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| Name | Class |
|---|---|
| Universidad de Granada | OTHER |
| University of Colorado, Denver | OTHER |
| Instituto Nacional de Salud Publica, Mexico | OTHER |
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Insomnia is a highly prevalent sleep disorder worldwide, with an increasing incidence in athletes, older adults, university students, and individuals with metabolic syndrome. This disorder has been associated with metabolic dysfunction, cardiovascular diseases, and genetic instability. Recent evidence suggests that insomnia negatively impacts cardiorespiratory fitness, insulin sensitivity, and overall health through mechanisms involving neuroendocrine dysregulation, oxidative stress, and alterations in energy metabolism. However, the specific biological and environmental factors that contribute to its prevalence and health consequences remain poorly understood, particularly across different populations. Understanding these associations is crucial for developing effective prevention and intervention strategies to mitigate the long-term impact of insomnia. Therefore, this study aims to analyze the impact of insomnia on body composition, cardiorespiratory fitness, metabolic flexibility, and DNA integrity, across populations with high prevalence of insomnia, including athletes, older adults, university students, and individuals with metabolic syndrome. This study will also investigate which biological and lifestyle behaviors contribute to insomnia and its health consequences. By doing so, this work will provide critical insights into the physiological and molecular mechanisms that link insomnia with metabolic and cardiovascular dysfunction, contributing to the development of targeted interventions for at-risk populations
Insomnia is a prevalent sleep disorder characterized by difficulty initiating or maintaining sleep despite adequate sleep opportunities and an appropriate sleep environment. It affects 10-50% of the adult population worldwide, with several biological, sociodemographic, and psychological-behavioral factors contributing to its occurrence. Notably, its prevalence is higher in women than in men (risk ratio: 1.58, p<0.01) and increases with age, affecting 30-48% of older adults compared to 12-20% of young adults. Additionally, insomnia is more frequently reported among university students than in the general population (18.5% vs. 7.5%), and 13-70% of elite athletes experience persistent sleep disturbances indicative of insomnia.
Recent research has highlighted the long-term negative impact of insomnia on quality of life, as it induces chronic fatigue and excessive daytime sleepiness, which are strongly associated with reduced work productivity, academic performance, and athletic capabilities. Additionally, insomnia has been linked to an increased risk of cardiovascular and metabolic diseases, with a higher prevalence observed in individuals with obesity, type 2 diabetes, and hypertension.
Some studies have reported an inverse association between multiple indicators of insomnia and cardiorespiratory fitness in individuals without chronic diseases, further reinforcing the connection between insomnia and cardiovascular disease risk. This phenomenon may be driven by dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis and the autonomic nervous system, both of which contribute to increased cardiac contractility and altered neuroendocrine function. Moreover, the observed negative correlation between insomnia and oxygen uptake capacity suggests that insomnia may compromise capillary and mitochondrial density as well as cardiovascular efficiency, which are key determinants of maximal oxygen consumption (VO₂max). Another plausible mechanism underlying this association is reduced heart rate variability (HRV) in individuals with chronic insomnia, likely resulting from elevated norepinephrine and cortisol levels, which are known to heighten sympathetic nervous system activity and impair cardiovascular function.
Beyond its cardiovascular implications, sleep deficiency disrupts metabolic homeostasis, promoting high-calorie food consumption through both hormonal (e.g., increased ghrelin secretion) and neurocognitive mechanisms (e.g., heightened hedonic drive for food intake). Over time, these physiological alterations contribute to body weight gain and insulin resistance, increasing the risk of metabolic disorders such as obesity and type 2 diabetes.
At the molecular level, chronic sleep deprivation has been shown to impair DNA repair cycles, which may contribute to the development of metabolic and cardiovascular diseases. Specifically, fragmentation of DNA strands has been observed following sleep restriction, leading to slower chromosomal dynamics and impaired cellular recovery. Additionally, sleep deprivation has demonstrated genotoxic effects in multiple organs and tissues, increasing oxidative DNA damage.
Despite the growing body of evidence linking insomnia to cardiovascular and metabolic dysfunction, most human studies have focused primarily on young adult males with low physical activity levels and without chronic diseases. Similarly, the genotoxic effects of sleep disorders have been assessed mainly in preclinical models, with limited investigation of their correlation with cardiovascular and metabolic biomarkers in humans.
Given these knowledge gaps, this study aims to examine the physiological and molecular consequences of insomnia across diverse populations, including athletes, older adults, university students, and individuals with metabolic syndrome. This research will provide valuable insights into the mechanisms underlying insomnia-related dysfunctions, ultimately contributing to the development of targeted interventions to mitigate its long-term health effects. The findings from this study will play a crucial role in guiding future clinical interventions aimed at improving sleep quality and metabolic health. Given that 27-40% of the Mexican adult population is affected by insomnia, addressing this disorder has become a public health priority. This research is aligned with the United Nations Sustainable Development Goals (SDGs), particularly in the areas of (i) health and well-being, (ii) quality education, and (iii) partnerships for achieving these objectives.
Additionally, the project will provide academic training opportunities for undergraduate and graduate students, reinforcing their competencies in research methodologies, data analysis, and clinical evaluations. Furthermore, collaboration with the National Institute of Public Health and the University of Granada will foster international research partnerships, enhancing the study's scientific impact.
By addressing the underlying insomnia and its multisystem effects, this project will contribute significantly to the prevention, diagnosis, and treatment of sleep disorders in vulnerable populations, ultimately improving overall public health and quality of life.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Healthy young adults | This group consists of individuals aged 18-35 with no prior diagnosis of insomnia, sleep disorders, or chronic metabolic conditions. Body composition, cardiorespiratory fitness, lifestyle behaviors, DNA integrity and metabolic flexibility will be examined in all participants. |
| |
| College Students | University students aged 18-35 years, with current affiliation to the Universidad Autonoma de Baja California. Body composition, cardiorespiratory fitness, lifestyle behaviors, DNA integrity and metabolic flexibility will be examined in all participants. |
| |
| Athletes | Amateur and professional athletes with 2 years of training and competitive experience. Body composition, cardiorespiratory fitness, lifestyle behaviors, DNA integrity and metabolic flexibility will be examined in all participants. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Exercise | Other | A cardiopulmonary exercise test in a treadmill will be performed after an overnight fasting. Gas exchange, heart rate, and muscle oxygen saturation levels will be assessed continuously during the entire test. Blood pressure and rate of perceived exertion will be recorded prior the end of each stage whereas blood glucose concentration will be assessed before and after the test. All the hemodynamic parameters will be assessed at rest to standardize the cardio-metabolic condition of the participants prior to exercise testing. Maximal exertion will be requested from all participants except elders, in whom a submaximal test will be applied, following the guidelines provided by the American College of Sports Medicine. From this trial, maximal oxygen uptake, ventilatory thresholds/dynamics, chronotropic and inotropic response, and metabolic flexibility will be examined. A trained exercise physiologist will supervise all the tests and validate the obtained data. |
| Measure | Description | Time Frame |
|---|---|---|
| Insomnia severity index | A Spanish version of the insomnia severity index scale will be applied to examine the absence or presence of clinical insomnia. This five-item scale provides a range score between 0-28 that is interpreted as follows:
| Day 1 |
| Daytime sleepiness | A Spanish version of the Epworth Sleepiness Scale will be applied to examine day-time sleepiness. This is an 8-items self-administered questionnaire that provides a range score between 0-24, interpreted as follows:
| Day 1 |
| Sleep quality Index | A Spanish version of the Pittsburgh Sleep Quality Index scale will be applied to examine sleep quality. This 9-item scale provides a range score between 0-21 that is interpreted as follows: *<5 good sleep quality *>5 poor sleep quality | Day 1 |
| Body composition | Bioelectrical impedance analysis (BIA) will be used to measure the components of the body, including fat mass (kg, %), lean mass (kg, %), muscle mass (kg), visceral adipose tissue area (cm2), phase angle (°), and total body water (L), through a mechanism of resistance and reactance. A multi-frequency device (1-1000 kHz), with 8-point Tactile Electrode System will be used for this measurements (InBody 770, KOR). This system also provides a segmental analysis of fat mass (kg, %), and lean mass (kg, %) (right/left arms or legs, and trunk). A body composition score, ranging from 0-100, will be retrieved from a predetermined algorithm provided by the fabricant. | Day 1 |
| DNA integrity |
| Measure | Description | Time Frame |
|---|---|---|
| Nutrition | A semi quantitative food frequency questionnaire will be applied to collect data about macronutrient intake and supplements consumption. Hierarchical consumption of each food groups will be also assessed. Last meal consumed prior to exercise testing will be also recorded in conjunction with fasting time. | Responding the food frequency questionnaire will take around 10 minutes and the questionnaire will be applied at the single visit the subjects will be requested to attend the laboratory. |
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Inclusion Criteria:
Each population group will meet the following inclusion criteria:
Healthy Individuals (18-35 years old, men and women)
Athletes (18-35 years old, men and women)
*Engaged in structured sports training with a physical activity level >1500 MET-min/week
Older Adults (65-75 years old, men and women)
*Free of cognitive or mental health disorders. No specific cardiometabolic or body composition criteria due to the study's exploratory nature.
University Students (18-35 years old, men and women)
*No specific cardiometabolic or body composition criteria due to the study's exploratory nature.
Individuals with Metabolic Syndrome (18-35 years old, men and women)
Exclusion Criteria:
Individuals with rotating or night-shift work schedules (e.g., emergency personnel, security guards), as circadian rhythm disruptions significantly impact sleep quality
Transgender and intersex people wont be considered for this study given that hormonal therapy could influence many of the metabolic and cardiorespiratory outcomes that will be examined in this study. People identified as heterosexual, bisexual, or gay/lesbian will be considered for participation if they fulfill the criteria settled for each study cohort.
The study will recruit 60 healthy individuals, 60 athletes, 60 university students, 60 older adults, and 60 individuals with metabolic syndrome, ensuring a 1:1 male-to-female ratio in all groups . Participants will be classified based on the presence or absence of insomnia (cases vs. controls), allowing for comparisons of physiological and molecular indicators related to insomnia.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Ivan Renteria, PhD | Contact | +52 646 152 823 | 65600 | irenteria@uabc.edu.mx |
| Name | Affiliation | Role |
|---|---|---|
| Isaac A Chavez-Guevara, PhD | Universidad Autonoma de Baja California | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Laboratorio de Fisiologia Aplicada al Ejercicio | Recruiting | Ensenada | Estado de Baja California | 22890 | Mexico |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 23866243 | Background | Gonzalez-Ramirez MT, Rodriguez-Ayan MN, Hernandez RL. The perceived stress scale (PSS): normative data and factor structure for a large-scale sample in Mexico. Span J Psychol. 2013;16:E47. doi: 10.1017/sjp.2013.35. | |
| 37424534 | Background | Chavez-Guevara IA. Assessment of metabolic flexibility by measuring maximal fat oxidation during submaximal intensity exercise: Can we improve the analytical procedures? Sports Med Health Sci. 2023 Feb 14;5(2):156-158. doi: 10.1016/j.smhs.2023.02.001. eCollection 2023 Jun. |
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Throughout the study, personal data collected from participants will include medical affiliation, family and personal medical history, social security number, socioeconomic information, and contraceptive use (for women only). These data, along with all clinical, psychometric, and behavioral information, will be accessible exclusively to the principal investigator and the research team.
All individual records will be kept for five years following the Official Mexican Standard for the management of clinical records in human research. After this period, physical documents will be shredded and disposed of properly.
All participant records will be securely stored in the Laboratory of Applied Exercise Physiology, with physical documents kept under restricted access and digital records stored in a private Google Drive folder. To further protect participant confidentiality, once individual analyses are completed, all identifying information will be removed, and data will be anonymized in an Excel database.
Only aces to final datasets will be available to researchers associated to this study after appropiate request via Google Drive. Only verified institutional emails will be accepted.
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Buccal epithelial cells and blood samples
| Elders | Older adults (65-75 years) without a medical history of cognitive disorders or mental health issues. Body composition, cardiorespiratory fitness, lifestyle behaviors, DNA integrity and metabolic flexibility will be examined in all participants. |
|
| Metabolic syndrome | Individuals aged 18-35 with previous diagnosis of metabolic syndrome. Body composition, cardiorespiratory fitness, lifestyle behaviors, DNA integrity and metabolic flexibility will be examined in all participants. |
|
|
|
| Bioelectrical Impedance | Other | Bioelectrical impedance analysis will be used to estimate body compartments through a mechanism of resistance and reactance (InBody 770, KOR) . The compartments measured include body cell mass, fat mass, extracellular tissue, lean mass, muscle mass, visceral adipose tissue area, phase angle, among others. |
|
| Micronucleus Assay | Genetic | The frequency of micronuclei, nuclear buds, basal cells, binucleated cells, condensed chromatin cells, karyorrhexis, karyolysis, and pyknosis will be determined through microscopic examination of exfoliated oral mucosal cells from each participant. |
|
| Physical activity and sedentary time | Behavioral | Physical activity and sedentary time will be assessed through the Spanish version of the International Questionnaire of Physical activity. In half of the analyzed subjects a wearable device (Fitbit luxe, Fit bit Inc) will be also used to record daily steps, energy expenditure and heart rate patterns. |
|
| Sleep | Behavioral | Insomnia severity index, sleep quality, somnolence and chronotype will be subjectively assessed in all participants, using validated scales such as the Pittsburgh, Epworth and ISI questionnaires. In half of the participants, sleep quality will be tracked by wearing a Fit band luxe device in the wrist. |
|
|
| blood sampling | Biological | The concentrations of glucose, glycated hemoglobin, and lipid profile will be determined through serum analysis using a blood chemistry analyzer (Spin120, Spinreact, ESP). Serum samples will be obtained by centrifuging peripheral venous blood samples (4-6 mL) collected in Vacutainer tubes at 2500 rpm for 10 minutes. From the same serum samples, circulating levels of insulin, ovarian hormones (estradiol and progesterone), insulin-like growth factor 1 (IGF-1), and vascular endothelial growth factor (VEGF) will be assessed using enzyme-linked immunosorbent assays (ELISA) on a microplate reader (iMark, BIORAD, USA), following the specifications provided by each kit manufacturer (Biotechne, USA; AccuBind, GUA). Glucose, insulin and triglyceride values obtained from the blood chemistry analyzer and ELISA assays will be used to calculate the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) and the triglyceride-glucose index. |
|
|
| psychometrics | Behavioral | Perceived stress will be obtained from the Perceived Stress Scale adapted for Mexican population. Additionally, depression and anxiety scores will be obtained from the Becks Depression Inventory, validated in Mexican adults. Ruminative thinking will be assessed through the short version of the Ruminative Responses Scale and substance abuse will be examined through the 10-items Drug Abuse Screening Test. Social media disorder and screen time will be also investigated from the Social Media Disorder Test and a cell-phone screen capture. |
|
| Nutritional Supplement | Behavioral | A semi quantitative food frequency questionnaire will be applied to collect data about macronutrient intake and supplements consumption. Hierarchical consumption of each food groups will be also assessed. Last meal consumed prior to exercise testing will be also recorded in conjunction with fasting time. |
|
|
| Genotyping | Genetic | The P10L polymorphism of the OPN4 gene, previously associated with chronic insomnia and severe daytime sleepiness in the Mexican population will be determined using RFLP-PCR assays. DNA will be extracted from previously collected blood samples (4 ml) using the Master Pure DNA purification kit from Epicentre (Illumina Inc., US). |
|
The frequency of micronuclei, nuclear buds, basal cells, binucleated cells, condensed chromatin cells, karyorrhexis, karyolysis, and pyknosis will be determined through microscopic examination of exfoliated oral mucosal cells from each participant. |
| Day 1 |
| OPN4 Single nucleotide polymorphism | The P10L polymorphism of the OPN4 gene, previously associated with chronic insomnia and severe daytime sleepiness in the Mexican population will be determined using RFLP-PCR assays. DNA will be extracted from previously collected blood samples (4 ml) using the Master Pure DNA purification kit from Epicentre (Illumina Inc., US). | Day 1 |
| Cardiorespiratory fitness | A cardiopulmonary exercise test in a treadmill will be performed after an overnight fasting. Gas exchange, heart rate, and muscle oxygen saturation levels will be assessed continuously during the entire test. Blood pressure and rate of perceived exertion will be recorded prior the end of each stage whereas blood glucose concentration will be assessed before and after the test. All the hemodynamic parameters will be assessed at rest to standardize the cardio-metabolic condition of the participants prior to exercise testing. Maximal exertion will be requested from all participants except elders, in whom a submaximal test will be applied, following the guidelines provided by the American College of Sports Medicine. From this trial, maximal oxygen uptake, ventilatory thresholds/dynamics, chronotropic and inotropic response, and will be examined. A trained exercise physiologist will supervise all the tests and validate the obtained data. | Day 1 |
| Metabolic flexibility | A cardiopulmonary exercise test in a treadmill will be performed after an overnight fasting. Gas exchange will be assessed continuously during the entire test to determine fat and carbohydrate oxidation. The maximal rate of fat oxidation, its shape and area under the curve will be defined in conjunction with the workload at which carbohydrates become the predominant energy source (cross over point). The increase in fat oxidation from rest to exercise will be also relativized to the change in energy expenditure to characterize metabolic flexibility. Resting metabolic rate and respiratory quotient will be also assessed at rest to standardize the metabolic condition of the participants prior to exercise testing. A trained exercise physiologist will supervise all the tests and validate the obtained data. | Day 1 |
| Homeostatic Model Assessment of Insulin Resistance | The serum concentrations of glucose and insulin will be determined under fasting conditions, using a blood chemistry analyzer (Spin120, Spinreact, ESP), and enzyme-linked immunosorbent assays (ELISA) on a microplate reader (iMark, BIORAD, USA) . Serum samples will be obtained by centrifuging peripheral venous blood samples collected in vacutainer tubes under fasting conditions (4-6 mL; 2500 rpm for 10 minutes). The Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) will be then calculated with the following equation: HOMA-IR = glucose (mg/dL) x insulin (uU/mL) / 405 | Day 1 |
| Cholesterol | Total cholesterol (mg/dL) will be will be assessed in a blood chemistry analyzer (Spin120, Spinreact, ESP). For this, serum samples will be obtained by centrifuging peripheral venous blood samples collected in Vacutainer tubes under fasting conditions (4-6 mL; 2500 rpm for 10 minutes). | Day 1 |
| Triglycerides | Triglycerides levels (mg/dL) will be will be assessed with a blood chemistry analyzer (Spin120, Spinreact, ESP). For this, serum samples will be obtained by centrifuging peripheral venous blood samples collected in Vacutainer tubes under fasting conditions (4-6 mL; 2500 rpm for 10 minutes). | Day 1 |
| High-density lipoproteins | High-density lipoproteins concentration (mg/dL) will be will be assessed with a blood chemistry analyzer (Spin120, Spinreact, ESP). For this, serum samples will be obtained by centrifuging peripheral venous blood samples collected in Vacutainer tubes under fasting conditions (4-6 mL; 2500 rpm for 10 minutes). | Day 1 |
| Insulin-like growth factor 1 | The concentration of Insulin-like growth factor 1 (0.1 - 30 ng/mL) will be will be assessed through an enzyme-linked immunosorbent assays (ELISA) on a microplate reader (iMark, BIORAD, USA). For this, serum samples will be obtained by centrifuging peripheral venous blood samples collected in Vacutainer tubes (4-6 mL; 2500 rpm for 10 minutes). | Day 1 |
| Vascular endothelial growth factor | The concentration of vascular endothelial growth factor (31.3 - 2,000 pg/mL) will be will be assessed through an enzyme-linked immunosorbent assays (ELISA) on a microplate reader (iMark, BIORAD, USA). For this, serum samples will be obtained by centrifuging peripheral venous blood samples collected in Vacutainer tubes (4-6 mL; 2500 rpm for 10 minutes). | Day 1 |
| Estradiol | The concentration of Estradiol (10 pg/ml - 4300 pg/mL) in young women will be will be assessed through an enzyme-linked immunosorbent assays (ELISA) on a microplate reader (iMark, BIORAD, USA). For this, serum samples will be obtained by centrifuging peripheral venous blood samples collected in Vacutainer tubes (4-6 mL; 2500 rpm for 10 minutes). Current stage of the menstrual cycle and contraceptive use will be recorded for a proper interpretation of Estradiol levels. | Day 1 |
| Progesterone | The concentration of Progesterone (0.15 ng/mL - 128 ng/mL) in young women will be will be assessed through an enzyme-linked immunosorbent assays (ELISA) on a microplate reader (iMark, BIORAD, USA). For this, serum samples will be obtained by centrifuging peripheral venous blood samples collected in Vacutainer tubes (4-6 mL; 2500 rpm for 10 minutes). Current stage of the menstrual cycle and contraceptive use will be recorded for a proper interpretation of Estradiol levels. | Day 1 |
| Self-Reported Physical Activity Level | Physical activity and sedentary time will be assessed through the Spanish version of the International Questionnaire of Physical activity, a 7-item tool that allows the estimation of low, moderate, and vigorous physical activity (Mets/min/week), for representing the physical activity level of each participant. | Day 1 |
| Perceived Stress | Perceived stress will be obtained from the Perceived Stress Scale, previously adapted and validated for Mexican population. This 14-item scale provides a range score between 0-40 that is interpreted as follows:
| Day 1 |
| Depressive symptoms | Characteristic attitudes and symptoms of depression will be assessed through the Beck Depression Inventory (BDI-II), a 21-item, self-report rating inventory with a range score between 0-63, with the following cut-offs:
| Day 1 |
| Ruminative thinking | Ruminative thinking will be assessed through the Spanish, short version of the Ruminative Responses Scale, which consist of 10-items using 4-points Likert type scales with anchors of 1: Never and 4: Always, that measure an individuals response to negative emotions describing self and symptom-focused responses to depressed mood. Ruminative thinking can be then categorized as follows: <14 = low 14-26 =moderate >26 = high | Day 1 |
| Substance abuse | Substance abuse will be assessed with the Drug Abuse Screening Test, a 20-item self-report questionnaire that assesses the extent of the problems related to drug misuse, using two response options in each item (yes-no). The DAST total score is computed by summing all items; thus, the total score might range from 0 to 20 | Day 1 |
| Screen time | Monthly and weekly screen time will be obtained from screenshots voluntarily provided from each participants. Most used apps and its corresponding category (social media, tools, etc) will be also recorded. | Day 1 |
| 36373239 | Background | Duan D, Kim LJ, Jun JC, Polotsky VY. Connecting insufficient sleep and insomnia with metabolic dysfunction. Ann N Y Acad Sci. 2023 Jan;1519(1):94-117. doi: 10.1111/nyas.14926. Epub 2022 Nov 13. |
| 38511758 | Background | de Souza DV, Rosario BDA, Viana MB, Pisani LP, da Silva GN, Ribeiro DA. Sleep deprivation induces genetic damage in mammalian cells: a systematic review. Rev Assoc Med Bras (1992). 2024 Mar 15;70(1):e20231097. doi: 10.1590/1806-9282.20231097. eCollection 2024. No abstract available. |
| Background | Serra Laborde, P. L., Torterolo Pizzuti, C., & Calvo Pesce, M. S. (2023). Calidad y cronotipo del sueño y su relación con la obesidad en población adulta. Revisión bibliográfica narrativa. Enfermería: Cuidados Humanizados, 12(2), e3213. https://doi.org/10.22235/ech.v12i2.3213 |
| 30837464 | Background | Zada D, Bronshtein I, Lerer-Goldshtein T, Garini Y, Appelbaum L. Sleep increases chromosome dynamics to enable reduction of accumulating DNA damage in single neurons. Nat Commun. 2019 Mar 5;10(1):895. doi: 10.1038/s41467-019-08806-w. |
| 23288976 | Background | Strand LB, Laugsand LE, Wisloff U, Nes BM, Vatten L, Janszky I. Insomnia symptoms and cardiorespiratory fitness in healthy individuals: the Nord-Trondelag Health Study (HUNT). Sleep. 2013 Jan 1;36(1):99-108. doi: 10.5665/sleep.2310. |
| 21411507 | Background | Knutson KL, Van Cauter E, Zee P, Liu K, Lauderdale DS. Cross-sectional associations between measures of sleep and markers of glucose metabolism among subjects with and without diabetes: the Coronary Artery Risk Development in Young Adults (CARDIA) Sleep Study. Diabetes Care. 2011 May;34(5):1171-6. doi: 10.2337/dc10-1962. Epub 2011 Mar 16. |
| 36280789 | Background | Chaput JP, McHill AW, Cox RC, Broussard JL, Dutil C, da Costa BGG, Sampasa-Kanyinga H, Wright KP Jr. The role of insufficient sleep and circadian misalignment in obesity. Nat Rev Endocrinol. 2023 Feb;19(2):82-97. doi: 10.1038/s41574-022-00747-7. Epub 2022 Oct 24. |
| 26298588 | Background | Jiang XL, Zheng XY, Yang J, Ye CP, Chen YY, Zhang ZG, Xiao ZJ. A systematic review of studies on the prevalence of insomnia in university students. Public Health. 2015 Dec;129(12):1579-84. doi: 10.1016/j.puhe.2015.07.030. Epub 2015 Aug 20. |
| 33329116 | Background | Zeng LN, Zong QQ, Yang Y, Zhang L, Xiang YF, Ng CH, Chen LG, Xiang YT. Gender Difference in the Prevalence of Insomnia: A Meta-Analysis of Observational Studies. Front Psychiatry. 2020 Nov 20;11:577429. doi: 10.3389/fpsyt.2020.577429. eCollection 2020. |
| 29066053 | Background | Benjamins JS, Migliorati F, Dekker K, Wassing R, Moens S, Blanken TF, Te Lindert BHW, Sjauw Mook J, Van Someren EJW. Insomnia heterogeneity: Characteristics to consider for data-driven multivariate subtyping. Sleep Med Rev. 2017 Dec;36:71-81. doi: 10.1016/j.smrv.2016.10.005. Epub 2016 Nov 9. |
| 28348990 | Background | Bhaskar S, Hemavathy D, Prasad S. Prevalence of chronic insomnia in adult patients and its correlation with medical comorbidities. J Family Med Prim Care. 2016 Oct-Dec;5(4):780-784. doi: 10.4103/2249-4863.201153. |
| Background | Carrillo-Mora, P., Barajas-Martinez, K.G., Sanchez-Vazquez, I., Rangel-Caballero, M.F. (2017). Trastornos del sueño: ¿qué son y cuáles son sus consecuencias? Revista de la Facultad de Medicina de la UNAM, 61(1), 6-20. |
| ID | Term |
|---|---|
| D007319 | Sleep Initiation and Maintenance Disorders |
| D008659 | Metabolic Diseases |
| D009043 | Motor Activity |
| ID | Term |
|---|---|
| D020919 | Sleep Disorders, Intrinsic |
| D020920 | Dyssomnias |
| D012893 | Sleep Wake Disorders |
| D009422 | Nervous System Diseases |
| D001523 | Mental Disorders |
| D009750 | Nutritional and Metabolic Diseases |
| D001519 | Behavior |
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| ID | Term |
|---|---|
| D015444 | Exercise |
| D005080 | Exercise Test |
| D017097 | Electric Impedance |
| D015162 | Micronucleus Tests |
| D012890 | Sleep |
| D001800 | Blood Specimen Collection |
| D001774 | Blood Chemical Analysis |
| D011594 | Psychometrics |
| D019587 | Dietary Supplements |
| D004435 | Eating |
| D005838 | Genotype |
| ID | Term |
|---|---|
| D009043 | Motor Activity |
| D009068 | Movement |
| D009142 | Musculoskeletal Physiological Phenomena |
| D055687 | Musculoskeletal and Neural Physiological Phenomena |
| D006334 | Heart Function Tests |
| D003935 | Diagnostic Techniques, Cardiovascular |
| D019937 | Diagnostic Techniques and Procedures |
| D003933 | Diagnosis |
| D012129 | Respiratory Function Tests |
| D003948 | Diagnostic Techniques, Respiratory System |
| D016552 | Ergometry |
| D008919 | Investigative Techniques |
| D004553 | Electric Conductivity |
| D004560 | Electricity |
| D055590 | Electromagnetic Phenomena |
| D060328 | Magnetic Phenomena |
| D055585 | Physical Phenomena |
| D009152 | Mutagenicity Tests |
| D005821 | Genetic Techniques |
| D009424 | Nervous System Physiological Phenomena |
| D013048 | Specimen Handling |
| D019411 | Clinical Laboratory Techniques |
| D011677 | Punctures |
| D013514 | Surgical Procedures, Operative |
| D019963 | Clinical Chemistry Tests |
| D011581 | Psychological Tests |
| D004191 | Behavioral Disciplines and Activities |
| D005502 | Food |
| D000066888 | Diet, Food, and Nutrition |
| D010829 | Physiological Phenomena |
| D019602 | Food and Beverages |
| D009747 | Nutritional Physiological Phenomena |
| D004068 | Digestive System Physiological Phenomena |
| D055688 | Digestive System and Oral Physiological Phenomena |
| D055614 | Genetic Phenomena |
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