Purpose
While the research over the last two years has covered almost all the original aims of the multiple disadvantage work programme, we have yet to formally examine the relationship between multiple disadvantage across the different dimensions of wellbeing and how this impacts on people’s overall sense of wellbeing. To close this gap, this report investigates the relationship between multiple disadvantage and life satisfaction and aims to characterise the nature of that relationship.
Methodology
Two datasets are used in this analysis. These are the 2014 and 2016 waves of the New Zealand General Social Survey (NZGSS). During the early stages of the project consideration was given to including Te Kupenga 2013 and the 2013 Disability Survey in the analysis to achieve a larger total sample size. However, initial exploratory analysis identified that there was not a sufficient range of wellbeing measures in common between Te Kupenga, the Disability Survey and the NZGSS for this to be feasible. While some of the key measures were collected consistently across all surveys (eg life satisfaction), a number of important measures of specific dimensions of disadvantage were available only in the NZGSS.
Key Results
The idea that specific combinations or increasing levels of multiple disadvantage might be associated with particularly severe hardship is an intuitive one. It is easy to imagine how different types of disadvantage might compound each other, resulting in a situation where the total impact is greater than the sum of its parts.
Poor health, for example, might be compounded by social isolation if it prevented a person from seeking medical help or from obtaining support to help them manage their health condition. Similarly, it is easy to find reasons why an increasing number of disadvantages could have a greater-than-linear impact on peoples’ ability to cope (eg Mani et al, 2013).
If the effects of multiple disadvantage were especially severe for particular combinations of disadvantage, this would have important policy implications (Box 3). Specific combinations of disadvantages associated with a larger-than-anticipated impact on peoples’ lives would suggest areas for policy focus and may even provide some insight into the mechanisms contributing to low levels of wellbeing. There is clear evidence of an additive linear effect from each domain of disadvantage and from this perspective, multiple disadvantage is simply the sum of its parts.
Analysis of different combinations of disadvantage yielded some evidence that specific combinations might matter. In particular, poor health combined with either poor housing or a lack of social connection is associated with lower levels of life satisfaction than can be accounted for by the linear impact of the independent disadvantages.
Although the analysis in this paper cannot be considered definitive, these combinations ofdisadvantage present an intuitively appealing story. One important point to consider, however, is that the combined effect of all the combination variables only increases the adjusted R2 from 0.189 to 0.193. The increase is less than 0.4 percent of total variance, indicating that, while it may be important for small groups, the impact of the combinations of disadvantage on life satisfaction should not distract from a primary focus on the additive impact.