BACKGROUND: No study has directly compared the risk factors associated with subclinical coronary atherosclerosis and CRA.
STUDY: This was a cross-sectional study using multinomial logistic regression analysis of 4859 adults who participated in a health screening examination (2010 to 2011; analysis 2014 to 2015). CAC scores were categorized as 0, 1 to 100, or >100. Colonoscopy results were categorized as absent, low-risk, or high-risk CRA.
RESULTS: The prevalence of CAC>0, CAC 1 to 100 and >100 was 13.0%, 11.0%, and 2.0%, respectively. The prevalence of any CRA, low-risk CRA, and high-risk CRA was 15.1%, 13.0%, and 2.1%, respectively. The adjusted odds ratios (95% confidence interval) for CAC>0 comparing participants with low-risk and high-risk CRA with those without any CRA were 1.35 (1.06-1.71) and 2.09 (1.29-3.39), respectively. Similarly, the adjusted odds ratios (95% confidence interval) for any CRA comparing participants with CAC 1 to 100 and CAC>100 with those with no CAC were 1.26 (1.00-1.6) and 2.07 (1.31-3.26), respectively. Age, smoking, diabetes, and family history of CRC were significantly associated with both conditions.
CONCLUSIONS: We observed a graded association between CAC and CRA in apparently healthy individuals. The coexistence of both conditions further emphasizes the need for more evidence of comprehensive approaches to screening and the need to consider the impact of the high risk of coexisting disease in individuals with CAC or CRA, instead of piecemeal approaches restricted to the detection of each disease independently.
OBJECTIVE: To examine the associations of change in body mass index (BMI), waist circumference, and percent fat mass with change in intraocular pressure (IOP) in a large sample of Korean adults.
DESIGN, SETTING AND PARTICIPANTS: Cohort study of 274,064 young and middle age Korean adults with normal fundoscopic findings who attended annual or biennial health exams from January 1, 2002 to Feb 28, 2010 (577,981 screening visits).
EXPOSURES: BMI, waist circumference, and percent fat mass.
MAIN OUTCOME MEASURE(S): At each visit, IOP was measured in both eyes with automated noncontact tonometers.
RESULTS: In multivariable-adjusted models, the average increase in IOP (95% confidence intervals) over time per interquartile increase in BMI (1.26 kg/m2), waist circumference (6.20 cm), and percent fat mass (3.40%) were 0.18 mmHg (0.17 to 0.19), 0.27 mmHg (0.26 to 0.29), and 0.10 mmHg (0.09 to 0.11), respectively (all P < 0.001). The association was stronger in men compared to women (P < 0.001) and it was only slightly attenuated after including diabetes and hypertension as potential mediators in the model.
CONCLUSIONS AND RELEVANCE: Increases in adiposity were significantly associated with an increase in IOP in a large cohort of Korean adults attending health screening visits, an association that was stronger for central obesity. Further research is needed to understand better the underlying mechanisms of this association, and to establish the role of weight gain in increasing IOP and the risk of glaucoma and its complications.