Data (n = 10,855) originated from the second (in 2003) and third (in 2012) waves of a population-based Health and Social Support (HeSSup) study on working-age Finns. Unlike the first wave (in 1998), the questionnaires in these two waves included identical items in an identical or almost identical order for both SWB and health behavior. For details on response rates and the inclusion of participants see Fig. 1. Details of attrition of participants can be found elsewhere [13].
Measures
A continuous health behavior sum score (HBSS, range 0–4) is a count of the number of beneficial health behaviors including physical activity, dietary habits, alcohol consumption, and smoking status. Physical activity performed in leisure time or in commuting was first converted into a Metabolic Equivalent Task (MET). A MET score ≥ 2 corresponding to 30 min walking per day was the cut-off value for beneficial behavior and provided one point in the HBSS. Dietary habits were assessed by a non-validated index (range 0–100), but formed in compliance with the Nordic nutritional recommendations [14]. Each choice, if being in line with the recommendations, provided one point in the dietary index according to the following cut-off points: dark bread (≥ 2/day); fat free milk (≥ 1/day); pastries/ sweets, sausages, red meat or chicken/ turkey (each ≤ 1–2/week); fish (≥ 1–2/week); fresh fruits and berries (≥ 2/day); vegetables (≥ 2/day); alcohol use (< 10 g women, 20 g men/day). Then, the sum score ranging from 0 to 10 was multiplied by 10 to give a percentage of compliance to recommendations [15]. Lastly, a cut-off value above median in this dietary index (≥ 60) provided one point for HBSS. Alcohol consumption was dichotomized according to Finnish guidelines [16] where risky consumption for women is ≥ 140 g/week and for men ≥ 280 g/week. Then, the values lower than the relevant cut-off provided one point for HBSS. Smoking status was dichotomized into current smokers vs. non-smokers in combination with former-smokers. The latter choice provided one point in HBSS.
Categorical change in health behavior (i.e., positive, neutral, and negative change) was measured by the change in the health behavior sum score (HBSSchange) during follow-up (i.e. the difference between HBSS2012 and HBSS2003). For evaluating change, individuals reporting zero or one beneficial health behaviors were combined into one group due to the small number of participants. Participants were categorized into three groups according to the direction of change in the HBSS during follow-up: positive, neutral, and negative change.
SWB was measured with the continuous four-item life satisfaction scale (range 4–20) [17, 18] where a lower score indicates better subjective well-being. It has three life assessments (i.e., interest, happiness, and ease in life) representing the cognitive component of SWB [1]. The fourth item is perceived loneliness, which is not typical for a life satisfaction scale, but reflects social well-being. The wordings of the life assessments were “Do you feel that your life at the moment is …”, and for the perceived loneliness “Do you feel that at the moment you are …? The responses were scored as follows: very interesting/ happy/ easy/ not at all lonely = 1; fairly interesting/ happy/ easy = 2; cannot say = 3; fairly boring/ unhappy/ hard/ lonely = 4; very boring/ unhappy/ hard/ lonely = 5 [18, 19]. Previously, the life satisfaction scale has often had three categories: satisfied (score = 4–6); intermediate group (score = 7–11, within ± 1 SD from the mean); dissatisfied (score = 12–20). In the present study, the intermediate group was divided at the mean to create four groups of SWB: high (score = 4–6), high intermediate (score = 7–8), low intermediate (score = 9–11), and low (score = 12–20).
The change in subjective well-being (SWBchange) during follow-up was assessed based on the direction of change between SWB groups with three categories (as in HBSSchange): positive, neutral, or negative change (each: yes/no). Thus, the SWBchange indicated the direction of change from one SWB group to another during the follow-up according to the difference in the group levels of SWB2012 and SWB2003, not in their continuous scores.
Factors potentially affecting both SWB and health behavior were included as covariates according to groupings based on the initial random sampling (age) and previous publications of the data. Participants represented four age groups in 2003: 25–29 years (group 1), 35–39 years (group 2), 45–49 years (group 3), and 55–59 years (group 4). Education was also categorized into four groups: (1) no professional education; (2) vocational course/school/apprenticeship contract; (3) college; (4) university degree/university of applied sciences. Health status was categorized according to count of the self-reported diseases into three groups: 0, 1, ≥ 2 diseases. Disease count is commonly used due to its simplicity and the ease of data ascertainment. Even if it does not consider the severity of disease, it is linked with mortality and various health adversities [20]. The complete list of 35 diseases can be found in the Additional file 1. Negative life events before the follow-up survey could affect both SWB and health behavior. From a list of 21 life events in 2007–2012, participants reported burdensome and extremely burdensome life events [21] which were then transformed into a trichotomized covariate: 0, 1, ≥ 2 major negative life events. Details of the life events and the item in the survey can be found in the Additional file 1.
Statistical analyses
Linear regression models were used to analyze:
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(1)
The effect of the categorical HBSSchange on the association between baseline HBSS (continuous HBSS2003) and follow-up SWB (continuous SWBscore2012)
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(2)
The effect of categorical SWBchange on the association between baseline SWB (continuous SWBscore2003) and follow-up HBSS (continuous HBSS2012).
As already described, both HBSSchange and SWBchange were measured by the difference between their baseline and end of follow-up grouping divided into three categories (i.e. positive, neutral, and negative change). The first digit of the adjustment models identified the direction (1: from HBSS2003 to SWB2012; 2: from SWB2003 to HBSS2012) and the second digit was for the adjustment factors. Thus, the Model 1.1. from HBSS2003 to SWB2012 was adjusted for age, gender, education, and disease count (Table 3). The additional adjustments were for either HBSSchange (Model 1.2), or SWB2003 (Model 1.3) or both (Final model 1.4.). The Model 1.4 was then further adjusted with negative life events to create Model 1.5 (For clarification see Table 3). To study the effect of change without baseline level, HBSSchange was made the predictor instead of baseline HBSS2003 to create Model 1.6, which is otherwise parallel to Model 1.1. The Model 1.7 was created by adding also SWB2003 in Model 1.6. (Table 3).
In the opposite direction (from SWB2003 to HBSS2012) (Table 5), the Model 2.1 was adjusted for age, gender, education, and disease count as in Model 1.1., but it had also the SWB2003*education interaction term (Table 5). The additional adjustments were for either SWBchange (Model 2.2) or HBSS2003 (Model 2.3) or both (Final model 2.4). The Model 2.4 was then further adjusted with negative life events to create Model 2.5. To study the effect of change without baseline level, SWBchange was made the predictor instead of baseline SWB2003 and the interaction term SWB2003*education was converted to SWBchange*education to create Model 2.6 from the Model 2.1. The model 2.7 was created by adding also HBSS2003 in the Model 2.6. (Table 5). Data were analyzed with SAS software (version 9.4; SAS Institute Inc. Cary, NC, USA 2016).
To be able to compare the effects of the SWBchange and HBSSchange on their outcomes i.e. HBSS2012 (range 0–4 with 4 steps) and SWB2012 (range 4–20 with 16 steps), the HBSS2012 should be rescaled. Thus, the estimate for SWBchange is multiplied by 4 (4 × 4 = 16) to be comparable for the estimate of HBSSchange.