Table 3.
Income | All-cause mortality | |||||||
---|---|---|---|---|---|---|---|---|
Absolute inequality | Relative inequality | Absolute inequality | Relative inequality | |||||
Men | Women | Men | Women | Men | Women | Men | Women | |
Belgium | 30.00* | 34.61 | 0.29 | 1.15 | 2.27 | 8.45 | 1.67 | 2.63 |
Denmark | 74.04 | 60.16 | 2.08 | 2.06 | -18.06 | -4.35 | -1.05 | -0.09 |
England&Wales | 101.91* | 88.60*** | 3.08 | 3.16*** | -6.40* | -1.58 | 0.87* | 0.52 |
France | -3.33 | 5.67 | -2.75 | -1.18 | -14.86 | 5.18 | -3.73 | 2.05 |
Slovenia | 6.17 | 2.44 | -4.81 | -2.85 | 8.37 | 8.62 | 5.64*** | 5.00 |
Switzerland | 59.77* | 43.86 | 0.96 | 0.71 | -9.59* | 0.43 | 2.14* | 1.26 |
The annual changes are the slope coefficients from linear regression models of the particular inequality measure on the variable “year”. Statistically significant results are printed in bold, significance levels are *:p < 0.1; **:p < 0.05; ***:p < 0.01. Slopes for relative differences have been multiplied by 100 to make them more legible: 1.0 means that relative inequality changes e.g. from 1.55 to 1.56 in one year. For absolute differences, e.g. a slope of 30.00 means that absolute income inequality increases by US$ 30 per year