Purpose: A comprehensive health index is needed to measure an individual’s overall health and aging status and predict the risk of death and age-related disease incidence, and evaluate the effect of a health management program. The purpose of this study is to demonstrate the validity of estimated biological age (BA) in relation to all-cause mortality and age-related disease incidence based on National Sample Cohort database. Patients and methods: This study was based on National Sample Cohort database of the National Health Insurance Service – Eligibility database and the National Health Insurance Service – Medical and Health Examination database of the year 2002 through 2013. BA model was developed based on the National Health Insurance Service – National Sample Cohort (NHIS – NSC) database and Cox proportional hazard analysis was done for mortality and major age-related disease incidence. Results: For every 1 year increase of the calculated BA and chronological age difference, the hazard ratio for mortality significantly increased by 1.6% (1.5% in men and 2.0% in women) and also for hypertension, diabetes mellitus, heart disease, stroke, and cancer incidence by 2.5%, 4.2%, 1.3%, 1.6%, and 0.4%, respectively (p<0.001). Conclusion: Estimated BA by the developed BA model based on NHIS – NSC database is expected to be used not only as an index for assessing health and aging status and predicting mortality and major age-related disease incidence, but can also be applied to various health care fields.

The purpose of this study was to build a 10-year stroke prediction model and categorize a probability of stroke using the Korean national health examination data. Then it intended to develop the algorithm to provide a personalized warning on the basis of each user's level of stroke risk and a lifestyle correction message about the stroke risk factors. Subject to national health examinees in 2002-2003, the stroke prediction model identified when stroke was first diagnosed by following-up the cohort until 2013 and estimated a 10-year probability of stroke. It sorted the user's individual probability of stroke into five categories - normal, slightly high, high, risky, very risky, according to the five ranges of average probability of stroke in comparison to total population - less than 50 percentile, 50-70, 70-90, 90-99.9, more than 99.9 percentile, and constructed the personalized warning and lifestyle correction messages by each category. Risk factors in stroke risk model include the age, BMI, cholesterol, hypertension, diabetes, smoking status and intensity, physical activity, alcohol drinking, past history (hypertension, coronary heart disease) and family history (stroke, coronary heart disease). The AUC values of stroke risk prediction model from the external validation data set were 0.83 in men and 0.82 in women, which showed a high predictive power. The probability of stroke within 10 years for men in normal group (less than 50 percentile) was less than 3.92% and those in very risky group (top 0.01 percentile) was 66.2% and over. The women's probability of stroke within 10 years was less than 3.77% in normal group (less than 50 percentile) and 55.24% and over in very risky group. This study developed the stroke risk prediction model and the personalized warning and the lifestyle correction message based on the national health examination data and uploaded them to the personal health record service called My Health Bank in the health information website - Health iN. By doing so, it urged medical users to strengthen the motivation of health management and induced changes in their health behaviors.

We investigated the association between socioeconomic status and adherence to health check-ups in a Korean population aged 40 years or older. This cross-sectional study included 12,311 participants who participated in the 2010-2012 Korean National Health and Nutrition Examination Survey. Self-reported questionnaires were used to assess each participant's socioeconomic status (household income, occupation, and education) and adherence to health check-ups. Men with a higher income (highest vs. lowest: odds ratio [OR], 1.799; 95% confidence interval [CI], 1.296-2.497) and men with a higher education level (≥12 vs. <6 years: OR, 1.488; 95% CI, 1.078-2.054) and office workers compared with manual workers (men: OR, 1.431; 95% CI, 1.077-1.902; women: OR, 1.783; 95% CI, 1.256-2.532) appeared to undergo more health check-ups. In particular, men and women with a higher income and education appeared more likely to undergo opportunistic health check-ups (men: highest vs. lowest income: OR, 2.380; 95% CI, 1.218-4.653; ≥12 vs. <6 years education: OR, 2.121; 95% CI, 1.142-3.936; women: highest vs. lowest income: OR, 4.042; 95% CI, 2.239-7.297; ≥12 vs. <6 years education: OR, 2.475; 95% CI, 1.283-4.775). A higher socioeconomic status was associated with a higher rate of participation in health check-ups. More efforts are needed to identify the factors associated with disparity in adherence to health check-ups.

Objective: Sarcopenia is an age-related process, leading to cardio-metabolic diseases and disabilities. High-risk drinking is also closely related to diabetes, hypertension, and dyslipidemia, which are modifiable risk factors for sarcopenia. In the present study, we aimed to investigate the association between alcohol-drinking patterns and sarcopenia in Korean postmenopausal women. Methods: Data from 2,373 postmenopausal women were analyzed from the 2008 to 2011 Korean National Health and Nutrition Examination Survey. We defined sarcopenia as two standard deviations below the sex-specific means of the appendicular skeletal muscle/weight (percentage) values of a young reference group. Participants were categorized into three groups according to alcohol-drinking patterns, as assessed by the Alcohol Use Disorders Identification Test questionnaire. The odds ratios and 95% confidence intervals for sarcopenia were calculated using multiple logistic regression analyses. Results: In total, 8.2% of Korean postmenopausal women met criteria for sarcopenia. The prevalence of sarcopenia increased from low-risk to high-risk alcohol-drinking groups as follows: 7.6, 11.0, and 22.7%, respectively. Compared with the low-risk group, the odds ratio (95% confidence interval) for the high-risk group was 4.29 (1.87-9.82) after adjusting for age, body mass index, systolic blood pressure, total cholesterol, fasting blood glucose, household income, education level, daily calorie intake, current smoking and regular exercise, and household food security status Conclusions: High-risk alcohol drinking was associated with a higher risk of sarcopenia in postmenopausal Korean women.