Abstract
Purpose: :
The objective is to identify the individuals who will become myopic using parental history and environmental (near work) factors .
Methods: :
The Orinda Longitudinal Study of Myopia (OLSM) collected data from 1989 to 2001 to identify risk factors for myopia onset. We have previously shown that the amount of mean sphere in the third grade is the strongest predictor of myopia among the ocular components (IOVS, 1999). This analysis uses only parental history, and hours of near work and recreational activity, as predictors of myopia. Non–myopic subjects in the OLSM with complete data in the third grade who become myopic or had a final visit in eighth grade were included. Activity hours were collected from a resurvey form completed annually by a parent. Descriptive statistics (mean ± sd), proportional hazards and logistic analysis for univariate and multivariate modeling were used. Receiver operating curves were applied to the individual predictor variables and the multivariate models. Point estimates for the area under the curve and standard errors were calculated.
Results: :
Of the 504 eligible subjects, 107 (21.2%) became myopic by the end of the study. A myopic mother, a myopic father and a greater number of myopic parents were significantly associated with the myopia onset. Among the activities, only the number of hours in sports or outdoor activities differed between the pre–myopes and non–myopes (8.01 ± 6.62 vs. 11.64 ± 7.01, respectively, p<0.0001). This difference remained significant after controlling for sex of the subject. The area under the curve (AUC) for the number of myopic parents was 0.65 ((0.61, 0.70) 95% CI), and the AUC for the number of sports hours per week was 0.68 (0.63, 0.73). Reading hours had an AUC of 0.57 (0.52, 0.62). The best logistic multivariate model for predicting myopia included the number of myopic parents and the number of sports hours, with an AUC of 0.73 (0.68, 0.77).
Conclusions: :
Both parental history of myopia and children’s activity appear to be predictive of myopia onset. Among the activities, time spent playing sports was more predictive than reading hours. Sports hours were protective against myopia onset. Both a myopic mother and a myopic father were predictive of myopia onset, with the number of myopic parents most predictive. Both genetic and environmental factors, namely the number of myopic parents and hours playing sports, are risk factors for predicting myopia. The amount of time spent not reading may be more important than the time spent reading.
Keywords: refractive error development • clinical (human) or epidemiologic studies: risk factor assessment