Preceding psychological factors and calorie intake in patients with type 2 diabetes: investigation by ecological momentary assessment

The participants were nine outpatients with type 2 diabetes diagnosed according to the current criteria of the Japan Diabetes Society [8] (three men; median age = 49 years, range = 34 to 72) who also took part in another study [9]. Inclusion criteria were age ≥ 20 and an outpatient with type 2 diabetes at the University of Tokyo Hospital. Participants were excluded if they had HbA1c ≥ 8.4% (corresponding to 8.0% before converting to the NGSP value, which was the criterion for poorly controlled type 2 diabetes), had any active mental disorder, followed a restrictive diet with protein ≤0.5 g/kg/day or salt ≤5 g/day due to another disease, had cognitive impairment, or had severe complications that interfered with self-care activities. After providing written informed consent, participants were instructed to record daily dietary intake using a PDA-based food diary, SELFOOD [10], and to record mood states, such as anxiety and depression, on a personal digital assistant (PDA) (WS020SH, Sharp Corp, Osaka, Japan, 135 g, 50x116x17.9 mm, Windows Mobile 6.1) that was equipped with a 3.0-in color liquid crystal display and a touch panel manipulated by a finger. They were asked to record as soon as possible after eating for 6 consecutive months. Anthropometric measurements, including height, body weight, and blood pressure, were performed at the beginning of the study. Clinical data (e.g. fasting plasma glucose level, hemoglobin A1c value, and duration of diabetes) were collected at their most recent visit with a health care provider. They visited their physician regularly, and continued to take the medications prescribed for their conditions during the study period.

We developed an electronic food diary, “SELFOOD”, for use in a personal digital assistant (PDA). Its accuracy has been confirmed by comparison with a 24-h recall interview by registered dietitians [10]. SELFOOD includes a reference database with 423 color photographs of food and drink items and allows patients to add their own meals and recipes to the database if their nutrient information is given. SELFOOD calculates energy intake after every input. Calorie intake was summed on an input-by-input basis and converted to a daily bar graph with a horizontal line indicating the target value of daily calorie intake.

A PDA was used as electronic diary to record psychological stress, anxiety, and depressive mood [11]. The subjects were instructed on the use of the device and given manuals before the beginning of the study period. In addition, they practiced manipulating the device with the author until they became accustomed to its use.

The subjects used the PDAs for six consecutive months. Signal-contingent recordings were defined as recordings that were prompted with a beep as a signal [2], which was programmed to occur randomly within an interval of 30 mins, around 10:00 and 15:00. If the subjects did not enter a recording when the computer beeped, they were allowed to postpone input for 30 min. Recordings not made within 30 min were cancelled. The subjects were also asked to record their psychological stress, anxiety, and depressive mood when they woke up and when they went to bed by choosing “waking up” or “going to bed” from the menu. After selecting a “going to bed” recording, to avoid sleep disturbance the computers suspended the signal-contingent recordings until a selected “wake up” recording was played. Signal-contingent recordings and recordings when waking up and going to bed were treated as scheduled recordings. Momentary psychological stress, anxiety, and depressive mood were rated with a visual analog scale (VAS) that ranged from 0 to 100, which was displayed on the screen.

Multilevel modeling was used for statistical analyses to investigate preceding psychological factors on dietary intake because the dataset in this study had a nested structure in which a number of recordings belonged to each participant. Pairs of preceding psychological factors and dietary intake were lagged in the range of − 5 to 0 h [12]. The level of significance was set at 0.05. SAS Proc Mixed (SAS 9.3, SAS Institute Inc., Cary, NC, USA) was used. Each dietary intake recording was paired with the preceding momentary recording of psychological stress and mood states. Dietary intake was treated as the dependent variable. Momentary psychological stress, anxiety, and depressive mood were separately modeled as the independent variable, either as a fixed or random effect. Preceding momentary recordings of psychological factors were recorded within five hours before dietary intake, and there was no dietary intake between a preceding momentary recording of psychological factors and the dependent variable of dietary intake. Using these stratified time lags, models with different combinations of independent variables (with/without a preceding psychological factor as a fixed/random effect) were tested. Goodness of fit was compared to determine the best-fit model with a − 2 log likelihood function and χ² test when one model was nested in the other; otherwise, Akaike’s Information Criterion (AIC) was used. The level-1 (within-individual level) intercept was modeled as a random effect. In all analyses, the variance-covariance matrix (G matrix) was modeled as unstructured.

The characteristics of subjects are shown in Table 1.

In total, the data from 1353 days of recordings was available for analysis. The compliance rate for regular dietary intake was 77.2%, while the compliance rate for signal-contingent recordings of psychological factors was 42.8%. With regard to pairing dietary intake and preceding psychological factors, 1517 of 3667 dietary intakes could be paired with preceding psychological factors.

Preceding psychological stress was significantly, negatively associated with dietary intake for lunch and dinner, but positively associated for snacks (Tables 2, 3 and 4). The final model is as follows:

Level 1 equation:

Level 2 equation: where Y_ij is each momentary calorie intake for the ith patient; Company_ij is a corresponding accompanying person, recorded as alone or with someone; Place_ij is the corresponding eating place; home, office/school, dining out, or other (e.g. outdoors); Stress_ij is the corresponding preceding psychological stress; TargetCal_i is the target calorie intake for the ith patient. γ₀₀ is the average true value of mean calorie intake when all predictors are zero. π_1i, π_2i, and π_3i are the individual i’s slopes representing the effect of an accompanying person(s), eating place(s), or preceding psychological stress on momentary calorie intake, respectively, and γ₁₀, γ₂₀, and γ₃₀ are the average slopes. ε_ij and ζ_0i are residuals at each level. Including ζ_0i in the equation means that the intercept was modeled as random, which suggests that intercept can vary across individuals. The second level 2 equation included no residual, which means that the effect of an accompanying person(s), eating place(s), or preceding psychological stress on momentary calorie intake was modeled as a fixed effect.

Preceding anxiety was significantly, negatively associated with dietary intake only for breakfast (Table 5). The final model is as follows:

Level 1 equation:

Level 2 equation: where Y_ij is each momentary calorie intake for the ith patient; Company_ij is a corresponding accompanying person, either alone or with someone; Place_ij is the corresponding eating place, home, office/school, dining out, or other; Anxiety_ij is the corresponding preceding anxiety.

Preceding depressive mood was significantly, negatively associated with dietary intake only for lunch (Table 6). The final model is as follows:

Level 1 equation:

Level 2 equation: where Y_ij is each momentary calorie intake for the ith patient; Company_ij is a corresponding accompanying person, either alone or with someone; Place_ij is the corresponding eating place, home, office/school, dining out, or other; Depression_ij is the corresponding preceding depressive mood.