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. 2014 Feb 21;13:36. doi: 10.1186/2251-6581-13-36

Table 1.

Socio-economic predictors of poor subjective health among patients with diabetes in 15 countries

 
B
S.E.
Wald
Sig.
Exp (B)
95% C.I. for EXP (B)
            Lower Upper
China
Female
.183
.028
41.441
<.001
1.201
1.136
1.269
Age
−.016
.001
334.036
<.001
.984
.982
.986
Education
−.211
.016
176.776
<.001
.810
.785
.835
Income
.000
.000
178.850
<.001
1.000
1.000
1.000
Costa Rica
Female
.121
.083
2.116
.146
1.129
.959
1.328
Age
−.014
.004
12.238
<.001
.986
.978
.994
Education
−.378
.068
31.278
<.001
.685
.600
.782
Income
.000
.000
10.246
.001
1.000
1.000
1.000
Puerto Rico
Female
.487
.075
42.085
<.001
1.628
1.405
1.886
Age
−.004
.005
.630
.427
.996
.987
1.005
Education
−.462
.050
85.795
<.001
.630
.572
.695
Income
.000
.000
17.886
<.001
1.000
1.000
1.000
United States
Female
−.105
.082
1.636
.201
.901
.767
1.057
Age
.060
.055
1.198
.274
1.062
.953
1.183
Education
−.517
.102
25.588
<.001
.596
.488
.728
Income
.000
.000
23.914
<.001
1.000
1.000
1.000
Mexico
Female
.105
.080
1.691
.193
1.110
.948
1.300
Age
.016
.005
12.286
<.001
1.016
1.007
1.025
Education
−.305
.054
32.476
<.001
.737
.664
.819
Income
.000
.000
17.668
<.001
1.000
1.000
1.000
Argentina
Female
.363
.155
5.494
.019
1.438
1.061
1.949
Age
−.013
.010
1.718
.190
.987
.967
1.007
Education
−.763
.104
53.394
<.001
.466
.380
.572
Income
.000
.000
2.467
.116
1.000
1.000
1.000
Barbados
Female
.407
.120
11.421
.001
1.502
1.186
1.901
Age
.041
.007
31.863
<.001
1.042
1.027
1.057
Education
−.290
.099
8.624
.003
.748
.617
.908
Income
.000
.000
4.121
.042
1.000
1.000
1.000
Brazil
Female
.040
.090
.192
.661
1.040
.872
1.241
Age
.001
.005
.045
.832
1.001
.991
1.012
Education
−.279
.063
19.373
<.001
.756
.668
.856
Income
.000
.000
17.582
<.001
1.000
1.000
1.000
Chile
Female
.351
.125
7.875
.005
1.421
1.112
1.816
Age
.003
.008
.153
.696
1.003
.988
1.018
Education
−.326
.063
26.812
<.001
.722
.638
.817
Income
.000
.000
.016
.899
1.000
1.000
1.000
Cuba
Female
.531
.103
26.484
<.001
1.701
1.389
2.082
Age
−.005
.006
.623
.430
.995
.983
1.007
Education
−.317
.075
18.155
<.001
.728
.629
.842
Income
.000
.000
1.871
.171
1.000
1.000
1.000
Uruguay
Female
.387
.124
9.774
.002
1.472
1.155
1.876
Age
−.001
.008
.005
.945
.999
.984
1.015
Education
−.404
.070
32.948
<.001
.667
.581
.766
Income
.000
.000
1.744
.187
1.000
1.000
1.000
India
Female
.176
.069
6.487
.011
1.192
1.041
1.364
Age
.047
.003
193.134
<.001
1.048
1.041
1.055
Education
−.213
.041
26.517
<.001
.808
.746
.877
Income
.000
.000
17.654
<.001
1.000
1.000
1.000
Ghana
Female
.263
.105
6.257
.012
1.301
1.059
1.598
Age
.055
.005
135.610
<.001
1.056
1.047
1.066
Education
−.129
.055
5.598
.018
.879
.789
.978
Income
.000
.000
.132
.716
1.000
1.000
1.000
South Africa
Female
.057
.102
.306
.580
1.058
.866
1.293
Age
.025
.005
24.866
<.001
1.025
1.015
1.035
Education
−.061
.034
3.120
.077
.941
.880
1.007
Income
.000
.000
2.535
.111
1.000
1.000
1.000
Russia
Female
.277
.099
7.854
.005
1.319
1.087
1.602
Age
.074
.005
214.090
<.001
1.077
1.067
1.088
Education
−.261
.073
12.717
<.001
.771
.668
.889
Income .000 .000 16.061 <.001 1.000 1.000 1.000