Table 2

Binary logistic regression model coefficients for PMS participation given different sets of covariates (B=coefficient; SE= robust standard error)
Model 1 Model 2 Model 3 Model 4 Model 5
B SE B SE B SE B SE B SE
Covariate
Gender(reference group: female) −0.111 0.207 −0.053 0.211 −0.120 0.216 −0.105 0.207 −0.040 0.219
Age 0.048*** 0.018 0.039** 0.019 0.038** 0.018 0.042** 0.019 0.026 0.019
Residence in Wuhan (reference group: else) 0.670* 0.382 0.642* 0.383 0.630* 0.387 0.775* 0.391 0.706* 0.390
Residence in Suizhou (reference group: else) 1.370*** 0.410 1.413*** 0.415 1.214*** 0.414 1.388*** 0.418 1.288*** 0.423
Residence in Zaoyang (reference group: else) 0.087 0.460 0.190 0.459 −0.055 0.465 0.072 0.469 0.020 0.468
Ethnicity(reference group: non-Han) 0.006 0.537 −0.271 0.520 0.054 0.538 −0.121 0.602 −0.117 0.605
Profession is leader (reference group: common clerks) −0.115 0.213 −0.168 0.219 −0.165 0.221 −0.076 0.219 −0.135 0.228
Profession is scientist or teacher (reference group: common clerks) 0.388* 0.276 0.257 0.278 0.302 0.288 0.383 0.283 0.198 0.293
Profession is farmer (reference group: common clerks) −0.929* 0.671 −0.737 0.663 −0.845 0.709 −0.756 0.691 −0.712 0.744
Education −0.037 0.101 −0.091 0.104 −0.155 0.105 −0.067 0.102 −0.189* 0.107
Monthly income −0.066 0.110 −0.042 0.111 −0.067 0.114 −0.087 0.109 −0.75 0.113
Independent variable
Awareness of premarital screening 2.804*** 1.047 2.346** 1.050
Awareness of the free and voluntary mode 0.634*** 0.206 0.463** 0.217
Knowledge level of premarital screening 0.606*** 0.120 0.480*** 0.131
PMS items knowledge score 0.010 0.010 0.006 0.010
Attitude to the necessity of PMS 0.860*** 0.191 0.766*** 0.205
Attitude to the preventive effects of PMS −0.276 0.195 −0.425** 0.206
Pearson Chi-Square 40.686*** 72.967*** 70.279*** 62.731*** 104.195***
−2 Log Likelihood 697.500*** 665.218*** 656.745*** 674.581*** 521.946***
Cox&Snell R-Square 0.069 0.121 0.118 0.105 0.171
N 633 633 633 633 633

Wang et al.

Wang et al. BMC Public Health 2013 13:217   doi:10.1186/1471-2458-13-217

Open Data