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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