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Table 1 Characteristics of respondents

From: Comparison of the measurement properties of the EQ-5D-5L and SF-6Dv2 among overweight and obesity populations in China

Characteristics

Total sample

(N = 1,000)

N (%)

Test-retest sample

(N = 150)

N (%)

P value*

Gender

  

0.215

 Male

520 (52.0%)

85 (56.7%)

 

 Female

480 (48.0%)

65 (43.3%)

 

Age (mean [SD])

51.7 (15.3)

50.6 (15.1)

0.789

Age group (years)

  

0.306

 18–34

174 (17.4%)

28 (18.7%)

 

 35–44

162 (16.2%)

26 (17.3%)

 

 45–54

192 (19.2%)

27 (18.0%)

 

 55–64

179 (17.9%)

34 (22.7%)

 

 ≥ 65

293 (29.3%)

35 (23.3%)

 

Residence (Geographical division)

0.710

 North

184 (18.4%)

25 (16.7%)

 

 Northeast

173 (17.3%)

22 (14.7%)

 

 East

134 (13.4%)

20 (13.3%)

 

 Central

136 (13.6%)

22 (14.7%)

 

 South

96 (9.6%)

20 (13.3%)

 

 Southwest

131 (13.1%)

20 (13.3%)

 

 Northwest

146 (14.6%)

21 (14.0%)

 

BMI (mean [SD])

27.4 (2.8)

27.2 (2.7)

0.814

BMI

  

0.158

 24 ≤ BMI<28

677 (67.7%)

109 (72.7%)

 

 BMI ≥ 28

323 (32.3%)

41 (27.3%)

 

Residence

  

0.602

 Urban area

832 (83.2%)

127 (84.7%)

 

 Rural area

168 (16.8%)

23 (15.3%)

 

Ethnic group

  

0.745

 Han

977 (97.7%)

146 (97.3%)

 

 Minority

23 (2.3%)

4 (2.7%)

 

Education

  

0.207

 Primary or below

196 (19.6%)

22 (14.7%)

 

 Junior high school

312 (31.2%)

43 (28.7%)

 

 Senior high school

338 (33.8%)

58 (38.7%)

 

 College or above

154 (15.4%)

27 (18.0%)

 

Marital status

  

0.037

 Unmarried

81 (8.1%)

20 (13.3%)

 

 Married

890 (89.0%)

126 (84.0%)

 

 Divorced

12 (1.2%)

3 (2.0%)

 

 Widowed

17 (1.7%)

1 (0.7%)

 

Employment status

  

0.988

 Employed

683 (68.3%)

103 (68.7%)

 

 Retired

284 (28.4%)

42 (28.0%)

 

 Student

11 (1.1%)

2 (1.3%)

 

 Unemployed

22 (2.2%)

3 (2.0%)

 

Personal monthly income

  

0.672

 <2000 RMB

70 (7.0%)

11 (7.3%)

 

 2000–5000 RMB

386 (38.6%)

52 (34.7%)

 

 5000–10,000 RMB

444 (44.4%)

69 (46.0%)

 

 >10,000 RMB

100 (10.0%)

18 (12.0%)

 

Basic medical insurance

  

0.750

 Urban employee

811 (81.1%)

125 (83.3%)

 

 Urban and rural resident

174 (17.4%)

23 (15.3%)

 

 No

15 (1.5%)

2 (1.3%)

 

Commercial insurance

  

0.235

 Yes

88 (8.8%)

17 (11.3%)

 

 No

912 (91.2%)

133 (88.7%)

 

Self-report health status

  

0.898

 Poor

167 (16.7%)

24 (16.0%)

 

 General

440 (44.0%)

63 (42.0%)

 

 Good

314 (31.4%)

51 (34.0%)

 

 Very good

79 (7.9%)

12 (8.0%)

 

Hypertension

  

0.969

 Yes

292 (29.2%)

44 (29.3%)

 

 No

708 (70.8%)

106 (70.7%)

 

Diabetes

  

0.608

 Yes

89 (8.9%)

15 (10.0%)

 

 No

911 (91.1%)

135 (90.0%)

 

Hyperlipidemia

  

0.183

 Yes

327 (32.7%)

42 (28.0%)

 

 No

673 (67.3%)

108 (72.0%)

 

Number of chronic diseases

  

0.276

 0

410 (41.0%)

66 (44.0%)

 

 1

182 (18.2%)

22 (14.7%)

 

 2

169 (16.9%)

30 (20.0%)

 

 3

96 (9.6%)

9 (6.0%)

 

 ≥ 4

143 (14.3%)

23 (15.3%)

 

Weight loss therapy

  

0.017

 Yes

231 (23.1%)

46 (30.7%)

 

 No

769 (76.9%)

104 (69.3%)

 

Smoking status

  

0.357

 Never smoked

588 (58.8%)

85 (56.7%)

 

 Used to smoke

239 (23.9%)

33 (22.0%)

 

 Smoking now

173 (17.3%)

32 (21.3%)

 

Drinking status

  

0.188

 Never drink

393 (39.3%)

69 (46.0%)

 

 Used to drink

243 (24.3%)

33 (22.0%)

 

 Drinking now

364 (36.4%)

48 (32.0%)

 

Exercise duration/week

  

0.455

 ≤ 3.5 h

568 (56.8%)

81 (54.0%)

 

 3.5-7.5 h

395 (39.5%)

61 (40.7%)

 

 ≥ 7.5 h

37 (3.7%)

8 (5.3%)

 

Fruit and vegetable intake

0.650

 Rarely intake

174 (17.4%)

30 (20.0%)

 

 Sometimes intake

338 (33.8%)

50 (33.3%)

 

 Often intake

488 (48.8%)

70 (46.7%)

 

High sugar oil food intake

0.935

 Rarely intake

152 (15.2%)

22 (14.7%)

 

 Sometimes intake

473 (47.3%)

73 (48.7%)

 

 Often intake

375 (37.5%)

55 (36.7%)

 

Sleep duration (day)

  

0.077

 < 7 h

579 (57.9%)

77 (51.3%)

 

 ≥ 7 h

421 (42.1%)

73 (48.7%)

 
  1. Note:* difference between subgroups within the same classification; p value significant < 0.05
  2. The difference between scores, characteristics and utility values were tested using the ANOVA for continuous variables and chi-squared test for categorical variables