Table 2.
Multivariate logistical regression analysis and model comparison results*
| Variables |
DV: Incidence of myopic symptoms (Yes = 1, No = 0) |
||||||||
|---|---|---|---|---|---|---|---|---|---|
|
Model 1 (Unweighted hours)
|
Model 2 (Near-view weighted hours)
|
Model 3 (Blue-light weighted hours)
|
|||||||
|
OR
|
95% CI
|
P-value
|
OR
|
95% CI
|
P
|
OR
|
95% CI
|
P-value
|
|
| Daily digital device use |
1.25 |
1.21-1.30 |
<0.001 |
1.04 |
1.03-1.05 |
<0.001 |
2.25 |
1.94-2.60 |
<0.001 |
| Psychosocial stress level: | |||||||||
| Stressful |
1.98 |
1.67-2.36 |
<0.001 |
2.03 |
1.71-2.42 |
<0.001 |
2.00 |
1.68-2.37 |
<0.001 |
| Relaxed |
0.64 |
0.50-0.82 |
<0.001 |
0.64 |
0.50-0.82 |
<0.001 |
0.65 |
0.51-0.83 |
0.001 |
| Indifferent |
1 |
1 |
1 |
||||||
| Sex: | |||||||||
| Female |
1.02 |
0.89-1.18 |
0.746 |
1.05 |
0.91-1.21 |
0.507 |
1.03 |
0.90-1.19 |
0.662 |
| Male |
1 |
1 |
1 |
||||||
| Level of study: | |||||||||
| Primary |
1.76 |
1.37-2.24 |
<0.001 |
1.42 |
1.12-1.79 |
0.003 |
1.55 |
1.23-1.97 |
<0.001 |
| Secondary |
1.33 |
1.04-1.70 |
0.022 |
1.42 |
1.11-1.80 |
0.005 |
1.36 |
1.07-1.73 |
0.013 |
| University |
1 |
1 |
1 |
||||||
| Location of residence: | |||||||||
| Rural |
1.06 |
0.87-1.29 |
0.564 |
1.06 |
0.87-1.29 |
0.564 |
1.04 |
0.86-1.27 |
0.679 |
| Urban-rural |
0.78 |
0.60-0.99 |
0.044 |
0.75 |
0.58-0.97 |
0.029 |
0.76 |
0.59-0.99 |
0.039 |
| Urban |
1 |
1 |
1 |
||||||
| Pre-pandemic myopia condition | |||||||||
| Yes |
2.60 |
2.22-3.05 |
<0.001 |
2.75 |
2.34-3.23 |
<0.001 |
2.66 |
2.27-3.13 |
<0.001 |
| No | 1 |
1 |
1 |
||||||
OR – odds ratio, CI – confidence interval, DV – distance vision
*In the second analytic stage, we investigate the association between digital device use, psychosocial stress, and myopia development, after controlling for personal traits and pre-pandemic vision condition leveraging multivariate logistic regression.