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Chrononutrition patterns and their association with body weight: Differences across multiple chronotypes
Giovana Longo-Silva1, Renan Serenini2, Anny Pedrosa1
1Research Group 'Chronobiology, Nutrition and Health', Faculty of Nutrition, Federal University of Alagoas, Brazil.
Introduction:
In recent years, the focus of research on obesity and its management has expanded beyond traditional dietary factors to include the timing of food intake - in relation to the body's circadian rhythms - known as chrononutrition. However, chrononutrition patterns remain largely unexplored in low-medium income countries. Our study aimed to investigate the association between chrononutrition patterns and BMI.
Material And Methods:
Utilizing data from the virtual Survey SONAR-Brazil (n=2137,18-65 y), we defined the following chrononutrition patterns: 1. The clock time of the first, mid, and last eating events; 2. Morning and evening latencies (from wake-up time until the first eating event, and from the last eating event until bedtime); and 3. Eating window. Linear regression analyses assessed associations between chrononutrition variables and BMI. Quantile regression and restricted cubic splines were used to explore distributional correlations and association shapes.
Results:
Among all participants, BMI increased with each additional hour of the first eating event (β=0.17; 95% CI, 0.05,0.29; P=0.005), morning latency (β=0.27; 95% CI, 0.12,0.42; P<0.001), and eating midpoint (β=0.21; 95% CI, 0.05,0.38; P=0.01) and the effect was even stronger with higher BMI percentiles. There was no effect of eating times among intermediate and late chronotypes. However, among early types, positive associations were seen between the BMI and the timing of the first eating event, morning latency, and eating midpoint, as well as a negative association with evening eating.
Conclusions:
Our findings suggest that delaying the first eating event, the eating midpoint, and extending morning latency are associated with higher BMI, particularly in early chronotypes. These results highlight the importance of aligning eating patterns with chronotypes and support personalized dietary recommendations.
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