Key factors related to happiness and anxiety in Aotearoa New Zealand during the COVID-19 pandemic

The COVID-19 pandemic will undoubtedly be recalled as one of the defining events of the twenty-first century, with preliminary data already demonstrating widespread mental and physical health effects worldwide and throughout Aotearoa New Zealand.^1,2 Given the gravity and potential longevity of these changes, it is crucial our understanding of wellbeing reflects the changing socio-cultural, financial and political post-pandemic climate.

The December 2020 quarter wellbeing supplement of the Household Labour Force Survey (Statistics NZ Tatauranga Aotearoa) saw the addition of happiness and anxiety to the biennial survey, a measure of positive and negative affect and relevant emotional correlates of subjective wellbeing.³ This provides an opportunity to better understand how certain factors may relate to anxiety or decreased happiness, particularly during our current social climate. Such knowledge may prove useful in informing future interventions that are more sensitively tailored to the needs and concerns of our current situation.

With the increasing popularity of social determinant models,⁴ much of Aotearoa’s health research over the past 2 decades has focussed on establishing equity across age, gender, ethnic and socio-economic demographics. However, despite the extensive research this approach has birthed, the relationship between many of these factors and mental wellbeing in Aotearoa has remained poorly understood, with results usually being inconsistent and counterintuitive.

Like almost every developed country, Aotearoa has faced a number of challenges associated with an ageing population.⁵ These challenges were again brought to the forefront with the primary mortality and morbidity burden of COVID-19 placed disproportionately on older populations.⁶ It has also spurred a growing discourse that considers the ways ageing populations are discussed and portrayed, especially in the media.⁷ Previous research reporting the counterintuitive finding that wellbeing improves with age has garnered such attention that the phenomenon has become well-known in popular culture, dubbed “the paradox of ageing”.⁸ While the findings have been replicated, so too have they been critiqued and contradicted, with many outlining that such a pattern should not be considered paradoxical, that no such pattern exists, or indeed that older populations may be less happy and more anxious.^8–12 However, any association is likely a complex one, and thus it is unknown how a pandemic environment has influenced this, or will continue to shape wellbeing in older age. Given the potential long-term physiological and sociological effects that the pandemic may bring, investigating its effects on ageing populations will likely be of increasing importance.^1,13,14

In addition to the direct effects of social isolation, many of the chronic or acute illnesses associated with ageing became more difficult to manage with increased barriers to healthcare and medication throughout lockdowns.^15,16 Ageing is a multifactorial and complex process, influenced by a number of convoluted cultural, psychosocial and physiological interactions.¹⁷ Thus, the full effects of the pandemic on older populations have not yet been fully appreciated. This provides a strong rationale to track the wellbeing of older adult populations throughout, and perhaps beyond, the COVID-19 pandemic.

Physical health status and mental health status are undoubtedly closely intertwined, with numerous bidirectional associations having been previously outlined.¹⁸ Given the links between loneliness, social isolation and the constant threat of nationwide lockdown, the contribution of isolation to happiness and anxiety will likely be particularly prominent in the coming years, especially for communities with lower physical health.¹⁹ Similarly, disabled communities typically record higher rates of social isolation, alongside an increased number of mental health challenges.²⁰ As with elderly populations, stress associated with the management of chronic or acute illness may be amplified by isolations and difficulties accessing healthcare.

Gender difference is perhaps one of the most thoroughly explored topics in mental health fields, with literature—although often conflicting—generally supporting the idea that women experience higher rates of negative affect, such as anxiety or depressive symptoms, and yet are typically happier than men.^21–23 While we are yet to fully understand the impact of COVID-19 on such gender and mental health interactions, preliminary studies have suggested that participants reporting as female have experienced higher rates of distress during the COVID-19 pandemic than male-reporting participants.²⁴ In addition to the existing disparity in anxiety for women, a number of gender-related stressors have been influenced by the pandemic environment, such as increased violence against women and higher mental health risk for peripartum women.^25–27 Some studies have, however, found no difference between genders, and a Netherlands cohort showed women experiencing higher rates of anxiety, but men having higher rates of depression.^28–30 Thus, while gender continues to be a relevant factor in discussions of mental wellbeing, such associations have remained unclear, and we will likely continue to uncover new modifying factors within the post-COVID climate.

A number of socio-economic factors are strongly intertwined with mental wellbeing, with income, housing and employment each contributing significantly to subjective wellbeing.^31–33 Given the nationwide economic and commercial effects of COVID-19, struggles with job security, housing and employment may have contributed even more strongly to anxiety and happiness scores.

Previous studies have also disagreed about the nature of ethnic effects on mental wellbeing, with Māori and Pākehā populations having been contrastingly described as the group with the highest rate of mood disorders.^34,35 Further analysis of what factors may be contributing to feelings of anxiety and happiness may be central in understanding these apparent disagreements within the data, and better appreciating the unique challenges experienced by the different facets of Aotearoa’s increasingly multicultural population. And while we are not yet able to fully appreciate the broad scope of differences between ethnic group responses to the COVID-19 pandemic, given that socio-economic structure, workforce distribution, likelihood of hospitalisation and perspective on disease and vaccination all differ by ethnicity,^36,37 it is likely that different responses to the pandemic will become more apparent as we move forward.

Finally, trust on both institutional and personal levels have been previously shown to influence feelings of anxiety.^38–39 This has clear relevance to the pandemic’s effects, which were, of course, not solely biomedical, having effected dramatic socio-cultural and political change on a global scale.¹ Trust in the government and in the general populace has become actively discussed and critiqued on a daily basis, which may have influenced how strongly trust contributed to feelings of anxiety and happiness within this dataset. All these factors were considered for their potential association with anxiety and happiness scores in Aotearoa in December 2020.

Methods

Data

We conducted a cross-sectional study to identify the possible contributors to the mental health status of New Zealanders in December 2020. We used the data sample collected in the wellbeing survey, where up to 30,000 responders were contacted from across Aotearoa as part of the Household Labour Force Survey (HLFS).

Regression outcome variables

We conducted two separate analyses on the mental wellbeing outcome variables of happiness and anxiety. The use of two independent models allows us to assess contributing factors to both a positive aspect of mental wellbeing (i.e., happiness, from the answer to the question “How happy were you yesterday?” on a scale of 0–10) and a negative aspect of mental wellbeing (i.e., anxiety, from the answer to the question “How anxious were you yesterday?” on a scale of 0–10) as unvalidated measures of happiness and anxiety. Notably, the study data were collected in the midst of the global COVID-19 pandemic, and thus the results of this observational study taken at a single time point reflect the factors that were related to mental health within Aotearoa amid this pandemic, but at a time where most New Zealanders were able to undergo relatively normal activities under Alert Level 1 (international borders were closed).

Predictor variables

The predictor variables for each of the models constituted the key wellbeing measures provided within the HLFS, including:

• Age (in years)
• Sex (female/male)
• Ethnicity (categorical variables of Pākehā, Māori, Pacific peoples, Asian, MELAA [a combination of 39 ethnic groups] and other, and individuals could have multiple ethnicity identifications)
• Whether someone has been discriminated against in the last 12 months (yes/no/don’t know)
• Physical health (self-rated status: excellent/very good/good/fair/poor/don’t know)
• Whether someone has a disability (yes/no)
• Loneliness (how often someone felt lonely in the last 4 weeks: none of the time/a little of the time/some of the time/most of the time/all of the time/don’t know)
• Employment status (categorical variables of employed or unemployed)
• Financial wellbeing (how well the respondent’s [and partner’s] income meets everyday needs: excellent/very good/good/fair/poor/don’t know)
• Damp housing (does accommodation have no problem, a minor problem or a major problem with dampness or mould: no problem/minor problem/major problem/don’t know)
• Cold housing (does accommodation have no problem, a minor problem or a major problem with heating and/or keeping it warm in winter: no problem/minor problem/major problem/don’t know)
• Parent status (indicator showing whether a person is in a parent role in the household: yes/no)
• Family wellbeing (in general, how is your family doing: 0–10 extremely badly–extremely well)
• Generalised trust (how much respondent trusts most people in New Zealand: 0–10 not at all–completely)
• Trust in parliament (0–10 not at all–completely)
• Trust in the police (0–10 not at all–completely)
• Trust in the health system (0–10 not at all–completely)
• Trust in the media (0–10 not at all–completely)

Modelling

We firstly quantified a full correlation matrix between all variables within the statistical programming software R to assess the associations between the identified factors. Multiple linear regression models were then fit for both anxiety and happiness scores, with each of the predictor variables listed above. Variables were Z-scored prior to entry into the model, such that the magnitude of each of the covariates could be reported and compared.

Significance testing and correction for multiple comparisons

The significance of each of the predictor variables were assessed using a threshold of p <0.05, with additional Bonferroni correction to account for the number of predictors included within the model. Both corrected and uncorrected values are reported, with significance values that survive only the uncorrected threshold labelled as exploratory results.

Results

The respondents to the wellbeing supplement of the HLFS in December 2020 totalled 12,465. All counts below 6 have been suppressed, and randomly rounded to a base of three according to the output rules of Statistics New Zealand, to maintain data confidentiality. A summary of the data is provided in Tables 1 and 2.

View Table 1–4, Figure 1.

Correlations

Greater anxiety scores were found to be most strongly related to smaller happiness scores, greater loneliness, poorer physical health, poorer family wellbeing and poorer financial wellbeing. Alongside a negative correlation between happiness and anxiety, greater happiness scores were found to be most strongly related to greater family wellbeing, greater physical health, smaller loneliness scores, greater financial wellbeing, and greater generalised trust, trust in the police and trust in the health system. A depiction of the full correlation matrix results is presented in Figure 1, and R and p-values can be found in the Appendices.

Anxiety regression

The variables most strongly associated with self-reported anxiety using multiple linear regression were age, sex (female), discrimination, poor physical health, loneliness, unemployment status, poorer financial wellbeing and poorer family wellbeing. Other significant but more weakly associated variables include disability, damp housing, playing a parental role, less trust in the police and more trust in the media. While participants who identified as Māori or Other were associated with a p-value <0.05, these did not survive Bonferroni correction for multiple comparisons. The complete list of regression parameters is provided in Table 3.

Happiness regression

The variables most strongly associated with self-reported happiness using multiple linear regression were age, ethnicity (Māori and Pacific peoples), financial wellbeing and family wellbeing. Greater levels of generalised trust, trust in the police and trust in the health system also correlated with greater happiness scores. Contrastingly, poor physical health, being a parent and both being employed or unemployed (as opposed to not in the labour force, such as retired populations) were related to lower reports of happiness. Weaker associations were found between happiness, recording sex as female, lower reported discrimination and being without a disability. A full list of results is provided in Table 4.

Discussion

Here we investigated the relationships between anxiety and happiness with a host of social, physical, financial and mental health variables in Aotearoa, in the midst of the COVID-19 pandemic (December 2020). As expected, happiness and anxiety were inversely related, and shared a number of contributing variables. Loneliness, physical health, family wellbeing, financial wellbeing, age and gender all had associations with both anxiety and happiness. Furthermore, these results provide a platform for future longitudinal studies that may gauge social progressions in equity and wellbeing for Aotearoa.

Aligning with previous literature, older adults reported higher levels of happiness and lower levels of anxiety.^40,41 One leading hypothesis suggests that mental wellbeing in older adults may be more intrinsically generated rather than dependent on specific extrinsic stimuli, with greater emotional control possibly adaptive in combating the physical and social challenges of ageing.⁴² Such a perspective may explain why, despite the added and disproportionate stress COVID-19 placed on older populations, better mental wellbeing was still observed. This was supported by the regression analysis, with higher happiness and lower anxiety scores associated with age that persisted beyond the exclusion of employment status, financial wellbeing and a number of other extrinsic contributors to mental wellbeing. Additionally, the results also accounted for many of the potential insults to mental wellbeing in older adults, including loneliness, physical health and discrimination. Useful future research might include monitoring changes within populations reaching older age in a post-pandemic environment.

Our gender analyses also supported previous literature, with women reporting higher rates of anxiety,⁴³ with gender being one of the main associated factors in the anxiety regression. However, being female was also weakly associated with greater happiness in the regression analysis. It is unclear how this was influenced by the pandemic, however, due to the pandemic’s known effects on gender-related inequities such as violence, perinatal mental illness and employment.^25–27 It should also be noted that this study was restricted to a binary view of gender and therefore may not appreciate the full scope of mental wellbeing within non-binary populations.

One of the most prominent factors associated with both anxiety and happiness was physical health. This coincides with previous findings demonstrating links between mental and physical wellbeing, with many concluding that this relationship is likely complex and bidirectional.⁴⁴ It is also possible that the links between physical and mental health may have been intensified by COVID-19’s particular threat to populations with poor physical health, potentially exacerbating this relationship further.

Loneliness, both during and before the pandemic, has been clearly associated with higher anxiety and lower happiness.^45,46 This was certainly supported by our results, with loneliness being the factor with the highest association to anxiety, and among the highest (inverse) correlates of happiness. Perhaps counterintuitively, during the pandemic, younger populations were more likely to report high levels of loneliness.⁴⁷ Our data showed similar patterns, with age being inversely associated with loneliness. However, older populations have also seen an increase in loneliness during the pandemic.⁴⁸ The impacts of loneliness predictably affect selective demographics, being correlated with lower financial wellbeing, poorer physical health and disability. Being Pākehā or male was also protective against loneliness; however, these correlations were more subtle. Like with many other factors, while the effects may not be immediately evident, large aspects of social routine have been, and continue to be, disrupted. Evidence has shown such disruptions may have widespread mental and physical health effects, again underscoring the cruciality of monitoring our adjustment to post-pandemic society.⁴⁹

The impacts of financial wellbeing and socio-economic status have been among the most studied areas in the last few decades, spanning a number of disciplines.^50,51 Unsurprisingly, the far-reaching effects of financial wellbeing have been found to contribute to mental wellbeing during pandemic times in a number of countries.^52–54 However, due to the stark differences in healthcare, economic and social welfare systems, it is unknown whether such results are valid when applied internationally and cross-culturally. One study, in fact, observed greater decline in happiness among higher socio-economic groups.⁵⁵ Our results showed financial wellbeing as significantly correlated with happiness and inversely correlated with anxiety. While associations of damp or cold housing status did not survive Bonferroni correction, given the overlap between financial wellbeing and housing quality, much of the socio-economically relevant variance was likely accounted for by the overall financial wellbeing correlate. While employment had a small association with anxiety, unemployment demonstrated a stronger correlation. Contrastingly, employment was associated more strongly with unhappiness during the pandemic than was unemployment, while pre-pandemic studies describe employment as positively associated with happiness.⁵⁶ However, with the turbulent work environment brought on by the pandemic, many were required to work from home and increased burden was often placed on those whose work was deemed essential in Aotearoa. It should be noted, however, that studies from Israel and South Africa have outlined employment as protective against distress and poor mental health.^57,58 This may highlight the need for interventional measures to counteract challenges to mental wellbeing in post-pandemic professional environments.

Family wellbeing was strongly associated with both decreased anxiety and increased happiness, where nationwide household isolations may have further strengthened the impact of family on wellbeing. This association is not specific to pandemic times, with a number of studies outlining a clear association between family wellbeing and overall wellbeing, with many reporting family wellbeing as more important than personal wellbeing.⁵⁹ Poor family wellbeing was also associated with a number of other relevant factors including poor physical health, loneliness and decreased trust in all measured areas.

While no ethnic population findings survived Bonferroni correction in the anxiety regression, it is worth noting that discrimination was among the strongest of anxiety correlates and was correlated with identifying as Māori or Pacific peoples. The other primary correlates of anxiety were poor physical health, poor financial wellbeing, poor family wellbeing and loneliness, each of which was higher in Māori populations. Similarly, higher than average proportions of Pacific populations reported poor physical health and poor financial wellbeing. In contrast, the regression analyses demonstrated that being Māori or Pacific peoples was, in fact, associated with higher happiness scores. As with anxiety, this is after accounting for many ethnically distributed happiness correlates such as the influence of physical health, loneliness and family wellbeing. Interestingly, discrimination, while associated with anxiety, was not significant in its association with happiness after Bonferroni correction. These results highlight that the racial inequalities in mental wellbeing that exist in Aotearoa are likely deeply preventable, and potentially stem from a number of inadequacies within our social, economic and cultural structures.

Furthermore, reports have shown that while Māori, Pākehā and Pacific populations reported similar rates of psychological distress throughout lockdown, recovery after lockdown was decreased in Māori and Pacific communities.⁶⁰ Asian communities, however, reported less psychological distress during lockdown.⁶¹ It is unknown how this may affect contributing factors in happiness and anxiety between ethnic groups; however, if such trends continue, we may see ethnicity as more strongly associated with anxiety and happiness in the coming years, as lagging effects on wellbeing and recovery time become more apparent.

Finally, no measured trust variables showed significant independent associations with anxiety in the regression model. However, higher rates of generalised trust, trust in the police and trust in the health system were all significantly associated with higher levels of happiness. This aligns with past research on trust in Japanese populations, which has demonstrated an association between individual and social trust, and happiness.^38,39 However, trust in parliament and media showed no significant independent association in the current analyses, despite the constant, daily communication from parliament. While media transparency has perhaps never been a more salient issue in this country’s history, it is possible that this effect was accounted for by other significant trust measures.

Conclusion

The COVID-19 pandemic posed a number of novel socio-cultural, psychological and political challenges on a global scale. While much research has been conducted both during and after the pandemic to understand the ramifications of this, there has been limited documentation of how different demographics, attitudes, gender and ethnicity intersected with mental wellbeing in Aotearoa at a time of national crisis. While these cross-sectional analyses can only measure association rather than causation, it is hoped this will provide a valuable snapshot of national wellbeing. Moreover, it will prove valuable to compare this dataset with future trends in data, to aid our understanding of how the social and demographic determinants of mental wellbeing may differ during times of crises, such that future measures can be effectively and sensitively tailored to the needs of different subpopulations within Aotearoa.

View Appendices.