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Table 3 Comparing burden of all-cause mortality due to diabetes with those due to CVD

From: Shadow of diabetes over cardiovascular disease: comparative quantification of population-attributable all-cause and cardiovascular mortality

 

Diabetes

History of CVD

Women

 

Prevalence (%)

17.7

11.4

HR1 (95%CIs)

2.66 (1.83-3.85)

1.47 (0.98-2.20)

Wald χ2

4.65 (P for paired homogeneity test2 = 0.031 )

 

PAHF3 (95%CIs)

11.0 (8.4-13.5)

3.7 (0.0-7.3)

RAP4 (years)

8.6

3.1

Men

 

Prevalence (%)

16.3

9.3

HR1 (95%CIs)

1.81 (1.33-2.46)

1.47 (1.03-2.11)

Wald χ2

1.19 (P for paired homogeneity test2 = 0.275 )

 

PAHF3 (95%CIs)

7.9 (5.3-10.5)

3.0 (0.01-5.7)

RAP4 (years)

7.4

4.3

Total

 

Prevalence (%)

17.1

10.4

HR1 (95%CIs)

2.06 (1.65-2.57)

1.48 (1.15-1.91)

Wald χ2

5.26 (P for paired homogeneity test2 = 0.022 )

 

PAHF3 (95%CIs)

9.2 (7.3-11.1)

3.3 (1.1-5.5)

RAP4 (years)

8.0

3.5

  1. CVD, cardiovascular disease; HR, hazard ratio; PAHF, population-attributable hazard fraction; RAP, rate advancement period.
  2. 1. HRs and their 95% CIs were estimated by implementing the survival proportional hazard (Cox) regression analysis.
  3. 2. Wald tests of the linear hypotheses concerning the Cox survival regression models coefficients (paired homogeneity test) were performed to test the null hypotheses that the hazard ratios (effect size) for prevalent diabetes were equal to those for prevalent CVD [32].
  4. P A H F = h ( t ) − h 1 ( t ) h ( t ) = p ( t ) ( H R t − 1 ) 1 + p ( t ) ( H R t − 1 ) , where p(t) is the proportion exposed to hypertension at time t. We used proportion exposed at baseline, p = p(0).
  5. 4. RAP expresses how much sooner a given mortality rate is reached among exposed than among unexposed individuals [30].