Effect of physical activity and different exercise modalities on glycemic control in people with prediabetes: a systematic review and meta-analysis of randomized controlled trials

BackgroundNumerous studies have shown the beneficial effects of exercise on glycemic control in people with prediabetes. However, the most effective exercise modality for improving glycemic control remains unclear. We aimed to assess which exercise training modality is most effective in improving glycemic control in a population with prediabetes.MethodsWe conducted searches in Pubmed/MEDLINE, EMBASE, SPORTDiscus, Web of Science, PEDro, BVS, and the Cochrane Library from inception to June 2022. Included studies reported fasting plasma glucose (FPG), glycated hemoglobin (HbA1c), and 2-hour postprandial (2hPP) levels and implemented an exercise program lasting at least 12 weeks in adults with prediabetes. We performed a direct meta-analysis using a random-effects model and a network meta-analysis. Cochran’s Q statistic and the inconsistency I2 test were used to assess the heterogenicity between studies.ResultsTwenty trials were included, with 15 trials (comprising 775 participants with prediabetes) combined in the meta-analysis, and 13 in the network meta-analysis. The meta-analysis results did not show a statistically significant reduction in fasting plasma glucose (FPG) after aerobic training (AT) intervention compared to a control group (mean (95%CI) difference = -5.18 (-13.48; 3.12) mg/dL, Z=1.22, p=0.22). However, a difference of -7.25 (-13.79; -0.71) mg/dL, p=0.03, in FPG after interval training (IT) intervention was detected compared to a control group. After resistance training (RT) intervention, FPG was significantly lower -6.71 (-12.65,-0.77) mg/dL, Z=2.21, p=0.03, and HbA1c by -0.13 (-0.55, 0.29), p=0.54, compared to the control group. The impact of RT compared to no intervention on 2hPP was not statistically significant (p=0.26). The network meta-analysis did not show statistical significance. Most of the studies presented an unclear risk of bias, and a low and very low-quality of evidence. According to the GRADE criteria, the strength of the body of evidence was low.ConclusionResistance training and IT had demonstrated benefits on glycemic indices, especially on FPG, in a population with prediabetes. Further studies with larger sample sizes and a more robust methodology that compare different types of exercise modalities, frequencies, and durations, are needed to establish a beneficial exercise intervention.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=370688, identifier CRD42022370688

GDF15 and ACE2 stratify COVID-19 patients according to severity while ACE2 mutations increase infection susceptibility

Coronavirus disease 19 (COVID-19) is a persistent global pandemic with a very heterogeneous disease presentation ranging from a mild disease to dismal prognosis. Early detection of sensitivity and severity of COVID-19 is essential for the development of new treatments. In the present study, we measured the levels of circulating growth differentiation factor 15 (GDF15) and angiotensin-converting enzyme 2 (ACE2) in plasma of severity-stratified COVID-19 patients and uninfected control patients and characterized the in vitro effects and cohort frequency of ACE2 SNPs. Our results show that while circulating GDF15 and ACE2 stratify COVID-19 patients according to disease severity, ACE2 missense SNPs constitute a risk factor linked to infection susceptibility

Lifestyle factors and visceral adipose tissue: Results from the PREDIMED-PLUS study

Background: Visceral adipose tissue (VAT) is a strong predictor of cardiometabolic health, and lifestyle factors may have a positive influence on VAT depot. This study aimed to assess the cross-sectional associations between baseline levels of physical activity (PA), sedentary behaviours (SB) and adherence to the Mediterranean diet (MedDiet) with VAT depot in older individuals with overweight/obesity and metabolic syndrome. Methods: Baseline data of the PREDIMED-Plus study including a sample of 1,231 Caucasian men and women aged 55-75 years were used. Levels of leisure-time PA (total, light, and moderate-to-vigorous, in METs·min/day) and SB (total and TV-viewing, in h/day) were evaluated using validated questionnaires. Adherence to the MedDiet was evaluated using a 17-item energy-restricted MedDiet (erMedDiet) screener. The chair-stand test was used to estimate the muscle strength. VAT depot was assessed with DXA-CoreScan. Multivariable adjusted linear regression models were used to evaluate the association between lifestyle factors and VAT. For the statistics we had used multiadjusted linear regression models. Results: Total leisure-time PA (100 METs·min/day: β -24.3g, -36.7;-11.9g), moderate-to-vigorous PA (β -27.8g, 95% CI -40.8;-14.8g), chair-stand test (repeat: β -11.5g, 95% CI -20.1;-2.93g) were inversely associated, and total SB (h/day: β 38.2g, 95% CI 14.7;61.7) positively associated with VAT. Light PA, TV-viewing time and adherence to an erMedDiet were not significantly associated with VAT. Conclusions: In older adults with overweigh/obesity and metabolic syndrome, greater PA, muscle strength, and lower total SB were associated with less VAT depot. In this study, adherence to an erMedDiet was not associated with lower VAT

Isotemporal substitution of inactive time with physical activity and time in bed: cross-sectional associations with cardiometabolic health in the PREDIMEDPlus study

Background: This study explored the association between inactive time and measures of adiposity, clinical parameters, obesity, type 2 diabetes and metabolic syndrome components. It further examined the impact of reallocating inactive time to time in bed, light physical activity (LPA) or moderate-to-vigorous physical activity (MVPA) on cardio-metabolic risk factors, including measures of adiposity and body composition, biochemical parameters and blood pressure in older adults. Methods: This is a cross-sectional analysis of baseline data from 2189 Caucasian men and women (age 55-75 years, BMI 27-40 Kg/m2) from the PREDIMED-Plus study (http://www.predimedplus.com/). All participants had ≥3 components of the metabolic syndrome. Inactive time, physical activity and time in bed were objectively determined using triaxial accelerometers GENEActiv during 7 days (ActivInsights Ltd., Kimbolton, United Kingdom). Multiple adjusted linear and logistic regression models were used. Isotemporal substitution regression modelling was performed to assess the relationship of replacing the amount of time spent in one activity for another, on each outcome, including measures of adiposity and body composition, biochemical parameters and blood pressure in older adults. Results: Inactive time was associated with indicators of obesity and the metabolic syndrome. Reallocating 30 min per day of inactive time to 30 min per day of time in bed was associated with lower BMI, waist circumference and glycated hemoglobin (HbA1c) (all p-values < 0.05). Reallocating 30 min per day of inactive time with 30 min per day of LPA or MVPA was associated with lower BMI, waist circumference, total fat, visceral adipose tissue, HbA1c, glucose, triglycerides, and higher body muscle mass and HDL cholesterol (all p-values < 0.05). Conclusions: Inactive time was associated with a poor cardio-metabolic profile. Isotemporal substitution of inactive time with MVPA and LPA or time in bed could have beneficial impact on cardio-metabolic health

Long daytime napping is associated with increased adiposity and type 2 diabetes in an elderly population with metabolic syndrome

Research examining associations between objectively-measured napping time and type 2 diabetes (T2D) is lacking. This study aimed to evaluate daytime napping in relation to T2D and adiposity measures in elderly individuals from the Mediterranean region. A cross-sectional analysis of baseline data from 2190 elderly participants with overweight/obesity and metabolic syndrome, in the PREDIMED-Plus trial, was carried out. Accelerometer-derived napping was measured. Prevalence ratios (PR) and 95% confidence intervals (CI) for T2D were obtained using multivariable-adjusted Cox regression with constant time. Linear regression models were fitted to examine associations of napping with body mass index (BMI) and waist circumference (WC). Participants napping ≥90 min had a higher prevalence of T2D (PR 1.37 (1.06, 1.78)) compared with those napping 5 to <30 min per day. Significant positive associations with BMI and WC were found in those participants napping ≥30 min as compared to those napping 5 to <30 min per day. The findings of this study suggest that longer daytime napping is associated with higher T2D prevalence and greater adiposity measures in an elderly Spanish population at high cardiovascular risk

Objectively Measured Sleep Duration and Health-Related Quality of Life in Older Adults with Metabolic Syndrome: A One-Year Longitudinal Analysis of the PREDIMED-Plus Cohort

[EN] The aim of our cross-sectional and longitudinal study is to assess the relationship between daytime and night-time sleep duration and health-related quality of life (HRQoL) in adults with metabolic syndrome after a 1-year healthy lifestyle intervention. Analysis of the data from 2119 Spanish adults aged 55–75 years from the PREDIMED-Plus study was performed. Sleep duration was assessed using a wrist-worn accelerometer. HRQoL was measured using the SF-36 questionnaire. Linear regression models adjusted for socioeconomic and lifestyle factors and morbidity were developed. In cross-sectional analyses, participants with extreme night-time sleep duration categories showed lower physical component summary scores in Models 1 and 2 [β-coefficient (95% confidence interval) 9 h vs. 7–9 h: −1.1 (−2.0 to −0.3); p = 0.01]. Participants who sleep less than 7 h a night and take a nap are associated with higher mental component summary scores [β-coefficient (95% confidence interval) 6.3 (1.3 to 11.3); p = 0.01]. No differences between night-time sleep categories and 12-month changes in HRQoL were observed. In conclusion, in cross-sectional analyses, extremes in nocturnal sleep duration are related to lower physical component summary scores and napping is associated with higher mental component summary scores in older adults who sleep less than 7 h a night.S

Development and Evaluation of a Digital Health Intervention to Prevent Type 2 Diabetes in Primary Care: The PREDIABETEXT Study Protocol for a Randomised Clinical Trial

Background: Type 2 diabetes mellitus (T2DM) is a highly prevalent disease associated with an increased risk of comorbidities, premature death, and health costs. Prediabetes is a stage of glucose alteration previous to T2DM, that can be reversed. The aim of the study is to develop and evaluate a low-intensity, multifaceted, digital intervention to prevent T2DM. The intervention comprises: (1) the use of mobile health technology to send tailored text messages promoting lifestyle changes to people at risk of T2DM and (2) the provision of online education to primary healthcare physicians and nurses about management of prediabetes. Methods: In stages 1&ndash;4 we will design, develop and pilot-test the intervention. In Stage 5 we will conduct a phase II, six-month, three-arm, cluster randomized, clinical trial with 42 primary care professionals and 420 patients at risk of T2DM. Patients will be allocated to a control group (usual care), intervention A (patient messaging intervention), or intervention B (patient messaging intervention plus online education to their primary healthcare professionals). The primary outcome will be glycated haemoglobin. All the procedures obtained ethical approval in June 2021 (CEI-IB Ref No: IB4495/21PI). Discussion: Digital health interventions can effectively prevent T2DM and reduce important T2DM risk factors such as overweight or hypertension. In Spain, this type of intervention is understudied. Moreover, there is controversy regarding the type of digital health interventions that are more effective. Findings from this study may contribute to address T2DM prevention, through a low-cost and easily implementable intervention

Do Physical Fitness and Executive Function Mediate the Relationship between Physical Activity and Academic Achievement? An Examination Using Structural Equation Modelling

Background: Physical activity health benefits are widely known. However, the association between physical activity, physical fitness, executive function, and academic performance need further investigation. Additionally, one of the literature gaps reveals scarce and mixed findings on what mediators of physical activity may affect academic achievement. Purpose: This investigation aims to provide knowledge about the mediation role of physical fitness and executive function in the association of physical activity with academic achievement in a cohort of Spanish schoolchildren using a structural equation modelling approach. Methods: The data for this cross-sectional study were collected from a convenience sample of children from Spain (Balearic Islands) aged between 9 and 13 years. Physical activity levels were self-reported with the Physical Activity Questionnaire for Children; physical fitness was assessed using the International Fitness Scale; executive function was assessed with the Trail Making Test, and children’s achievements were collected from the school records. Structural equation modelling was used to explore the relationship between physical activity, physical fitness, executive function, and academic achievement. Findings: Statistically significant positive direct associations were observed between physical activity and physical fitness (β = 0.46, 95% CI [0.29, 0.64]), physical fitness and executive function (β = 0.28, 95% CI [0.04, 0.52]), and executive function and academic achievement (β = 0.46, 95% CI [0.28, 0.65]), while adjusting for the confounding effects of sex and body mass index. Furthermore, indirect associations were observed between physical activity and executive function mediated by physical fitness (β = 0.13, bias-corrected 95% CI [0.02, 0.31]) and between physical fitness and academic achievement through executive function (β = 0.13, bias-corrected 95% CI [0.03, 0.32]). Conclusions: This investigation adds to the literature with evidence supporting the idea that regular PA leads to improvements in physical fitness and may support cognitive skills and academic performance in children

DataSheet_1_Effect of physical activity and different exercise modalities on glycemic control in people with prediabetes: a systematic review and meta-analysis of randomized controlled trials.pdf

BackgroundNumerous studies have shown the beneficial effects of exercise on glycemic control in people with prediabetes. However, the most effective exercise modality for improving glycemic control remains unclear. We aimed to assess which exercise training modality is most effective in improving glycemic control in a population with prediabetes.MethodsWe conducted searches in Pubmed/MEDLINE, EMBASE, SPORTDiscus, Web of Science, PEDro, BVS, and the Cochrane Library from inception to June 2022. Included studies reported fasting plasma glucose (FPG), glycated hemoglobin (HbA1c), and 2-hour postprandial (2hPP) levels and implemented an exercise program lasting at least 12 weeks in adults with prediabetes. We performed a direct meta-analysis using a random-effects model and a network meta-analysis. Cochran’s Q statistic and the inconsistency I2 test were used to assess the heterogenicity between studies.ResultsTwenty trials were included, with 15 trials (comprising 775 participants with prediabetes) combined in the meta-analysis, and 13 in the network meta-analysis. The meta-analysis results did not show a statistically significant reduction in fasting plasma glucose (FPG) after aerobic training (AT) intervention compared to a control group (mean (95%CI) difference = -5.18 (-13.48; 3.12) mg/dL, Z=1.22, p=0.22). However, a difference of -7.25 (-13.79; -0.71) mg/dL, p=0.03, in FPG after interval training (IT) intervention was detected compared to a control group. After resistance training (RT) intervention, FPG was significantly lower -6.71 (-12.65,-0.77) mg/dL, Z=2.21, p=0.03, and HbA1c by -0.13 (-0.55, 0.29), p=0.54, compared to the control group. The impact of RT compared to no intervention on 2hPP was not statistically significant (p=0.26). The network meta-analysis did not show statistical significance. Most of the studies presented an unclear risk of bias, and a low and very low-quality of evidence. According to the GRADE criteria, the strength of the body of evidence was low.ConclusionResistance training and IT had demonstrated benefits on glycemic indices, especially on FPG, in a population with prediabetes. Further studies with larger sample sizes and a more robust methodology that compare different types of exercise modalities, frequencies, and durations, are needed to establish a beneficial exercise intervention.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=370688, identifier CRD42022370688.</p

Efficacy of Different Modalities and Frequencies of Physical Exercise on Glucose Control in People with Prediabetes (GLYCEX Randomised Trial)

To assess the efficacy of different modalities and frequencies of physical exercise on glycaemic control in adults with prediabetes. A two-phase, parallel, randomised, controlled clinical trial will be carried out, in 210 participants. In phase 1, 120 participants will be randomized into four arms: (1) aerobic exercise, (2) aerobic exercise combined with resistance, (3) high-intensity intervallic exercise and (4) control group. In phase 2, 90 new participants will be randomized into three arms, using the exercise modality that showed the best glycaemic control in phase 1 in the following manner: (1) frequency of 5 days/week, (2) frequency of 3 days/week and (3) frequency of 2 days/week. The control group (n = 30) will be included in phase 1 to evaluate the effect of any type of intervention versus no intervention. Data collection will be performed at baseline and after 15 weeks of follow up. Sociodemographic data, medication, comorbidity, blood biochemical parameters, blood pressure, anthropometric measurements, body composition, physical activity, sedentary lifestyle, diet, smoking, alcohol consumption, quality of life and sleep questionnaires will be collected. Physical activity, sedentary behaviour and sleep will be further determined with an accelerometer, and continuous glycaemia will be determined with a glycaemic monitor, both during seven days, at two time points. The main dependent variable will be the reduction in the mean amplitude of glycaemic excursions. The impact of these interventions on health will also be evaluated through gene expression analysis in peripheral blood cells. The results of this study will contribute to a better understanding of the mechanisms behind the glucose response to physical exercise in a population with prediabetes as well as improve physical exercise prescriptions for diabetes prevention. Increasing glycaemic control in people with prediabetes through physical exercise offers an opportunity to prevent diabetes and reduce associated comorbidities and health costs