**4. Discussion**

#### *4.1. Prevalence of Life Satisfaction*

Life satisfaction research has typically comprised cross-sectional observational studies correlating various demographic, economic, health, education, social and community, and personality factors with life satisfaction. In this study, we have extended this research to both prevalence and predictors for NZ people. Regarding the prevalence of life satisfaction in the NZ population between 2006–2017, we found small changes over time from a high of 7.61 (*SD* = 1.6) in 2007 to a low of 7.23 (*SD* = 1.73) in 2011 [7]. This result indicates that NZ is consistently higher than the world means reported in the World Happiness Reports across time, for example, from 2006 to 2015, these range from 4.45/10 to 5.3/10 (e.g., see [16,45,46]). Notably, the NZ low of 7.23 reported for 2011 occurs around the time of the significant earthquakes in the major NZ city of Christchurch at the end of 2010 and beginning of 2011. These earthquakes had devastating and ongoing impacts locally and nationally, which not only created immediate illbeing and traumatic impacts in the Christchurch region, but also created stress and anxiety nationally [47]. Also notable in this time period was the Global Financial Crisis (GFC) of 2007–2008 which negatively impacted many New Zealanders through the shrinking of the Gross Domestic Product (GDP) over five consecutive quarters [5]. Unemployment in 2007 was at a record low, but the GFC that followed contributed to the rise in unemployment back to 7% in late 2009 [7]. In sum, while the prevalence of life satisfaction in NZ was higher than the global average [45], there was a small amount of change during the study period in reported life satisfaction, which may be attributed to some extent to the major events that happened in NZ during that time period.

#### *4.2. Predictors of Life Satisfaction*

The existing literature holds mixed results for the relationship between gender and life satisfaction. Various studies reported a range of relationships, including men being more satisfied by a small amount, men and women being about as satisfied, and, as we have here, women being slightly more satisfied with their lives (see [48]). Donovan and Halpern [13] suggested that men may be under-reporting their emotional experiences. Regardless, it is becoming increasingly accepted that women tend to report higher levels of life satisfaction when compared to men of the same age [49]. Although the reasons have not ye<sup>t</sup> been thoroughly explored, the modest "U-shaped" relationship between age and life satisfaction in our results matches what has been found in many studies [13,50].

We found for all groups, across both age and gender, satisfaction with standards of living was the most important predictor of life satisfaction, and satisfaction with household income was the second or third most important predictor. There is most likely a direct relationship between these two variables, as satisfaction with household income is likely to impact satisfaction with standards of living. As can be seen in Figure 6, (objective) household income also seems to impact life satisfaction, especially for those with very low incomes. Studies using similar methodologies demonstrate the same incomerelated findings in a diverse range of nations, including Italy [51] and the United Arab Emirates [52]. The relationship between life satisfaction and income has been well studied, but is complex [53,54]. People from wealthier countries are more satisfied than citizens of poorer countries, and within a country, richer people are more satisfied with life than poorer people [55]. Yet, it appears that relative income matters for life satisfaction, and that habituation occurs as people adjust to levelling up through income brackets [12,56].

We found being married significantly predicted life satisfaction when looking at the whole population. This is in line with existing results for Australasia (and Western nations generally), which usually show that being married is positively associated with life satisfaction, and being divorced, widowed or separated is negatively associated with wellbeing [57]. However, age group analysis revealed that the association between being married and life satisfaction was driven by the older age group. Being married was a significant predictor for females over 40 years old and a significant and important predictor for males in the same age group. However, being married was an insignificant predictor for males and females under 40 years of age.

Education has been associated with life satisfaction, but the majority of the variance can be explained by differences in income, health, and social capital [49]. Life satisfaction is greater amongs<sup>t</sup> people with high physical and mental health, and subjective evaluations of health status are more strongly correlated with subjective wellbeing than objective measures [58]. Our results are in line with these findings. Education was not a significant predictor of life satisfaction, but subjective measures of income satisfaction, health problems, and negative emotions all were, with negative emotions being an important predictor and income satisfaction being the most important. Our more detailed analysis shows that income satisfaction is an important predictor for both age groups for males and females, and that negative experiences are also an important predictor for all groups except females under 40 years of age.

The importance of positive affect for life satisfaction has been stressed by Frederickson [59]. Our results reflect this. Positive experience, which contains items related to positive affect, was a significant predictor of life satisfaction. As shown in Table 4, positive experience was an important predictor of life satisfaction for males and females under 40 years old and males over 40 years old. It is unclear why positive experience was not an important predictor of life satisfaction for females over 40 years old in our study. Despite sex differences in life satisfaction found here and elsewhere, and the obvious differences in experiences and expectations across age groups, very little research has investigated the importance of positive and negative affect for life satisfaction across these different groups [60]. Future research should investigate this aspect in more detail.

In our study, feeling satisfied with city was important for females in both age groups and for men under 40. Perhaps people in these groups find it important to have suitable options for activities outside of their home. Life satisfaction has also been related to environmental factors in NZ. For example, residents with easy access to greenspace in their neighborhood reported higher levels of life satisfaction; however, this effect is nearly eliminated when the person has a high fear of crime in their neighborhood [61]. Feeling safe at night was not predictive of life satisfaction in our study. However, the evidence on the relationship between life satisfaction and with security and safety is somewhat patchy and mixed [49], but several recent studies do find it to be significant, albeit small [62–64].

The importance of satisfaction with living standards and household income, and the strong relationship between income and life satisfaction for the lowest income New Zealanders, suggests that improvements to the average life satisfaction of New Zealanders might be achieved by securing high incomes and standards of living for the worst off in society. While such policies generally require greater governmen<sup>t</sup> intervention, international studies sugges<sup>t</sup> that nations with greater income redistribution and social services have higher life satisfaction [65,66]. The minimum wage in NZ has increased recently, but further policies that increase incomes or living standards for the poorest New Zealanders may be required to address societal issues such as child poverty [67,68]. Alternatively, as the Sovereign study suggested [26], learning to live within your means, regardless of income level, seems to positively impact wellbeing. For example, in the Sovereign study, the odds ratio of having very high wellbeing was 12 times higher for people living within their means compared to people finding it difficult to live with their present income.

#### *4.3. Strengths and Limitations*

Jebb and colleagues noted limitations in studies assessing life satisfaction, including that life satisfaction is a cognitive assessment of happiness, which overlooks that the subjective wellbeing construct also contains positive and negative affect [69]. Instead of including affect in our outcome measure, we assessed positive and negative experiences in the present study (through affective items about emotions and enjoyment). Positive and

negative experiences were found to be important predictors of life satisfaction; so, they were still an important part of the study.

Another potential limitation is that, despite analysing a wide range of variables, the variables could not (even collectively) explain the majority of variance in life satisfaction. Furthermore, small effect sizes were found suggesting that whilst a statistical relationship was significant, the real-world impact of these findings may be small. This is to be expected. Previous research demonstrates the important contributions of genetics, behaviour, and personality to life satisfaction (e.g., see [70,71]). In the current study, we used demographic and other variables that are more closely related to the levers of policy in order to provide insights that are potentially useful for the generation of wellbeing policy recommendations. Further exploration of the relationships between income, satisfaction with income, and life satisfaction, as well as an individual's relationships to and perceptions of income remain a future research opportunity.
