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Myopia and later physical activity in adolescence: a prospective study
  1. K Deere1,
  2. C Williams5,
  3. S Leary2,
  4. C Mattocks1,
  5. A Ness2,
  6. S N Blair3,
  7. C Riddoch4
  1. 1
    Department of Social Medicine, University of Bristol, Bristol, UK
  2. 2
    Department of Oral and Dental Science, University of Bristol, Bristol, UK
  3. 3
    Department of Exercise Science, University of South Carolina, South Carolina, USA
  4. 4
    Department of Sport and Exercise Science, University of Bath, Bath, UK
  5. 5
    Centre for Child and Adolescent Health, University of Bristol, Bristol, UK
  1. Cathy Williams, Vision Research, Centre for Child and Adolescent Health, Barley House Group, Barley House, Oakfield Grove, Bristol BS8 2BN, UK; Cathy.Williams{at}


Objectives: To investigate associations between objectively measured physical activity (PA) and myopia in children.

Methods: Children from the Avon Longitudinal Study of Parents and Children (ALSPAC) were asked to wear a uniaxial accelerometer for 7 days. Measures of counts per minute (cpm), minutes spent in moderate to vigorous activity (MVPA) and minutes of sedentary behaviour (msed) were derived from the accelerometer worn at age 12. Children were also examined, at age 10, using an autorefractor to estimate myopia. Social and parental factors were collected from pregnancy and physical measures of the child were recorded at age 12.

Results: 4880 children had valid PA and autorefraction data. In minimally adjusted models (age and gender) myopic children were less active than the other children: β = −49.9 cpm (95% CI −73.5 to −26.4, p = <0.001). The myopic group spent less time in MVPA than the other children: β = −3.2 minutes MVPA (95% CI −5.2 to −1.1, p = 0.003) and more time sedentary: β = 15.8 minutes (95% CI 5.8 to 25.8, p = 0.002). The effect sizes were attenuated by adjustment for social and behavioural confounders although myopia status in the better (less myopic on autorefraction) eye remained strongly associated with cpm and MVPA but less so for sedentary behaviour: β = −36.8 cpm (95% CI –67.8 to −5.8, p = 0.02), β = −2.7 MVPA (95% CI −5.3 to −0.1, p = 0.04), β = 10.1 msed (95% CI –2.9 to 23.1, p = 0.13).

Conclusion: Myopic children may be more at risk of having lower levels of PA than their non-myopic peers, although the difference was modest.

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Physical activity in children is an important determinant of health.14 While studies have examined the association between physical activity and environmental factors5 and sociodemographic factors,6 few studies have reported on the role of specific physical characteristics such as eyesight that might influence physical activity.

Myopia, or short-sightedness, has been estimated to affect 8.4% of 4–12-year-olds in Australia7 and 9.2% of 5–17-year-olds in the USA.8 Myopia in children has been associated with spending less time playing sports9 and the perception by mothers that their children have poorer sporting ability.10 These studies used subjective measures of activity or sporting ability, which may not accurately assess levels of physical activity in children because recall is poor and activity is often sporadic and unplanned.10 Objective measurement may provide a more accurate estimate of physical activity in children.11 We examined the association between objectively measured physical activity and myopia (estimated by autorefraction) in a large prospective study of contemporary children.


ALSPAC recruited pregnant women with an expected date of delivery between 1 April 1991 and 31 December 1992 in the former county of Avon (south west of England). Further details are available elsewhere12 ( Ethical approval for the study was obtained from the ALSPAC Law and Ethics Committee and Local Research Ethics Committees. Prior to the beginning of each clinic visit the main carer of the child provided informed written consent. For the physical activity measurement the child and main carer gave verbal consent.

Children were invited to attend a clinic at approximately 12 years of age, between January 2003 and January 2005, and this included an objective measurement of physical activity. All children who attended were asked to wear an Actigraph accelerometer, model WAM 7164 (Actigraph LLC, Fort Walton Beach, FL) for 7 days. The Actigraph has been validated in both children and adolescents.13 Each child was given an Actigraph, which was programmed to start recording at 5 a.m. the next day, and instructed to return it by post in a prepaid envelope at the end of the monitoring period.

Data from the returned Actigraphs were downloaded and then imported into a Microsoft Access 2000 database. Children who did not provide a minimum of 600 minutes valid data on at least three separate days were omitted from the analyses.14 The analysis considered three physical activity variables: total physical activity measured as counts per minute (cpm), minutes of moderate to vigorous activity (MVPA) per day and time spent sedentary in minutes per day.

Children had their myopia assessed when they were approximately 10 years old at a previous clinic. We used autorefraction without cycloplegia and used validation studies to guide interpretation of the data.15 Our myopic group was decided by an autorefractor reading of −1.5 D mean spherical equivalent or more severe (more myopic) in either eye. We used the comparison between the myopic group and the rest of the sample as a model to estimate the strength of associations with myopia. We used a Canon R50 (Clement Clarke, Haag Streit UK, Harlow, UK) autorefractor, which estimated refractive error for each eye separately. The subjects were asked if they wore glasses during a clinic visit at age 10. They were also asked if they wore contact lenses.

Parental data included self-reported maternal and partner’s myopia and ethnicity. The ethnicity of the child was classified as white or non-white. Information on pubertal status at age 11 was derived from a questionnaire completed by the carer.

The data were analysed using Stata Version 8.0 (Stata Corporation, College Station, Texas). The distributions of cpm and MVPA were skewed. For the regression analysis, data were not transformed, but robust standard errors were used, which allow derivation of confidence intervals and standard errors based on the actual distribution of the outcome variable in the dataset.16 Two categorical myopia predictor variables were used, myopia based on estimations from the least myopic eye (best eye) and the most myopic eye (worst eye), at the 10 year clinic visit.

Multivariable linear regression was used to estimate associations between myopia and physical activity and to adjust for the effects of confounding factors. The results are presented for two models. Model 1 was our minimally adjusted model, which included gender and the age at which the Actigraph was worn. Model 2 was our maximally adjusted model, additionally adjusting for lowest social class of the parents, maternal education, glasses data, parental myopia and child ethnicity.


A total of 7159 children attended the clinic. Of them, 6622 agreed to wear an Actigraph, 5603 of whom provided valid activity data. Of these, 4880 had valid autorefractor data and were used in the analyses. The median total activity was 579.3 cpm, the median MVPA was 19.7 minutes and the average msed was 427.9 minutes.

There were 171 myopes in the “best eye” model (3.5%) and 274 in the “worst eye” model (5.6%). The average age was 11.8 years. Table 1 shows the results from multivariable regressions. The “best eye” model showed the myopic children to have 49.9 cpm (p = <0.001) less than their peers per day. They also had 3.2 minutes less MVPA per day than their peers (p<0.001) and had 15.8 minutes more sedentary time per day (p = 0.002). The effect sizes were attenuated by adjustment for social and behavioural confounders but the association remained.

Table 1 Multivariable regressions of physical activity variables at age 12 and myopia variables at age 10 for children from the ALSPAC study: myopic versus non-myopic


We have demonstrated an inverse association between myopia and physical activity in 12-year-old children. After adjustment, children defined as myopic at 10 years of age were less active than their peers at approximately 12 years of age. In general they had lower total activity, lower MVPA and increased sedentary time. This could be because children who wear glasses for myopia are reluctant to participate in physical activity due to the impracticality of wearing glasses during sports or vigorous activities.

We have used an approximation of myopia based on non-cycloplegic autorefraction, rather than accurate refractive measurements. Thus some non-myopic children may have been misclassified as myopic by the autorefractor. In addition, some children may have become myopic between the ages of measurement of myopia and PA (approximately 10 and 12 years of age, respectively).

As childhood behaviours have been demonstrated to track into adulthood,17 the reduced activity of the myopic group could give rise to an increased risk of disease associated with low physical activity levels if the associations persist.


These novel data suggest an increased risk of lower physical activity for myopic children and support the hypothesis that myopes are less active than their peers. This risk could be reduced if interventions were targeted at myopic children to make them aware of the risks of low physical activity. Further studies later in adolescence to test for tracking of these behaviours would further clarify the predictive nature of childhood myopia for the physical activity of children.

What is already known on this topic

It is known that physical activity is important to health. It has been observed that parents of myopic children describe them as spending less time playing sports and more time studying. Questionnaire data has shown that playing sports is inversely associated with myopia in adolescents.

What this study adds

This study is the first to show a relationship between myopia and physical activity in adolescents using an objective measurement of physical activity. The study shows myopic adolescents to be at risk of lower levels of physical activity than their peers.


We are extremely grateful to all the families who took part in this study, the midwives for their help in recruiting them, and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists and nurses.


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  • Funding: The UK Medical Research Council, the Wellcome Trust and the University of Bristol provide core support for ALSPAC. This research was specifically funded by a grant from National Heart, Lung and Blood Institute (R01 HL071248-01A). The funding body had no influence on the design of the study or the writing of this report.

  • Competing interests: None.