Wrist Temperature Research Articles

Thermal physiological characteristics of the Xizang people in asymmetrical dressing exposures on the plateau

The Xizang people, living in the “Third Pole of the World,” have long-formed asymmetrical dressing habits that pose unique challenges to their physiological mechanisms. This study examined the physiological parameters of the Xizang people under symmetrical and various asymmetrical dressing angles to analyze the influence of these dressing styles on their thermal responses. Partial correlation analysis was used to further clarify the physiological thermal assessment indicator of the Xizang people. The results showed that, compared to symmetrical dressing, the Xizang people exhibited higher blood perfusion index and core temperature under asymmetrical dressing. In cold environments, those with symmetrical dressing had higher mean arterial pressure, heart rate, and relative activity ratio of sympathetic to parasympathetic nervous system, indicating dominant sympathetic nerve activity. At an ambient temperature of 15 °C, the Xizang people demonstrated a mean skin temperature difference of 2.6 °C and a right wrist temperature difference of 4.5 °C between symmetrical and the asymmetrical dressing angle with 50° Skin temperature was identified as the physiological thermal assessment indicator for the Xizang people considering asymmetrical dressing styles. This study provided a physiological foundation for the accurate design of plateau built environments suitable for the Xizang people.

Genetic variants associated with chronic fatigue syndrome predict population-level fatigue severity and actigraphic measurements.

The diagnosis of myalgic encephalomyelitis/chronic fatigue syndrome (CFS) is based on a constellation of symptoms which center around fatigue. However, fatigue is commonly reported in the general population by people without CFS. Does the biology underlying fatigue in patients with CFS also drive fatigue experienced by individuals without CFS? We used UK Biobank actigraphy data to characterize differences in physical activity patterns and daily temperature rhythms between participants diagnosed with CFS compared to controls. We then tested if single nucleotide variants (SNVs) previously associated with CFS are also associated with the variation of these actigraphic CFS correlates and/or subjective fatigue symptoms in the general population. Participants diagnosed with CFS (n = 295) had significantly decreased overall movement (Cohen's d = 0.220, 95% CI of -0.335 to -0.106, p-value = 2.42x10-15), lower activity amplitudes (Cohen's d = -0.377, 95% CI of -0.492 to -0.262, p-value = 1.74x10-6), and lower wrist temperature amplitudes (Cohen's d = -0.173, 95% CI of -0.288 -0.059, p-value = 0.002) compared to controls (n = 63,133). Of 30 tested SNVs associated in the literature with CFS, one was associated in the control population with subjective fatigue and one with actigraphic measurements (FDR < 0.05). The genetic overlap of CFS risk with actigraphy and subjective fatigue phenotypes suggests that some biological mechanisms underlying pathologic fatigue in CFS patients also underlie fatigue symptoms at a broader population level. Therefore, understanding the biology of fatigue in general may inform our understanding of CFS pathophysiology.

Sleep and circadian rhythm alterations in myalgic encephalomyelitis/chronic fatigue syndrome and post-COVID fatigue syndrome and its association with cardiovascular risk factors: A prospective cohort study

ABSTRACT This study aimed to investigate circadian rhythm manifestations in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) patients (including a subpopulation of long-COVID patients) and matched healthy controls while also exploring their association with cardiovascular health variables. Thirty-one ME/CFS patients (75% females), 23 individuals diagnosed with post-COVID ME/CFS (56% females) and 31 matched healthy controls (68% females) were enrolled in this study. Demographic and clinical characteristics were assessed using validated self-reported outcome measures. Actigraphy data, collected over one week, were used to analyze the 24-h profiles of wrist temperature, motor activity, and sleep circadian variables in the study participants. Associations between lipid profile with endothelial dysfunction biomarkers (such as endothelin-1, ICAM-1 and VCAM-1) and with sleep and circadian variables were also studied. No differences were found in these variables between the two group of patients. Patients showed lower activity and worse sleep quality than matched healthy controls, together with a worse lipid profile than controls, that was associated with disturbances in the circadian temperature rhythm. ICAM-1 levels were associated with plasma lipids in healthy controls, but not in patients, who showed higher levels of endothelin-1 and VCAM-1. These findings suggest that lipid profiles in ME/CFS are linked to disrupted circadian rhythms and sleep patterns, likely due to endothelial dysfunction. Furthermore, they highlight the intricate relationship between sleep, circadian rhythms, and cardiovascular health in this condition.

Children with obesity have poorer circadian health as assessed by a global circadian health score.

Circadian health refers to individuals' well-being and balance in terms of their circadian rhythm. It is influenced by external cues. In adults, a close relationship between circadian-related alterations and obesity has been described. However, 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 differed between children with and without obesity as determined by a global circadian score (GCS) in a school-age population. Four hundred and thirty-two children (7-12 years) were recruited in Spain. Non-invasive tools were used to calculate 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. Circadian health, as assessed by the GCS, differed 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. Different 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). 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.

Sleep problems and circadian rhythm functioning in autistic children, autism with co-occurring attention deficit hyperactivity disorder, and typically developing children: A comparative study.

Sleep problems are common in autism spectrum disorder (ASD) and different factors can contribute to its occurrence in this population. Misalignment of the biological clock (our circadian system) has been described as one possible explanation. While there is a body of research on sleep problems, relatively less is known about circadian functioning and the specific population of autistic children with co-occurring attention deficit hyperactivity disorder (ADHD). Using an ambulatory circadian monitoring (ACM) system, which resembles a common watch, we gathered sleep parameters and the different rhythms obtained from measuring motor activity, light exposure and distal temperature in 87 autistic children and adolescents, 27 of whom were diagnosed with co-occurring ADHD, and 30 neurotypical children and adolescents as a comparison group. Autistic children and, especially, those with co-occurring ADHD showed greater motor activity during sleep which would be worth studying in future projects which could better define this restless sleep. Of note, we observed an atypical pattern of wrist temperature, with higher values in neurotypical children, followed by autistic children and, ultimately, those with co-occurring ADHD. Temperature is one of the most valuable factors evaluated here as it is closely connected to sleep-wakefulness and the hormone melatonin. Its special pattern during day and nighttime would support the hypothesis of an atypical secretion of melatonin in autistic individuals which would also link with the higher presence of sleep problems in this neurodevelopmental condition.

A Low-Cost Wearable Device to Estimate Body Temperature Based on Wrist Temperature.

The remote monitoring of vital signs and healthcare provision has become an urgent necessity due to the impact of the COVID-19 pandemic on the world. Blood oxygen level, heart rate, and body temperature data are crucial for managing the disease and ensuring timely medical care. This study proposes a low-cost wearable device employing non-contact sensors to monitor, process, and visualize critical variables, focusing on body temperature measurement as a key health indicator. The wearable device developed offers a non-invasive and continuous method to gather wrist and forehead temperature data. However, since there is a discrepancy between wrist and actual forehead temperature, this study incorporates statistical methods and machine learning to estimate the core forehead temperature from the wrist. This research collects 2130 samples from 30 volunteers, and both the statistical least squares method and machine learning via linear regression are applied to analyze these data. It is observed that all models achieve a significant fit, but the third-degree polynomial model stands out in both approaches. It achieves an R2 value of 0.9769 in the statistical analysis and 0.9791 in machine learning.

Blue Light and Temperature Actigraphy Measures Predicting Metabolic Health Are Linked to Melatonin Receptor Polymorphism.

This study explores the relationship between the light features of the Arctic spring equinox and circadian rhythms, sleep and metabolic health. Residents (N = 62) provided week-long actigraphy measures, including light exposure, which were related to body mass index (BMI), leptin and cortisol. Lower wrist temperature (wT) and higher evening blue light exposure (BLE), expressed as a novel index, the nocturnal excess index (NEIbl), were the most sensitive actigraphy measures associated with BMI. A higher BMI was linked to nocturnal BLE within distinct time windows. These associations were present specifically in carriers of the MTNR1B rs10830963 G-allele. A larger wake-after-sleep onset (WASO), smaller 24 h amplitude and earlier phase of the activity rhythm were associated with higher leptin. Higher cortisol was associated with an earlier M10 onset of BLE and with our other novel index, the Daylight Deficit Index of blue light, DDIbl. We also found sex-, age- and population-dependent differences in the parametric and non-parametric indices of BLE, wT and physical activity, while there were no differences in any sleep characteristics. Overall, this study determined sensitive actigraphy markers of light exposure and wT predictive of metabolic health and showed that these markers are linked to melatonin receptor polymorphism.

Measuring thermal comfort using wearable technology in transient conditions during office activities

This paper presents an experiment for assessing thermal comfort of occupants in the built environment, from a subjective perspective, focusing on office environment; a dedicated measurement campaign using sensors for acquisition of physiological and environmental parameters was conducted. Skin temperature was measured with two sensors: a minimally invasive sensor for measuring wrist temperature, and a thermal camera to retrieve forehead temperature; simultaneously, heart rate variability was measured using a wearable device. 15 participants were exposed to dynamic changes of air temperature. Data was collected to measure the participants’ thermal sensation vote, with machine learning algorithms. Decision Tree provided higher performances, using a dataset made of wrist temperature, heart rate variability features and air temperature, with mean average error and mean absolute percentage error of 0.86 and 20.9%. The research contributes to thermal comfort personalization in the built environment, to improve well-being and productivity of occupants using minimally invasive sensor network.

Diurnal rhythms of wrist temperature are associated with future disease risk in the UK Biobank

Many chronic disease symptomatologies involve desynchronized sleep-wake cycles, indicative of disrupted biorhythms. This can be interrogated using body temperature rhythms, which have circadian as well as sleep-wake behavior/environmental evoked components. Here, we investigated the association of wrist temperature amplitudes with a future onset of disease in the UK Biobank one year after actigraphy. Among 425 disease conditions (range n = 200-6728) compared to controls (range n = 62,107-91,134), a total of 73 (17%) disease phenotypes were significantly associated with decreased amplitudes of wrist temperature (Benjamini-Hochberg FDR q < 0.05) and 26 (6.1%) PheCODEs passed a more stringent significance level (Bonferroni-correction α < 0.05). A two-standard deviation (1.8° Celsius) lower wrist temperature amplitude corresponded to hazard ratios of 1.91 (1.58-2.31 95% CI) for NAFLD, 1.69 (1.53-1.88) for type 2 diabetes, 1.25 (1.14-1.37) for renal failure, 1.23 (1.17-1.3) for hypertension, and 1.22 (1.11-1.33) for pneumonia (phenome-wide atlas available at http://bioinf.itmat.upenn.edu/biorhythm_atlas/). This work suggests peripheral thermoregulation as a digital biomarker.

Skin temperature indexes to evaluate thermal sensation and cognitive performance in hot environments

With further study on human thermal comfort, the correlation between human thermal physiological parameters and thermal sensation in different environments has received increasing attention from many researchers. And the relationship between skin temperature and thermal sensation and cognitive performance is being further explored. In this study, the skin temperature indexes to evaluate thermal sensation and cognitive performance in hot environments were explored based on human objective responses (skin temperature, cognitive tests) and subjective assessments (thermal sensation) in climate chamber. The results showed that the CVs (coefficient of variation) and TDs (maximum temperature difference) of skin temperature were significantly higher during stage II(>30min) than during stage I(≤30min) (p < 0.05). The forehead and wrist were highly correlated with thermal sensation in stage I and stage II, respectively. Meanwhile forehead and wrist thermoneutral temperature ranges were 34.4 °C∼34.8 °C and 34.3 °C∼34.6 °C, respectively. Cognitive performance was highly correlated with skin temperature at the wrist during stage II (R = −0.96**). And the best performance was achieved when the TSV was approximately −0.008 and the wrist temperature was 34.5 °C. Overall, 34.5 °C was recommended for exposed areas such as the forehead and wrist to obtain best cognitive performance and thermal sensation.

Response to Melatonin Treatment in Children With Autism spectrum Disorder and Relationship to Sleep Parameters and Melatonin Levels.

Melatonin is one of the most used pharmacologic treatments for sleep problems in autism spectrum disorder, though its relationship with circadian and sleep parameters is still not well stablished. A naturalistic study was conducted in children with autism spectrum disorder, previously drug-naïve, before and after treatment with immediate-release melatonin. Circadian rhythms and sleep parameters were studied using an ambulatory circadian-monitoring device, and saliva samples were collected enabling determination of dim light melatonin onset. Twenty-six children with autism spectrum disorder (age 10.50 ± 2.91) were included. Immediate-release melatonin modified circadian rhythm as indicated by wrist skin temperature, showing an increase at night. A positive correlation was found between time of peak melatonin and sleep efficiency improvement values. Sleep-onset latency and efficiency improved with immediate-release melatonin. Immediate-release melatonin could be an effective treatment to improve sleep onset and restore a typical pattern of wrist temperature, which appears to be lost in autism spectrum disorder.

Skin Temperature Circadian Rhythms and Dysautonomia in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: The Role of Endothelin-1 in the Vascular Tone Dysregulation.

There is accumulating evidence of autonomic dysfunction in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS); however, little is known about its association with circadian rhythms and endothelial dysfunction. This study aimed to explore the autonomic responses through an orthostatic test and analysis of the peripheral skin temperature variations and vascular endothelium state in ME/CFS patients. Sixty-seven adult female ME/CFS patients and 48 healthy controls were enrolled. Demographic and clinical characteristics were assessed using validated self-reported outcome measures. Postural changes in blood pressure, heart rate, and wrist temperature were recorded during the orthostatic test. Actigraphy during one week was used to determine the 24-h profile of peripheral temperature and activity. Circulating endothelial biomarkers were measured as indicators of endothelial functioning. Results showed that ME/CFS patients presented higher blood pressure and heart rate values than healthy controls in the supine and standing position (p < 0.05 for both), and also a higher amplitude of the activity rhythm (p < 0.01). Circulating levels of endothelin-1 (ET-1) and vascular cell adhesion molecule-1 (VCAM-1) were significantly higher in ME/CFS (p < 0.05). In ME/CFS, ET-1 levels were associated with the stability of the temperature rhythm (p < 0.01), and also with the self-reported questionnaires (p < 0.001). This suggests that ME/CFS patients exhibited modifications in circadian rhythm and hemodynamic measures, which are associated with endothelial biomarkers (ET-1 and VCAM-1). Future investigation in this area is needed to assess dysautonomia and vascular tone abnormalities, which may provide potential therapeutic targets for ME/CFS.

New Insights into Stroke from Continuous Passively Collected Temperature and Sleep Data Using Wrist-Worn Wearables.

Actigraphy may provide new insights into clinical outcomes and symptom management of patients through passive, continuous data collection. We used the GENEActiv smartwatch to passively collect actigraphy, wrist temperature, and ambient light data from 27 participants after stroke or probable brain transient ischemic attack (TIA) over 42 periods of device wear. We computed 323 features using established algorithms and proposed 25 novel features to characterize sleep and temperature. We investigated statistical associations between the extracted features and clinical outcomes evaluated using clinically validated questionnaires to gain insight into post-stroke recovery. We subsequently fitted logistic regression models to replicate clinical diagnosis (stroke or TIA) and disability due to stroke. The model generalization performance was assessed using a leave-one-subject-out cross validation method with the selected feature subsets, reporting the area under the curve (AUC). We found that several novel features were strongly correlated (|r|>0.3) with stroke symptoms and mental health measures. Using selected novel features, we obtained an AUC of 0.766 to estimate diagnosis and an AUC of 0.749 to estimate whether disability due to stroke was present. Collectively, these findings suggest that features extracted from the temperature smartwatch sensor may reveal additional clinically useful information over and above existing actigraphy-based features.

Phase Response Curve to Light under Ambulatory Conditions: A Pilot Study for Potential Application to Daylight Saving Time Transitions.

Several studies have investigated the relationship between daylight saving time (DST) and sleep alterations, psychiatric disorders, cardiovascular events and traffic accidents. However, very few have monitored participants while maintaining their usual lifestyle before and after DST. Considering that DST transitions modify human behavior and, therefore, people's light exposure patterns, the aim of this study was to investigate the potential effects of DST on circadian variables, considering sleep and, for the first time, the human phase response curve to light. To accomplish this, eight healthy adults (33 ± 11 years old, mean ± SD) were recruited to monitor multivariable circadian markers and light exposure by means of a wearable ambulatory monitoring device: Kronowise®. The following night phase markers were calculated: midpoints of the five consecutive hours of maximum wrist temperature (TM5) and the five consecutive hours of minimum time in movement (TL5), sleep onset and offset, as well as sleep duration and light intensity. TM5 for wrist temperature was set as circadian time 0 h, and the balance between advances and delays considering the phase response curve to light was calculated individually before and after both DST transitions. To assess internal desynchronization, the possible shift in TM5 for wrist temperature and TL5 for time in movement were compared. Our results indicate that the transition to DST seems to force the circadian system to produce a phase advance to adapt to the new time. However, the synchronizing signals provided by natural and personal light exposure are not in line with such an advance, which results in internal desynchronization and the need for longer synchronization times. On the contrary, the transition back to ST, which implies a phase delay, is characterized by a faster adaptation and maintenance of internal synchronization, despite the fact that exposure to natural light would favor a phase advance. Considering the pilot nature of this study, further research is needed with higher sample sizes.

Investigation of personal thermal comfort in office building by implementation of smart bracelet: A case study

Thermal comfort is significant factor in the overall satisfaction level and affects directly the building energy performance within heating and cooling systems. Through this work, the short-term field investigation of smart monitoring devices was applied for personal thermal comfort investigation. The conceptual approach was presented for the case of specific office building. The low cost sensing technology was implemented in this investigation as key advantage of herein considered approach. The users wore smart bracelets which monitored physiological parameters, i.e. skin wrist temperature and heart rate during the day in office facility. Simultaneously, the environmental parameters were measured (air temperature, relative air humidity and CO2 concentration). Field survey (subjective response from occupants) was conducted as well. Wrist skin temperature from the individual users has a positive correlation with thermal comfort evaluation for female (0.54) and male (0.36) user. Additionally, for the data from male user, the CO2 concentration in the office had a positive correlation as well (0.45). The positive correlation between examined parameters endorse the application of the proposed measuring technology (wearable device) for detection of personal thermal comfort. The proposed approach represents a basis for further development of novel regulation approach for heating/cooling systems in buildings, since it allows more complex evaluation of the personal thermal comfort factors.

Reliability of Non-Contact Infrared Thermometers for Fever Screening Under COVID-19.

PurposeFever is one of the most typical clinical symptoms of coronavirus disease 2019 (COVID-19), and non-contact infrared thermometers (NCITs) are commonly used to screen for fever. However, there is a lack of authoritative data to define a “fever” when an NCIT is used and previous studies have shown that NCIT readings fluctuate widely depending on ambient temperatures and the body surface site screened. The aim of this study was to establish cut-off points for normal temperatures of different body sites (neck, forehead, temples, and wrist) and investigate the accuracy of NCITs at various ambient temperatures to improve the standardization and accuracy of fever screening.Patients and MethodsA prospective investigation was conducted among 904 participants in the outpatient and emergency departments of Chengdu Women’s and Children’s Central Hospital. Body temperature was measured using NCITs and mercury axillary thermometers. A receiver operating characteristic curve was used to determine the accuracy of body temperature detection at the four body surface sites. Data on participant characteristics were also collected.ResultsAmong the four surface sites, the neck temperature detection group had the highest accuracy. When the neck temperature was 37.35°C as the optimum fever diagnostic threshold, the sensitivity was 0.866. The optimum fever diagnostic thresholds for forehead, temporal, and wrist temperature were 36.65°C, 36.65°C, and 36.75°C, respectively. Moreover, triple neck temperature detection had the highest sensitivity, up to 0.998, whereas the sensitivity of triple wrist temperature detections was 0.949. Notably, the accuracy of NCITs significantly reduced when the temperature was lower than 18°C.ConclusionNeck temperature had the highest accuracy among the four NCIT temperature measurement sites, with an optimum fever diagnostic threshold of 37.35°C. Considering the findings reported in our study, we recommend triple neck temperature detection with NCITs as the fever screening standard for COVID-19.

Forehead, Temple and Wrist Temperature Assessment of Ethnic Groups using Infrared Technology

Non-contact infrared sensors are widely used as a diagnostic tool for elevated body temperature during initial screening for coronaviruses. The aim of this study was to investigate the thermal differences at three anatomical points: temple, forehead, and wrist, in the initial screening for temperature indicative of febrile and non-febrile states in skin pigmentation variations in Black, Half-Black and Caucasian skins, correlated with height and weight variables. Temperatures were obtained by means of an infrared thermometer in 289 volunteers with mean age of 18.30 ± 0.76, in a controlled environment according to Singapore Standard, SS582 part 1 and 2, normative standard IEC 80601-2-59, with standard technical protocols established by the International Organization for Standardization, ISO / TR 13154. The data were processed in MATLAB® R2021a, and data normality verified by Kolmogorov-Smirnov test, non-parametric data paired between temple / forehead / wrist were compared using the Wilcoxon signed-rank test. The results show different median temperatures in these anatomical regions, 37.2°C at the temple, 36.8°C at the forehead and 36.4°C at the wrist. As the temple region presents a temperature higher than the other investigated regions and, therefore, close to the core temperature, it should be considered for the initial screening of SARS-CoV-2 when using non-contact infrared thermometers. Furthermore, no significant changes were found due to variation in skin tone, height, or weight.

A Wearable Skin Temperature Monitoring System for Early Detection of Infections

This paper describes a wearable, open-source wrist temperature monitoring system that enables the reliable identification of slowly-varying skin temperature patterns that may be indicative of infections. The hardware platform uses a Bluetooth Low Energy (BLE) wireless interface and includes three skin temperature sensors, a thermally-isolated ambient temperature sensor, an inertial measurement unit (IMU), and a Galvanic skin response (GSR) sensor. A template-matching algorithm is used to detect weak but long-lived anomalous temperature patterns that deviate from the normal circadian rhythm are thus may be driven by infections. Experimental and simulation results confirm that small temperature anomalies (peak value <0.4°C) extending over 2–3 weeks can be detected with a total error rate <10%.

Wearable Device for Observation of Physical Activity with the Purpose of Patient Monitoring Due to COVID-19

In late 2019, a new genre of coronavirus (COVID-19) was first identified in humans in Wuhan, China. In addition to this, COVID-19 spreads through droplets, so quarantine is necessary to halt the spread and to recover physically. This modern urgency creates a critical challenge for the latest technologies to detect and monitor potential patients of this new disease. In this vein, the Internet of Things (IoT) contributes to solving such problems. This paper proposed a wearable device that utilizes real-time monitoring to detect body temperature and ambient conditions. Moreover, the system automatically alerts the concerned person using this device. The alert is transmitted when the body exceeds the allowed temperature threshold. To achieve this, we developed an algorithm that detects physical exercise named “Continuous Displacement Algorithm” based on an accelerometer to see whether a potential temperature rise can be attributed to physical activity. The people responsible for the person in quarantine can then connect via nRF Connect or a similar central application to acquire an accurate picture of the person’s condition. This experiment included an Arduino Nano BLE 33 Sense which contains several other sensors like a 9-axis IMU, several types of temperature, and ambient and other sensors equipped. This device successfully managed to measure wrist temperature at all states, ranging from 32 °C initially to 39 °C, providing better battery autonomy than other similar devices, lasting over 12 h, with fast charging capabilities (500 mA), and utilizing the BLE 5.0 protocol for data wireless data transmission and low power consumption. Furthermore, a 1D Convolutional Neural Network (CNN) was employed to classify whether the user is feverish while considering the physical activity status. The results obtained from the 1D CNN illustrated the manner in which it can be leveraged to acquire insight regarding the health of the users in the setting of the COVID-19 pandemic.

Chronodisruption and diet associated with increased cardiometabolic risk in coronary heart disease patients: the CORDIOPREV study

Individuals with evening chronotypes are prone to suffer chronodisruption and display worse lifestyle habits than morning-types, exhibiting higher cardiovascular diseases (CVD). However, it is unknown whether CVD patients, who are evening chronotypes, have higher cardiometabolic risk than morning-types. This study explored whether individual chronotypes were associated with cardiometabolic risk in patients from the CORDIOPREV study (n=857). We also investigated whether potential associations were moderated by long-term consumption of two healthy diets (Mediterranean and Low-fat diets). This population was classified into chronotypes using the Morningness-Eveningness Questionnaire. Seven-day daily rhythms in wrist temperature (T), rest-activity (A) and position (P) were recorded in a subset of patients (n=168), and an integrative variable TAP was determined. Metabolic Syndrome (MetS) was determined at baseline, and metabolic and inflammation markers were measured at baseline and yearly during the 4 years of follow-up. Differences in several lifestyle factors were analyzed according to chronotype. At all times, evening-types had higher triglycerides, C-reactive protein and homocysteine and lower high density lipoprotein cholesterol than morning-types (P < 0.05). Evening-types had a higher prevalence of MetS (OR 1.58 IC 95% [1.10 - 2.28], P = 0.01). Moreover, they were more sedentary, displayed less and delayed physical activity and ate and slept later. In addition, evening-types had lower amplitude, greater fragmentation, lower robustness and less stable circadian pattern at TAP (P < 0.01), all related to a less healthy circadian pattern. In conclusion, evening-types with CVD had higher cardiometabolic risk and less robust circadian-related rhythms than morning-types, regardless of the nutritional intervention.