Profile of anisometropia and aniso-astigmatism in children; prevalence and association with age, ocular biometric measures, and refractive status

Purpose. We describe the profile and associations of anisometropia and aniso-astigmatism in a population-based sample of children. Methods. The Northern Ireland Childhood Errors of Refraction (NICER) study used a stratified random cluster design to recruit a representative sample of children from schools in Northern Ireland. Examinations included cycloplegic (1% cyclopentolate) autorefraction, and measures of axial length, anterior chamber depth, and corneal curvature. ?2 tests were used to assess variations in the prevalence of anisometropia and aniso-astigmatism by age group, with logistic regression used to compare odds of anisometropia and aniso-astigmatism with refractive status (myopia, emmetropia, hyperopia). The Mann-Whitney U test was used to examine interocular differences in ocular biometry. Results. Data from 661 white children aged 12 to 13 years (50.5% male) and 389 white children aged 6 to 7 years (49.6% male) are presented. The prevalence of anisometropia =1 diopters sphere (DS) did not differ statistically significantly between 6- to 7-year-old (8.5%; 95% confidence interval [CI], 3.9–13.1) and 12- to 13-year-old (9.4%; 95% CI, 5.9–12.9) children. The prevalence of aniso-astigmatism =1 diopters cylinder (DC) did not vary statistically significantly between 6- to 7-year-old (7.7%; 95% CI, 4.3–11.2) and 12- to 13-year-old (5.6%; 95% CI, 0.5–8.1) children. Anisometropia and aniso-astigmatism were more common in 12- to 13-year-old children with hyperopia =+2 DS. Anisometropic eyes had greater axial length asymmetry than nonanisometropic eyes. Aniso-astigmatic eyes were more asymmetric in axial length and corneal astigmatism than eyes without aniso-astigmatism. Conclusions. In this population, there is a high prevalence of axial anisometropia and corneal/axial aniso-astigmatism, associated with hyperopia, but whether these relations are causal is unclear. Further work is required to clarify the developmental mechanism behind these associations.

Risk factors for childhood myopia:findings from the NICER study

PURPOSE. We explored risk factors for myopia in 12- to 13-year-old children in Northern Ireland (NI). METHODS. Stratified random sampling was performed to obtain representation of schools and children. Cycloplegia was achieved using cyclopentolate hydrochloride 1%. Distance autorefraction was measured using the Shin-Nippon SRW-5000 device. Height and weight were measured. Parents and children completed a questionnaire, including questions on parental history of myopia, sociodemographic factors, childhood levels of near vision, and physical activity to identify potential risk factors for myopia. Myopia was defined as spherical equivalent ≤0.50 diopters (D) in either eye. RESULTS. Data from 661 white children aged 12-to 13-years showed that regular physical activity was associated with a lower estimated prevalence of myopia compared to sedentary lifestyles (odds ratio [OR] = 0.46 adjusted for age, sex, deprivation score, family size, school type, urbanicity; 95% confidence interval [CI], 0.23–0.90; P for trend = 0.027). The odds of myopia were more than 2.5 times higher among children attending academically-selective schools (adjusted OR = 2.66; 95% CI, 1.48–4.78) compared to nonacademically-selective schools. There was no evidence of an effect of urban versus nonurban environment on the odds of myopia. Compared to children with no myopic parents, children with one or both parents being myopic were 2.91 times (95% CI, 1.54–5.52) and 7.79 times (95% CI, 2.93– 20.67) more likely to have myopia, respectively. CONCLUSIONS. In NI children, parental history of myopia and type of schooling are important determinants of myopia. The association between myopia and an environmental factor, such as physical activity levels, may provide insight into preventive strategies.