Skipping breakfast is highly prevalent but it is not clear whether breakfast frequency is associated with metabolic syndrome in young adults. We aimed to assess the association between breakfast frequency and metabolic syndrome in Korean young adults. This cross-sectional study was based on health check-up data of university students aged 18-39 years between 2016 and 2018. Participants were stratified into three groups based on breakfast frequency (non-skipper, skipper for 1-3 days per week, and skipper for 4-7 days per week). Meal patterns were classified into healthy, fair, and unhealthy patterns by combination of breakfast frequency, binge eating frequency, and meal regularity. Multivariable-adjusted logistic regression was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) of metabolic syndrome. Of the total 12,302 participants, 56.8% skipped breakfast for 3 days or more per week. The prevalence of metabolic syndrome was higher among participants skipping breakfast for 3 days or more per week than non-skipper (3.1% vs. 1.7%). In the age- and sex-adjusted model, individuals skipping breakfast for 4-7 days per week had a higher OR of metabolic syndrome (OR 1.73, 95% CI 1.21-2.49) compared to non-skipper. Although this association became insignificant (OR 1.49, 95% CI 0.99–2.23) after multivariable adjustment, trends of positive association between frequency of breakfast skipping and metabolic syndrome was significant (P for trend = 0.038). Among components of metabolic syndrome, high blood pressure was significantly associated with frequent breakfast skipping (OR 1.34, 95% CI 1.09-1.65). Binge eating and having irregular meals was not significantly associated with metabolic syndrome. Individuals with unhealthy meal patterns had a higher OR of metabolic syndrome compared to those with healthy meal patterns (OR 1.80, 95% CI 1.02-3.19). Frequent skipping breakfast was associated with higher odds of metabolic syndrome in young adults. Unhealthy meal patterns were significantly associated with higher odds of metabolic syndrome (p < 0.001). Further longitudinal studies in the long term are needed to understand the association of meal patterns with metabolic syndrome.
Purpose: To establish the accuracy of the newly released biometer Ocuscan RxP Ⓡ (Alcon, USA) by comparison with the established Ultrasonic Biometer Model 820 Ⓡ (Allergan Humphrey, USA), and to compare the accuracy of contact and immersion biometries.Methods: This is a prospective study involving 27 patients (40 eyes) who were scheduled for cataract surgery and had axial lengths measured with an Ocuscan RxP Ⓡ biometer using both contact (Method 1) and immersion (Method 2) techniques. As a reference, a contact type Ultrasonic biometer 820 Ⓡ (Method 3) was also used. IOL(Intraocular Lens) power for the cataract surgery was calculated using this result. An axial length which would have caused no post-operative refractive error was reversely calculated from the difference of target diopter and post-operative refractive error. This length was compared with the axial lengths obtained via Methods 1, 2 and 3.
Results:The means and standard deviations for the measurement sets were compared. Methods 1 and 2 showed no significant difference (23.22±0.68, 23.24±0.69 mm, p=0.55). The axial length measured by Method 3 was 23.32±0.67 mm. The difference between the target refraction and post-operative refractive error was 0.29±0.60D. The axial length was reversely calculated from the difference (23.07±0.84 mm). The differences between the reversely calculated axial lengths and those of Methods 1, 2 and 3 were 0.15± 0.31, 0.17±0.31 and 0.24±0.28 mm, respectively. Conclusions: Biometric results from Methods 1 and 2 caused less refractive error than did Method 3. The contact and immersion methods are both accurate for IOL power calculation if performed by a well-skilled examiner.
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