Lifestyle and myopia among primary school students in urban areas of Fujian following implementation plan for comprehensive prevention and control of myopia of children and dolescents: a cross-sectional study
关键词
摘要
全文
HIGHLIGHTS
• Adopting AUC to quantify predictive performance of lifestyle factors and demonstrate the association between lifestyle and myopia onset.
• Targeted interventions: Prioritize students with myopic parents (especially biparental myopia) for early screening and structured outdoor programs.
• School policy reforms: Advocate for extended outdoor recess and mandatory daily outdoor time (≥2 hours) to align with national guidelines.
• Conducting longitudinal studies with wearable devices to objectively and precisely measure lifestyle factors to assess the effect of lifestyle on myopia development and progression.
INTRODUCTION
MATERIALS AND METHODS
Participants
Vision Examination
Questionnaire Survey
Quality control
Statistical analysis
RESULTS
Demographic characteristics and Lifestyle
Table 1 Demographic characteristics and lifestyle of the primary school students in Fujian
|
Total
N = 811 |
Myopia
N = 376 |
Non-myopia
N = 435 |
P
|
|
|
Age, year |
9.73±0.48 |
9.67±0.58 |
0.08 |
|
|
Sex |
|
|
|
|
|
Girls |
376(46.4) |
178(47.3) |
198(45.5) |
0.65 |
|
Boys |
435(53.6) |
198(52.7) |
237(54.5) |
|
|
Parental myopia |
|
|
|
<0.001 |
|
None |
330(40.7) |
100(26.6) |
230(52.9) |
|
|
One |
294(36.3) |
147(39.1) |
147(33.8) |
|
|
Both |
187(23.1) |
129(34.3) |
58(13.3) |
|
|
|
|
|
<0.001 |
|
|
Inside classroom |
298(36.7) |
165(43.9) |
133(30.6) |
|
|
Outside classroom |
513(63.3) |
211(56.1) |
302(69.4) |
|
|
Time outdoor, h/d |
|
|
|
<0.001 |
|
1-2 h |
602(74.2) |
302(80.3) |
300(69) |
|
|
2-3 h |
161(19.9) |
62(16.5) |
99(22.8) |
|
|
>3 h |
48(5.9) |
12(3.2) |
36(8.3) |
|
|
Screen time, h/d |
|
|
|
0.27 |
|
<1 h |
471(58.1) |
224(59.6) |
247(56.8) |
|
|
1-2 h |
263(32.4) |
123(32.7) |
140(32.2) |
|
|
>2 h |
77(9.5) |
29(7.7) |
48(11.0) |
|
|
Study time after school, h/d |
|
|
|
0.68 |
|
<2 h |
437(53.9) |
208(55.3) |
229(52.6) |
|
|
2-3 h |
281(34.6) |
128(34) |
153(35.2) |
|
|
>3 h |
93(11.5) |
40(10.6) |
53(12.2) |
|
|
|
|
|
0.94 |
|
|
<8 h |
291(35.9) |
137(36.5) |
154(35.4) |
|
|
8-9 h |
441(54.4) |
202(53.7) |
239(54.9) |
|
|
>9 h |
79(9.7) |
37(9.8) |
42(9.7) |
|
The impact of lifestyle on myopia
Lifestyle-related factors with P-values <0.2 in the univariate logistic regression analyses were further analyzed using multivariate logistic regression. These factors included average daily time spent on outdoor activities, recess outside classroom, and screen time. After adjusting for sex, age and parental myopia, the results demonstrated that engaging in outdoor activity during class recess (OR = 0.646 [95% CI: 0.473-0.881], P = 0.006) and average daily time spent outdoors (2-3 hours: OR = 0.682 [95% CI: 0.466-0.993], P = 0.047; over 3 hours: OR = 0.403 [95% CI: 0.192-0.796], P = 0.01) were independent protective factors against the development of myopia. Additionally, parental myopia emerged as a significant risk factor. Compared to students with neither parent having myopia, students with myopic parents were much more likely myopic (either myopic parent: OR = 2.247 [95% CI: 1.612–3.145], P < 0.001); both myopic parents: (OR = 4.824 [95% CI: 3.262–7.204], P < 0.001) (Table 3).
Table 2 Association between myopia and each factor of lifestyle among primary school students using univariate logistic regression
|
Lifestyle |
OR [95%CI] |
P value |
|
Class recess |
|
|
|
Inside classroom |
1 |
|
|
Outside classroom |
0.614[0.451, 0.835] |
0.002 |
|
Time outdoor, h/d |
|
|
|
1-2 h |
1 |
|
|
2-3 h |
0.643[0.441, 0.932] |
0.02 |
|
>3 h |
0.379[0.182, 0.739] |
0.006 |
|
Screen time, h/d |
|
|
|
<1 h |
1 |
|
|
1-2 h |
0.99[0.721, 1.363] |
0.96 |
|
>2 h |
0.683[0.399, 1.152] |
0.16 |
|
|
|
|
|
<2 h |
1 |
|
|
2-3 h |
0.935[0.682, 1.283] |
0.68 |
|
>3 h |
0.831[0.513, 1.338] |
0.45 |
|
Sleep duration, h/d |
|
|
|
<8 h |
1.023[0.747, 1.400] |
0.89 |
|
8-9 h |
1 |
|
|
>9 h |
1.151[0.690, 1.915] |
0.59 |
Logistic regression adjusted for sex, age and parental myopia.
OR, Odds Ratio;CI, confidence interval; h, hour.
Table 3 Association between myopia and lifestyle among primary school students using multivariate logistic regression
|
Variable |
OR [95%CI] |
P value |
|
Age, year |
1.314[0.995, 1.740] |
0.06 |
|
Sex |
|
|
|
Girls |
1 |
|
|
Boys |
0.966[0.714, 1.308] |
0.82 |
|
Parental myopia |
|
|
|
Neither |
1 |
|
|
One |
2.247[1.612, 3.145] |
<0.001 |
|
Both |
4.824[3.262, 7.204] |
<0.001 |
|
Class recess |
|
|
|
Inside classroom |
1 |
|
|
Outside classroom |
0.646[0.473, 0.881] |
0.006 |
|
Time outdoor, h/d |
|
|
|
1-2 h |
1 |
|
|
2-3 h |
0.682[0.466, 0.993] |
0.047 |
|
>3 h |
0.403[0.192, 0.796] |
0.01 |
|
Screen time, h/d |
|
|
|
<1 h |
1 |
|
|
1-2 h |
1.022[0.741, 1.409] |
0.90 |
|
>2 h |
0.739[0.427, 1.258] |
0.27 |
OR, Odds Ratio;CI, confidence interval; h, hour.
Lifestyle improved myopia prediction capacity
Figure 1 ROC curve plot of myopia prediction using lifestyle