IntroductionTo examine how the risk of cardiovascular disease changes according to degree of change in body mass index (BMI) and low-density lipoprotein (LDL)-cholesterol in patients with diabetes using the health medical examination cohort database of the National Health Insurance Service in Korea. In comparison, the pattern in a non-diabetic control group was also examined.Research design and methodsThe study samples were 13 800 patients with type 2 diabetes and 185 898 non-diabetic controls, and their baseline characteristics and repeatedly measured BMI and LDL-cholesterol until occurrence of cardiovascular disease were collected in longitudinal data. We used the variability model that is joint of mixed effects and regression model, then estimated parameters about variability by Bayesian methods.ResultsThe risk of cardiovascular disease was increased significantly with high average real variability (ARV) of BMI in the patients with diabetes, but the risk of cardiovascular disease was not increased according to degree of ARV in non-diabetic controls. The Bayesian variability model was used to analyze the effects of BMI and LDL-cholesterol change pattern on development of cardiovascular disease in diabetics, showing that variability did not have a statistically significant effect on cardiovascular disease. This shows the danger of the former simple method when interpreting only the mean of the absolute value of the variation.ConclusionsThe approach of simple SD in previous studies for estimation of individual variability does not consider the order of observation. However, the Bayesian method used in this study allows for flexible modeling by superimposing volatility assessments on multistage models.

The National Health Insurance Service–Health Examinee Cohort during 2002 to 2013 was used to investigate the associations between periodontal disease (PD) and the following non-communicable diseases (NCDs): hypertension, diabetes mellitus, osteoporosis, cerebral infarction, angina pectoris, myocardial infarction, and obesity.Univariate and multivariate logistic regression analyses adjusting for potential confounders during the follow-up period—including age, sex, household income, insurance status, residence area, health status, and comorbidities—were used to estimated odds ratios (ORs) with 95% confidence intervals (CIs) in order to assess the associations between PD and NCDs.We enrolled 200,026 patients with PD and 154,824 subjects with a healthy oral status. Statistically, significant associations were found between PD and the investigated NCDs except for cerebral and myocardial infarction after adjusting for sociodemographic and comorbidity factors (P < .05). In particular, obesity (OR = 1.30, 95% CI = 1.04–1.63, P = .022), osteoporosis (OR = 1.22, 95% CI = 1.18–1.27, P < .001), and angina pectoris (OR = 1.22, 95% CI = 1.17–1.27, P < .001) were significantly and positively associated with PD.This longitudinal cohort study has provided evidence that patients with PD are at increased risk of NCDs. Further studies are required to confirm the reliability of this association and elucidate the role of the inflammatory pathway in periodontitis pathogenesis as a triggering and mediating mechanism.

Background: The coronavirus disease 2019 has rapidly turned into a public health emergency worldwide; however, the risk factors for infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have not been well-described. We aimed to identify the clinical risk factors for SARS-CoV-2 infections in Korea, where social distancing and face masks have been strongly recommended.Methods: The data of individuals who underwent the reverse transcription polymerase chain reaction test for SARS-CoV-2 between January 3 and May 31, 2020 were retrieved from the Health Insurance Review and Assessment Service dataset. We used multivariable logistic regression models to identify the risk factors for SARS-CoV-2 infections in the population. Results:We retrieved the results of 219,729 SARS-CoV-2 tests, of which 7,333 were positive results. In the multivariable analysis, female sex was associated with a higher risk of testing positive for SARS-CoV-2 [odds ratio (OR) =1.30, 95% confidence interval (CI): 1.24-1.37, P<0.0001]. Additionally, populations living in areas that had large outbreaks of COVID-19 were at an increased risk of testing positive for SARS-CoV-2 (OR =6.87, 95% CI: 6.55-7.21, P<0.0001). The odds of a positive test were greater for the Medical Aid beneficiaries (OR =1.99, 95% CI: 1.82-2.18, P<0.0001) than for the National Health Insurance beneficiaries.Individuals with diabetes mellitus (DM) were more likely to test positive (OR =1.15, 95% CI: 1.07-1.24, P=0.0002).Conclusions: Women, individuals living in areas with large outbreaks of COVID-19, Medical Aid beneficiaries, and individuals with DM might have greater risks of contracting SARS-CoV-2 infections despite practicing social distancing and using face masks.

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