Social Well-being Predictors of Positive Mental Health in the Irish Adult Population
- Van Lente, E.1, Barry, M. M.1, Molcho M.1, on behalf of the SLÁN 2007 consortium2
- Health Promotion Research Centre, Department of Health Promotion, National University of Ireland, Galway
- PIs – RCSI (Professor H. McGee), NUIG (Professor M. Barry), UCC (Professor I. Perry), ESRI (Dr. D. Watson). Funding: Department of Health & Children.
- With the exception of community involvement, coefficients and odds ratios were weaker for socio-demographic variables than for social well-being variables.
- Men were more likely to experience higher levels of energy and vitality, with women being more than a third less likely to be in the top 5% of scores.
- Age only seems to matter for predicting the highest levels of energy and vitality, which tend to be among those aged 18-29.
- Other than gender, age, and residential location, being in the top 5% is not associated with other socio-demographic variables. On the other hand, in the linear regression model, education, medical card status and employment (but not residential location) are significant predictors.
- Predictors of mental health problems have been extensively reported, but fewer studies have examined predictors of positive mental health (e.g. Barry & Friedli, 2008; Keyes 2005) at a population level. The SLÁN 2007 survey of lifestyle, attitudes and nutrition (see e.g. Barry, Van Lente, Molcho et al., 2009; Morgan et al., 2007) provides an opportunity to establish predictors of positive mental health in the Irish population. The aims of this study are to examine the relationships between positive mental health and social well-being variables in general, and specifically for those with very high levels of positive mental health.
- Low levels of loneliness, high social support and fewer neighbourhood problems emerge as being protective of positive mental health. While the highest levels of energy and vitality are less associated with socio-demographic variables, the relationship with these social well-being variables is consistent in both models.
- These findings point to the need for policy-level interventions that address the social-determinants of mental health, as well as the more individual-level determinants (see e.g. DOHC, 2006). In particular - policy that leads to reductions in levels of loneliness, increases in social support and reductions in problems in the neighbourhood may lead to increases in positive mental health, even at the highest levels. Policy promoting community involvement may also increase positive mental health.
- Further refinement of measures of positive mental health in the general population is required (e.g. Bartlett, 1998) in order to examine the determinants of positive mental health among different population groups and the nature of their relationship to other indicators of health and well-being.
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- In both linear (Table 1) and logistic regression (Table 2) models, (poor) social support, loneliness and neighbourhood problems were significant predictors of energy and vitality. Coefficients and odds ratios were highest for loneliness, followed by (poor) social support. A respondent who is lonely is about a third as likely to be in the top 5% of energy and vitality scores, whereas a respondent who has poor social support is less than half as likely.
- Community involvement was not significant predictor of the top 5% of energy and vitality scores. It was also the weakest social well-being predictor in the linear model.