What is the sociodemographic recipe for mental well-being?

Everyone thinks they know who the happiest people in England are: those who are young, rich, well-educated, married, and employed. Perhaps male as well? And white? The opposite of those who are most prone to mental illness.

A recent study set out to examine this assumption and to determine whether the same sociodemographic characteristics that predispose to mental illness also influence mental well-being (Stewart-Brown et al, 2015).

Mental illness is known to be influenced by social gradients, as explored in a previous blog: deprived groups experience higher rates of mental illness.

However, increasingly, we are interested in not just reducing mental illness but increasing mental well-being. ‘Mental well-being’ comes as close to the idea of happiness as formalised public mental health definitions will allow. It extends beyond the simple absence of mental illness and has been described by the WHO as a state in which a person realises their own abilities, copes with the normal stresses of life, works productively and is able to contribute to their community (World Health Organization, 2001).

So which sociodemographic characteristics influence mental well-being?

Young, rich, white, male, well-educated, married, employed. Is this the recipe for happiness?

Methods

The researchers used data collected from 13,983 participants in the 2010 and 2011 Health Surveys for England to examine the relationship between high and low mental well-being, and socioeconomic gradients.

Well-being was measured with the Warwick–Edinburgh Mental Well-being Scale (WEMWBS), a scale that the authors described as well validated and widely used in public health studies. Participants with high mental well-being (top 15^th centile), and low well-being (bottom 15^th centile) were compared to those with middle-range well-being. Low mental well-being as measured by the WEMWBS correlates reasonably well with incidence of depression, for example, the CES-D depression scale (but the authors point out that low mental well-being is not synonymous with mental illness).

The study examined sociodemographic variables already known to associate with rates of mental illness to see their relationship to rates of mental well-being, including:

Age;
Gender;
Ethnicity;
Religion (none, Christian, Muslim, other);
Economic status (employed, unemployed seeking work, retired, economically inactive);
Marital status;
Educational attainment; and
Household income (divided into quintiles).

Logistic regression analyses were used to estimate the independent odds ratios of high and low mental well-being, compared with middle-range mental well-being for the sociodemographic variables listed above.

The authors used logistic regression analyses to estimate odds ratios of high and low mental well-being.

Results

Socioeconomic determinants of low mental well-being

A dose-response trend was observed for both education and equivalised income (both p<0.001 for linear trend). That is, the chance of low mental well-being was increased along with reduced income and reduced educational attainment. Those with no qualification were twice as likely to have low mental well-being as those with a degree. Those in the second lowest income bracket were 40% more likely to have low mental well-being than those in the highest (although those in the lowest income bracket showed no difference to the highest).

People who were unemployed were more likely to have lower mental well-being compared to the employed (odds ratios (OR) = 1.46), while retired people showed no difference to the employed.

35–54 year olds were more likely to have low mental well-being (OR = 1.58) compared to the reference 16-34 year old group.

People with a partner were less likely to have low mental well-being than single people (OR = 0.78)

People of African-Carribean descent were less likely to have lower mental well-being, compared with the reference population of white people (OR = 0.36).

Males and females did not differ on levels of low mental well-being, and religious status also showed no significant effect.

A linear trend was observed with education and equivalised income.

People with a poor education and low income were more likely to have low mental well-being.

Socioeconomic determinants of high mental well-being

The relationships for high mental well-being were not mirror images of those for low mental well-being.

For example, there was no relationship between educational achievement and high mental well-being, with all groups (from no qualification to degree level) showing similar levels of high mental well-being.

There was also no evidence of a dose-response relationship for income and high mental well-being. While those in the highest income bracket were more likely to have high mental well-being than those in lower brackets, the four lowest brackets showed very similar levels of high mental well-being.

Older people (55+) were more likely to have high mental well-being than those younger than them (OR = 1.48), as were those retired (OR = 1.35). There was no difference between the employed and the unemployed.

Gender and religious status had no effect on high mental well-being.

African-Carribeans, Indians and Pakistanis showed higher levels of mental well-being than other groups, largely attributed to increased odds amongst men.

Older retired people were more likely to have high mental well-being.

Discussion

The most striking finding of this study is that the relationship between socio-economic characteristics and low mental well-being is not the inverse of the relationship with high mental well-being.

In particular, while higher educational attainment and increased income was associated with a decreased chance of low mental well-being, it did not have the same relationship with high mental well-being.

These findings seem to support the old adage that money can’t buy happiness (with the proviso that being in the highest income category did increase the likelihood of high mental well-being).

In addition, this data throws into doubt assumptions about the recipe for happiness. Although the relationships in this study are associative rather than causative, it suggests the possibility that increased rates of education may not increase mental well-being.

These findings suggest that a reduction in social inequality may have an effect on rates of low mental well-being, and mental illness, but that different programmes may be needed to improve mental well-being.

This evidence suggests that the socioeconomic factors associated with positive mental health are different from those associated with mental illness.

Conclusions

Several further questions are raised by this study:

If the assumed determinants of mental well-being (education and income) do not play a significant role, which characteristics do influence high mental well-being?
Do interventions aimed to influence modifiable sociodemographic characteristics (like education and income, amongst others) reduce levels of low mental well-being and prevent mental illness? Are such population-level interventions preferable (and comparably cost effective) to the individualised treatment model currently pursued? Clearly, interventional studies of this nature are difficult to conduct compared with individual treatment trials, but such studies may be needed to demonstrate the benefits of reducing social inequality.
Finally, as pointed out by the authors, generally ethnic minorities are targeted when trying to reduce social inequality, but if the finding that these groups demonstrate increased levels of high mental well-being (alongside increased rates of mental illness) are robust, perhaps there are lessons that can be learnt from these groups that can be spread to other groups?

African-Carribean, Indian and Pakistani men showed higher levels of mental well-being than other groups. What’s their secret?

Links

Primary paper

Stewart-Brown S, Samaraweera P, Taggart F, Kandala NB, Stranges S. (2015) Socio-economic gradients and mental health: implications for public health. Br J Psychiatry 2015 206 (6) 461-465; DOI: 10.1192/bjp.bp.114.147280 [Abstract]