Hyun Tae Kim1, Joon Mo Kim2, Jung Hoon Kim3, Jae Hyuck Lee1, Mi Yeon Lee4, Jae Yeun Lee1, Yu Sam Won5, Ki Ho Park6, Hyun Seok Kwon7. 1. Department of Ophthalmology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea. 2. Department of Ophthalmology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea. Electronic address: kjoonmo1@gmail.com. 3. Department of Ophthalmology, Inje University, Sanggye Paik Hospital, Seoul, Korea. 4. Department of Biostatistics, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea. 5. Department of Neurosurgery, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea. 6. Department of Ophthalmology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea. 7. SU Yonsei Eye Clinic, Seoul, Korea.
Abstract
PURPOSE: To evaluate the relationship between intraocular pressure (IOP) and various anthropometric measures. DESIGN: A population-based cross-sectional study. METHODS: A total of 5008 participants, 2080 men and 2928 women ≥19 years of age were included from the Korea National Health and Nutrition Examination Survey V database, focusing on the years 2010 and 2011. We selected IOP in the right eye of a normal healthy population as the outcome variable of our study. We analyzed the relationship between IOP and anthropometric parameters using dual-energy X-ray absorptiometry by sex. Lean body mass was calculated as total body mass minus fat mass. We used general linear models and logistic regression analysis to evaluate risk factors of high IOP. Our main outcome measure was correlation between anthropometric data and IOP. RESULTS: In multivariate general linear models, greater body mass index (BMI) and waist circumference were correlated with higher IOP for both men (BMI, β = 0.053, P = .026; waist circumference, β = 0.016, P = .067) and women (BMI, β = 0.074, P < .001; waist circumference, β = 0.028, P < .001). Greater fat mass (β = 0.027, P = .037) and fat mass/lean body mass (β = 1.170, P = .06) were correlated with higher IOP, while greater lean body mass/weight (β = -3.188, P = .025), lean body mass/BMI (β = -1.379, P = .002), appendicular skeletal muscle mass/BMI (β = -2.270, P = .022), and bone mineral content/BMI (β = -11.653, P = .031) were correlated with lower IOP in women, but not in men (P > .10). CONCLUSIONS: In healthy women, greater fat mass was associated with higher IOP, and greater muscle mass was associated with lower IOP after adjusting for weight and BMI. Fat and muscle influenced IOP in women independently. Copyright Â
PURPOSE: To evaluate the relationship between intraocular pressure (IOP) and various anthropometric measures. DESIGN: A population-based cross-sectional study. METHODS: A total of 5008 participants, 2080 men and 2928 women ≥19 years of age were included from the Korea National Health and Nutrition Examination Survey V database, focusing on the years 2010 and 2011. We selected IOP in the right eye of a normal healthy population as the outcome variable of our study. We analyzed the relationship between IOP and anthropometric parameters using dual-energy X-ray absorptiometry by sex. Lean body mass was calculated as total body mass minus fat mass. We used general linear models and logistic regression analysis to evaluate risk factors of high IOP. Our main outcome measure was correlation between anthropometric data and IOP. RESULTS: In multivariate general linear models, greater body mass index (BMI) and waist circumference were correlated with higher IOP for both men (BMI, β = 0.053, P = .026; waist circumference, β = 0.016, P = .067) and women (BMI, β = 0.074, P < .001; waist circumference, β = 0.028, P < .001). Greater fat mass (β = 0.027, P = .037) and fat mass/lean body mass (β = 1.170, P = .06) were correlated with higher IOP, while greater lean body mass/weight (β = -3.188, P = .025), lean body mass/BMI (β = -1.379, P = .002), appendicular skeletal muscle mass/BMI (β = -2.270, P = .022), and bone mineral content/BMI (β = -11.653, P = .031) were correlated with lower IOP in women, but not in men (P > .10). CONCLUSIONS: In healthy women, greater fat mass was associated with higher IOP, and greater muscle mass was associated with lower IOP after adjusting for weight and BMI. Fat and muscle influenced IOP in women independently. Copyright Â
Authors: Jae Yeun Lee; Tae-Woo Kim; Hyun Tae Kim; Mi Yeon Lee; Hye Won Min; Yu Sam Won; Hyun Seok Kwon; Ki Ho Park; Joon Mo Kim Journal: PLoS One Date: 2017-05-08 Impact factor: 3.240