We evaluated the concordance between visceral fat area (VFA) estimated by bioelectrical impedance analysis (BIA) or computed tomography (CT) in Korean subjects with a wide range in age and body mass index (BMI). In 1006 individuals (mean age 55.2 ± 11.8 (19–87) years, mean BMI 26.0 ± 3.5 (17–46) kg/m², 48.9% men), VFA quantified by CT was compared with VFA using multifrequency BIA machines within 15 days. Concordance rates were compared by age or BMI using correlation analysis, Bland-Altman plots, and intraclass correlation coefficient (ICC). Using BIA data, we established a regression formula to reflect CT-VFA. The mean VFAs by CT and BIA were 131.9 ± 57.3 cm² and 110.5 ± 33.9 cm², respectively (r = 0.605, p < 0.001). The mean difference was 21.4 ± 45.6 cm², tending to increase with BMI. In women with BMI <25 kg/m² or age <50 years, the VFAs by BIA were similar to those by CT (ICC = 0.496 in BMI <25 kg/m² and ICC = 0.638 in age <50 years). However, the difference was greater in men with BMI ≥25 kg/m² or age ≥50 years. Applying our formula, the difference between estimations decreased to 0.2 ± 38.2cm². VFA estimated by BIA correlated well with that by CT, but a more accurate formula is needed to match CT data, particularly in older men or subjects with a high BMI.

Background: There are inconsistent results for the effectiveness of using smartphone applications (apps) or websites on weight loss. We investigated the efficacy of a smartphone intervention using a designated app that utilizes a lifestyle intervention-focused approach, including a human coaching element, toward weight loss in overweight or obese Korean adults. Methods: One hundred four adults aged 20–60 years with a body mass index ≥23 kg/m², who signed up for a smartphone program for weight loss (using the Noom app), were recruited. Participants received an in-person orientation about the study and app use, and a baseline blood sample was obtained. The in-app intervention with daily behavior and nutrition education content and coaching lasted 15 weeks. The primary endpoint of the study was a change in weight. The secondary endpoints were changes in metabolic risk factors such as blood pressure, waist circumference, and glucose and lipid profiles. Body composition changes were also assessed, and body weight at 52 weeks was measured to ascertain long-term effects. Results: Participants showed a clinically significant weight loss effect of −7.5% at the end of the 15-week program (P < 0.001), and at a 52-week follow-up, a weight loss effect of −5.2% was maintained. At 15 weeks, percent body fat and visceral fat decreased by −6.0 ± 5.4% and −3.4 ± 2.7 kg, respectively (both P < 0.001). Fasting glucose level also decreased significantly by −5.7 ± 14.6 mg/dL at 15 weeks. Lipid parameters showed significant improvements, except for high-density lipoprotein cholesterol. The frequency of logging meals and exercise was associated with body fat loss. Conclusions: This advanced smartphone app was a useful tool to maintain weight loss in overweight or obese people.

Background: Active surveillance (AS) has been considered one of the management options in patients with low-risk papillary thyroid microcarcinoma (PTMC). It is important to evaluate clinical lymph node (LN) metastasis to select appropriate candidates with low-risk disease. We investigated the predictive accuracy of computed tomography (CT) for cervical LN metastasis in patients who have PTMC with tumor characteristics appropriate for AS. Methods: This was a retrospective study. Medical records from December 2014 to the end of 2016 were reviewed. Patients who underwent thyroidectomy and who had pathologically confirmed PTMC were included. A total of 464 patients who had tumors with ultrasound (US) characteristics appropriate for AS and who underwent preoperative CT were included in the analysis. Results: CT showed higher diagnostic values especially in positive predictive value (PPV) than US. In patient-based analyses, CT showed low sensitivity and negative predictive value (NPV) (16.0% and 58.5%, respectively), but high specificity and PPV (99.6% and 97.1%, respectively) for detecting cervical LN metastasis. Similar trends were observed for the results of the central neck-level by CT (sensitivity, 14.9%; specificity, 97.4%; PPV, 82.9%; and NPV, 57.4%) in level-by-level analyses. When restricted to lateral neck levels, CT showed high diagnostic accuracy of 95.4% for detecting LN metastasis. In all analyses, CT showed better diagnostic values for cervical LN metastasis than US. Combining US and CT did not improve the diagnostic accuracy compared with CT. Conclusions: In patients with PTMC whose tumor has characteristics suitable for AS, CT had additional benefit after cervical LN assessment by US. Further studies are needed to evaluate routine initial CT scanning for patients who are candidates for AS.

Although body mass index (BMI) is a potential risk factor for bronchiectasis in young adults, the association between BMI and incident bronchiectasis has not been well elucidated. This study included 6,329,838 individuals aged 20–40 years from the Korean National Health Insurance Service database 2009–2012 who were followed up until the date of the diagnosis of bronchiectasis, death, or 31 December 2018. We evaluated the incidence and risk of bronchiectasis according to the BMI category. The incidence rate of bronchiectasis increased as BMI decreased in a dose-dependent manner (p for trend <0.01). In multivariable Cox regression analysis, being underweight was an independent risk factor for the development of bronchiectasis, with a hazard ratio of 1.24 (95% confidence interval, 1.19–1.30) compared to being normal weight. In subgroup analysis, the effect of being underweight on the development of bronchiectasis was more evident in males and older individuals (30–40 years) than females and younger individuals (20–29 years), respectively (p for interaction <0.01 for both). These results remained significant in subgroup analysis in which subjects with comorbidities related to being underweight were excluded. Being underweight may be a novel risk factor for the development of bronchiectasis in young adults.

Objectives: This study investigated the 10-year trends of weight and prevalence of underweight, overweight and obesity according to disability grade and types compared with those without disabilities. Methods: This serial cross-sectional analysis was conducted using national disability registration data with national general health checkup data from 2008 to 2017. Age-standardized prevalence of underweight and obesity were analyzed for each year, according to the presence, type, and severity of disabilities. Odds of underweight, overweight, obesity, and severe obesity were examined by multinomial logistic regression after adjusting for socio-demographic and clinical variables using data in 2017. Results: Over 10 million subjects in each year were included in the analysis. In 2017, 14,246,785 people with age between 19 and 110 years were included and 53.1% was men. For 10 years, age-standardized prevalence of obesity and severe obesity showed significant increases regardless of sex and presence of disability. However, age-standardized underweight prevalence in people without disability tended to decrease whereas it was an increase in 2012 and the prevalence has remained steady since in people with disability. People with disabilities had higher odds of underweight compared to those without disability (OR 1.41, 95% CI 1.38–1.44 in male and OR 1.31, 95% CI 1.28–1.34 in female), especially in those with severe disabilities (OR 2.00, 95% CI 1.94–2.06 in male and OR 1.83, 95% CI 1.77–1.89 in female). Women with disabilities are more likely to be obese than those without disabilities regardless of disability severity (OR 1.40, 95% CI 1.38–1.41). Participants with mental disorder showed the highest prevalence of obesity, followed by epilepsy and developmental disability. Conclusions: Having a disability was associated with higher odds/probability of both obesity and underweight. The intersection of female, severe disability, and mental/developmental disabilities was associated with probability of severe obesity. Simultaneous efforts are needed to develop health policy to reduce both the prevalence of obesity and underweight.