Development of a nomogram for predicting myopia risk among school-age children: a case-control study

Figures & data

Table 1. Baseline characteristics of participants (n = 3512).

Variables	Non-myopia (n = 1734)	Myopia (n = 1778)	Test statistic	p
Age, $\overline{x}\pm s$ (years)	8.5 ± 1.85	10.24 ± 2.24	t = −25.191	<0.001
Sex, n (%)
Male	1007 (51.9)	932 (48.10)	χ^2= 11.354	0.001
Female	727 (46.2)	846 (53.8)
BMI, $\overline{x}\pm s$	17.84 ± 6.08	19.81 ± 27.11	χ^2= −3.001	0.003
PM, n (%)
No	1205 (51.2)	1149 (48.8)	χ^2= 9.418	0.002
Yes	529 (45.7)	629 (54.3)
MM, n (%)
No	1143 (53.2)	1004 (46.8)	χ^2= 32.987	<0.001
Yes	591 (43.3)	774 (56.7)
PI, n (%)
No	984 (50.4)	968 (49.6)	χ^2= 1.888	0.169
Yes	750 (48.1)	810 (51.9)
Breast feeding, n (%)
Yes	919 (50.5)	900 (49.5)	χ^2= 1.992	0.158
No	815 (48.1)	878 (51.9)
CMI, n (%)
≥10,000 yuan	856 (51.9)	793 (48.1)	χ^2= 8.002	0.005
<10,000 yuan	878 (47.1)	985 (52.9)
LAP, n (%)
≥20 m^2	1103 (49.7)	1115 (50.3)	χ^2= 0.305	0.581
<20 m^2	631 (48.8)	663 (51.2)
SER, $\overline{x}\pm s$ (D)	−0.04 ± 0.94	−2.15 ± 1.59	t = 48.011	<0.001

BMI, body mass index; PM, paternal myopia; MM, maternal myopia; PI, premature infant; CMI, per capita monthly income; LAP, living area per person; SER, spherical equivalent refraction; D, dioptre; $\overline{x}\pm s$, mean ± standard deviation.

Table 2. Behaviour characteristics of participants (n = 3512).

Variables	Non-myopia (n = 1734)	Myopia (n = 1778)	χ^2	p
SB, n (%)
<3 time/week	287 (52.9)	256 (47.1)	3.114	0.078
≥3 time/week	1447 (49.4)	1522 (51.3)
Sweet food, n (%)
<3 time/week	87 (50.0)	87 (50.0)	0.029	0.865
≥3 time/week	1647 (49.3)	1691 (50.7)
FF, n (%)
<3 time/week	237 (52.9)	211 (47.1)	2.557	0.110
≥3 time/week	1497 (48.9)	1567 (51.1)
Fruit, n (%)
≥3 time/week	1217 (51)	1168 (49)	8.131	0.004
<3 time/week	517 (45.9)	610 (54.1)
Vegetable, n (%)
≥3 time/week	1258 (50.1)	1255 (49.9)	1.664	0.197
<3 time/week	475 (47.6)	523 (52.4)
SD, n (%)
≥9 h	801 (55.6)	640 (44.4)	37.735	<0.001
<9 h	933 (45.1)	1138 (54.9)
PRW, n (%)
Correct	723 (54.6)	601 (45.4)	23.288	<0.001
Incorrect	1011 (46.2)	1177 (53.8)

SB, sugared beverages; FF, fried food; SD, sleep duration; PRW, posture during reading and writing.

Table 3. Biometric parameters of the eye of participants (n = 3512).

Variables	Non-myopia (n = 1734)	Myopia (n = 1778)	t	p
AL, mm ($\overline{x}\pm s$)	23.24 ± 0.79	24.27 ± 1.05	−33.029	<0.001
CCT, um ($\overline{x}\pm s$)	549.77 ± 32.38	551.84 ± 32.53	−1.883	0.06
AD, mm ($\overline{x}\pm s$)	3.05 ± 0.25	3.23 ± 0.26	−20.195	<0.001
CR, mm ($\overline{x}\pm s$)	7.87 ± 0.32	7.85 ± 0.30	1.910	0.028

AL, axial length; CCT, Central corneal thickness; AD, anterior chamber depth; CR, corneal radius; $\overline{x}\pm s$, mean ± standard deviation.

Table 4. Collinear diagnosis of the independent variables (n = 3512).

Variables	Tolerance	Variance inflation factor
Age	0.686	1.459
Sex	0.907	1.103
MM	0.966	1.035
PRW	0.985	1.015
AL	0.515	1.941
CR	0.734	1.362

MM, maternal myopia; PRW, posture during reading and writing; AL, axial length; CR, corneal radius.

Table 5. Multivariate logistic regression analysis of risk factors for myopia among school-age children (n = 3512).

Variables	β	Standard error	Wald χ^2	p	OR (95% CI)
Age	0.151	0.024	40.606	<0.001	1.164 (1.111–1.219)
Sex	0.877	0.093	88.355	<0.001	2.405 (2.003–2.887)
MM	0.286	0.090	9.972	0.002	1.331 (1.114–1.589)
PRW	0.250	0.089	7.859	0.005	1.283 (1.078–1.528)
AL	1.957	0.081	590.644	<0.001	7.708 (6.044–8.288)
CR	−3.313	0.185	322.269	<0.001	0.036 (0.025–0.052)

OR, odds rate; CI, confidence interval; MM, maternal myopia; PRW, posture during reading and writing; AL, axial length; CR, corneal radius.

Figure 1. Nomogram for predicting the risk of myopia. MM, maternal myopia; PRW, posture during reading and writing; AL, axial length; CR, corneal radius. For sex, 0 = male and 1 = female; For MM, 0 = no and 1 = yes; For PRW, 0 = correct and 1 = incorrect.

Figure 2. Verification of nomogram for predicting the risk of myopia. (A) ROC curve of nomogram. (B) Calibration curve of nomogram. (C) DCA curve of nomogram. ROC, receiver operating characteristic; DCA, decision curve analysis; AUC, area under the curve.

Data availability statement

All data supporting the results reported in this study are available from the corresponding author upon request.