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Table 3 Stroke and MI and Its Correlation with Income, Subsample Analysis

From: Disease and disparity in China: a view from stroke and MI disease

 

non-Smoker

ever-Smoker

Excess. Drinker

Seld. Drinker

Non-Drinker

Variables

[1]

[2]

[3]

[4]

[5]

Income

 20~40%

−0.197

− 0.00973

0.0436

− 0.497

−0.186**

 

(−1.273)

(−0.125)

− 0.145

(− 1.246)

(− 2.070)

 40~60%

− 0.368***

− 0.241***

−0.163

− 0.584

−0.532***

 

(− 2.919)

(−2.727)

(− 0.762)

(−1.513)

(− 3.514)

 60~80%

−0.0503

− 0.120

0.122

− 0.183

− 0.311**

 

(− 0.249)

(− 0.827)

−0.323

(− 0.389)

(−2.013)

 80~100%

−0.467*

− 0.300***

0.0774

− 0.272

−0.761***

 

(− 1.949)

(−2.669)

− 0.222

(− 0.690)

(−3.736)

Weighted Obs.

1,002,012,235

592,515,561

447,570,308

341,024,681

942,302,085

 Year

Y

Y

Y

Y

Y

 Fixed Effects

Province

Province

Province

Province

Province

  1. Notes: Robust z-statistics in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1. Regression results were from three-year pooled data. All regressions were controlled for Gender, Rural-Urban status, East, West, and Central regions, Drinking Behavior, Job Type, and Age Groups. Logistic regression results are expressed in the form of natural logarithm odds ratio