Author:
Zhang Tianlin,Ying Haojiang,Wang Huiqun,Zhao Fouxi,Pan Qiying,Zhan Qingqing,Zhang Fuyan,An Qinyu,Liu Tao,Hu Yuandong,Zhang Yang
Abstract
ObjectivesThis current study is based on a set of visual motion sensitivity tests, investigating the correlation between visual motion sensitivity and diabetic retinopathy (DR) in type 2 diabetes mellitus (T2DM), thereby furnishing a scientific rationale for preventing and controlling DR.MethodsThis research was conducted by a combination of questionnaire collection and on-site investigation that involved 542 T2DM recruited from a community. The visual motion sensitivity determined the visual motion perception of the participants across three spatial frequencies (low, medium, and high) for both the first- and second-order contrast. The logistic regression model was adopted to investigate the relationship between visual motion sensitivity and DR prevalence. Besides, the Pearson correlation analysis was used to analyze the factors influencing visual motion sensitivity and restricted cubic spline (RCS) functions to assess the dose–response relationship between visual motion sensitivity and glycated hemoglobin.ResultsAmong 542 subjects, there are 162 cases of DR, with a prevalence rate of 29.89%. After adjusting factors of age, gender, glycated hemoglobin, duration of diabetes, BMI, and hypertension, we found that the decline in first- and second-order high spatial frequency sensitivity increased the risk for DR [odds ratio (OR): 1.519 (1.065, 2.168), 1.249 (1.068, 1.460)]. The decline in perceptual ability of second-order low, medium, and high spatial frequency sensitivity is a risk factor for moderate to severe DR [OR: 1.556 (1.116, 2.168), 1.388 (1.066, 1.806), 1.476 (1.139, 1.912)]. The first-order and the second-order high spatial frequency sensitivity are significantly positively correlated with glycated hemoglobin (r = 0.105, p = 0.015 and r = 0.119, p = 0.005, respectively).ConclusionVisual motion sensitivity especially for the second-order high spatial frequency stimuli emerges as a significant predictor of DR in T2DM, offering a sensitive diagnostic tool for early detection.