Participants and procedure

Participants were 25- to 74-year-old Finnish men and women who attended the baseline (n = 5024) and follow-up (n = 3735) phases of the DIetary, Lifestyle and Genetic determinants of Obesity and Metabolic syndrome (DILGOM) study (for a participant flow chart, see [35]). The baseline phase was conducted in 2007 as a part of the FINRISK 2007 study in which a random sample of 10,000 people, stratified by 10-year age groups and gender, was drawn from the Finnish population register in five large study areas [36]. All participants who attended the FINRISK 2007 study (n = 6258, response rate = 63%) in January–March were invited to the DILGOM 2007 study (n = 5024, response rate = 80%) conducted in April–June. The baseline phase contained a health examination (including measurements on height, weight and WC) at a study center and several self-administered questionnaires completed either during the visit or at home. All baseline participants alive at the end of the year 2013 received an invitation to the follow-up phase conducted in April–June 2014 (n = 3735, response rate = 82%). The data collection was carried out in two groups: 1) participants who lived in the areas of Turku and Loimaa and in the cities of Helsinki and Vantaa were invited to a similar health examination to the one at baseline (n = 1312); 2) participants who lived in the other three study areas (North Karelia, North Savo, Oulu) received a mail-back questionnaire and self-reported their current weight and height (n = 2423). They also measured their WC themselves, with a measurement tape that was sent to them together with detailed measurement instructions. Participants who did not attend the follow-up phase were more often men (χ2 = 7.22, df = 1, P = 0.007) and tended to be younger (F(1, 5022) = 13.83, P < 0.001, η2 = 0.003) and have higher BMI and WC (F(1, 5015) = 26.56, P < 0.001, η2 = 0.005 and F(1, 4992) = 30.88, P < 0.001, η2 = 0.006, respectively) at baseline than follow-up participants, but these mean differences were small in size. There were no statistically significant differences between these two groups of participants in terms of baseline education (F(1, 4983) = 3.68, P = 0.055, η2 = 0.001), depression (F(1, 4727) = 3.70, P = 0.055, η2 = 0.001) or emotional eating (F(1, 4853) = 0.60, P = 0.438, η2 = 0.000).

The research protocols of the DILGOM baseline and follow-up studies were designed and conducted in accordance with the guidelines of the Declaration of Helsinki and have been approved by the Ethics Committee of Helsinki and Uusimaa Hospital District (decision numbers 229/E0/2006 and 332/13/03/00/2013, respectively). In addition, written informed consent was obtained from all participants.

Outcome variables

BMI and WC

Trained research nurses measured participant’s height, weight and WC by using standardized international protocols [37] at baseline and follow-up. Weight was measured to the nearest 0.1 kg, height to the nearest 0.1 cm and WC to the nearest 0.5 cm. All measurements were made in a standing position in light clothing and without shoes. WC was measured at a level midway between the lower rib margin and iliac crest. At baseline, weight and height measurements were available for 5017 (99.9%) participants to calculate BMI (kg/m2), while WC measurement was available for 4994 (99.4%) participants. At follow-up, BMI and WC were based on measured (n = 1310 and 1305, respectively) or self-reported (n = 2352 and 2288, respectively) information. In a recent validation study conducted in a subset of DILGOM participants, the mean differences between self-reported and nurse-measured height, weight and WC were small and the intra-class correlations were 0.95 or greater in both genders [38]. Respondents with measured and self-reported anthropometric data at follow-up were therefore included in this study.

Predictor variables

Depression

The 20-item Center for Epidemiological Studies - Depression (CES-D) Scale [39] was used to measure depressive symptoms at baseline. The scale is designed to measure depressive symptomatology in the general population, and it has been found to be adequately related to clinical ratings of depression [40]. For each item, respondents indicate how often they have felt in the described way during the past week using a four-point scale (from 0 “rarely or none of the time” to 3 “almost all of the time”). A meta-analysis of 28 studies examining the structure of the CES-D scale concluded that the proposed four-factor structure (negative affect, somatic and retarded activity, lack of positive affect, interpersonal difficulties) best described the scale [41]. In line with this and our previous cross-sectional study [5], we modelled depression as a latent factor with four indicators where each indicator was the mean of the items belonging to the respective original factor. It is noteworthy that the CES-D scale contains one item on loss of appetite (“I did not feel like eating; my appetite was poor”), while there is no corresponding item on increased appetite. We decided to exclude the loss of appetite item from the present analyses, because it represents an unbalanced measurement of appetite change with potentially biasing the measurement towards depression subtype characterized by decreased appetite and weight loss. Thus, somatic and retarded activity indicator variable was calculated based on 6 items instead of 7 items.

Emotional eating

Emotional eating at baseline was assessed by using the emotional eating scale of the 18-item Three-Factor Eating Questionnaire (TFEQ-R18) [42]. Karlsson et al. [42] developed the TFEQ-R18 on the basis of a factor analysis of the original 51-item TFEQ in the Swedish Obese Subjects study and it has been found to be valid in the general population [43, 44]. The scale contains three items that are all rated on a four-point scale (from 1″ does not describe me at all″ to 4″ describes me exactly″): 1) When I feel anxious, I find myself eating, 2) When I feel blue I often overeat, and 3) When I feel lonely, I console myself by eating. In line with our previous cross-sectional study [5], emotional eating was modelled as a latent factor with the three items as indicators.

Moderators and covariates

Night sleep duration and physical activity

Night sleep duration at baseline was assessed with the following question “How many hours per night do you usually sleep?”. The item was treated as a continuous variable in the analyses. Physical activity at baseline was measured with the International Physical Activity Questionnaire - Short Form (IPAQ-SF) [45]. It asks respondents to report their physical activity during the past 7 days across a comprehensive set of domains (leisure time, work, transport, domestic work and gardening) and three intensity levels (vigorous activities, moderate activities and walking). The data were scored according to the IPAQ manual and a combined total physical activity score (minutes per week) was used on a continuous scale in the main analyses. We repeated the analyses with vigorous physical activity score (minutes per week), but it should be noted that 41.6% of participants had not engaged in any vigorous activities during the past week.

Age and gender

Baseline age was treated as a continuous variable (years) and gender as a dichotomous variable (1 = men, 2 = women) in the analyses.

Statistical methods

We used structural equation modelling (SEM) to test the hypothesized mediation models between depression, emotional eating and 7-year change in adiposity indicators. Depression and emotional eating were modelled as latent factors because ignoring measurement error in predictors can lead to biased regression coefficients and latent variables allow taking measurement error into account [46]. The analyses were conducted in three steps. Firstly, confirmatory factor analysis with two latent factors (depression and emotional eating) was used to test whether the four depression indicators and the three emotional eating indicators loaded on separate factors. Secondly, the hypothesized mediation models with baseline age and gender as covariates were estimated separately for change in BMI and WC – change modelled by regressing the measurement at follow-up on the baseline measurement. The absence of an interaction between exposure (i.e. depression latent factor) and mediator (i.e. emotional eating latent factor) in both models allowed us to apply the SEM approach to mediation analysis (β = 0.12, SE = 0.07, P = 0.080 and β = 0.04, SE = 0.07, P = 0.585 for the interaction in the model for BMI and WC, respectively) [46, 47]. The results were reported as the total, direct and indirect effects (i.e. regression coefficients and bias-corrected bootstrap 95% confidence intervals) of depression and emotional eating. The reported indirect effect reflects how much of the association between depression and change in adiposity indicator is explained by emotional eating [48]. The total effect represents the relationship between depression and change in adiposity indicator before adjustment for emotional eating. Thirdly, the moderator effects of gender, age, night sleep duration and physical activity were examined in a separate set of models by adding a moderator (in the case of sleep duration and physical activity) and interaction terms (moderator × emotional eating, moderator × depression) as predictors, and testing the significance of these interactions (Mplus code was obtained from Stride et al. [49] – model 59 with X and M as latent variables).

Full Information Maximum Likelihood (FIML) was used as an estimator, which allows estimation with missing data [50, 51]. It does not impute missing values, but estimates parameters directly using all the observed data. Model fit was evaluated by utilizing Chi-Square statistic, Standardized Root Mean Square Residual (SRMR), Tucker-Lewis Index (TLI), Comparative Fit Index (CFI), and Root Mean Square Error of Approximation (RMSEA). As proposed by Hu and Bentler [52], TLI and CFI values ≥0.95, SRMR values ≤0.08, and RMSEA values ≤0.06 were defined to indicate an adequate fit for the data. Descriptive statistics were derived from IBM SPSS Statistics for Windows, Version 24.0 (IBM Corp., Armonk, NY), while all other analyses were performed with Mplus Version 8 (Muthén & Muthén, Los Angeles, CA).