A new study published in npj Digital Medicine has revealed strong links between daily lifestyle habits and metabolic function in people at risk for type 2 diabetes (T2D), underscoring the critical role of meal timing, sleep, and physical activity in shaping metabolic health.
T2D continues to rise globally, affecting 589 million adults worldwide and 38 million in the United States. Another 88 million Americans live with prediabetes, with 70% expected to progress to T2D within four years. Preventing that progression is a major public health goal, and lifestyle interventions remain one of the most effective tools.
Researchers examined how habitual behaviors—particularly diet, activity, and sleep—correlate with glucose metabolism and metabolic subtypes in people at risk for T2D. The study included two groups: a primary cohort of 36 adults (16 with normal glucose levels and 20 with prediabetes or T2D) and a validation cohort of 10 individuals. Participants tracked their food intake via an app, while Fitbit bands collected sleep and physical activity data. Glucose was monitored using Dexcom devices, and several metabolic tests were conducted to assess insulin resistance, beta-cell function, and incretin response.
The findings revealed that individuals with elevated HbA1c had distinct patterns in when they consumed food. They ate less between 2 p.m. and 5 p.m. and more between 5 p.m. and 9 p.m. compared to those with normal HbA1c levels. Those with impaired incretin function tended to consume more calories from late morning to evening.
Timing, not just quantity, of food played a key role. Higher energy intake between 5 p.m. and 9 p.m. was associated with prolonged hyperglycemia, reduced nighttime glucose control, and elevated glucose levels the next day. In contrast, eating more between 2 p.m. and 5 p.m. was linked to lower fasting glucose. These effects were not explained by overall calorie intake, suggesting that when people eat may be more important than how much they eat.
Diet composition also mattered. Carbohydrates from non-starchy vegetables were associated with better glucose levels, while those from starchy vegetables were linked to worse outcomes.
Sleep patterns were another critical factor. Greater variability in sleep efficiency and wake-up times correlated with higher nighttime and next-day glucose levels. An earlier wake-up time was tied to reduced incretin function. More sedentary behavior was linked to higher glucose levels, while higher step counts after the last meal reduced nighttime hyperglycemia.
Timing of physical activity also showed divergent effects based on metabolic profiles. Morning steps lowered next-day glucose in insulin-resistant individuals. For insulin-sensitive participants, afternoon steps were more beneficial. Conversely, nighttime activity (midnight to 5 a.m.) raised glucose levels across both groups.
The researchers also explored how diet, sleep, and activity interact. For example, higher rice intake was linked to poorer sleep, while legumes, fruits, fiber, and potassium were associated with longer, better-quality sleep. Longer fasting periods and morning energy intake were also tied to longer sleep duration.
Machine learning models developed from lifestyle data were able to predict metabolic subtypes with 80% accuracy in the validation cohort. Key predictors included high carbohydrate intake from sweets, starchy vegetables, and pasta—factors associated with prediabetes, higher HbA1c, and impaired incretin function. In contrast, fruit-based carbohydrates and longer physical activity durations predicted healthier metabolic function.
While the study is limited by its small sample size and single-location recruitment, it offers compelling evidence that daily lifestyle patterns—especially meal timing, sleep consistency, and physical activity windows—are tightly linked to metabolic risk.
The results suggest that precision lifestyle interventions, tailored to an individual’s metabolic profile, could become a powerful tool in preventing the onset of type 2 diabetes.
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