The different results between the current study and previous studies may be due to differences in the LE concentration (0.2% versus 0.5 or 0.95%) and the reactive oxygen species inhibitor (vitamin E analogue tiron versus vitamin C) [ 17, 25].
Additionally, we investigated whether there were gender-based differences in the association between LEs and HRQoL [ 28]; and whether desirable and undesirable events and those which occurred within the family context versus extra-family impacted differently on HRQoL.
We had anticipated that no gender differences in the association between LEs and HRQoL would be found, and that undesirable events and those related to family life would be more strongly associated with HRQoL[ 3, 4, 27].
We tested gender differences in the association between LEs on HRQoL by running similar models where the gender and the interaction between gender and LCU scores were included and evaluating the significance of the interaction effect with a two-sided significance test at α = 0.05.
It also measures, for the first time, the differences in the reduction of LE of persons who have diabetes mellitus or myocardial infarction for different income groups.
As we are only interested in relative differences in LE between the different groups studied, we for simplicity ignore the bias for the statistical analysis.
The study also provides important new information by addressing a public health topic rarely discussed to date, i.e. the socio-economic differences in the relative reduction of LE of people who have diabetes mellitus or myocardial infarction.
Looking at the differences in LE at birth between the two methods (SIR GWM), the Chinese group shows the largest discrepancy with 3.9 years (men) and 2.7 years (women) whilst for the White British group, the two methods lead to the same LE.
While the differences in LE among different social groups are a measure of health inequalities within a country, the LE gap within disease groups represents a possible measure of health inequalities within a health care system.
We use the MONICA/KORA dataset to explore and quantify first the socio-economic differences in LE and then the impact of diabetes and myocardial infarction on LE of people belonging to different socio-economic groups.
