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

Abstract

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.

Fig. 1. 95% eating window compared to a daily eating interval.

Feedograms displaying all caloric food and beverage entries (dots) over a 24-h period for 14 days during baseline (A) and during a TRE intervention (B) for a given participant. The 95% eating window is indicated by the dotted line on the feedogram and the daily eating duration is shown on the right. From Wilkinson et al., 2020.

Fig. 2. Adults have a long eating window.

24-h plots of (A) all food, beverage, water, and medication events and (B) caloric food and beverage events. (C) Percentage of participants in each eating duration bin (h). Data from 156 adults for 21 consecutive days. From Gill and Panda, 2015 [32].

Fig. 3

Data captured on the myCircadianClock smartphone app.

Fig. 4. The myCircadianClock app user interface.

A Home screen, live camera to quickly take a photo of what will be logged. B Annotation page (logging the name of items). C Exercise logging home screen. D Sleep logging home screen. E Health logging home screen. F Intake history page for a given week. G Activity and Sleep history page.

Fig. 5. The myCircadianClock digital platform.

Participants Data (orange arrows; food/beverages, water, medication, sleep, exercise, health measures, and survey responses) logged on the mCC app is sent to the cloud-based mCC server. Study-specific data can be accessed by the research team (navy) in real-time on the mCC dashboard. The research team can also send notifications, surveys, and educational material to participants on the mCC app via the mCC server. Participant data can be downloaded for data integration and analysis by the research team at any time.