Abstract
BackgroundNumerous diets, apps and websites help guide and monitor dietary behaviour with the goal of losing weight, yet dieting success is highly dependent on personal preferences and circumstances. To enable a more quantitative approach to dieting, we developed an integrated platform that allows tracking of life-style information alongside molecular biofeedback measurements (lactate and insulin).MethodsTo facilitate weight loss, participants (≥18 years) omitted one main meal from the usual three-meal routine. Daily caloric intake was restricted to ~1200KCal with one optional snack ≤250KCal. A mobile health platform (personalhealth.warwick.ac.uk) was developed and used to maintain diaries of food intake, weight, urine collection and volume. A survey was conducted to understand participants’ willingness to collect samples, motivation for taking part in the study and reasons for dropout.ResultsMeal skipping resulted in weight loss after a 24 h period in contrast to 3-meal control days regardless of the meal that was skipped, breakfast, lunch or dinner (p < 0.001). Common reasons for engagement were interest in losing weight and personal metabolic profile. Total insulin and lactate values varied significantly between healthy and obese individuals at p = 0.01 and 0.05 respectively.ConclusionIn a proof of concept study with a meal-skipping diet, we show that insulin and lactate values in urine correlate with weight loss, making these molecules potential candidates for quantitative feedback on food intake behaviour to people dieting.
Highlights
Numerous diets, apps and websites help guide and monitor dietary behaviour with the goal of losing weight, yet dieting success is highly dependent on personal preferences and circumstances
The mobile health platform creates a timeline of the logs or events that are entered by the user. This electronic information is sent to a web server that allows users to store their information securely and access it anywhere using either a web browser based interface or a native mobile application from their smart phones or tablets
Biomarker and BMI Because BMI was correlated with a number of parameters (Fig. 5), we investigated if pre-defined BMI groups differed in correlation of parameters (Fig. 5b)
Summary
Apps and websites help guide and monitor dietary behaviour with the goal of losing weight, yet dieting success is highly dependent on personal preferences and circumstances. Besides body image considerations, being overweight or obese can raise blood pressure and concentrations of cholesterol, as well as cause insulin resistance This increases the risk of developing heart disease, stroke, type 2 diabetes and certain types of cancers among other conditions [2, 3]. Even if a device that accurately measures caloric intake and expenditure was widely available, the information may not be sufficient to motivate a user to make changes in their behaviour that would result in weight loss. This is evidenced by the fact that even when meticulously keeping records of food intake, individuals still find it hard to lose weight [13]. The prerequisite for such a device is a quantitative and science-based biomarker of weight loss that has the potential to provide a biological feedback loop to the dieter
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