BackgroundTo assess the socio-demographic and health-related risk factors associated with cataract subtypes in Korea.MethodsA total of 11,591 participants (aged ≥40 years) were selected from the Korean National Health and Nutrition Examination Survey between 2008 and 2010. The Korean Ophthalmologic Society conducted detailed ophthalmologic examinations on these participants based on the Lens Opacity Classification System III. Risk factors for developing any type of cataract, and its subtypes (nuclear, cortical, posterior subcapsular and mixed), were identified from univariate and multivariate logistic regression analysis.ResultsThe prevalence of cataracts was 40.1% (95% CI, 37.8 − 42.3%) in participants over 40 years old. Older age, lower monthly household income, lower education, hypercholesterolemia, hypertension, and diabetes mellitus (DM) were independent risk factors for development of any cataract. Older age, lower monthly household income, lower education, hypercholesterolemia, and DM were independent risk factors for development of pure cortical cataracts. Older age, lower education, metabolic syndrome, and DM were independent risk factors for development of pure nuclear cataracts. Older age and DM were independent risk factors for development of pure posterior subcapsular cataracts. Older age, lower monthly household income, lower education, and DM were independent risk factors for development of mixed cataracts.ConclusionAlthough socioeconomic disparities are related to cataract development, this study identified several “modifiable” risk factors that may help to lower the incidence of cataracts and associated vision loss. Improved control of blood pressure, blood, glucose, and cholesterol may help to reduce the incidence of cataracts in the general Korean population.

BACKGROUND:The large-scale social distancing efforts to reduce SARS-CoV-2 transmission have dramatically changed human behaviors associated with traumatic injuries. Trauma centers have reported decreases in trauma volume, paralleled by changes in injury mechanisms. We aimed to quantify changes in trauma epidemiology at an urban Level I trauma center in a county that instituted one of the earliest shelter-in-place orders to inform trauma care during future pandemic responses. METHODS:A single-center interrupted time-series analysis was performed to identify associations of shelter-in-place with trauma volume, injury mechanisms, and patient demographics in San Francisco, California. To control for short-term trends in trauma epidemiology, weekly level data were analyzed 6 months before shelter-in-place. To control for long-term trends, monthly level data were analyzed 5 years before shelter-in-place. RESULTS:Trauma volume decreased by 50% in the week following shelter-in-place (p < 0.01), followed by a linear increase each successive week (p < 0.01). Despite this, trauma volume for each month (March-June 2020) remained lower compared with corresponding months for all previous 5 years (2015-2019). Pediatric trauma volume showed similar trends with initial decreases (p = 0.02) followed by steady increases (p = 0.05). Reductions in trauma volumes were due entirely to changes in nonviolent injury mechanisms, while violence-related injury mechanisms remained unchanged (p < 0.01). CONCLUSION:Although the shelter-in-place order was associated with an overall decline in trauma volume, violence-related injuries persisted. Delineating and addressing underlying factors driving persistent violence-related injuries during shelter-in-place orders should be a focus of public health efforts in preparation for future pandemic responses.

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