized anxiety and depression disorders as they get [...]