Life on Earth has evolved within a 24-hour cycle of environmental changes, influencing food availability and predator avoidance. Organisms have developed endogenous circadian oscillators to anticipate and prepare for daily activities, sleep, and food intake. Both food ingestion and fasting affect metabolic states, leading to temporal dynamics in molecular responses with a 24-hour period. The circadian oscillator and feeding time interact to regulate daily rhythms in gene expression and protein function. Disruptions to circadian rhythms, as seen in shift workers, are linked to metabolic diseases. Frequent caloric intake dampens molecular circadian rhythms, while time-restricted feeding (TRF) in animal models, limiting caloric intake to an 8-12 hour window, offers various health benefits including reduced adiposity, increased lean mass, improved sleep, and enhanced endurance. However, the applicability of TRF to humans was unknown due to the lack of objective methods to assess human eating patterns. Current methods are subjective, disruptive, or provide negative feedback. The widespread use of smartphones presents an opportunity to objectively monitor eating patterns in free-living individuals, leveraging this technology to study behaviors at scale.

Existing literature highlights the importance of circadian rhythms in metabolic health. Studies in animal models have demonstrated the benefits of time-restricted feeding (TRF) in improving various metabolic parameters. However, there's a lack of research on the precise temporal dynamics of human eating patterns and the potential impact of TRF in humans. The limited existing methods for assessing human dietary intake are often subjective, inconvenient, and prone to bias. This study aimed to address this gap by developing a novel smartphone-based approach for objectively monitoring eating patterns and assessing the efficacy of TRF in improving metabolic health in humans.

A smartphone application was developed to monitor daily eating patterns in free-living adults. Participants used the app's camera function to take pictures of their food and beverages before consumption, along with optional text annotations. Data, including timestamps and geolocation, were immediately transferred to a server, and then deleted from the participant's device to minimize feedback effects. Push notifications were randomly sent throughout the day to check for unreported food intake. The baseline study monitored healthy adults (males and females) for 3 weeks, recording ingestion events. Caloric intake was estimated using Calorie King or FNDDS databases. A subset of participants with a BMI > 25 and daily eating duration > 14 hours participated in a 16-week intervention study. Participants were instructed to restrict their eating to a self-selected 10-12 hour window, while maintaining their usual dietary habits. Data visualization, in the form of "feedograms," was used to provide feedback. Anthropometrics, subjective assessments (energy levels, hunger, sleep satisfaction), and estimated caloric intake were measured at baseline, after 16 weeks, and at 1 year post-intervention. Actigraphy data from a subset of participants were collected to correlate eating patterns with activity and sleep.

The baseline study revealed that most participants exhibited erratic and highly variable daily eating patterns, often extending over 15 hours or more. A significant portion of caloric intake occurred after 6 p.m. A notable "metabolic jetlag" was observed due to varying eating patterns between weekdays and weekends. The 16-week intervention study showed that reducing the daily eating duration to 10-11 hours resulted in significant weight loss (average 3.27 kg), improvements in sleep quality, and increased energy levels. These benefits persisted for at least one year after the intervention concluded. The intervention also led to a reduction in estimated daily caloric intake, likely because food was not transferred from outside the eating window to inside but rather simply eliminated. The reduction in both eating duration and metabolic jet lag are likely contributors to the health benefits.

This study introduces a scalable and objective method to assess human eating patterns in free-living conditions. The findings challenge the conventional assumption of a three-meals-a-day structure and highlight the prevalence of erratic eating habits in healthy adults. The strong correlation between sleep duration and overnight fasting duration suggests a potential mechanism linking sleep deprivation to metabolic diseases. The success of the time-restricted feeding intervention demonstrates that modulating the temporal pattern of eating can have significant positive effects on weight management and overall health. The reduction in total caloric intake is a noteworthy finding.

This research demonstrates that a smartphone-based approach can effectively monitor human eating patterns, revealing the prevalence of erratic and prolonged daily eating durations. Time-restricted feeding, even without changing dietary quality or quantity, resulted in clinically relevant improvements in weight, sleep, and energy levels. Future research should investigate the long-term effects of time-restricted feeding, explore variations across diverse populations and lifestyles, and delineate the precise mechanisms underlying these beneficial effects. The role of metabolic jetlag in obesity needs further exploration.

The study sample size, particularly in the intervention group, was relatively small, limiting the generalizability of the findings. The reliance on self-reported data for certain subjective measures introduces potential for bias. The study primarily focused on overweight individuals, and further research is needed to evaluate the effects of time-restricted feeding in other populations. More investigation on how time restricted feeding impacts caloric reduction, specifically what portion of food intake is eliminated from total intake, is necessary.