BackgroundRecent studies suggest that neighborhood environments influence levels of health and disease in individuals. Evidence suggests that green environments have positive effects on physical and psychological health. In this study, we examined the association between public park per person (PPP) and physical activity in 7 large Korean cities with a population of over 1 million.MethodsWe obtained data from the third Korea National Health and Nutritional Survey and data on the area of PPP from the Korean national statistics office.ResultsPhysical activity and adjusted mean of physical activity increased significantly with PPP. When stratified by family income, physical activity increased significantly in all groups in a PPP-dependent manner. Physical activity significantly increased as PPP increased (coefficient, 16.025; 95% confidence interval, 12.392 to 19.658) before and after adjustment for age, sex, and family income. Physical activity increased in all income groups including the low income group.ConclusionThese results show that green park spaces independently promote physical activity and influence healthy lifestyles. Therefore, the importance of PPP for physical activity and health should be emphasized in urban planning.

Background and Aims:The effect of sarcopenic visceral obesity on risk of nonalcoholic fatty liver disease (NAFLD) is uncertain. We investigated whether: a) the skeletal muscle mass to visceral fat area ratio (SV ratio), as a measure of sarcopenic visceral obesity, is a risk factor for NAFLD; and b) the SV ratio adds to conventional adiposity measures to improve prediction of incident NAFLD.Methods: Adults without NAFLD (n=151,017) were followed up for a median of 3.7 years.

Purpose: While increased breast density is a risk factor for breast cancer, the effect of fatty liver disease on breast density is unknown. We investigated whether fatty liver is a risk factor for changes in breast density over ~4 years of follow-up in pre-and postmenopausal women.Methods: This study included 74,781 middle-aged Korean women with mammographically determined dense breasts at baseline. Changes in dense breasts were identified by more screening mammograms during follow-up.Hepatic steatosis (HS) was measured using ultrasonography. Flexible parametric proportional hazards models were used to determine the adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs), and a Weibull accelerated failure time model (AFT) was used to determine the time ratios (TRs) and 95% CIs.Results: During a median follow-up of 4.1 years, 4,022 women experienced resolution of the dense breasts. The association between HS and dense breast resolution differed by the menopause status (P for interaction<0.001).After adjusting for body mass index and other covariates, the aHRs (95% CI) for dense breast resolution comparing HS to non-HS were 0.81 (0.70-0.93) in postmenopausal women, while the association was converse in premenopausal women with the corresponding HRs of 1.30 (1.18-1.43). As an alternative approach, the multivariable-adjusted TR (95% CI) for dense breast survival comparing HS to non-HS were 0.81 (0.75-0.87) and 1.19 (1.06-1.33) in premenopausal and postmenopausal women, respectively. Conclusion:The association between HS and changes in dense breasts differed with the menopause status. HS increased persistent dense breast survival in postmenopausal women but decreased it in premenopausal women. menopause status.

Objective The effect of changes in glycemic status on subclinical atherosclerosis is uncertain. We assessed the association of persistence, regression, or progression of prediabetes with coronary artery calcium score (CACS) as a measure of subclinical atherosclerosis. Design A cross-sectional study, comprising 126 765 adults, and longitudinal sub-study, comprising 40 622 adults (with baseline and at least 1 follow-up computed tomography scan to assess changes in CACS), were undertaken. Methods Changes in glycemic status over 1.5 years (interquartile range, 1.0-2.0) before the first CACS assessment were categorized according to 6 groups: persistent normoglycemia (reference), normoglycemia to prediabetes, normoglycemia to diabetes, prediabetes to normoglycemia, persistent prediabetes, and prediabetes to diabetes. Logistic regression was used to calculate the odds ratios (ORs) and 95% CIs for prevalent coronary artery calcification (CAC). Mixed models with random intercepts and random slopes were used to estimate 5-year CAC progression rates. Results Mean (SD) age was 41.3 (7.0) years (74.7% male) (n = 126 765). Multivariable-adjusted OR for prevalent CAC was 1.13 (95% CI, 1.08-1.18) for persistent prediabetes, 1.05 (0.98-1.12) for regression to normoglycemia, and 1.46 (95% CI, 1.27-1.67) for progression from prediabetes to diabetes, compared with persistent normoglycemia. Coronary artery calcification progression increased significantly in all prediabetes groups. Multivariable-adjusted ratio of 5-year CAC progression rates was 1.19 (95% CI, 1.16-1.22) (persistent prediabetes), 1.11 (1.07-1.14) (regression to normoglycemia), and 1.63 (95% CI, 1.26-2.10) (progression from prediabetes to diabetes). Conclusions Unfavorable changes in glycemic status, including persistence of prediabetes or progression to diabetes from prediabetes, were associated with increased risk of CAC.

Introduction The incidence rate of prostate cancer (PCa) has continued to rise in Korea. This study aimed to construct and evaluate a 5-year PCa risk prediction model using a cohort with PSA < 10 ng/mL by incorporating PSA levels and individual factors. Methods The PCa risk prediction model including PSA levels and individual risk factors was constructed using a cohort of 69,319 participants from the Kangbuk Samsung Health Study. 201 registered PCa incidences were observed. A Cox proportional hazards regression model was used to generate the 5-year risk of PCa. The performance of the model was assessed using standards of discrimination and calibration. Results The risk prediction model included age, smoking status, alcohol consumption, family history of PCa, past medical history of dyslipidemia, cholesterol levels, and PSA level. Especially, an elevated PSA level was a significant risk factor of PCa (hazard ratio [HR]: 1.77, 95% confidence interval [CI]: [1.67–1.88]). This model performed well with sufficient discrimination ability and satisfactory calibration (C-statistic: 0.911, 0.874; Nam-D’Agostino test statistic:19.76, 4.21 in the development and validation cohort, respectively). Conclusions Our risk prediction model was effective in predicting PCa in a population according to PSA levels. When PSA levels are inconclusive, an assessment of both PSA and specific individual risk factors (e.g., age, total cholesterol, and family history of PCa) could provide further information in predicting PCa.