Table 1 Characteristics of parents in three cities
From: Autism prevalence in China is comparable to Western prevalence
Characteristics | Category | Shenzhen City | Jiamusi City | Jilin City | ||||
|---|---|---|---|---|---|---|---|---|
Number | (%) | Number | (%) | Category | Number | (%) | ||
Mother’s education | Junior high school | 6980 | 33.6 | 6413 | 41.5 | Junior high school | 1522 | 23.7 |
High school | 8316 | 40.0 | 5211 | 33.7 | High school | 2009 | 31.3 | |
College | 4872 | 23.4 | 3373 | 21.8 | College | 2061 | 32.1 | |
Graduate school | 154 | 0.7 | 252 | 1.6 | Graduate | 276 | 4.3 | |
Missing | 479 | 2.3 | 219 | 1.4 | Missing | 552 | 8.6 | |
Father’s education | Junior high school | 4951 | 23.8 | 6092 | 39.4 | Junior high school | 1104 | 17.2 |
High school | 8208 | 39.5 | 5337 | 34.5 | High school | 1900 | 29.6 | |
College | 6604 | 31.8 | 3445 | 22.3 | College | 2408 | 37.5 | |
Graduate school | 374 | 1.8 | 310 | 2.0 | Master or higher | 372 | 5.8 | |
Missing | 665 | 3.2 | 284 | 1.8 | Missing | 636 | 9.9 | |
Mother’s occupation | Government officer | 89 | 0.4 | 438 | 2.8 | Worker or farmer | 1682 | 26.2 |
Company clerk | 6173 | 29.7 | 1858 | 12.0 | Clerk | 1438 | 22.4 | |
Technical staff | 1393 | 21.7 | ||||||
Industry | 1475 | 7.1 | 1806 | 11.7 | Manager | 161 | 2.5 | |
Self-employed | 5461 | 26.3 | 4655 | 30.1 | Own-business | 995 | 15.5 | |
Worker | 1578 | 7.6 | 1354 | 8.6 | Missing | 751 | 11.7 | |
Student | 32 | 0.2 | 7 | 0.1 | ||||
Farmer | 937 | 4.5 | 2032 | 13.1 | ||||
Unemployed | 4002 | 24.1 | 3109 | 20.1 | ||||
Missing | 55 | 0.3 | 209 | 1.4 | ||||
Father’s occupation | Government officer | 293 | 1.4 | 782 | 5.1 | Worker or farmer | 1367 | 21.3 |
Company clerk | 7518 | 36.1 | 1628 | 10.5 | Clerk | 1830 | 28.5 | |
Industry | 1836 | 8.8 | 1634 | 10.6 | Technical staff | 1284 | 20.0 | |
Self-employed | 7617 | 36.6 | 5022 | 32.5 | Manager | 276 | 4.3 | |
Worker | 1690 | 8.1 | 2771 | 17.9 | Own-business | 1021 | 15.9 | |
Missing | 642 | 10.0 | ||||||
Student | 10 | 0.1 | 5 | 0.0 | ||||
Farmer | 588 | 2.8 | 2071 | 13.4 | ||||
Unemployed | 1199 | 5.8 | 1305 | 8.4 | ||||
Missing | 51 | 0.3 | 250 | 1.6 | ||||
Mother’s age | ≤ 24 | 61 | 0.3 | 36 | 0.2 | |||
25–30 | 2552 | 12.3 | 1981 | 12.8 | ||||
31–34 | 11,921 | 57.3 | 8603 | 55.6 | ||||
35–40 | 4816 | 23.2 | 945 | 6.1 | ||||
≥ 40 | 410 | 2.0 | 2 | 0.0 | ||||
Missing | 1042 | 5.0 | 3901 | 25.2 | ||||
Father’s age | ≤ 24 | 32 | 0.2 | 25 | 0.2 | |||
25–30 | 677 | 3.3 | 769 | 5.0 | ||||
31–34 | 10,468 | 50.3 | 10,229 | 66.1 | ||||
35–40 | 7577 | 36.4 | 1589 | 10.3 | ||||
≥ 40 | 985 | 4.7 | 2 | 0.0 | ||||
Missing | 1063 | 5.1 | 3854 | 18.5 | ||||
Income | ≤ 1999 | 829 | 4.0 | 2699 | 17.5 | |||
2000–3999 | 3355 | 16.1 | 5252 | 34.0 | ||||
4000–5999 | 3836 | 18.4 | 3880 | 25.1 | ||||
6000–7999 | 3050 | 14.7 | 1704 | 11.0 | ||||
8000–9999 | 2389 | 11.5 | 569 | 3.7 | ||||
≥ 10,000 | 5399 | 26.0 | 569 | 3.7 | ||||
Missing | 1944 | 9.4 | 795 | 5.1 | ||||