Eating Chocolate at the Right Time Benefits the Circadiam Sytem and Metabolic Efficiency.

The investigators will measure the fragmentation parameter derived from wrist temperature after each condition (no chocolate, Morning Chocolate, Night Chocolate). Intradaily variability (IV) characterizes the rhythm fragmentation.

Changes in daily rhythm of wrist temperature fragmentation were measured by changes in the fragmentation parameter derived from wrist temperature along the two weeks of intervention in each of the three conditions. The participants wore a wristwatch during the last 7 days of each condition on the non-dominant wrist to record body temperature and activity. Wrist temperature parameters were measured to represent the wrist body temperature pattern, which provides an objectively measure of sleep and siesta (together with activity rhythm).

A low fragmentation involves a low intraday rhythmicity of the circadian rhythm.

Its values oscillated between 0, when the wave was perfectly sinusoidal, and 2, when the wave was as Gaussian noise.

The investigators will measure the regularity parameter derived from wrist temperature after each condition (no chocolate, Morning Chocolate, Night Chocolate). RegularIty is measured as interdaily stability (IS), that means rhythm stability over different days; it varied between 0 for Gaussian noise to 1 for perfect stability, where the rhythm repeated itself exactly day after day.

Changes in daily rhythm of wrist temperature regularity were measured by changes in the regularity parameter derived from wrist temperature along the two weeks of intervention in each of the three conditions. A regular rhythm means recurring at uniform intervals. The participants wore a wristwatch during the last 7 days of each condition on the non-dominant wrist to record body temperature and activity. Wrist temperature parameters were measured to represent the wrist body temperature pattern, which provides an objectively measure of sleep and siesta (together with activity rhythm).

The investigators will measure the amplitude parameter derived from wrist temperature after each condition (no chocolate, Morning Chocolate, Night Chocolate). In the cosinor analysis to characterize the WT rhythm, we calculate amplitude (difference between the maximum [or minimum] value of the cosine function and mesor) Changes in daily rhythm of wrist temperature amplitude were measured by changes in the amplitude parameter derived from wrist temperature along the two weeks of intervention in each of the three conditions. The participants wore a wristwatch during the last 7 days of each condition on the non-dominant wrist to record body temperature and activity. Wrist temperature parameters were measured to represent the wrist body temperature pattern, which provides an objectively measure of sleep and siesta (together with activity rhythm).

A healthy circadian rhythm is considered as the one with high amplitude.

Microbiota diversity changes were measured using Inverse Simpson Index, accounting for both species richness (number of species) and evenness (distribution of species). A higher Inverse Simpson Index indicates greater diversity because it reduces the impact of dominant species and gives more weight to rarer species. Unlike the regular Simpson Index (which decreases as diversity increases), the inverse form is more intuitive: higher values mean a more diverse microbiota. This index is widely used in microbiome studies to compare microbial diversity across different samples, such as in health versus disease states.

Short-chain fatty acids (SCFAs) in fecal samples were analyzed using gas-liquid chromatography (GLC) with a GC-FID system. Samples were mixed with NaOH, lyophilized, and homogenized with formic acid, methanol, and an internal standard (2-ethyl butyric acid). After ultrasonic treatment and centrifugation, the supernatant was filtered and injected into an Agilent 7890A GC system equipped with a Nukol capillary column. Helium was used as the carrier gas, and the FID temperature was set at 220°C. SCFAs were identified by comparing retention times with authentic standards, and quantification was performed using calibration curves with a high correlation (R² = 0.99). Total average values of SCFA (acetate, propionate, other minorities) in each condition were calculated.

The investigators will measure changes in total energy intake measured as kilocalories between baseline and after 2 weeks in each condition (no chocolate, Morning Chocolate, Night Chocolate) At baseline and during the 2 weeks of each condition, time-stamped photographs were captured with a cell phone app. Total energy intake during the 14 days of each condition was analyzed with the nutritional evaluation software (Grunumur 2.0 8).

The investigators will measure macronutrient composition measured as and grams per day between baseline and after 2 weeks in each condition (no chocolate, Morning Chocolate, Night Chocolate). At baseline and during the 2 weeks of each condition, time-stamped photographs were captured with a cell phone app. Macronutrient composition during the 14 days of each condition was analyzed with the nutritional evaluation software (Grunumur 2.0 8).