2026-04-01, Longo Silva, Giovana, Rodríguez Martín, María, Salmerón Martínez, Diego, Scheer, Frank A. J. L., Garaulet Aza, Marta, Fisiología, Facultades de la UMU::Facultad de Biología

Background Overweight and obesity continue to rise globally, and sleep has emerged as an important behavioral determinant of body weight. While nighttime sleep has been widely studied, the role of daytime napping—especially nap timing—remains unclear. Existing research relies on clock time, which may not reflect individual rhythms. This study investigates whether nap timing referenced to daily events is associated with BMI in two adult populations of habitual nappers (Spain and Brazil). Secondary aims included the association of nap duration and weekend–weekday differences in nap timing and duration with BMI. Methods Habitual nappers (n = 3550) aged 18–65 years were studied. Nap timing was calculated relative to wake time and lunch time. As secondary analyses, nap duration and weekend–weekday differences in nap timing (nap jet lag) and in nap duration were evaluated. Linear regression and restricted cubic spline models were applied. Results BMI and excess weight prevalence were similar between countries. Compared with Spaniards, Brazilians showed earlier naps (by >2 h), longer weekend naps (by 13 min), and greater nap jet lag (by 23 min) (all p < 0.001). Despite these differences, no significant interactions by country were observed in nap–BMI associations, and data were pooled. Nap timing relative to wake and lunch displayed L-shaped associations with BMI: the highest BMI corresponded to early naps (~3h after waking and ~2h before lunch), whereas the lowest BMI (i.e. the inflection points) occurred when naps were 7h18min after wake (β = −0.48 kg/m2 per hour before the inflection point, p = 0.001) and 1h15min after lunch (β = −0.53 kg/m2 per hour before the inflection point, p = 0.031). Shorter and more consistent nap duration across the week was associated with lower BMI (p < 0.05). Conclusions Findings highlight nap timing as a novel behavioral factor associated with BMI, warranting further longitudinal research to explore its potential causal role.

2024-06-08, Rodríguez Martín, María, Martínez Lozano, Nuria, Santaclara Maneiro, Vicente, Gris Peñas, Antonio, Salmerón Martínez, Diego, Ríos, Rafael, Tvarijonaviciute, Asta, Garaulet Aza, Marta, Ciencias Sociosanitarias, Fisiología

Background Circadian health refers to individuals’ well-being and balance in terms of their circadian rhythm. It is infuenced by external cues. In adults, a close relationship between circadian-related alterations and obesity has been described. How ever, studies in children are scarce, and circadian health and its association with obesity have not been evaluated globally. We aimed to assess whether circadian health difered between children with and without obesity as determined by a global circadian score (GCS) in a school-age population. Methods Four hundred and thirty-two children (7–12 years) were recruited in Spain. Non-invasive tools were used to calcu late the GCS: (1) 7-day rhythm of wrist temperature (T), activity (A), position (P), an integrative variable that combines T, A, and P (TAP); (2) cortisol; and (3) 7-day food and sleep records. Body mass index, body fat percentage, waist circumference (WC), melatonin concentration, and cardiometabolic marker levels were determined. Results Circadian health, as assessed by the GCS, difered among children with obesity, overweight, and normal weight, with poorer circadian health among children with obesity. Children with obesity and abdominal obesity had 3.54 and 2.39 greater odds of having poor circadian health, respectively, than did those with normal weight or low WC. The percentage of rhythmicity, a marker of the robustness of the TAP rhythm, and the amplitude, both components of the GCS, decreased with increasing obesity. Diferent lifestyle behaviors were involved in the association between circadian health and obesity, particularly protein intake (P=0.024), physical activity level (P=0.076) and chronotype (P=0.029). Conclusions The GCS can capture the relationship between circadian health and obesity in school-age children. Protein intake, physical activity level, and chronotype were involved in this association. Early intervention based on improving circadian health may help to prevent childhood obesity.

2026-04-01, Longo-Silva, Giovana, Rodríguez Martín, María, Salmerón Martínez, Diego, Scheer, Frank A. J. L., Garaulet Aza, Marta, Ciencias Sociosanitarias, Facultad de Medicina

Background: Overweight and obesity continue to rise globally, and sleep has emerged as an important behavioral determinant of body weight. While nighttime sleep has been widely studied, the role of daytime napping—especially nap timing—remains unclear. Existing research relies on clock time, which may not reflect individual rhythms. This study investigates whether nap timing referenced to daily events is associated with BMI in two adult populations of habitual nappers (Spain and Brazil). Secondary aims included the association of nap duration and weekend–weekday differences in nap timing and duration with BMI. Methods: Habitual nappers (n = 3550) aged 18–65 years were studied. Nap timing was calculated relative to wake time and lunch time. As secondary analyses, nap duration and weekend–weekday differences in nap timing (nap jet lag) and in nap duration were evaluated. Linear regression and restricted cubic spline models were applied. Results: BMI and excess weight prevalence were similar between countries. Compared with Spaniards, Brazilians showed earlier naps (by >2 h), longer weekend naps (by 13 min), and greater nap jet lag (by 23 min) (all p < 0.001). Despite these differences, no significant interactions by country were observed in nap–BMI associations, and data were pooled. Nap timing relative to wake and lunch displayed L-shaped associations with BMI: the highest BMI corresponded to early naps (~3h after waking and ~2h before lunch), whereas the lowest BMI (i.e. the inflection points) occurred when naps were 7h18min after wake (β = −0.48 kg/m2 per hour before the inflection point, p = 0.001) and 1h15min after lunch (β = −0.53 kg/m2 per hour before the inflection point, p = 0.031). Shorter and more consistent nap duration across the week was associated with lower BMI (p < 0.05). Conclusions: Findings highlight nap timing as a novel behavioral factor associated with BMI, warranting further longitudinal research to explore its potential causal role.

2026-04-09, Rodríguez Martín, María, Moreno Caballero, Fernando, Dashti, Hassan S., Saxena, Richa, Scheer, Frank A. J. L., Fernández Breis, Jesualdo Tomás, Garaulet Aza, Marta, Fisiología, Facultades de la UMU::Facultad de Biología

Objectives To predict siesta behavior using machine learning models trained on self-reported and objective data—temperature (T), activity (A), position (P), and the integrated TAP variable—and to explore its associations with obesity-related traits. Methods From ONTIME-MT, 889 adults wore wrist sensors for 7 days to continuously record temperature, activity, and position, and self-reported daily siesta. Machine learning models were developed to classify 30-second epoch siesta data, to reconstruct weekly siesta behavior. Anthropometric and metabolic parameters were assessed. Associations were analyzed using linear and logistic regression. Model generalizability was evaluated in an independent Mediterranean cohort (n = 70). Results The machine learning model allowed to obtain 83% of success in siesta patterns prediction. Among the input variables, activity was the most discriminative by the decision tree (threshold: 27 Δ°/min), followed by TAP (0.51 AU) and position (4.7°). In an independent external validation cohort, success in prediction reached 77%, indicating strong alignment between algorithm-based and self-reported siesta patterns detection. Predicted siesta—but not self-reported alone—was significantly associated with obesity-related traits. Later siesta timing was linked to increased waist circumference in women (β = 0.769 cm per hour; P = 0.026). Longer siesta duration was associated with increased obesity risk (OR=2.081; P=0.002), BMI (β=0.013 kg/m²/h; P = 0.034), and systolic blood pressure (β = 3.540 mmHg/h; P = 0.049). Greater siesta frequency was associated with lower corrected insulin response (β = −0.037 AU/day; P = 0.012). Conclusion Objective data from temperature, activity, position, and TAP, combined with ML models, accurately predict siesta behavior and its metabolic relevance. These findings support the use of machine learning approaches based on temperature, activity, position, and the integrated TAP, to assess siesta under free-living conditions. ClinicalTrials.gov identifier NCT03036592

2024-07-12, Rodríguez Martín, María, Pérez Sanz, Fernando, Zambrano, Carolina, Luján, Juan, Ryden, Mikael, Scheer, Frank A. J. L., Garaulet Aza, Marta, Fisiología, Facultades de la UMU::Facultad de Biología

Study Objectives Napping is a common habit in many countries. Nevertheless, studies about the chronic effects of napping on obesity are contradictory, and the molecular link between napping and metabolic alterations has yet to be studied. We aim to identify molecular mechanisms in adipose tissue (AT) that may connect napping and abdominal obesity. Methods In this cross-sectional study, we extracted the RNA repeatedly across 24 hours from cultured AT explants and performed RNA sequencing. Circadian rhythms were analyzed using six consecutive time points across 24 hours. We also assessed global gene expression in each group (nappers vs. non-nappers). Results With napping, there was an 88% decrease in the number of rhythmic genes compared to that in non-nappers, a reduction in rhythm amplitudes of 29%, and significant phase changes from a coherent unimodal acrophase in non-nappers, towards a scattered and bimodal acrophase in nappers. Those genes that lost rhythmicity with napping were mainly involved in pathways of glucose and lipid metabolism, and of the circadian clock. Additionally, we found differential global gene expression between nappers and non-nappers with 34 genes down- and 32 genes upregulated in nappers. The top upregulated gene (IER3) and top down-regulated pseudogene (VDAC2P2) in nappers have been previously shown to be involved in inflammation. Conclusions These new findings have implications for our understanding of napping’s relationship with obesity and metabolic disorders.

2024-12-23, Rodríguez Martín, María, Salmerón Martínez, Diego, Dashti, Hassan S., Cascales Sanchez, Ana Isabel, Aragón Alonso, Aurora, Scheer, Frank A. J. L., Saxena, Richa, Garaulet Aza, Marta, Ciencias Sociosanitarias, Fisiología

Objective: In this cross-sectional study, we aim to investigate the interactions between obesity, siesta behavior, and the genetic propensity for siesta in a Mediterranean population, in whom siesta is deeply rooted. Methods: We applied a previously generated Siesta-Polygenic Score (PGS) in the ONTIME study (n = 1278). Siesta and other Mediterranean lifestyle behaviors were characterized using questionnaires. We further determined obesity grade. Secondarily, we measured weight loss during treatment as well as long-term weight-loss mainte nance. Logistic regression analyses were performed to address our aim. Results: A total of 42.4% of the population usually took siesta. A significant genetic influence on siesta propensity was found, with a higher genetic predisposition linked to taking siesta more frequently (odds ratio [OR] = 1.17, 95% CI: 1.03–1.32; p = 0.015). Participants with a higher genetic propensity for siesta showed poorer dietary habits (p < 0.05). Among individuals with a high genetic propensity for siesta, we found that those who usually take siesta have lower odds of having obesity (p =0.038) compared with those who do not. Similarly, in exploratory analysis, among individuals with a high genetic propensity for siesta, we found that those who usually take siesta have higher odds of weight-loss success (p = 0.007) compared with those who do not. Conclusions: Considering the ongoing debate regarding whether siesta is beneficial or detrimental, our findings suggest that individual genetic predisposition to siesta might influence the association between siesta and health.

2025-09-19, Rodríguez Martín, María, Szczerbinski, Lukasz, Garaulet Aza, Marta, Dashti, Hassan S., Fisiología, Facultades de la UMU::Facultad de Biología

Background Sleep duration affects metabolic health and regulates appetite, but its role in behavioral weight loss interventions remains unclear as prior studies are limited by small sample sizes, cross-sectional designs, and inconsistent findings. Objectives This study aims to examine the associations between nighttime sleep duration and weight loss during a behavioral intervention in adults with overweight or obesity in Spain. Methods This secondary analysis included adults with overweight or obesity from the Obesity, Nutrigenetics, Timing, and Mediterranean study, a 25-wk behavioral weight loss program. Participants self-reported sleep duration at enrollment and were categorized as short (<7 h), recommended (7–8 h), or long (>8 h) sleepers. Outcomes included percentage of weight loss, clinically meaningful or successful weight loss (≥5% of initial body weight), rate of weight loss (high/rapid rate ≥0.53 kg/wk), and attrition. Associations were examined using logistic regression and linear mixed-effects models adjusted for age, sex, baseline weight, intervention duration, and clinic site. Results Among 3628 participants (mean age 41.2 ± 14.1 y; 77.6% women), 23.7% reported sleeping >8 h, 60.9% reported sleeping 7–8 h, and 15.4% reported sleeping <7 h per night. Long sleepers had significantly lower average weight loss (7.42% of baseline weight) compared with recommended sleepers (7.90%, P = 0.015). Long sleep was associated with 21% lower odds of achieving a weight loss ≥5% of baseline weight [odds ratio (OR): 0.79; 95% confidence interval (CI): 0.66, 0.96], 25% lower odds of rapid weight loss (OR: 0.75; 95% CI: 0.63, 0.89), and 21% higher odds of attrition (OR: 1.21; 95% CI: 1.03, 1.43) compared with recommended sleep. No significant associations were observed for short sleepers. Linear mixed-effects models indicated lower weight loss among long sleepers [β: 0.099; standard error (SE): 0.040; P = 0.015], but not for short sleepers (β: −0.031; SE: 0.048; P = 0.514). Conclusions Habitual long sleep duration is associated with reduced weight loss success and increased risk of attrition in a behavioral weight loss intervention. This trial was registered at clinicaltrials.gov as NCT02829619.

2023-04-26, Vizmanos, Barbara, Cascales Sanchez, Ana Isabel, Rodríguez Martín, María, Salmerón Martínez, Diego, Morales Bartolomé, Eva, Aragón Alonso, Aurora, Scheer, Frank A. J. L., Garaulet Aza, Marta, Ciencias Sociosanitarias, Fisiología

Objective: The aim of this study was to determine the association between siestas/no siestas and obesity, considering siesta duration (long: >30 minutes, short: ≤30 minutes), and test whether siesta traits and/or lifestyle factors mediate the association of siestas with obesity and metabolic syndrome (MetS). Methods: This was a cross-sectional study of 3275 adults from a Mediterranean population (the Obesity, Nutrigenetics, TIming, and MEditerranean [ONTIME] study) who had the opportunity of taking siestas because it is culturally embedded. Results: Thirty-five percent of participants usually took siestas (16% long siestas). Compared with the no-siesta group, long siestas were associated with higher values of BMI, waist circumference, fasting glucose, systolic blood pressure, and diastolic blood pressure, as well as with a higher prevalence of MetS (41%; p = 0.015). In contrast, the probability of having elevated SBP was lower in the short-siesta group (21%; p = 0.044) than in the no-siesta group. Smoking a higher number of cigarettes per day mediated the association of long siestas with higher BMI (by 12%, percentage of association mediated by smoking; p < 0.05). Similarly, delays in nighttime sleep and eating schedules and higher energy intake at lunch (the meal preceding siestas) mediated the association between higher BMI and long siestas by 8%, 4%, and 5% (all p < 0.05). Napping in bed (vs. sofa/armchair) showed a trend to mediate the association between long siestas and higher SBP (by 6%; p = 0.055). Conclusions: Siesta duration is relevant in obesity/MetS. Timing of nighttime sleep and eating, energy intake at lunch, cigarette smoking, and siesta location mediated this association.

2026-01-20, Peña Armada, Rocío de la, Longo Silva, Giovana, Rodríguez Martín, María, Yang, Hui-Wen, Garaulet Aza, Marta, Fisiología, Facultades de la UMU::Facultad de Biología

Objective This longitudinal study aims to identify the key factors influencing the weight loss trajectory during a 24-week intervention and their relevance at different stages of the treatment. Methods We studied 1252 participants (age 18–65 years) of a cognitive behavioral program to lose weight. Body weight was measured weekly, and a range of variables at baseline and throughout the treatment period were assessed. Linear regression analyses were conducted to understand the factors involved in the weight loss trajectory across three treatment periods (0–6, 7–12, 13–24 weeks). Results The rate of weight loss progressively decreased from the 1st to the 3rd period (770–198 g/week). During the 1st period, the recent history of the individual, including baseline metabolic status, dietary habits, and motivation, was the highest-ranked determinant. In the 2nd period, the sole predictor was the long-term personal history of obesity, that is, the duration of the individual's lifetime spent with overweight/obesity. In the 3rd period, emotional eating behaviors and related barriers emerged as the two highest-ranked determinants of reduced rate of weight loss. Conclusions Findings suggest targeted interventions that address the specific challenges of each period of weight loss interventions. As treatment progresses, strategies focused on emotional-related behaviors may be crucial for sustaining weight loss. Trial Registration ClinicalTrials.gov identifier NCT02829619

2025-07-20, Peña-Armada, Rocío de la, Rodríguez Martín, María, Dashti, Hassan S., Cascales Sanchez, Ana Isabel, Scheer, Frank A. J. L., Saxena, Richa, Garaulet Aza, Marta, Fisiología, Facultades de la UMU::Facultad de Biología

Objective We examined whether meal timing is associated with long-term weight-loss maintenance and whether meal timing interacts with a genome-wide polygenic score (PRS-BMI) on body weight-related outcomes. We then examined the interaction of meal timing with 97 BMI-related single-nucleotide polymorphisms on obesity outcome. Methods Participants (N = 1195, mean age 41.07 [SD 12.68] years, female 80.8%, baseline mean BMI 31.32 [SD 5.53] kg/m2) were adults with overweight or obesity from the Obesity, Nutrigenetics, Timing, and Mediterranean (ONTIME) study. We developed a PRS-BMI to assess the genetic risk for obesity and estimated the timing of the midpoint of meal intake. We also calculated the success in long-term weight-loss maintenance after a dietary obesity treatment (at least 3 years). Linear regression analyses were performed for association and interaction assessments. Results Each hour of delay in meal timing was associated with 2.2% higher long-term body weight (β [SE] = 2.177% [1.067%]; p = 0.042) (i.e., with lower weight-loss maintenance following dietary obesity treatment). There was a significant interaction between meal timing and PRS-BMI (p = 0.008); BMI increased by more than 2 kg/m2 for every hour of delay in meal timing in individuals with high PRS-BMI (β [SE] = 2.208 [0.502] kg/m2; p = 1.0E-5), whereas no associations were evident for those with lower genetic risk. Conclusions Meal timing is associated with weight-loss maintenance and may influence the association between obesity genetics and BMI. Findings underscore the importance of personalized obesity management.