Table 3.
Multivariate logistic regression analysis
| Variables | Total | Positive for anti-HEV IgG (rate %) | P-value | OR (95% CI) |
|---|---|---|---|---|
| Sex | 0.058* | |||
| Female | 3589 | 189 (5.3) | 1 | |
| Male | 2680 | 111 (4.1) | 0.78 (0.62–1.00) | |
| Ethnic | 0.017* | |||
| Overall | 6269 | 300 (4.8) | 1 | |
| Bai | 60 | 6 (10.0) | 1.67 (0.65–4.29) | |
| Bouyei | 74 | 6 (8.1) | 1.33 (0.52–3.38) | |
| Dong | 74 | 13 (17.6) | 3.21 (1.54–6.67) | |
| Dongxiang | 124 | 2 (1.6) | 0.25 (0.06–1.06) | |
| Gelao | 41 | 4 (9.8) | 1.63 (0.53–4.96) | |
| Han | 2292 | 92 (4.0) | 0.63 (0.39–1.01) | |
| Hui | 846 | 16 (1.9) | 0.29 (0.15–0.56) | |
| Kazakh | 40 | 0 (0.0) | 0.0 | |
| Li | 69 | 3 (4.3) | 0.68 (0.20–2.34) | |
| Man | 118 | 2 (1.7) | 0.26 (0.06–1.12) | |
| Miao | 278 | 34 (12.2) | 2.1 (1.20–3.65) | |
| Mongol | 245 | 4 (1.6) | 0.25 (0.08–0.73) | |
| Monguor | 54 | 4 (7.4) | 1.20 (0.40–3.62) | |
| Others | 161 | 13 (8.1) | 1.32 (0.40–3.62) | |
| She | 26 | 1 (3.85) | 0.60 (0.08–4.64) | |
| Tibetan | 555 | 31 (5.6) | 0.89 (0.51–1.55) | |
| Tujia | 353 | 15 (4.2) | 0.67 (0.34–1.30) | |
| Uighur | 280 | 9 (3.2) | 0.50 (0.23–1.10) | |
| Yao | 56 | 5 (8.9) | 1.47 (0.54–4.05) | |
| Yi | 154 | 17 (11.0) | 1.87 (0.97–3.60) | |
| Zhuang | 369 | 23 (6.2) | 1.00 (0.65–1.48) | |
| Province | 0.00* | |||
| Overall | 6269 | 300 (4.8) | 1 | |
| Anhui | 62 | 2 (3.2) | 0.97 (0.16–8.75) | |
| Chongqing | 223 | 13 (5.8) | 1.85 (0.41–8.46) | |
| Fujian | 67 | 0 (0.0) | 0 | |
| Gansu | 887 | 47 (5.3) | 1.68 (0.40–7.08) | |
| Guangxi | 433 | 29 (6.9) | 2.23 (0.52–9.59) | |
| Guizhou | 516 | 59 (11.4) | 3.87 (0.92–16.26) | |
| Hainan | 101 | 4 (4.0) | 1.24 (0.22–6.96) | |
| Hebei | 118 | 2 (1.7) | 0.52 (0.07–3.76) | |
| Heilongjiang | 119 | 2 (1.7) | 0.51 (0.07–3.73) | |
| Henan | 176 | 2 (1.1) | 0.34 (0.05–2.49) | |
| Hubei | 151 | 7 (4.6) | 1.47 (0.30–7.27) | |
| Hunan | 280 | 12 (4.3) | 1.34 (0.29–6.17) | |
| Inner Mongolia | 291 | 2 (0.7) | 0.21 (0.03–1.50) | |
| Jiangsu | 51 | 3 (5.9) | 1.87 (0.30–11.68) | |
| Jiangxi | 54 | 3 (5.6) | 1.76 (0.28–10.98) | |
| Jilin | 112 | 1 (0.9) | 0.27 (0.02–3.04) | |
| Liaoning | 152 | 4 (2.6) | 0.81 (0.14–4.54) | |
| Ningxia | 341 | 5 (1.5) | 0.45 (0.08–2.35) | |
| Qinghai | 409 | 11 (2.7) | 0.83 (0.18–3.83) | |
| Shaanxi | 118 | 4 (3.4) | 1.05 (0.19–5.91) | |
| Shandong | 104 | 1 (1.0) | 0.29 (0.03–3.28) | |
| Shanxi | 51 | 0 (0.0) | 0.00 | |
| Sichuan | 257 | 26 (10.1) | 3.38 (0.78–14.63) | |
| Others | 82 | 1 (1.2) | 0.37 (0.03–4.18) | |
| Tibet | 231 | 6 (2.6) | 0.80 (0.16–4.06) | |
| Xinjiang | 427 | 15 (3.5) | 1.09 (0.24–4.89) | |
| Yunnan | 399 | 37 (9.3) | 3.06 (0.72–13.06) | |
| Zhejiang | 57 | 1 (1.8) | 0.54 (0.05–6.07) |
*The ORs and 95% confidence intervals (CIs) use multivariate logistic regression analysis
#Others provinces (Beijing: 4, Guangdong: 18, Shanghai: 6, Tianjin: 6 and unknown (not mentioned provincial background detail: 48)