Abstract
ABSTRACTPurpose: Previous studies have demonstrated positive associations between myopia and environmental risk factors such as urbanization. However, these have failed to account for the clustering of individuals within geographical areas, opening analyses to theoretical and statistical limitations. We demonstrate how a multilevel modelling approach can provide a more nuanced understanding of the relationship between geography and myopia. We examined longitudinal associations between onset of myopia and urban/rural status or population density.Methods: Data were collected over 5 visits during an 8-year period for a UK cohort of 3,512 children. Associations between incident myopia (spherical equivalent ≤ −1.00 diopters) and both urban/rural status and population density were examined using discrete time multilevel hazard models which allow the partitioning of variance into different neighborhood and school areas.Results: There was evidence for an association between myopia and higher population density (Hazard Ratio = 1.14; 95% CI = 1.032 to 1.26) after adjustment for a range of risk factors. There was no strong evidence that urban/rural status was associated with incident myopia. Only a minor amount of variation in myopia was attributable to geographical areas (<2.2%), and this was not explained by rurality or population density.Conclusion: Our findings contrast with previous studies and raise the possibility that some of the results reported may have been driven by confounding bias whereby geographical differences in myopia are driven by lifestyle factors that are correlated with geographical setting.
Highlights
Accounting for covariates did not attenuate the association between population density and myopia (Model 2 HR: 1.12; 95% CI: 1.03, 1.24; Model 3 HR: 1.14; 95% CI: 1.03,1.26), but the unexplained between-neighborhood variation as indicated by the Variance Partition Coefficient (VPC) increased from 0.7% to 1.7%
Our results using a multilevel modeling approach indicated that geography was not strongly associated with onset of myopia
Regarding specific aspects of geographical location, we found no strong evidence for an association between myopia and rurality, but strong evidence for associations between myopia and population density
Summary
The development of myopia is associated with a wide range of genetic, behavioral, social and environmental factors[1,2] including socio-economic status[3,4]; time spent outdoors[5,6]; time spent reading[7,8,9]; educational attainment[10]; and geographical setting.[11,12,13,14,15,16] While the underlying drivers for many of these factors are generally well understood, research into geographical setting remains limited. Failing to account for the clustering of individuals will result in biased model parameters because people in the same areas are likely to be more similar than those from different areas This means that standard errors will all be underestimated as study participants (observations) are not independent.[20] do they experience the same area, but they are likely to have been subject to similar socioeconomic and demographic sorting mechanisms which cause the non-random distribution of individuals across space. To overcome this limitation, we propose a multilevel modelling approach that (i) appropriately accounts for the clustering of individuals within geographical areas, and (ii) explicitly investigates variation across residential and school geographical environments. We hypothesize that myopia onset amongst children living in urban or densely populated areas is higher than in those living in rural or sparsely populated areas
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