Mental health is influenced not only by trait markers, general living conditions and major life events, but also, as increasing evidence indicates, by simple everyday behaviours that can be altered by an individual. Prospective studies consistently find a bidirectional relationship between various lifestyle factors and physical as well as mental health, with important health improvements and wellbeing following relatively small changes in lifestyle (Jonsdottir et al. 2010; Xu et al. 2010).
Various lifestyle choices are known promoters of physical health, including engaging in sports or moderate to rigorous physical activity (Fogelholm 2010), participating in cultural or mental activities, like singing in a choir or reading a book (Bygren et al. 1996; Bygren et al. 2009), refraining from smoking (Schane et al. 2010), practicing moderation in alcohol consumption (Ronksley et al. 2011), maintaining a body mass index (BMI) within the range of normal weight (Harriss et al. 2009b), and eating a healthy diet (Scarborough et al. 2012). A robust relationship between these lifestyle choices and various somatic diseases, including cancer (Harriss et al. 2009a), heart disease (Sattelmair et al. 2011), or stroke (He et al. 2006) is well documented.
Evidence indicates that such lifestyle factors also have a positive effect on the psychological domain, reducing depression as well as anxiety (Scott et al. 2008; Xu et al. 2010), increasing life satisfaction (Headey et al. 2013) and self-perceived general mental health (Chaney et al. 2007; Hamer et al. 2009; Rohrer et al. 2005). A recent review by Mammen and Faulkner (2013) analysed 30 prospective longitudinal studies and identified physical activity as an important protective factor in reducing the risk of developing depression. Another systematic review acknowledged positive effects of exercise training interventions on reducing symptoms of anxiety in patients with chronic illnesses. Systematic aggregation of 40 treatment studies estimated the anxiety reduction with an average effect size of d = 0.29 for the training condition as compared with the controls without exercise training (Herring et al. 2010). Cuypers et al. (2012) reported a small, but positive effect of cultural or creative activities on various mental health outcomes, including depression, anxiety and life satisfaction in both men and women. As in the domain of physical health outcomes, smoking has also been identified as a risk factor for psychological distress (Kinnunen et al. 2006; Lien et al. 2009). The relationship between alcohol consumption and psychological distress is still controversial. While some studies identify a nonlinear relationship, with elevated risks for depression and anxiety for abstainers and heavy drinkers as compared to light/moderate drinkers (Rodgers et al. 2000), other studies did not find any meaningful correlation between alcohol consumption and symptoms of psychological distress (Xu et al. 2010). The research regarding the relationship between body mass index (BMI) and mental health is also contradictory. Data from 46,704 participants in the South Australian Monitoring and Surveillance System, which measures nationwide trends in risk factors and chronic diseases, indicated a nonlinear relationship between BMI and mental health, with greater odds of mental health problems only in obese women (Kelly et al. 2011). Other studies suggested elevated risks for mental disorders for young women with obesity (Becker et al. 2001) or described underweight individuals (Molarius et al. 2009) as an additional risk group. In addition to the above mentioned lifestyle factors, the influence of circadian and social rhythms on mental health are currently under investigation. The association between various mental disorders and disturbances of circadian rhythms is also documented, especially for schizophrenia, bipolar disorder and depression (Jagannath et al. 2013). Disruptions of circadian rhythms may indeed trigger or exaggerate episodes of mania (McClung 2007) and first evidence suggests that cognitive behavioural treatment of insomnia may improve psychotic symptoms in individuals with persistent delusions (Myers et al. 2011). Although the exact mechanisms are still unclear, there is evidence that the circadian system is also an important regulator of other vital functions and influences one’s capacity for mood regulation (McClung 2013). Additionally, irregular social rhythms, which include social contacts, are also associated with mood disorders. A recent study indicated that elderly patients with major depressive disorder exhibit a lower regularity in their social rhythms compared to healthy controls (Lieverse et al. 2013). Although the understanding of the bidirectional relations between affective disorders and life rhythm is still preliminary, research indicates that social and circadian rhythms play an important role in understanding mood disorders (Grandin et al. 2006).
Lifestyle composite scores
Healthy and unhealthy lifestyle behaviours tend to occur in clusters (Conry et al. 2011). A healthy way of life can be characterized as an accumulation of multiple healthy lifestyle choices. Therefore, research has recently been approaching lifestyle with a more holistic view and seeks to evaluate the cumulative effects of protective lifestyle behaviours on health outcomes.
An evaluation of data from the EPIC-Norfolk Prospective Population Study indicated that the presence of a combination of four important healthy lifestyle behaviours decreased mortality substantially when compared with an absence of these behaviours (Khaw et al. 2008). Healthy lifestyle behaviours in this study included non-smoking, at least 30 minutes of daily physical activity, moderate or no alcohol intake and at least sufficient fruit/vegetable intake (measured via plasma vitamin C levels). With rising number of healthy behaviours, a corresponding reduced mortality risk over the evaluated period of eleven years was observed. For example, individuals that engaged in all four health behaviours had a 4-fold reduced mortality risk – equivalent to 14 years longer life expectancy – as compared to persons who did not meet the threshold on any of these behaviours (Khaw et al. 2008). The same pattern of results was found for the relation between the number of health behaviours and stroke. These four behaviours predicted more than a twofold difference in incidence of stroke in the same study population (Myint et al. 2009).
A similar protective lifestyle behaviour (PLB) score was used to evaluate the effect of lifestyle on self-perceived overall health and depression (Harrington et al. 2010). This PLB score also included being physically active, non-smoking, moderate alcohol consumption and adequate fruit and vegetable intake. A higher number of PLBs was associated with better perceived overall health and greater mental health outcomes. Individuals displaying no PLBs had a more than four times higher likelihood of suffering from a major depressive disorder and a seven times lower chance of perceiving their health as excellent/very good than subjects with four PLBs.
While there is evidence that physical health and depressive symptoms improve with a rising number of PLBs, there is a lack of literature concerning the effect of a combination of PLBs on life satisfaction or on other psychological syndromes like anxiety or stress. Research has focused mainly on certain lifestyle factors, such as physical activity, smoking or alcohol consumption, while other aspects of everyday life have not been researched satisfactorily. Social and circadian rhythm, although known predictors or mental health, have not been investigated as part of a PLB score and although research revealed a dose–response relationship between the number of cultural and creative activities and mental health (Cuypers et al. 2012), this health-related lifestyle has not yet been investigated in combination with other lifestyle factors.
The present study
The aim of the present study, therefore, was to extend the work on the impact of major lifestyle factors to a broad spectrum of aspects of mental health and to analyse the individual and combined associations between lifestyle health behaviours and psychological distress or wellbeing. The study included major lifestyle factors previously shown to have an effect on physical health and depression, including smoking, alcohol drinking frequency, physical activity and body-mass-index as predictors of mental health in a representative community sample. Additionally, we included mental/cultural activity and circadian and social rhythms, previously under-investigated in population-based surveys, and aimed to investigate their unique contributions in predicting mental wellbeing in the general public. Following the approach of Harrington et al. (2010) and Khaw et al. (2008), we sought to examine the combined associations of the examined lifestyle behaviours with mental health and life satisfaction.
Positive lifestyle factors were expected to be independently associated with lowered psychological distress and greater life satisfaction. We also expected an additive effect; in that the more healthy lifestyle choices an individual reported, the lower the psychological distress and the greater the life satisfaction reported by that participant would be.
This study was conducted as part of the Bochum optimism and mental health studies (BOOM-studies), which aim to investigate risk and protective factors of mental health in representative and student samples with cross-sectional and longitudinal assessments across different cultures. Presented data were collected between November 2012 and February 2013 through three professional opinion research institutes. Four different assessment methods were used: face-to-face interviews, telephone interviews, online survey, and a mixed-method-approach that allowed individuals to participate either online or via set-top box. All analyses and results presented in this study are controlled for their data assessment methods. Participants were either recruited via telephone or were registered members of an online panel. Trained professional interviewers conducted the telephone and personal interviews with computer assistance. The online and mixed-method data were assessed through self-administered surveys. Depending on the data assessment method, participants gave their informed consent written or orally after being informed about anonymity and voluntariness of the survey. Participants received no financial compensation. Representativeness for the German adult residential population, based on the register-assisted census data from 2011 regarding age, gender and education, was ensured via systematized sampling procedures. This procedure included the next-birthday-method, resulting in an equal chance for all household members of being selected for the telephone or face-to-face interview. The Ethics Committee of the Faculty of Psychology of the Ruhr-Universität Bochum approved the study.