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. 2016 Aug 30;11(8):e0161999. doi: 10.1371/journal.pone.0161999

Table 3. Factors associated with WCRB for ESCC-risk behaviors and poor hygiene, 2013*.

Variable WCRB for ESCC-risk behavior a WCRB for poor hygiene
N = 233 (%) b Univariate OR c Multivariate OR c N = 381 (%) Univariate OR Multivariate OR
Age (continuous) - 0.98 (0.96–1.01) 0.99 (0.96–1.01) - 0.99 (0.97–1.01) 0.99 (0.97–1.02)
Gender
    Female 66 (28.3) Ref Ref 258 (67.7) Ref Ref
    Male 167 (71.7) 0.71 (0.40–1.29) 0.81 (0.42–1.55) 123 (32.3) 1.14 (0.73–1.77) 0.89 (0.54–1.46)
SES
    Low 24 (10.3) Ref NA 43 (11.3) Ref Ref
    Middle 165 (70.8) 0.77 (0.31–1.90) NA 303 (79.5) 1.69 (0.89–3.21) 1.46 (0.74–2.86)
    High 33 (14.2) 0.85 (0.29–2.51) NA 25 (6.6) 4.19 (1.33–13.21) 3.31 (0.97–11.26)
    Unknown 11 (4.7) - - 10 (2.6) - -
Exposure of risky behavior
    Low 138 (59.2) Ref Ref 165 (43.3) Ref Ref
    High 95 (40.8) 0.35 (0.20–0.61) 0.38 (0.21–0.68) 211 (55.4) 0.54 (0.35–0.82) 0.54 (0.33–0.87)
    Unknown 0 (0) - - 5 (1.3) - -
Previously diagnosed diseases
    No 105 (45.1) Ref NA 212 (55.6) Ref NA
    Yes 128 (54.9) 0.73 (0.42–1.27) NA 169 (44.4) 0.83 (0.55–1.26) NA
Score on the “Faith in People” Scale
    0–2 148 (63.5) Ref Ref 247 (64.8) Ref Ref
    3–5 85 (36.5) 0.70 (0.40–1.23) 0.62 (0.34–1.11) 134 (35.2) 0.58 (0.38–0.89) 0.51 (0.32–0.81)
Behavioral change of surrounding people
    No 135 (57.9) Ref Ref 268 (70.3) Ref Ref
    Yes 98(42.1) 1.63 (0.93–2.87) 1.71 (0.95–3.07) 113 (29.7) 2.47 (1.50–4.05) 2.25 (1.32–3.81)
Family history of ESCC
    No 182 (78.1) Ref NA 296 (77.7) Ref NA
    Yes 51 (21.9) 0.77 (0.40–1.51) NA 85 (22.3) 0.78 (0.48–1.28) NA

* Among 410 participants who were engaged in the behavior. The backward-selection method with a significance threshold of 0.1 was used to identify variables included in the final multivariate models. Confidence intervals that do not overlap the null value of 1 were shown in bold.

a ESCC-risk behavior included smoking, alcohol consumption and risky dietary behavior.

b One participant might contribute to multiple observations in these frequencies.

c The GEE logistic-regression model was used.