METHODOLOGY: The Cochrane Central Register of Controlled Trials (CENTRAL) and PubMed (1985-January 2022) and trial registries for relevant randomised clinical trials were used. Relevant and published randomised clinical trials were reviewed and evaluated. The primary outcomes were anthropometry measurements, which were weight, waist circumference, body mass index (BMI), and body fat percentages. The secondary outcomes were changes in quality of life, psychological impact, lipid profile measurement, presence of adverse events, and changes in blood pressure and blood glucose. We assessed the data for risk of bias, heterogeneity, sensitivity, reporting bias, and quality of evidence.
RESULTS: 15 studies are included, involving 1161 participants. The analysis performed is based on three comparisons. For the first comparison between yoga and control, yoga reduces the waist circumference (MD -0.84, 95% CI [-5.12 to 3.44]), while there is no difference in body weight, BMI, or body fat percentages. In the second comparison between yoga and calorie restriction, yoga reduces body weight (MD -3.47, 95% CI [-6.20 to -0.74]), while there is no difference in waist circumference, BMI, or body fat percentage. In the third comparison between yoga and exercise, yoga reduces the body weight (MD -7.58, 95% CI [-11.51 to -3.65]), while there is no difference in waist circumference or BMI. For the secondary outcomes, yoga intervention reduces total cholesterol (MD -17.12, 95% CI [-32.24 to -2.00]) and triglycerides (MD -21.75, 95% CI [-38.77 to -4.73]) compared to the control group, but there is no difference compared to the calorie restriction and exercise group. There is no difference in the rest of the outcomes, which are LDL, HDL, quality of life, psychological impact, adverse events, blood pressure, and blood glucose. However, findings are not robust due to a high risk of bias and low-quality evidence.
CONCLUSION: From our review, there were methodological drawbacks and very low to moderate quality of evidence across all comparisons, and hence, it is inconclusive to say that yoga can significantly improve anthropometric parameters. More well-designed trials are needed to confirm and support the beneficial effects of yoga.
METHODS: Fifty overweight/obese individuals aged 22-29 years were assigned to either no-exercise control (n=25) or HIIT (n=25) group. The HIIT group underwent a 12-week intervention, three days/week, with intensity of 65-80% of age-based maximum heart rate. Anthropometric measurements, homeostatic model of insulin resistance (HOMA-IR) and gene expression analysis were conducted at baseline and post intervention.
RESULTS: Significant time-by-group interactions (p<0.001) were found for body weight, BMI, waist circumference and body fat percentage. The HIIT group had lower body weight (2.3%, p<0.001), BMI (2.7%, p<0.001), waist circumference (2.4%, p<0.001) and body fat percentage (4.3%, p<0.001) post intervention. Compared to baseline, expressions of PGC-1∝ and AdipoR1 were increased by approximately three-fold (p=0.019) and two-fold (p=0.003) respectively, along with improved insulin sensitivity (33%, p=0.019) in the HIIT group.
CONCLUSION: Findings suggest that HIIT possibly improved insulin sensitivity through modulation of PGC-1∝ and AdipoR1. This study also showed that improved metabolic responses can occur despite modest reduction in body weight in overweight/obese individuals undergoing HIIT intervention.
METHODS: In a sample of 9448 participants followed for a mean of 15.3 years (186,158.5 person-years) from the Monitoring of Trends and Determinants in Cardiovascular Disease Augsburg/Cooperative Health Research in the Region of Augsburg population-based cohort conducted in Germany, we investigated the association of social connectivity, measured by the Social Network Index, and body mass index (BMI) with the risk of clinically validated T2D incidence using stratified Cox proportional hazards regression models adjusted for sociodemographic, life-style, cardiometabolic, and psychosocial risk factors.
RESULTS: During a mean follow-up of 14.1 years (186,158.5 person-years), 975 (10.3%) participants developed T2D. Participants with low social connectivity developed T2D at a higher rate than socially connected participants (10.0 versus 8.0 cases/10,000 person-years); however, BMI played a significant role in the association of social connectivity with T2D ( p < .001). In comparison to their socially connected counterparts, low social connectivity was associated with a higher rate of T2D incidence in normal-weight (6.0 versus 2.0 cases/10,000 person-years), but not overweight (13.0 versus 13.0 cases/10,000 person-years) or obese participants (32.0 versus 30.0 cases/10,000 person-years). Correspondingly, Cox regression analysis showed that 5-unit increments in BMI increased the risk of T2D in socially connected participants (hazard ratio = 3.03, 95% confidence interval = 2.48-3.79, p < .001) at a substantially higher rate than in low socially connected participants (hazard ratio = 1.77, 95% confidence interval = 1.45-2.16, p < .001).
CONCLUSION: The detrimental link between low social connectivity and increased risk of T2D is substantially stronger in participants with a lower BMI.
Subjects and methods: A cross-sectional study was conducted at the Faculty of Medicine in Rabigh, King Abdul-Aziz University, Saudi Arabia. The study included 197 medical students from Rabigh and Jeddah branches of the university. The study employed a Gastroesophageal Reflux Disease Questionnaire which is derived from a self-administered validated GERD questionnaire (GerdQ).
Results: The prevalence of GERD symptoms was 25.9%. The most frequent symptoms were regurgitation and burning sensation. High BMI, family history, energy drinks and fried food were found to be statistically significant risk factors (p<0.05) by univariate analysis. However, the logistic regression for the prediction of GERD symptoms among medical students showed that only family history had a significant correlation (p<0.05).
Conclusion: GERD symptoms were common in medical students of King Abdulaziz University, Saudi Arabia. Family history was found to be a significant predictor of GERD symptoms. Effective educational strategies for groups with significant risk factors of GERD need to be implemented.
SETTING: Fifteen participating cardiology centres contributed to the Malaysian National Cardiovascular Disease Database-Percutaneous Coronary Intervention (NCVD-PCI) registry.
PARTICIPANTS: 28 742 patients from the NCVD-PCI registry who had their first PCI between January 2007 and December 2014 were included. Those without their BMI recorded or BMI <11 kg/m2 or >70 kg/m2 were excluded.
MAIN OUTCOME MEASURES: In-hospital death, major adverse cardiovascular events (MACEs), vascular complications between different BMI groups were examined. Multivariable-adjusted HRs for 1-year mortality after PCI among the BMI groups were also calculated.
RESULTS: The patients were divided into four groups; underweight (BMI <18.5 kg/m2), normal BMI (BMI 18.5 to <23 kg/m2), overweight (BMI 23 to <27.5 kg/m2) and obese (BMI ≥27.5 kg/m2). Comparison of their baseline characteristics showed that the obese group was younger, had lower prevalence of smoking but higher prevalence of diabetes, hypertension and dyslipidemia. There was no difference found in terms of in-hospital death, MACE and vascular complications after PCI. Multivariable Cox proportional hazard regression analysis showed that compared with normal BMI group the underweight group had a non-significant difference (HR 1.02, p=0.952), while the overweight group had significantly lower risk of 1-year mortality (HR 0.71, p=0.005). The obese group also showed lower HR but this was non-significant (HR 0.78, p=0.056).
CONCLUSIONS: Using Asian-specific BMI cut-off points, the overweight group in our study population was independently associated with lower risk of 1-year mortality after PCI compared with the normal BMI group.
DESIGN AND SETTINGS: This was a cross-sectional study to examine the association between OSA parameters and IR using homeostasis model assessment (HOMA) on patients who underwent polysomnogram (PSG) in a tertiary center between March 2011 and March 2012 (1 year).
PATIENTS AND METHODS: A total of 62 patients underwent PSG within the study period, of which 16 patients were excluded due to abnormal fasting blood sugar. Information on patients' medical illnesses, medications, and Epworth sleepiness scale (ESS) was obtained. Patients' body mass index (BMI), neck circumference, and waist circumference (WC) were measured. Blood samples were collected after 8 hours of fasting to measure HOMA-IR value. Overnight PSG was performed for all patients. Data was recorded and analyzed using SPSS, version 12.0 (SPSS Inc, Chicago, USA).
RESULTS: The prevalence of IR in OSA patients was 64.3%. There was significant correlation between OSA parameters (apnea-hypopnea index, ESS, BMI, and WC) and HOMA-IR with correlation coefficient of 0.529, 0.224, 0.261, and 0.354, respectively.
CONCLUSION: A linear correlation exists between OSA parameters and IR concluding a definite causal link between OSA and IR. IR screening is recommended in severe OSA patients.