Testosterone is a representative sex hormone for men, and low testosterone causes erectile dysfunction and cardiovascular disease. The purpose of this study was to investigate the association between low testosterone (LTT) and health behaviors, such as alcohol, smoking, and exercise habits. We included 2980 men aged 65 to 80. Total serum testosterone and body composition were measured. A testosterone level less than 300 ng/dL was defined as low testosterone. A questionnaire on smoking, alcohol, and exercise was included. The odds ratio (OR) of LTT was calculated through logistic regression. Model 1 only used age as the adjustment variable, whereas Model 2 adjusted for age, waist circumference, and smoking. The prevalence of LTT was 626 (21.0%). The prevalence of LTT was significant in fat mass (Model 1: OR, 2.133) and muscle mass (Model 1: medium OR, 2.130 and low OR, 3.022; Model 2: medium OR, 1.638 and low OR, 1.740). The prevalence of LTT was also different based on smoking (Model 1: OR, 1.590; Model 2: OR, 1.629) and strength exercise (Model 1: OR, 0.849; Model 2: OR, 0.923). In conclusion, high frequency strength exercise and smoking cessation lower the prevalence of low testosterone, and obesity and low muscle mass increase the prevalence of low testosterone.

Background and PurposeDiabetes mellitus is a major cause of death and can lead to complications of cardiovascular disease. High physical activity (HPA) and normal weight play a role in reducing the risk of diabetes. This study analyzed the relative risk (RR) of diabetes according to obesity and physical activity using national health census data. MethodsNationwide health screening was performed for all adults every 2 years. Data from 5,590,120 men and 4,102,523 women, who were followed up for 10 years, were analyzed. Physical activity questionnaires about weekly exercise frequency were used to define low physical activity (LPA, 0-2 days), moderate physical activity (MPA, 3-5 days), and high physical activity (HPA, 6-7 days). Body mass index (BMI) ≤24.9 kg/m 2 was defined as normal, BMI 25.0-29.9 kg/m 2 was overweight, and BMI ≥30.0 kg/m 2 was obese. The RR was calculated using Cox analysis. ResultsDiabetes incidence rates were 14.8% in overweight men, 20.0% in men with obesity, 17.9% in overweight women, and 22.7% in women with obesity. The RR increased by 2.5 times in men with obesity and 3.4 times in women with obesity as compared with that of individuals with a normal BMI. Among overweight and obese individuals, those with HPA had decreased risks of developing Longitudinal study on the relative risk of type 2 DM

Badminton requires both aerobic fitness and anaerobic ability for high performance. High intensity interval training (HIIT) is a traditional training method for improving fitness. In this study, we investigated whether short-term Wingate-based HIIT is effective for improving anaerobic activity in youth badminton players. Participants included 32 total badminton players in middle school and high school. They were divided into two groups (HIIT and moderate continuous training (MCT)). Training occurred for 4 weeks in total, three times a week, for 30 min each session. A body composition test, isokinetic knee muscle function test (60°/s, 240°/s), Wingate anaerobic power test (30 s × 5 sets), and analysis of heart rate changes were undertaken before and after training. After 4 weeks, body fat decreased in the HIIT group (p = 0.019); they also showed superior anaerobic ability compared to the MCT group. Differences were statistically significant in 3–4 sets (three sets, p = 0.019; four sets, p = 0.021). Regarding fatigue, the HIIT group showed superior fatigue improvement after training and better fatigue recovery ability in 3~5 sets (three sets, p = 0.032; four sets, p = 0.017; five sets, p = 0.003) than the MCT group. Neither group exhibited changes in heart rate during the anaerobic power test after training. Both groups improved in terms of isokinetic knee muscle function at 60°/s with no differences. However, at 240°/s, the HIIT group showed a statistically significant improvement (p = 0.035). Therefore, HIIT for 4 weeks improved the athletes’ performance and physical strength.

The prevalence of metabolic syndrome in adolescents is increasing. Recently, the relevance of grip strength as a factor of metabolic syndrome in this population has raised questions. This study investigated the prevalence of metabolic syndrome according to grip strength in children and adolescents using large-scale data from the Korean National Health and Nutrition Survey (KNHNS). From 2014 to 2018, 1527 boys and 1292 girls participated in the KNHNS. The participants were classified into three groups according to age: 10–12 years (early teenager, ET), 13–15 years (middle teenager, MT), and 16–18 years (late teenager, LT). The participants were classified as having metabolic syndrome if they fulfilled three of the adolescent metabolic syndrome criteria. The grip strength was divided into groups with high and low grip strength, respectively, and the cutoff value for the prevalence was calculated using receiver operating characteristic curve analysis. There were significant differences in waist circumference, high-density lipoprotein cholesterol, and triglyceride levels based on grip strength in the ET, MT, and LT groups. Therefore, the prevalence of metabolic syndrome was lower when grip strength was higher. The cut-off values of the relative grip strength (kg/body weight) to predict metabolic syndrome among boys were 0.349, 0.466, and 0.485 for the ET, MT, and LT groups, respectively. The corresponding cut-off values for girls were 0.373, 0.383, and 0.382, respectively. In conclusion, there is a non-linear relationship between grip strength and metabolic syndrome in adolescents.

Purpose: One cause of metabolic syndrome (MetS) is inactivity. This study analyzed the prevalence of MetS due to causes of activity limitation (AL) in adults over 40 years old. Paticipants and Methods: Participants included 2885 people aged 40-79 (1198 men and 1687 women) who completed the Korean National Health and Nutrition Survey (KNHANES) conducted between 2013 and 2017. They were divided into two groups based on age: the middle age group (MA) included 1148 total participants, 515 men and 633 women from 40-59 years old; the older age group (OA) included 1737 total participants, 683 men and 1054 women from 60-79 years old. MetS was diagnosed according to the Third Report of the National Cholesterol Education Program and the Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (NCEP-ATP III). Logistic regression was conducted to calculate the odds ratio for MetS prevalence. Results: The prevalence of MetS in people with AL increased 1.432-fold in the MA men group, 1.511-fold in the OA men group, 1.546-fold in the MA women group, and 1.565-fold in the OA women group. There were several causes of AL; people with physical activity for diabetes mellitus and hypertension increased MetS prevalence in both sexes and all age groups: MA men group (OR=3.216, 95% CI=1.852-7.354, P=0.034), MA women group (OR=2.159, 95% CI=1.854-5.346, P=0.032), OA men group (OR=3.200, 95% CI=1.235-7.841, P=0.009), and OA women group (OR=3.444, 95% CI=1.310-6.627, P=0.008). Also, mental problems in the MA men group (OR=2.284, 95% CI=1.591-4.986, P=0.012) and OA men group (OR=1.149, 95% CI=1.017-2.941, P=0.012), and musculoskeletal problems in the MA women group (OR=1.784, 95% CI=1.102-2.902, P=0.021) and OA women group (OR=1.459, 95% CI=1.054-1.993, P=0.004) increased the prevalence. Conclusion: The prevalence of MetS due to activity limitation was increased in MA and OA groups. Activity limitation increased the MetS prevalence from 1.4-to 1.5-times, Therefore, to prevent metabolic syndrome, physical activity should be increased, and guidelines should be presented according to the activity limitation causes, age, and sex.