Body Fat Is Related to Sedentary Behavior and Light Physical Activity but Not to Moderate-Vigorous Physical Activity in Type 2 Diabetes Mellitus

Explanatory variables of objectively measured 24-h movement behaviors in people with prediabetes and type 2 diabetes: A systematic review

AIM

Physical activity (PA), sedentary behavior (SB) and sleep (i.e. 24-h movement behaviors) are associated with health indicators in people with prediabetes and type 2 diabetes (T2D). To optimize 24-h movement behaviors, it is crucial to identify explanatory variables related to these behaviors. This review aimed to summarize the explanatory variables of 24-h movement behaviors in people with prediabetes or T2D.

METHODS

A systematic search of four databases (PubMed, Web of Science, Scopus & Embase) was performed. Only objective measurements of 24-h movement behaviors were included in the search strategy. The explanatory variables were classified according to the levels of the socio-ecological model (i.e. intrapersonal, interpersonal and environmental). The risk of bias was assessed using the Joanna Briggs Institute appraisal checklist.

RESULTS

None of the 78 included studies investigated 24-h movement behaviors. The majority of the studies investigated PA in isolation. Most studied explanatory variables were situated at the intrapersonal level. Being male was associated with more moderate to vigorous PA but less light PA in people with T2D, and more total PA in people with prediabetes. An older age was associated with a decrease in all levels of PA in people with T2D. HbA1c was positively associated with sleep and SB in both groups. No associations were found at the interpersonal or environmental level.

CONCLUSION

The results of this review underscore the lack of a socio-ecological approach toward explanatory variables of 24-h movement behaviors and the lack of focus on an integrated 24-h movement behavior approach in both populations.

Association between depression, anemia and physical activity using isotemporal substitution analysis

BACKGROUND

Depression is a leading cause of disability and mortality, with estimated number of deaths exceeding 2.2 million worldwide. We examined depression in relation to anemia and physical activity, both of which have an impact on depression mechanisms.

METHODS

This cross-sectional study used data from the Korean National Health and Nutrition Examination Survey, including 18,622 participants. Depression was measured by The Patient Health Questionnaire-9, and physical activity was assessed by the Global Physical Activity Questionnaire. Anemia was defined by World Health Organization criteria for blood hemoglobin levels. Isotemporal substitution model for physical activity was used to assess the effect of replacing sedentary behavior to each intensity level of physical activity. Logistic regression was applied to estimate the association on depression.

RESULTS

Replacing sedentary behavior with moderate or vigorous physical activity was associated with a lower risk of depression in the anemic (OR: 0.875, 95% CI: 0.782-0.978) and non-anemic groups (OR: 0.943, 95% CI: 0.919-0.967). Depression risk was significantly reduced by replacing walking with moderate to vigorous physical activity in both anemic (OR: 0.877, 95% CI: 0.784-0.982) and non-anemic groups (OR: 0.951, 95% CI: 0.927-0.976).

CONCLUSIONS

Moderate to vigorous physical activity had a protective association against depression in both anemic and non-anemic groups. Anemic patients are recommended to perform physical activity for any duration acceptable to them to prevent depression.

The Physical Activity Assessment of Adults With Type 2 Diabetes Using Accelerometer-Based Cut Points: Scoping Review

Background

Incorporating physical activity into lifestyle routines is recommended for individuals with type 2 diabetes. Accelerometers offer a promising method for objectively measuring physical activity and for assessing interventions. However, the existing literature for accelerometer-measured physical activity among middle-aged and older adults with type 2 diabetes is lacking.

Objective

This study aims to identify research studies in which accelerometer-based cut points were used to classify the physical activity intensity of middle-aged to older adults with type 2 diabetes as sedentary, light, moderate, vigorous, and very vigorous, and to determine if validated accelerometer cut points specifically for this population exist.

Methods

We followed the Joanna Briggs Institute methodology for scoping reviews. Between June 23 and July 12, 2020, two reviewers independently screened records from four databases (PubMed, Web of Science, Embase, Engineering Village) and the ActiGraph Corp web site for eligible studies that included patients with type 2 diabetes with a sample mean age ≥50 years, used research-grade accelerometers, applied cut points to categorize objectively measured physical activity, and were available in English. We excluded studies reporting exclusively steps or step counts measured by accelerometers or pedometers and conference abstracts or other sources that did not have a full text available. Data extraction was completed using Microsoft Excel. Data for the following variables were tabulated based on frequency distributions: study design, accelerometer type, device placement, epoch length, total wear time, and cut points used. Study aims and participant demographic data were summarized.

Results

A total of 748 records were screened at the abstract level, and 88 full-text articles were assessed for eligibility. Ultimately, 46 articles were retained and analyzed. Participants’ mean ages ranged from 50 to 79.9 years. The ActiGraph accelerometer and the Freedson et al and Troiano et al counts-per-minute cut points were the most frequently used across the literature. Freedson et al and Troiano et al counts-per-minute cut points for light, moderate, and vigorous activity correspond to <1952, 1952-5724, and ≥5725, and 100-2019, 2020-5998, and ≥5999, respectively. The Lopes et al cut points were developed by calibrating the ActiGraph in middle-aged and older adults with overweight/obesity and type 2 diabetes. These counts-per-minute thresholds are ≥200 (light), ≥1240 (moderate), and ≥2400 (vigorous), and were applied in 1 interventional study.

Conclusions

An assortment of accelerometer cut points have been used by researchers to categorize physical activity intensity for middle-aged and older adults with diabetes. Only one set of cut points was validated and calibrated in our population of interest. Additional research is warranted to address the need for diabetes-specific cut points to inform public health recommendations. This includes confirmation that the Lopes et al cut points reflect clinically meaningful changes in physical activity for adults with diabetes who have comorbidities other than overweight/obesity and the development of relative intensity cut points that may be more suitable for those with suboptimal physical functioning.

The Correlation of Prediabetes and Type 2 Diabetes With Adiposity in Adults

Background

Fat metabolism is associated with prediabetes and type 2 diabetes mellitus (T2DM). The aim of this study was to evaluate the detailed correlation of diabetes status with adiposity among adults.

Methods

Briefly, 28,429 adults aged ≥18 years from both sexes in the National Health and Nutrition Examination Survey (NHANES) 1999–2018 were included in this study. Multivariable linear regression models were used to examine associations of prediabetes and diabetes status, disease duration of T2DM, serum glucose, glycohemoglobin (HbA1c) with total percent fat (TPF), and fat mass distribution.

Results

After adjusting for sociodemographic covariates, health behaviors, hypertension, hypercholesterolemia, there were direct associations of prediabetes and T2DM status with TPF, trunk fat mass, android fat mass, gynoid fat mass and android to gynoid ratio compared with non-diabetes. But the fat mass decreased with the increase of the disease duration in patients with T2DM. Besides, when stratifying by diabetes status, we found direct associations of serum glucose and HbA1c with TPF, trunk fat mass, android fat mass, gynoid fat mass, and android to gynoid ratio in non-diabetic and prediabetic participants. But in patients with T2DM, inverse associations of serum glucose and HbA1c with fat mass were observed.

Conclusions

This study indicated that adults with prediabetes and T2DM had significantly higher TPF, trunk fat mass, android fat mass, gynoid fat mass, and android to gynoid ratio compared with those without diabetes. Moreover, fat mass decreased as the disease duration increased in patients with T2DM. The associations of serum glucose and HbA1c with TPF and fat mass distribution in patients with T2DM were opposite to the relationships observed in non-diabetic and prediabetic participants.

The Impact of Wearable Technologies in Health Research: Scoping Review

Background

Wearable devices hold great promise, particularly for data generation for cutting-edge health research, and their demand has risen substantially in recent years. However, there is a shortage of aggregated insights into how wearables have been used in health research.

Objective

In this review, we aim to broadly overview and categorize the current research conducted with affordable wearable devices for health research.

Methods

We performed a scoping review to understand the use of affordable, consumer-grade wearables for health research from a population health perspective using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) framework. A total of 7499 articles were found in 4 medical databases (PubMed, Ovid, Web of Science, and CINAHL). Studies were eligible if they used noninvasive wearables: worn on the wrist, arm, hip, and chest; measured vital signs; and analyzed the collected data quantitatively. We excluded studies that did not use wearables for outcome assessment and prototype studies, devices that cost >€500 (US $570), or obtrusive smart clothing.

Results

We included 179 studies using 189 wearable devices covering 10,835,733 participants. Most studies were observational (128/179, 71.5%), conducted in 2020 (56/179, 31.3%) and in North America (94/179, 52.5%), and 93% (10,104,217/10,835,733) of the participants were part of global health studies. The most popular wearables were fitness trackers (86/189, 45.5%) and accelerometer wearables, which primarily measure movement (49/189, 25.9%). Typical measurements included steps (95/179, 53.1%), heart rate (HR; 55/179, 30.7%), and sleep duration (51/179, 28.5%). Other devices measured blood pressure (3/179, 1.7%), skin temperature (3/179, 1.7%), oximetry (3/179, 1.7%), or respiratory rate (2/179, 1.1%). The wearables were mostly worn on the wrist (138/189, 73%) and cost <€200 (US $228; 120/189, 63.5%). The aims and approaches of all 179 studies revealed six prominent uses for wearables, comprising correlations—wearable and other physiological data (40/179, 22.3%), method evaluations (with subgroups; 40/179, 22.3%), population-based research (31/179, 17.3%), experimental outcome assessment (30/179, 16.8%), prognostic forecasting (28/179, 15.6%), and explorative analysis of big data sets (10/179, 5.6%). The most frequent strengths of affordable wearables were validation, accuracy, and clinical certification (104/179, 58.1%).

Conclusions

Wearables showed an increasingly diverse field of application such as COVID-19 prediction, fertility tracking, heat-related illness, drug effects, and psychological interventions; they also included underrepresented populations, such as individuals with rare diseases. There is a lack of research on wearable devices in low-resource contexts. Fueled by the COVID-19 pandemic, we see a shift toward more large-sized, web-based studies where wearables increased insights into the developing pandemic, including forecasting models and the effects of the pandemic. Some studies have indicated that big data extracted from wearables may potentially transform the understanding of population health dynamics and the ability to forecast health trends.

Inter-Individual Variability of a High-Intensity Interval Training With Specific Techniques vs. Repeated Sprints Program in Sport-Related Fitness of Taekwondo Athletes

This study investigated the effect of 4 weeks of high-intensity interval training (HIIT) with specific techniques (TS-G) vs. repeated sprints (RS-G) and analyzed the inter-individual variability [classified into responders (Rs) and non-responders (NRs)] on sport-related fitness in taekwondo (TKD) athletes. Athletes of both genders (n = 12) were randomly assigned into TS-G and RS-G groups. Both groups trained 3 days/week for 4 weeks [two blocks of three rounds of 2 min of activity (4-s of all-out efforts with 28-s dynamical pauses) with 1 min of recovery in between and 5 min between blocks] during their regular training. The related sport fitness assessments included squat jump (SJ), countermovement jump (CMJ), multiple frequency speed of kick test (FSKT_MULT), specifically total kicks and Kick Decrement Index (KDI), and 20-m shuttle run (20MSR). Relevant results indicate a significant effect of the time factor in both groups for SJ performance and a significant decrease for KDI in RS-G. In addition, an improvement in performance according to the effect size analysis in the TS-G in total kicks, KDI, and 20MSR. Complementarily, a higher proportion of athlete Rs was reported in TS-G vs. RS-G for SJ (50% vs. 30.3%, respectively), CMJ, and total kicks (16.6% vs. 0%). In conclusion, the addition to the regular training of a HIIT with specific-techniques and repeated-sprints associated with intervals and similar structure of the combat during 4 weeks of training can improve the concentric characteristics of lower limb performance, although they were not the sufficient stimuli in the other components of TKD-related fitness.

EFFECT OF SPORTS MEDICINE ON REDUCING BODY FAT PERCENTAGE AND LEAN BODY MASS

ABSTRACT Introduction: Aerobic exercise has begun to be widely recognized as a reasonable means of preventing fat and losing weight. Scholars have confirmed that sports can help the human body lose weight and lose fat. Objective: This article measures the exercise performance indicators of subjects in different body fat percentage groups and studies the relationship between body fat percentage and exercise performance indicators. Methods: The study uses experimental methods to determine the percentage of body fat of the subjects. After physical exercise and aerobic exercise, the volunteers were tested for aerobic capacity indicators. Results: The body fat percentage of physically inactive persons was negatively correlated with aerobic and anaerobic exercise capacity indexes. Conclusion: The mechanism of aerobic exercise in weight loss treatment has the effect of promoting lipolysis and regulating blood lipid metabolism. At the same time, it has a significant influence on the number and activity of fat cells. Level of evidence II; Therapeutic studies - investigation of treatment results.

Effects of 4 Weeks of a Technique-Specific Protocol with High-Intensity Intervals on General and Specific Physical Fitness in Taekwondo Athletes: An Inter-Individual Analysis

The aim of this research was to compare the effects of a technique-specific high-intensity interval training (HIIT) protocol vs. traditional taekwondo training on physical fitness and body composition in taekwondo athletes, as well as to analyse the inter-individual response. Utilising a parallel controlled design, sixteen male and female athletes (five females and 11 males) were randomly divided into an experimental group (EG) that participated in the technique-specific HIIT and a control group (CG) that participated in traditional taekwondo training. Both groups trained three days/week for four weeks. Squat jump (SJ), countermovement jump (CMJ), 5-metre sprint (5M), 20-metre shuttle run (20MSR), taekwondo specific agility test (TSAT), multiple frequency speed of kick test (FSKT_MULT), total kicks, and kick decrement index (KDI), as well as body composition were evaluated. Results indicate that there are no significant differences (p > 0.05) in the factors group and time factor and group by time interaction (p > 0.05). Although percentage and effect size increases were documented for post-intervention fitness components in TSAT, total kicks, KDI, and 20MSR, responders and non-responders were also documented. In conclusion, a HIIT protocol based on taekwondo-specific technical movements does not report significant differences in fitness and body composition compared to traditional taekwondo training, nor inter-individual differences between athletes.

Brain activity during a working memory task in different postures: an EEG study

While working is more comfortable in a supine position and healthier in a standing, most people work in a sitting. However, it is unclear whether there are differences in brain activity efficiency in different postures. Here, we, therefore, compared changes in brain activity across three different postures to determine the optimal posture for performing working memory tasks. Their effect on brain activity was examined using EEG signals together with the information of accuracy and reaction times during 2-back task in 24 subjects. Substantial differences in brain waves were observed at sitting and standing positions compared to the supine, especially in delta waves and frontal lobe, where is known to improve the modulation of brain activity efficiently. Brain efficiency was higher during standing and sitting than in a supine. These findings show that postural changes may affect the efficiency of brain activity during working memory tasks. Practitioner summary: Differences in brain efficiency between different postures during working memory tasks have not been explored. This study suggests that efficiency in several brain areas is higher during sitting and standing than in a supine position. This finding has important implications regarding workplace environments. Furthermore, this result would be useful to improve accomplishment and reduce negative effects of work posture. Abbreviations: EEG: electroencephalogram; PSQI: Pittsburgh sleep quality index; KSS: Karolinska sleepiness scale; FFT: fast fourier transform; ROI: region of interest; ANS: autonomic nervous system; Fp: prefrontal; AF: anterior frontal; frontal; Fz: midline frontal; temporal; central; Cz: midline central; P: parietal; Pz: midline parietal; O: occipital; Oz: midline occipital.

Validation of the effectiveness of a digital integrated healthcare platform utilizing an AI-based dietary management solution and a real-time continuous glucose monitoring system for diabetes management: a randomized controlled trial

BACKGROUND

Despite the numerous healthcare smartphone applications for self-management of diabetes, patients often fail to use these applications consistently due to various limitations, including difficulty in inputting dietary information by text search and inconvenient and non-persistent self-glucose measurement by home glucometer. We plan to apply a digital integrated healthcare platform using an artificial intelligence (AI)-based dietary management solution and a continuous glucose monitoring system (CGMS) to overcome those limitations. Furthermore, medical staff will be performing monitoring and intervention to encourage continuous use of the program. The aim of this trial is to examine the efficacy of the program in patients with type 2 diabetes mellitus (T2DM) who have HbA1c 53-69 mmol/mol (7.0-8.5%) and body mass index (BMI) ≥ 23 mg/m2.

METHODS

This is a 48-week, open-label, randomized, multicenter trial consisting of patients with type 2 diabetes. The patients will be randomly assigned to three groups: control group A will receive routine diabetes care; experimental group B will use the digital integrated healthcare platform by themselves without feedback; and experimental group C will use the digital integrated healthcare platform with continuous glucose monitoring and feedback from medical staff. There are five follow-up measures: baseline and post-intervention at weeks 12, 24, 36, and 48. The primary end point is change in HbA1c from baseline to six months after the intervention.

DISCUSSION

This trial will verify the effectiveness of a digital integrated healthcare platform with an AI-driven dietary solution and a real-time CGMS in patients with T2DM.

TRIAL REGISTRATION

Clinicaltrials.gov NCT04161170, registered on 08 November 2019. https://clinicaltrials.gov/ct2/show/NCT04161170?term=NCT04161170&draw=2&rank=1.