Mental well-being of the general population: direct and indirect effects of socioeconomic, relational and health factors

Abstract

Purpose: The aim of this study was to analyse the association between individual mental well-being and social, economic, lifestyle and health factors.

Methods: Cross-sectional study on a representative sample of 13,632 participants (> 15y/o) from the Catalan Health Interview Survey 2013-2016 editions. Mental well-being was assessed with the Warwick-Edinburg Mental Well-being Scale (WEMWBS). Linear regressions were fitted to associate well-being and sociodemographic, relational, lifestyle and health variables according to minimally sufficient adjustment sets identified using directed acyclic graphs. Predictors entered the model in blocks of variable types and analysed individually. Direct and total effects were estimated.

Results: Health factors significantly contributed to mental well-being variance. Presence of a mental disorder and self-reported health had the largest effect size (eta² = 13.4% and 16.3%). The higher individual impact from a variable came from social support (β = - 12.8, SE = 0.48, eta² = 6.3%). A noticeable effect gradient (eta² = 4.2%) from low to high mental well-being emerged according to economic difficulties (from β = 1.59, SE = 0.33 for moderate difficulties to β = 6.02 SE = 0.55 for no difficulties). Younger age (β = 5.21, SE = 0.26, eta² = 3.4%) and being men (β = 1.32, SE = 0.15, eta² = 0.6%) were associated with better mental well-being. Direct gender effects were negligible.

Conclusions: This study highlights health and social support as the most associated factors with individual mental well-being over socioeconomic factors. Interventions and policies aimed to these factors for health promotion would improve population mental well-being.

Keywords: Directed acyclic graphs; Health determinants; Health survey; Mental health; WEMWBS; Well-being.

Fig. 1

Directed acyclic graph (DAG-1). Variable names are abbreviated: origin country of origin; education educational level; work employment status; income family economic difficulties; BMI body mass index; smoke smoking status; sleep hours of sleep; dependency lack of autonomy. Node colours represent the group to which each variable belongs: demographic factors (in blue), socioeconomic factors (in green), relational factors (in purple), lifestyle factors (in grey), health factors (in red), and self-reported health (in orange). (Color figure online)

Fig. 2

Variable total effects, as regression coefficient value, decomposed into direct (light area) and indirect (dark area). Values adjusted by each variable’s minimally sufficient adjustment set (MSAS) a from DAG-1 that includes health factors; and b from DAG-2 that excludes health factors. Values over bars represent the percentage of direct effects over total effects. Only variables significantly associated with mental well-being are represented (P < 0.05). (Color figure online)