Analysis of risk and protective factors associated with retinal nerve fiber layer defect in a Chinese adult population
Authors:   Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology＆Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China; Department of Ophthalmology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China, Wang Ye-Nan , Zhou Jin-Qiong ,   Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology＆Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China, Wan Qian-Qian ,   Department of Ophthalmology, the Second Hospital of Anhui Medical University, Hefei 230011, Anhui Province, China, Fang Li-Jian ,   Department of Ophthalmology, Beijing Liangxiang Hospital, Capital Medical University, Beijing 102401, China, Wang Hai-Wei ,   Department of Ophthalmology, Fuxing Hospital, Capital Medical University, Beijing 100045, China, Yang Jing-Yan ,   Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology＆Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China, Dong Li ,   Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology＆Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China, Wang Jin-Yuan ,   Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology＆Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China, Yang Xuan ,   Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology＆Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China, Yan Yan-Ni ,   Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology＆Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China, Wang Qian ,   Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology＆Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China, Wu Shou-Ling ,   Cardiology Department, Kailuan General Hospital, Tangshan 063001, Hebei Province, China, Chen Shuo-Hua ,   Health Care Center, Kailuan Group, Tangshan 063000, Hebei Province, China, Zhu Jing-Yuan ,   Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology＆Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China, Wei Wen-Bin ,   Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Ophthalmology＆Visual Sciences Key Lab, Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China, Jonas Jost B. ,   Department of Ophthalmology, Medical Faculty Mannheim of the Ruprecht-Karls-University of Heidelberg, Heidelberg 68167, Germany
Published: March 2023

AIM: To investigate the risk and protective factors associated with the retinal nerve fiber layer defect (RNFLD) in a Chinese adult population.
METHODS: This study was a cross-sectional population-based investigation including employees and retirees of a coal mining company in Kailuan City, Hebei Province. All the study participants underwent a comprehensive systemic and ophthalmic examination. RNFLD was diagnosed on fundus photographs. Binary logistic regression was used to investigate the risk and protective factors associated with the RNFLD.
RESULTS: The community-based study included 14 440 participants. There were 10 473 participants in our study, including 7120 males (68.0%) and 3353 females (32.0%). The age range was 45-108y, averaging 59.56±8.66y. Totally 568 participants had RNFLD and the prevalence rate was 5.42%. A higher prevalence of RNFLD was associated with older age [P<0.001, odds ratio (OR): 1.032; 95% confidence interval (CI): 1.018-1.046], longer axial length (P=0.010, OR: 1.190; 95%CI: 1.042-1.359), hypertension (P=0.007, OR: 0.639; 95%CI: 0.460-0.887), and diabetes mellitus (P=0.019, OR: 0.684; 95%CI: 0.499-0.939). The protective factors of RNFLD were visual acuity (P=0.038, OR: 0.617; 95%CI: 0.391-0.975), and central anterior chamber depth (P=0.046, OR: 0.595; 95%CI: 0.358-0.990).
CONCLUSION: In our cross-sectional community-based study, with an age range of 45-108y, RNFLD is associated with older age, longer axial length, hypertension, and diabetes mellitus. The protective factors of RNFLD are visual acuity and central anterior chamber depth. These can help to predict and evaluate RNFLD related diseases and identify high-risk populations early.