1. Sudden Vision Loss and Mortality: The Jackson Heart Study.
- Author
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Greenberg PB, Chen AJ, and Wu WC
- Subjects
- Adult, Black or African American statistics & numerical data, Aged, Aged, 80 and over, Female, Humans, Male, Middle Aged, Proportional Hazards Models, Risk Factors, United States epidemiology, Young Adult, Myocardial Infarction epidemiology, Stroke epidemiology, Vision Disorders mortality
- Abstract
Purpose: It is unknown whether sudden vision loss (SVL) is an independent marker for future cardiovascular disease (CVD) events in African Americans. We examined the hazard of future stroke or myocardial infarction (MI) and mortality associated with self-reported SVL lasting 24 hours or longer in a cohort of African Americans enrolled in the Jackson Heart Study (JHS)., Methods: The study sample comprised 4670 African Americans aged 20-95 years enrolled in the JHS without previous coronary heart disease or stroke at baseline. All participants who responded to the question "Have you ever had any sudden loss of vision or blurring, lasting 24 hours or longer?" on the baseline stroke questionnaire were included in the study. Ten years of follow-up data was used. Cox proportional hazards modeling was used to examine the association between SVL (n = 142) and risk of future stroke/MI and mortality., Results: In age- and sex-adjusted Cox models, SVL was significantly associated with higher hazards of future stroke/MI (hazard ratio, HR, 2.08, 95% confidence interval, CI, 1.09-3.96) and mortality (HR 1.73, 95% CI 1.07-2.78). After adjusting for diabetes mellitus, total/high-density lipoprotein cholesterol ratio, smoking, hypertension and income, the relationships between SVL and future stroke/MI (adjusted HR 1.51, 95% CI 0.78-2.90) or mortality (adjusted HR 1.29, 95% CI 0.78-2.11) were no longer significant., Conclusions: Self-reported SVL lasting 24 hours or longer was significantly associated with future stroke/MI and mortality, but its effect is likely a surrogate for underlying CVD risk factors rather than being an independent predictor.
- Published
- 2016
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