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Table 2 Factors associated with the awareness status of syphilis knowledge in logistic regression analysis

From: Poor awareness of syphilis prevention and treatment knowledge among six different populations in south China

 

Number of participants

Awareness of syphilis knowledge

ORu

(95 % CI)

ORm

(95 % CI) a

Frequency

%

Population

 Urban residents

665

435

65.4

1.00

 

1.00

 

 Factory workers

679

380

56.0

0.67

(0.54–0.84)***

1.08

(0.84–1.39)

 College students

718

371

51.7

0.57

(0.46–0.70)***

0.45

(0.32–0.64)***

 Pregnant women

683

451

66.0

1.03

(0.82–1.29)

0.99

(0.76–1.29)

 FSWs

371

200

53.9

0.62

(0.48–0.80)***

1.38

(1.02–1.88)*

 MSM

354

287

81.1

2.26

(1.66–3.09)***

1.59

(1.13–2.24)**

Age (years)

  ≤ 20

686

346

50.4

1.00

 

1.00

 

 21–25

884

468

52.9

1.11

(0.91–1.35)

1.03

(0.82–1.30)

 26–30

846

582

68.8

2.17

(1.76–2.67)***

1.76

(1.33–2.33)***

 31–35

452

314

69.5

2.24

(1.74–2.87)***

1.79

(1.31–2.45)***

  > 35

602

414

68.8

2.16

(1.72–2.72)***

1.64

(1.20–2.25)**

Gender

 Male

1289

880

68.3

1.00

 

1.00

 

 Female

2181

1244

57.0

0.62

(0.53–0.71)***

0.64

(0.54–0.77)***

Ethnicity

 Han

3307

2022

61.1

1.00

   

 Others

163

102

62.6

1.06

(0.77-1.47)

  

Education

 Junior middle school or lower

1042

542

52.0

1.00

 

1.00

 

 Senior middle school

939

613

65.3

1.73

(1.45–2.08)***

1.67

(1.38-2.02)***

 College or above

1489

969

65.1

1.72

(1.46–2.02)***

2.66

(2.07-3.42)***

Hukou

 Shenzhen

839

572

68.2

1.00

   

 Other cities in Guangdong province

936

543

58.0

0.64

(0.53–0.78)***

0.79

(0.64–0.97)*

 Other provinces in China

1645

970

59.0

0.67

(0.56–0.80)***

0.67

(0.54–0.84)***

 Hong Kong, Macao, and Taiwan

50

39

78.0

1.65

(0.83–3.28)

1.10

(0.53–2.29)

  1. CI Confidential interval, OR u odds ratio in univariate analysis, OR m odds ratio in multivariate logistic regression
  2. *p < 0.05; **p < 0.01; ***p < 0.001
  3. aAll the variables with p < 0.05 in univariate analysis were selected stepwise via a forward method, to be entered into the multivariate logistic regression model