29 Environmental Risk Factors for Myopia in Children

The OLSM looked at 366 eighth-grade predominantly Caucasian children (mean age of 13.7 ± 0.5 years) and found that the OR of myopia (defined as SE at least –0.75 D) was 1.02 (95% CI = 1.008–1.032) for every diopter-hours spent per week, after controlling for parental myopia, diopter-hours per week and achievement scores (Table 2).24 However, there was no interaction between parental myopia and near work (p = 0.67). Children with myopia were more likely to have parents with myopia.

Other studies suffered from methodological limitations such as small sample size, inappropriate sampling strategies, lack of cycloplegic refraction, and lack of control for major confounders.30–35

Near work was also shown to be not associated with myopia.31,36 Lu and co-workers (Table 2)36 analyzed 998 Chinese school children aged 13 to 17 years from the Xichang Pediatric Refractive Error Study (X-PRES) and reported the multivariate adjusted OR of myopia (defined as SE at least –0.5 D) was 1.27 (95% CI = 0.75–2.14) for reading in hours per week and SE was not associated with near work. However, the study subjects may not be representative of the general population since this was a school-based design. In another study, Saw and co-workers recruited 128 children from one kindergarten in Singapore (Table 2).31 The cross-sectional study found that after adjusting for parental history of myopia and age, the OR of myopia was 1.0 (95% CI = 0.8–1.3) for close-up work activity. However, this finding could be due to the small sample size.

Outdoor activity

There were few prior studies that analyzed outdoor activity as a major environmental factor for myopia.14,15,23,36,37

Jones and co-workers (Table 3)23 conducted a longitudinal study of children in the OLSM in California. 514 children in the third to eighth grade (aged 8 to 13 years) were included. Children who became myopic (defined as SE at least –0.75 D) by the eighth grade were found to perform less sports and outdoor activity (hours per week) at the third grade compared to those who did not become myopic (7.98 ± 6.54 hours vs. 11.65 ± 6.97 hours). In predictive models for future myopia, combined amount of sports and outdoor hours per week conferred a protective effect against future myopia (OR = 0.91; 95% CI = 0.87–0.95) after adjusting for parental myopia, reading hours, and sports and outdoor hours. Significant

31 Environmental Risk Factors for Myopia in Children

interaction was found between the number of parents with myopia and hours of sports and outdoor activity on the development of myopia.

The SMS (Table 3)14 analyzed 2367 school children aged 11 to 14 years and found a higher level of outdoor activity (>2.8 hours per day) was associated with more hyperopic mean SE refraction (0.54 D) after adjusting for gender, ethnicity, parental myopia, near work activity, maternal and paternal education. Furthermore, in an analysis combining amount of outdoor activity and near work activity spent, children with low outdoor and high near work had the (OR = 2.6; 95% CI = 1.2–6.0) higher odds for myopia compared to those performing low near work and high outdoor (reference group).

In Singapore, a cross-sectional analysis of SCORM was conducted to analyze the effect of outdoor activity on myopia in 1249 teenagers aged 11 to 20 years (71.1%, Chinese, 20.7% Malays and 0.8% other ethnicities) (Table 3).15 After adjusting for age, gender, ethnicity, school, number of books read per week, height, parental myopia, father’s education and IQ level, outdoor activity was significantly negatively associated with myopia (OR = 0.90; 95% CI = 0.84–0.96). For each hour increase in outdoor activity per day, the SE refraction increased by 0.17 D (95% CI = 0.10–0.25), and the AL decreased by 0.06 mm (95% CI = −0.1 − −0.03), after adjusting for the same confounders.

An analysis on a two-year longitudinal cohort study conducted in 143 Caucasian Danish medical students (mean age = 23 years) was performed to investigate the level of physical activity on myopia.37 The multiple regression showed that time spent reading scientific literature was associated with a refractive change toward myopia (regression coefficient = –0.063; 95% CI = –0.117– –0.008; p = 0.024), while the association was inversed for the level of physical activity (regression coefficient = 0.175; 95% CI = 0.035–0.315; p = 0.015). Although the total amount of time spent on outdoor activity was not recorded, the author postulated that the level of physical activity could parallel that of outdoor activity and thus the protective effect of physical activity on myopia could be attributed in part to outdoor activity.

In the X-PRES, Lu and co-workers (Table 3)36 initiated a school-based cross-sectional study of 998 secondary school Chinese children aged 13 to 17 years from Xichang, China. After controlling for age, gender, parental education, homework, reading and TV watching, outdoor activity was not significantly associated with myopia (OR = 1.14; 95% CI = 0.69–1.89). The students were administered a near-work survey to collect information on

32 W.C.J. Low, T.Y. Wong and S.-M. Saw

the time spent during the previous week on schoolwork, reading, watching television, video games and computer use, family business related near-work tasks and outdoor activities. Nevertheless, the authors acknowledged the lack of association between outdoor and myopia could be biased by estimating near work and outdoor activities based on self-reported questionnaires and by focusing on a single week rather than the children’s long term experience. In addition, the interpretation of the findings was possibly limited by the school-based design, high refusal (13%), and incomplete near-work survey (19%).

Stature

In a cross-sectional study of 1449 Singapore Chinese schoolchildren aged seven to nine years from the SCORM, Saw and co-workers (Table 4)38 compared height in the first quartile and fourth quartile (adjusting for age, gender, parental myopia, number of books per week, school, and weight). The analysis showed that the AL was 0.46 mm longer. On the other hand, the SE refraction was more negative by 0.47 D. In multiple linear regression models for AL adjusting for the same factors, each cm increase in height resulted in a 0.032 mm increase in AL (p < 0.001). For each cm in height, the SE refraction decrease by 0.031 D (p = 0.002), while for each kg increase in weight, the SE refraction decreased by 0.027 D (p = 0.01).

The SMS conducted a population-based cross-sectional analysis on 1765 six-year-old schoolchildren; 64.5% were Caucasians, 17.2% were East Asians, and 18.3% belonged to other races (Table 4).39 Children in the first quintile for height had AL of 22.39 ± 0.04 mm compared with 22.76 ± 0.04 mm in children in the fifth quintile. After adjusting for age, gender, parental myopia, weight, BMI, body fat percentage and waist circumference, each 10 cm increase in height corresponded to a 0.29 mm (95% CI = 0.19–0.39) increase in AL. However, height was not significantly associated with SE refraction.

A population-based cross-sectional study (the Tanjong Pagar survey (TPS)) in Singapore analyzed data of 951 Chinese adults aged between 40 and 80 years, (Table 4)40 and demonstrated that a 10 cm greater height was associated with a longer AL of 0.23 mm (95% CI = 0.1–0.37), after adjusting for age, gender, education, occupation, housing, income, and weight. Adjusting for the same factors, for every 10 kg increase in weight, the SE refraction increased by 0.22 D (95% CI = 0.05–0.39), and every 10 kg/m2