Scatterplots of SER at Phase 1 versus SER at Phase 3 for the younger and older cohorts respectively.

<p>Data are grouped into refractive classifications as illustrated in the key. The gray boxes indicate participants who became myopic (younger cohort n = 27; older cohort n = 8) or lost their hyperopia (younger cohort n = 20; older cohort n = 4) between Phase 1 and 3. The dashed lines represent the myopia cut-off point of -0.50D or less and the dotted line represents the hyperopia cut-off of +2.00D or greater. The solid black line represents unity- those falling below the line are showing a myopic change in SER.</p

Flow diagram describing participant contactability, recruitment and exclusion from Phase 1 to Phase 3.

<p>Flow diagram describing participant contactability, recruitment and exclusion from Phase 1 to Phase 3.</p

Distribution of spherical equivalent refractive errors in 6–7 year old children within the NICER study Phase 1 (2006–2008) and 6–7 year old children from Sorsby <i>et al</i>.[14].

<p>Data points represent a one dioptre interval (for example, the % of participants represented at point 0 on the x-axis have an SER of less than or equal to 0DS but greater than -1 DS. Data points at the extremes of the x-axis represent participants with SER of greater than or equal to +5DS or less than or equal to -5DS.</p

Comparison of refractive error prevalence in the UK (NICER Study) to Australia (SMS/SAVES) at baseline and 5–6 year follow-up.

<p>The brackets show the statistical comparisons of the proportions of myopes between the two studies; black indicates statistically significant difference, gray indicates no statistically significant difference (Two sample test of proportion).</p

Comparison of UK refractive error distribution between 1950’s-1960’s (Sorsby study) and 2006–2014 (NICER study) at baseline and follow-up.

<p>The brackets indicate the statistical comparisons of the proportions of myopes between the two studies; black indicates statistically significant difference, gray indicates no statistically significant difference (Two sample test of proportion).</p

ROC curves: use of uncorrected visual acuity (LogMAR) to detect significant refractive error.

<p>ROC curves: use of uncorrected visual acuity (LogMAR) to detect significant refractive error.</p

Sensitivity and specificity of an uncorrected visual acuity cut-off of poorer than 0.20logMAR to detect different refractive conditions (right eye data).

*<p>n = 1.</p

The prevalence of significant refractive error, myopia, hyperopia and astigmatism.

<p> <i>CIs: Confidence Intervals.</i></p><p> <i>n = number of cases of specified refractive error.</i></p

ROC curves: use of uncorrected visual acuity (LogMAR) to detect astigmatism.

<p>ROC curves: use of uncorrected visual acuity (LogMAR) to detect astigmatism.</p

Optimal cut-off points for uncorrected visual acuity (LogMAR) to detect different refractive conditions.

*<p>n = 1.</p