Associations of time-limited consuming with health-related high quality of life and sleep in adults: a secondary evaluation of two pilot research earlier than and after the BMC Diet pilot challenge

Both studies were conducted as pilot studies in a pre-post observational design. Details are already reported elsewhere [13]. The primary outcome for both studies was the percentage of days that reached the fasting goal of ≥ 15 hours of the total number of days recorded in the diary per participant. According to the study protocol, secondary results included changes in sleep quality and duration as well as HRQoL between baseline and follow-up.


The participants from Ulm University were recruited with the support of occupational safety management and flyers. Existing metabolic disorders were the exclusion criteria. The patients in the family doctor’s office were informed about the study by flyers in the waiting room or invited by the doctor during a consultation. Exclusion criteria were insulin-dependent diabetes or any other disease for which fasting is contraindicated [3]. Finally, 63 participants at Ulm University and 40 participants in the general practitioner’s office were included in the studies.


Participants in both studies were asked to limit their daily food intake to 8 to 9 hours and then increase their nightly fast to 15 to 16 hours. The duration of the intervention was 3 months. At the start of the study, the participants had an introductory meeting with the investigator or the doctor to clarify possible questions and problems in advance, and were given an information brochure. In addition, all participants were invited to contact the respective study center at any time if they had any questions or problems.

Data evaluation

The basic assessment comprised a questionnaire to collect data on lifestyle, health behavior and HRQoL (EQ-5D VAS). [14]and anthropometric measurements of waist, height and weight (for details see [13]). All participants received a diary in which the times of their first and last meal and the quality and duration of their sleep were recorded. The latter was rated on a visual analog scale from 0 (worst possible sleep quality) to 100 (best possible sleep quality). The waist to height ratio (WHtR) was calculated by dividing the waist by the height in centimeters. Abdominal obesity was then defined as WHtR ≥ 0.5, as recommended in the literature [15]. The body weight in kilograms was divided by the height in square meters to determine the body mass index (BMI) and then divided into overweight (≥ 25) and obesity (≥ 30).

After 3 months, follow-up measurements were performed in the same way, with some additional items in the questionnaire relating to individual experiences and attitudes towards TRE.

Statistical analysis

The baseline characteristics are given descriptively for each study group and for both groups together. The intergroup differences were tested using the T-test, Welch’s T-test, or Mann Whitney U-test for distribution and heterogeneity of variance for continuous data and Fisher’s exact test for categorical data.

Follow-up data and computational differences between baseline and follow-up data, represented as the respective Δ, were treated in the same way. Pre and post comparisons for both groups together were determined by the Wilcoxon Signed Rank test for related samples.

Means and standard deviations for the data from the diaries were calculated for each participant. The time of the first meal and the time of the last meal were used to determine the duration of the fast and the eating phase. The percentage of days with a fasting goal was calculated for all recorded days. Differences between groups were tested as described above.

To assess the differences between the duration and quality of sleep at the beginning and the end of the TRE intervention period, mean values ​​were calculated for the first 10% and the last 10% of the data (or days), respectively. The differences between the first and last 10% of the data were then calculated as the respective Δ. They are given along with the average number of days per group and for the whole group.

The Pearson correlation coefficient was used to test bivariate correlations between continuous variables.

Linear regression analyzes were performed for the pre-post differences in HRQoL and the differences in sleep quality between the first 10% and the last 10% of the days recorded. Possible factors that could correlate with HRQoL or sleep quality were identified and, together with variables that differed between the two groups at the start of the study, were gradually eliminated backwards. Gender, age, baseline HRQoL, sleep quality and duration of sleep in the first 10% of the reported days, mean fasting time, percentage of fasting goal achieved and finally group membership were considered as possible associated factors. Anthropometric measurements represented both potential associated factors and differences between groups at baseline. Therefore weight, waist circumference, BMI, WHtR, overweight, obesity, abdominal obesity and the respective Δ between pre- and post-measurements of the continuous variables were considered in the regression analysis. All linear regression assumptions (linear relationship, multivariate normality, multicollinearity, autocorrelation, homoscedasticity) were examined.

The significance level for two-tailed tests was set to α = 0.05. All statistical analyzes were performed with the statistical software packages IBM SPSS Statistics for Windows, Version 25.0. (IBM Corp., Armonk, NY, USA).

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