Assessing temporal eating pattern in free living humans through the myCircadianClock app

Int J Obes (Lond). 2022 Apr;46(4):696-706. doi: 10.1038/s41366-021-01038-3. Epub 2022 Jan 8.


The quality and quantity of nutrition impact health. However, chrononutrition, the timing, and variation of food intake in relation to the daily sleep-wake cycle are also important contributors to health. This has necessitated an urgent need to measure, analyze, and optimize eating patterns to improve health and manage disease. While written food journals, questionnaires, and 24-hour dietary recalls are acceptable methods to assess the quantity and quality of energy consumption, they are insufficient to capture the timing and day-to-day variation of energy intake. Smartphone applications are novel methods for information-dense real-time food and beverage tracking. Despite the availability of thousands of commercial nutrient apps, they almost always ignore eating patterns, and the raw real-time data is not available to researchers for monitoring and intervening in eating patterns. Our lab developed a smartphone app called myCircadianClock (mCC) and associated software to enable long-term real-time logging that captures temporal components of eating patterns. The mCC app runs on iOS and android operating systems and can be used to track multiple cohorts in parallel studies. The logging burden is decreased by using a timestamped photo and annotation of the food/beverage being logged. Capturing temporal data of consumption in free-living individuals over weeks/months has provided new insights into diverse eating patterns in the real world. This review discusses (1) chrononutrition and the importance of understanding eating patterns, (2) the myCircadianClock app, (3) validation of the mCC app, (4) clinical trials to assess the timing of energy intake, and (5) strengths and limitations of the mCC app.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Diet
  • Diet Records
  • Eating
  • Energy Intake
  • Feeding Behavior
  • Humans
  • Mobile Applications*