Subjective well-being predicts health behavior in a population-based 9-years follow-up of working-aged Finns

Säde Stenlund; Heli Koivumaa-Honkanen; Lauri Sillanmäki; Hanna Lagström; Päivi Rautava; Sakari Suominen

doi:10.1016/j.pmedr.2021.101635

Subjective well-being predicts health behavior in a population-based 9-years follow-up of working-aged Finns

Prev Med Rep. 2021 Nov 14:24:101635. doi: 10.1016/j.pmedr.2021.101635. eCollection 2021 Dec.

Authors

Säde Stenlund^{1

2}, Heli Koivumaa-Honkanen^{3

4}, Lauri Sillanmäki^{1

2

5}, Hanna Lagström^{1

2

6}, Päivi Rautava^{1

2}, Sakari Suominen^{1

2

7}

Affiliations

¹ Department of Public Health, University of Turku, Kiinamyllynkatu 10, 20014 Turku, Finland.
² Research Services, Turku University Hospital, Kiinamyllynkatu 4-8, 20521 Turku , Finland.
³ Institute of Clinical Medicine, Psychiatry, University of Eastern Finland, Yliopistonranta 1A, 70029 Kuopio, Finland.
⁴ Mental Health and Wellbeing Center, Kuopio University Hospital, Puijonlaaksontie 2, 70029 Kuopio, Finland.
⁵ Department of Public Health, University of Helsinki, Tukholmankatu 8 B, 00014 Helsinki, Finland.
⁶ Centre for Population Health Research, University of Turku and Turku University Hospital, Kiinamyllynkatu 10, 20014 Turku, Finland.
⁷ School of Health Sciences, University of Skövde, Högskolevägen 1, 54128 Skövde, Sweden.

Abstract

The cross-sectional association between measures of subjective well-being (SWB) and various health behaviors is well-established. In this 9-year (2003-2012) follow-up study, we explored how a composite indicator of SWB (range 4-20) with four items (interest, happiness, and ease in life, as well as perceived loneliness) predicts a composite health behavior measure (range 0-4) including dietary habits, physical activity, alcohol consumption, and smoking status. Study subjects (n = 10,855) originated from a population-based random sample of working-age Finns in the Health and Social Support study (HeSSup). According to linear regression analysis, better SWB predicted better health behavior sum score with a β = 0.019 (p < 0.001) with a maximum effect of 0.3 points after adjusting for age (p = 0.038), gender (p < 0.001), education (p = 0.55), baseline self-reported diseases (p = 0.020), baseline health behavior (β = 0.49, p < 0.001), and the interaction between SWB and education (p < 0.001). The results suggest that SWB has long-term positive effect on health behavior. Thus, interventions aiming at health behavioral changes could benefit from taking into account SWB and its improvement in the intervention.

Keywords: AIC, Akaike information criterion; Follow-up; HBSS, health behavior sum score; Health behavior; LS, life satisfaction; Life satisfaction; Longitudinal study; SWB, subjective well-being; Subjective well-being.