1
|
Lian XQ, Jiang K, Chen XX, Dong HC, Zhang YQ, Wang LS. Association between late sleeping and major adverse cardiovascular events in patients with percutaneous coronary intervention. BMC Public Health 2024; 24:2100. [PMID: 39097694 PMCID: PMC11297643 DOI: 10.1186/s12889-024-19634-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Accepted: 07/29/2024] [Indexed: 08/05/2024] Open
Abstract
BACKGROUND Sleeping late has been a common phenomenon and brought harmful effects to our health. The purpose of this study was to investigate the association between sleep timing and major adverse cardiovascular events (MACEs) in patients with percutaneous coronary intervention (PCI). METHODS Sleep onset time which was acquired by the way of sleep factors questionnaire in 426 inpatients was divided into before 22:00, 22:00 to 22:59, 23:00 to 23:59 and 24:00 and after. The median follow-up time was 35 months. The endpoints included angina pectoris (AP), new myocardial infarction (MI) or unplanned repeat revascularization, hospitalization for heart failure, cardiac death, nonfatal stroke, all-cause death and the composite endpoint of all events mentioned above. Cox proportional hazards regression was applied to analyze the relationship between sleep timing and endpoint events. RESULTS A total of 64 composite endpoint events (CEEs) were reported, including 36 AP, 15 new MI or unplanned repeat revascularization, 6 hospitalization for heart failure, 2 nonfatal stroke and 5 all-cause death. Compared with sleeping time at 22:00-22:59, there was a higher incidence of AP in the bedtime ≥ 24:00 group (adjusted HR: 5.089; 95% CI: 1.278-20.260; P = 0.021). In addition, bedtime ≥ 24:00 was also associated with an increased risk of CEEs in univariate Cox regression (unadjusted HR: 2.893; 95% CI: 1.452-5.767; P = 0.003). After multivariable adjustments, bedtime ≥ 24:00 increased the risk of CEEs (adjusted HR: 3.156; 95% CI: 1.164-8.557; P = 0.024). CONCLUSION Late sleeping increased the risk of MACEs and indicated a poor prognosis. It is imperative to instruct patients with PCI to form early bedtime habits.
Collapse
Affiliation(s)
- Xiao-Qing Lian
- Department of Cardiology, The Affiliated Jiangning Hospital of Nanjing Medical University, 169 Hushan Road, Nanjing, 211100, Jiangsu Province, China
| | - Kun Jiang
- Department of Cardiology, The Affiliated Jiangning Hospital of Nanjing Medical University, 169 Hushan Road, Nanjing, 211100, Jiangsu Province, China
| | - Xiang-Xuan Chen
- Department of Cardiology, The Affiliated Jiangning Hospital of Nanjing Medical University, 169 Hushan Road, Nanjing, 211100, Jiangsu Province, China
| | - Hai-Cui Dong
- Department of Cardiology, The Affiliated Jiangning Hospital of Nanjing Medical University, 169 Hushan Road, Nanjing, 211100, Jiangsu Province, China
| | - Yu-Qing Zhang
- Department of Cardiology, The Affiliated Jiangning Hospital of Nanjing Medical University, 169 Hushan Road, Nanjing, 211100, Jiangsu Province, China.
| | - Lian-Sheng Wang
- Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing, 210029, Jiangsu Province, China.
| |
Collapse
|
2
|
Koren D, Knutson KL, Burke BK, Drews KL, Bacha F, Katz L, Marcus MD, McKay S, Nadeau K, Mokhlesi B. The association of self-reported sleep and circadian measures with glycemic control and diabetes complications among young adults with type 2 diabetes. Am J Physiol Heart Circ Physiol 2024; 326:H1386-H1395. [PMID: 38607342 PMCID: PMC11380995 DOI: 10.1152/ajpheart.00550.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 03/19/2024] [Accepted: 04/04/2024] [Indexed: 04/13/2024]
Abstract
We aim to examine the association of sleep duration, sleep quality, late chronotype, and circadian misalignment with glycemic control and risk of complications in young adults with youth-onset type 2 diabetes followed in the Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) study. Self-reported sleep duration, quality, timing, and circadian misalignment were assessed via a modified Pittsburgh Sleep Quality Index (PSQI) questionnaire, and chronotype was assessed via the Morningness-Eveningness Questionnaire (MEQ). We examined diabetes complications including loss of glycemic control (defined as hemoglobin A1c ≥8%), hypertension, dyslipidemia, albuminuria, and diabetic peripheral neuropathy. Multivariable logistic regression models were constructed to assess associations between sleep and circadian measures with outcomes of interest, such as loss of glycemic control and diabetes complications. A total of 421 participants (34.2% male), mean age 23.6 ± 2.5 yr, mean body mass index (BMI) of 36.1 ± 8.3 kg/m2, and mean diabetes duration of 10.0 ± 1.5 yr were evaluated. Self-reported short sleep duration, daytime sleepiness, and sleep quality were not associated with loss of glycemic control or diabetes complications. Late self-reported bedtime (after midnight) on work/school nights, rather than self-expressed chronotype or circadian misalignment, was independently associated with loss of glycemic control. An association was seen between late bedtimes and albuminuria but was attenuated after adjusting for depression. In conclusion, late bedtime on work/school days, rather than short sleep duration, daytime sleepiness, or poor sleep quality, was independently associated with loss of glycemic control in this longitudinal cohort of young adults with youth-onset type 2 diabetes.NEW & NOTEWORTHY The prevalence of type 2 diabetes in youth is increasing at an alarming rate. Identifying potentially modifiable factors modulating glycemic control is critically important to reduce micro and macrovascular complications. In a large cohort of youth-onset type 2 diabetes, self-reported late bedtime on work/school days was independently associated with loss of glycemic control in this longitudinal cohort of young adults with youth-onset type 2 diabetes.
Collapse
Affiliation(s)
- Dorit Koren
- Massachusetts General Hospital, Boston, Massachusetts, United States
| | | | - Brian K Burke
- The Biostatistics Center, George Washington University, Rockville, Maryland, United States
| | - Kimberly L Drews
- The Biostatistics Center, George Washington University, Rockville, Maryland, United States
| | - Fida Bacha
- Baylor College of Medicine, Houston, Texas, United States
| | - Lorraine Katz
- Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
| | - Marsha D Marcus
- University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States
| | - Siripoom McKay
- Baylor College of Medicine, Houston, Texas, United States
| | - Kristen Nadeau
- University of Colorado Anschutz Medical Center, Aurora, Colorado, United States
| | - Babak Mokhlesi
- Rush University Medical Center, Chicago, Illinois, United States
| |
Collapse
|
3
|
Tracy EL, Chin BN, Lehrer HM, Hasler BP, Thomas MC, Smagula S, Kimutis S, Hall MH, Buysse DJ. Behavioral-Social Rhythms and Cardiovascular Disease Risk in Retired Night Shift Workers and Retired Day Workers. Psychosom Med 2024; 86:227-233. [PMID: 38573015 PMCID: PMC11081820 DOI: 10.1097/psy.0000000000001287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/05/2024]
Abstract
OBJECTIVE Stability in the timing of key daily routine behaviors such as working/doing housework, sleeping, eating, and engaging in social interactions (i.e., behavioral-social rhythms) contributes to health. This study examined whether behavioral-social rhythms were associated with cardiovascular disease (CVD) risk factors in retired night shift workers and retired day workers and explored whether past night shift work exposure moderated this association. METHODS A total of 154 retired older adults participated in this study. Multiple logistic regression models were used to examine associations between behavioral-social rhythms and CVD risk factors. Independent variables included Social Rhythm Metric (SRM)-5 score and actigraphy rest-activity rhythm intradaily variability (IV) and interdaily stability (IS). Dependent variables were metabolic syndrome prevalence and its five individual components. RESULTS More regular behavioral-social rhythms were associated with lower odds of prevalent metabolic syndrome (SRM: odds ratio [OR] = 0.57, 95% confidence interval [CI] = 0.35-0.88; IV: OR = 4.00, 95% CI = 1.86-8.58; IS: OR = 0.42, 95% CI = 0.24-0.73) and two of its individual components: body mass index (SRM: OR = 0.56, 95% CI = 0.37-0.85; IV: OR = 2.84, 95% CI = 1.59-5.07; IS: OR = 0.42, 95% CI = 0.26-0.68) and high-density lipoprotein cholesterol (SRM: OR = 0.49, 95% CI = 0.30-0.80; IV: OR = 2.49, 95% CI = 1.25-4.96; IS: OR = 0.35, 95% CI = 0.19-0.66). Past shift work history did not moderate the association between behavioral-social rhythms and metabolic syndrome. CONCLUSIONS Behavioral-social rhythms were related to CVD risk factors in retired adults regardless of prior night shift work exposure. Older retired workers may benefit from education and interventions aiming to increase behavioral-social rhythm regularity.
Collapse
Affiliation(s)
- Eunjin Lee Tracy
- From the Department of Human Development and Family Science (Tracy), University of Missouri, Columbia, Missouri; Department of Psychology (Chin), Trinity College, Hartford, Connecticut; Department of Psychiatry (Lehrer, Hasler, Smagula, Kimutis, Hall, Buysse), University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; and VISN 4 Mental Illness Research (Thomas), Education and Clinical Center, VA Pittsburgh Healthcare System, Pittsburgh, Pennsylvania
| | | | | | | | | | | | | | | | | |
Collapse
|
4
|
Speksnijder EM, Bisschop PH, Siegelaar SE, Stenvers DJ, Kalsbeek A. Circadian desynchrony and glucose metabolism. J Pineal Res 2024; 76:e12956. [PMID: 38695262 DOI: 10.1111/jpi.12956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 04/02/2024] [Accepted: 04/15/2024] [Indexed: 05/09/2024]
Abstract
The circadian timing system controls glucose metabolism in a time-of-day dependent manner. In mammals, the circadian timing system consists of the main central clock in the bilateral suprachiasmatic nucleus (SCN) of the anterior hypothalamus and subordinate clocks in peripheral tissues. The oscillations produced by these different clocks with a period of approximately 24-h are generated by the transcriptional-translational feedback loops of a set of core clock genes. Glucose homeostasis is one of the daily rhythms controlled by this circadian timing system. The central pacemaker in the SCN controls glucose homeostasis through its neural projections to hypothalamic hubs that are in control of feeding behavior and energy metabolism. Using hormones such as adrenal glucocorticoids and melatonin and the autonomic nervous system, the SCN modulates critical processes such as glucose production and insulin sensitivity. Peripheral clocks in tissues, such as the liver, muscle, and adipose tissue serve to enhance and sustain these SCN signals. In the optimal situation all these clocks are synchronized and aligned with behavior and the environmental light/dark cycle. A negative impact on glucose metabolism becomes apparent when the internal timing system becomes disturbed, also known as circadian desynchrony or circadian misalignment. Circadian desynchrony may occur at several levels, as the mistiming of light exposure or sleep will especially affect the central clock, whereas mistiming of food intake or physical activity will especially involve the peripheral clocks. In this review, we will summarize the literature investigating the impact of circadian desynchrony on glucose metabolism and how it may result in the development of insulin resistance. In addition, we will discuss potential strategies aimed at reinstating circadian synchrony to improve insulin sensitivity and contribute to the prevention of type 2 diabetes.
Collapse
Affiliation(s)
- Esther M Speksnijder
- Department of Endocrinology and Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Gastroenterology Endocrinology and Metabolism (AGEM), Amsterdam, The Netherlands
| | - Peter H Bisschop
- Department of Endocrinology and Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Gastroenterology Endocrinology and Metabolism (AGEM), Amsterdam, The Netherlands
| | - Sarah E Siegelaar
- Department of Endocrinology and Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Gastroenterology Endocrinology and Metabolism (AGEM), Amsterdam, The Netherlands
| | - Dirk Jan Stenvers
- Department of Endocrinology and Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Gastroenterology Endocrinology and Metabolism (AGEM), Amsterdam, The Netherlands
- Department of Endocrinology and Metabolism, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Andries Kalsbeek
- Department of Endocrinology and Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Gastroenterology Endocrinology and Metabolism (AGEM), Amsterdam, The Netherlands
- Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands
- Laboratory of Endocrinology, Department of Clinical Chemistry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| |
Collapse
|
5
|
Diao T, Liu K, Lyu J, Zhou L, Yuan Y, Yang H, Wu T, Zhang X. Changes in Sleep Patterns, Genetic Susceptibility, and Incident Cardiovascular Disease in China. JAMA Netw Open 2024; 7:e247974. [PMID: 38652473 DOI: 10.1001/jamanetworkopen.2024.7974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/25/2024] Open
Abstract
Importance The associations of changes in sleep patterns with incident cardiovascular disease (CVD) are not fully elucidated, and whether these associations are modified by genetic susceptibility remains unknown. Objectives To investigate the associations of 5-year changes in sleep patterns with incident CVD and whether genetic susceptibility modifies these associations. Design, Setting, and Participants This prospective cohort study of the Dongfeng-Tongji cohort was conducted from 2008 to 2018 in China. Eligible participants included those with complete sleep information at baseline survey (2008-2010) and the first follow-up survey (2013); participants who had no CVD or cancer in 2013 were prospectively assessed until 2018. Statistical analysis was performed in November 2023. Exposures Five-year changes in sleep patterns (determined by bedtime, sleep duration, sleep quality, and midday napping) between 2008 and 2013, and polygenic risk scores (PRS) for coronary heart disease (CHD) and stroke. Main Outcomes and Measures Incident CVD, CHD, and stroke were identified from 2013 to 2018. Cox proportional hazards regression models were applied to estimate hazard ratios (HRs) and 95% CIs. Results Among 15 306 individuals (mean [SD] age, 65.8 [7.4] years; 8858 [57.9%] female and 6448 male [42.1%]), 5474 (35.78%) had persistent unfavorable sleep patterns and 3946 (25.8%) had persistent favorable sleep patterns. A total of 3669 incident CVD cases were documented, including 2986 CHD cases and 683 stroke cases, over a mean (SD) follow-up of 4.9 (1.5) years. Compared with those with persistent unfavorable sleep patterns, individuals with persistent favorable sleep patterns over 5 years had lower risks of incident CVD (HR, 0.80; 95% CI, 0.73-0.87), CHD (HR, 0.84; 95% CI, 0.76-0.92), and stroke (HR, 0.66; 95% CI, 0.54-0.82) in the subsequent 5-year period. No significant effect modification by PRS was observed for sleep pattern change and CHD or stroke risk. However, sleep pattern changes and PRS were jointly associated with the CHD and stroke risk in a dose-dependent manner, with the lowest risk being among those with persistent favorable sleep patterns combined with low PRS (HR for CHD, 0.65; 95% CI, 0.52-0.82 and HR for stroke, 0.48; 95% CI, 0.29-0.79). Conclusions and Relevance In this cohort study of middle-aged and older Chinese adults, individuals with persistent favorable sleep patterns had a lower CVD risk, even among those with higher genetic risk. These findings highlight the importance of maintaining favorable sleep patterns for CVD prevention.
Collapse
Affiliation(s)
- Tingyue Diao
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Kang Liu
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- School of Public Health, Guangzhou Medical University, Guangzhou, China
| | - Junrui Lyu
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lue Zhou
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yu Yuan
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Handong Yang
- Department of Cardiovascular Diseases, Sinopharm Dongfeng General Hospital, Hubei University of Medicine, Shiyan, China
| | - Tangchun Wu
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaomin Zhang
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| |
Collapse
|
6
|
Savin KL, Carlson JA, Patel SR, Jankowska MM, Allison MA, Sotres-Alvarez D, Sallis JF, Talavera GA, Roesch SC, Malcarne VL, Larsen B, Rutledge T, Gallo LC. Social and built neighborhood environments and sleep health: The Hispanic Community Health Study/Study of Latinos Community and Surrounding Areas and Sueño Ancillary Studies. Sleep 2024; 47:zsad260. [PMID: 37788570 PMCID: PMC10851842 DOI: 10.1093/sleep/zsad260] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 09/15/2023] [Indexed: 10/05/2023] Open
Abstract
STUDY OBJECTIVES To test associations between neighborhood social, built, and ambient environment characteristics and multidimensional sleep health in Hispanic/Latino adults. METHODS Data were from San Diego-based Hispanic/Latino adults mostly of Mexican heritage enrolled in the Hispanic Community Health Study/Study of Latinos (N = 342). Home addresses were geocoded to ascertain neighborhood characteristics of greenness, walkability (density of intersections, retail spaces, and residences), socioeconomic deprivation (e.g. lower income, lower education), social disorder (e.g. vacant buildings, crime), traffic density, and air pollution (PM 2.5) in the Study of Latinos Communities and Surrounding Areas Study. Sleep dimensions of regularity, satisfaction, alertness, timing, efficiency, and duration were measured by self-report or actigraphy approximately 2 years later. Multivariable regression models accounting for study design (stratification and clustering) were used to examine associations of neighborhood variables with individual sleep dimensions and a multidimensional sleep health composite score. RESULTS Neighborhood characteristics were not significantly associated with the multidimensional sleep health composite, and there were few significant associations with individual sleep dimensions. Greater levels of air pollution (B = 9.03, 95% CI: 1.16, 16.91) were associated with later sleep midpoint, while greater social disorder (B = -6.90, 95% CI: -13.12, -0.67) was associated with earlier sleep midpoint. Lower walkability was associated with more wake after sleep onset (B = -3.58, 95% CI: -7.07, -0.09). CONCLUSIONS Living in neighborhoods with lower walkability and greater air pollution was associated with worse sleep health, but otherwise findings were largely null. Future research should test these hypotheses in settings with greater variability and investigate mechanisms of these associations.
Collapse
Affiliation(s)
- Kimberly L Savin
- San Diego State University/University of California San Diego, Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA
| | - Jordan A Carlson
- Center for Children’s Health Lifestyles and Nutrition, Children’s Mercy Kansas City, Kansas City, MO, USA
- Department of Pediatrics, Children’s Mercy Kansas City and University of Missouri Kansas City, Kansas City, MO, USA
| | - Sanjay R Patel
- Center for Sleep and Cardiovascular Outcomes Research, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Matthew A Allison
- Department of Family Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Daniela Sotres-Alvarez
- Collaborative Studies Coordinating Center, Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - James F Sallis
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC, Australia
| | - Gregory A Talavera
- Department of Psychology, San Diego State University, San Diego, CA, USA
| | - Scott C Roesch
- Department of Psychology, San Diego State University, San Diego, CA, USA
| | - Vanessa L Malcarne
- Department of Psychology, San Diego State University, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Britta Larsen
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Thomas Rutledge
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Department of Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
| | - Linda C Gallo
- Department of Psychology, San Diego State University, San Diego, CA, USA
| |
Collapse
|
7
|
Chen DM, Taporoski TP, Alexandria SJ, Aaby DA, Beijamini F, Krieger JE, von Schantz M, Pereira AC, Knutson KL. Altered sleep architecture in diabetes and prediabetes: findings from the Baependi Heart Study. Sleep 2024; 47:zsad229. [PMID: 37658822 DOI: 10.1093/sleep/zsad229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 08/16/2023] [Indexed: 09/05/2023] Open
Abstract
STUDY OBJECTIVES People with diabetes and prediabetes are more likely to have sleep-disordered breathing (SDB), but few studies examined sleep architecture in people with diabetes or prediabetes in the absence of moderate-severe SDB, which was the aim of our cross-sectional study. METHODS This cross-sectional sample is from the Baependi Heart Study, a family-based cohort of adults in Brazil. About 1074 participants underwent at-home polysomnography (PSG). Diabetes was defined as fasting glucose >125 mg/dL or HbA1c > 6.4 mmol/mol or taking diabetic medication, and prediabetes was defined as HbA1c ≥ 5.7 & <6.5 mmol/mol or fasting glucose ≥ 100 & ≤125 mg/dl. We excluded participants with an apnea-hypopnea index (AHI) ≥ 30 in primary analyses and ≥ 15 in secondary analysis. We compared sleep stages among the 3 diabetes groups (prediabetes, diabetes, neither). RESULTS Compared to those without diabetes, we found shorter REM duration for participants with diabetes (-6.7 min, 95%CI -13.2, -0.1) and prediabetes (-5.9 min, 95%CI -10.5, -1.3), even after adjusting for age, gender, BMI, and AHI. Diabetes was also associated with lower total sleep time (-13.7 min, 95%CI -26.8, -0.6), longer slow-wave sleep (N3) duration (+7.6 min, 95%CI 0.6, 14.6) and higher N3 percentage (+2.4%, 95%CI 0.6, 4.2), compared to those without diabetes. Results were similar when restricting to AHI < 15. CONCLUSIONS People with diabetes and prediabetes had less REM sleep than people without either condition. People with diabetes also had more N3 sleep. These results suggest that diabetes and prediabetes are associated with differences in sleep architecture, even in the absence of moderate-severe sleep apnea.
Collapse
Affiliation(s)
- Daniel M Chen
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | | | | | - David A Aaby
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | | | - José E Krieger
- University of São Paulo School of Medicine, São Paulo, São Paulo, Brazil
| | - Malcolm von Schantz
- Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, UK
| | - Alexandre C Pereira
- University of São Paulo School of Medicine, São Paulo, São Paulo, Brazil
- Brigham and Women´s Hospital, Harvard Medical School, Boston, MA, USA
| | - Kristen L Knutson
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| |
Collapse
|
8
|
Hoopes EK, Brewer B, Robson SM, Witman MA, D’Agata MN, Malone SK, Edwards DG, Patterson F. Temporal associations between nightly sleep with daytime eating and activity levels in free-living young adults. Sleep 2023; 46:zsad123. [PMID: 37083715 PMCID: PMC10639157 DOI: 10.1093/sleep/zsad123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 04/06/2023] [Indexed: 04/22/2023] Open
Abstract
STUDY OBJECTIVES This study aimed to quantify the temporal associations between nightly sleep quantity and timing with daytime eating behavior and activity levels in free-living (i.e. non-experimental) settings. METHODS Generally healthy young adults (N = 63; 28.9 ± 7.1 years) completed concurrent sleep (wrist actigraphy), eating (photo-assisted diet records), and activity (waist actigraphy) assessments over 14 days. Multilevel models quantified the associations between nightly sleep (total sleep time, timing of sleep and wake onset) with next-day eating behavior (diet quality, caloric intake, timing of eating onset/offset, eating window duration) and activity levels (total physical activity, sedentary time). Associations in the reverse direction (i.e. eating and activity predicting sleep) were explored. Models adjusted for demographic and behavioral confounders and accounted for multiple testing. RESULTS At within- and between-subject levels, nights with greater-than-average total sleep time predicted a shorter eating window the next day (all p ≤ 0.002). Later-than-average sleep and wake timing predicted within- and between-subject delays in next-day eating onset and offset, and between-subject reductions in diet quality and caloric intake (all p ≤ 0.008). At within- and between-subject levels, total sleep time was bidirectionally, inversely associated with sedentary time (all p < 0.001), while later-than-average sleep and wake timing predicted lower next-day physical activity (all p ≤ 0.008). CONCLUSIONS These data underscore the complex interrelatedness between sleep, eating behavior, and activity levels in free-living settings. Findings also suggest that sleep exerts a greater influence on next-day behavior, rather than vice versa. While testing in more diverse samples is needed, these data have potential to enhance health behavior interventions and maximize health outcomes.
Collapse
Affiliation(s)
- Elissa K Hoopes
- College of Health Sciences, University of Delaware, Newark, DE, USA
| | - Benjamin Brewer
- College of Health Sciences, University of Delaware, Newark, DE, USA
| | - Shannon M Robson
- College of Health Sciences, University of Delaware, Newark, DE, USA
| | - Melissa A Witman
- College of Health Sciences, University of Delaware, Newark, DE, USA
| | | | - Susan K Malone
- Rory Meyers College of Nursing, New York University, New York, NY, USA
| | - David G Edwards
- College of Health Sciences, University of Delaware, Newark, DE, USA
| | - Freda Patterson
- College of Health Sciences, University of Delaware, Newark, DE, USA
| |
Collapse
|
9
|
Kim Y, An HJ, Seo YG. The Relationship between Breakfast and Sleep and Cardiovascular Risk Factors. Nutrients 2023; 15:4596. [PMID: 37960249 PMCID: PMC10650383 DOI: 10.3390/nu15214596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 10/21/2023] [Accepted: 10/26/2023] [Indexed: 11/15/2023] Open
Abstract
Despite extensive research on the individual effects of breakfast and sleep on health outcomes, there has been limited investigation into their combined effects. We aimed to evaluate the relationship between breakfast-eating behavior and sleep timing on cardiovascular disease (CVD) risk factors. A total of 16,121 participants (6744 men and 9377 women) aged 19 years or older were selected from the Korea National Health and Nutrition Examination Surveys (2016-2018, 2021). We classified participants into four groups: early sleep + regular breakfast eaters (group 1), late sleep + regular breakfast eaters (group 2), early sleep + infrequent breakfast eaters (group 3), and late sleep + infrequent breakfast eaters (group 4). In men, group 4 had a lower prevalence of obesity than group 1 (OR 0.78, 95%CI 0.62-0.97), and groups 2, 3, and 4 had a higher prevalence of metabolic syndrome (MetS) than group 1 (OR 1.43, 1.62, and 1.47, respectively). In women, group 4 had a lower prevalence of dyslipidemia than group 1 (OR 0.59, 95%CI 0.44-0.80), and group 2 had a higher prevalence of MetS than group 1 (OR 1.24, 95%CI 1.03-1.50). The combination of skipping breakfast and late sleep timing was associated with the higher prevalence of MetS particularly in men. Moreover, the relationship between breakfast and sleep timing on CVD risk factors differed by sex and age group.
Collapse
Affiliation(s)
| | | | - Young-Gyun Seo
- Department of Family Medicine, Hallym University Sacred Heart Hospital, Anyang 14068, Republic of Korea; (Y.K.); (H.-J.A.)
| |
Collapse
|
10
|
Henríquez-Beltrán M, Dreyse J, Jorquera J, Jorquera-Diaz J, Salas C, Fernandez-Bussy I, Labarca G. The U-Shaped Association between Sleep Duration, All-Cause Mortality and Cardiovascular Risk in a Hispanic/Latino Clinically Based Cohort. J Clin Med 2023; 12:4961. [PMID: 37568362 PMCID: PMC10419896 DOI: 10.3390/jcm12154961] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 07/24/2023] [Accepted: 07/26/2023] [Indexed: 08/13/2023] Open
Abstract
Sleep is essential for life, and inappropriate sleep duration patterns may lead to chronic consequences regarding human health. Several studies have confirmed the presence of a U-shaped association between sleep duration and mortality. Moreover, many consequences related to cardiometabolic aspects have been suggested in patients with abnormal sleep durations. In this study, we analyzed the associations between sleep duration, total sleep time (TST), the risk of all-cause mortality, and 10-year cardiovascular risk in a cohort of patients at a sleep medicine center in Santiago, Chile. We conducted a prospective cohort study of patients (SantOSA). A short TST was defined as ≤6 h, a normal TST as 6 to 9 h, and a long TST as ≥9 h. Adjusted hazard ratios (aHRs) for all-cause mortality were calculated. A cross-sectional analysis between TST and 10-year cardiovascular risk (calculated using the Framingham 2008 formula) was determined using logistic regression models. A total of 1385 subjects were included in the results (78% male; median age: 53, interquartile range (IQR): 42-64 years; median BMI: 29.5, IQR: 16.7-33.1). A total of 333 subjects (24%) reported short TSTs, 938 (67.7%) reported normal TSTs, and 114 (8.3%) reported long TSTs. In the fully adjusted model, the association remained significant for short (aHR: 2.51 (1.48-4.25); p-value = 0.01) and long TSTs (aHR: 3.97 (1.53-10.29); p-value = 0.04). Finally, a U-shaped association was found between short and long TSTs, with an increase in cardiovascular risk at 10 years. Compared with normal TSTs, short (≤6 h) and long (≥9 h) TSTs were significantly associated with all-cause mortality and increased 10-year cardiovascular risk.
Collapse
Affiliation(s)
- Mario Henríquez-Beltrán
- Escuela de Kinesiología, Facultad de Salud, Universidad Santo Tomás, Los Angeles 4440000, Chile;
| | - Jorge Dreyse
- Centro de Enfermedades Respiratorias, Clínica Las Condes, Facultad de Medicina Universidad Finis Terrae, Santiago 7591047, Chile; (J.D.); (J.J.); (C.S.)
| | - Jorge Jorquera
- Centro de Enfermedades Respiratorias, Clínica Las Condes, Facultad de Medicina Universidad Finis Terrae, Santiago 7591047, Chile; (J.D.); (J.J.); (C.S.)
| | | | - Constanza Salas
- Centro de Enfermedades Respiratorias, Clínica Las Condes, Facultad de Medicina Universidad Finis Terrae, Santiago 7591047, Chile; (J.D.); (J.J.); (C.S.)
| | | | - Gonzalo Labarca
- Department of Clinical Biochemistry and Immunology, Faculty of Pharmacy, University of Concepción, Concepción 4070112, Chile
- Division of Sleep Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Ave., Boston, MA 02215, USA
| |
Collapse
|
11
|
Kurnool S, McCowen KC, Bernstein NA, Malhotra A. Sleep Apnea, Obesity, and Diabetes - an Intertwined Trio. Curr Diab Rep 2023:10.1007/s11892-023-01510-6. [PMID: 37148488 DOI: 10.1007/s11892-023-01510-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/18/2023] [Indexed: 05/08/2023]
Abstract
PURPOSE OF REVIEW To synthesize the existing literature regarding the complex interplay between sleep disturbance, obesity, and diabetes. The review emphasizes the three pillars of health being diet, exercise, and sleep, with the notion that if one is ignored, then the other two could suffer. RECENT FINDINGS Sleep deprivation is associated with incident obesity, perhaps mediated by dysregulation in leptin and ghrelin - hormones important in regulation of appetite. Sleep apnea is very common particularly among obese people with type 2 diabetes mellitus. Treatment of sleep apnea has clear symptomatic benefits although its impact on long-term cardiometabolic health is less clear. Sleep disturbance may be an important modifiable risk for patients at risk of cardiometabolic disease. An assessment of sleep health may be an important component of the comprehensive care of patients with obesity and diabetes mellitus.
Collapse
Affiliation(s)
- Soumya Kurnool
- UC San Diego Department of Medicine, 9500 Gilman Drive, UC San Diego, La Jolla, CA, 92037, USA
| | - Karen C McCowen
- UC San Diego Department of Medicine, 9500 Gilman Drive, UC San Diego, La Jolla, CA, 92037, USA
| | - Nicole A Bernstein
- UC San Diego Department of Medicine, 9500 Gilman Drive, UC San Diego, La Jolla, CA, 92037, USA
| | - Atul Malhotra
- UC San Diego Department of Medicine, 9500 Gilman Drive, UC San Diego, La Jolla, CA, 92037, USA.
| |
Collapse
|
12
|
Chen DM, Taporoski TP, Alexandria SJ, Aaby DA, Beijamini F, Krieger JE, von Schantz M, Pereira A, Knutson KL. Altered sleep architecture in diabetes and prediabetes: findings from the Baependi Heart Study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.03.23.23287631. [PMID: 36993582 PMCID: PMC10055606 DOI: 10.1101/2023.03.23.23287631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Objective People with diabetes are more likely to have obstructive sleep apnea, but there are few studies examining sleep architecture in people with diabetes, especially in the absence of moderate-severe sleep apnea. Therefore, we compared sleep architecture among people with diabetes, prediabetes or neither condition, whilst excluding people with moderate-severe sleep apnea. Research design and methods This sample is from the Baependi Heart Study, a prospective, family-based cohort of adults in Brazil. 1,074 participants underwent at-home polysomnography (PSG). Diabetes was defined as 1) FBG>125 OR 2) HbA1c>6.4 OR 3) taking diabetic medication, and prediabetes was defined as 1) [(5.7≤HbA1c≤6.4) OR (100≤FBG≤125)] AND 2) not taking diabetic medication. We excluded participants that had an apnea-hypopnea index (AHI)>30 from these analyses to reduce confounding due to severe sleep apnea. We compared sleep stages among the 3 groups. Results Compared to those without diabetes, we found shorter REM duration for participants with diabetes (-6.7min, 95%CI -13.2, -0.1) or prediabetes (-5.9min, 95%CI -10.5, -1.3), even after adjusting for age, gender, BMI, and AHI. Diabetes was also associated with lower total sleep time (-13.7min, 95%CI -26.8, -0.6), longer slow-wave sleep (N3) duration (+7.6min, 95%CI 0.6, 14.6) and higher N3 percentage (+2.4%, 95%CI 0.6, 4.2), compared to those without diabetes. Conclusions People with diabetes and prediabetes had less REM sleep after taking into account potential confounders, including AHI. People with diabetes also had more N3 sleep. These results suggest that diabetes is associated with different sleep architecture, even in the absence of moderate-severe sleep apnea.
Collapse
|
13
|
Ansu Baidoo V, Knutson KL. Associations between circadian disruption and cardiometabolic disease risk: A review. Obesity (Silver Spring) 2023; 31:615-624. [PMID: 36750239 PMCID: PMC9974590 DOI: 10.1002/oby.23666] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 11/23/2022] [Accepted: 11/29/2022] [Indexed: 02/09/2023]
Abstract
The human circadian system plays a vital role in many physiological processes, and circadian rhythms are found in virtually all tissues and organs. The disruption of circadian rhythms may lead to adverse health outcomes. Evidence from recent population-based studies was reviewed because they represent real-world behavior and can be useful in developing future studies to reduce the risk of adverse health conditions, including cardiovascular diseases, obesity, and diabetes mellitus, which may occur because of circadian disruption. An electronic search in PubMed and Web of Science (2012-2022) was performed. Selected articles were based on specific inclusion and exclusion criteria. Five factors that may disrupt circadian rhythm alignment are discussed: shift work, late chronotype, late sleep timing, sleep irregularity, and late meal timing. Evidence from observational studies of these circadian disruptors suggests potential detrimental effects on cardiometabolic health, including higher BMI/obesity, higher blood pressure, greater dyslipidemia, greater inflammation, and diabetes. Future research should identify the specific underlying pathways in order to mitigate the health consequences of shift work. Furthermore, optimal sleep and mealtimes for metabolic health can be explored in intervention studies. Lastly, it is important that the timing of external environmental cues (such as light) and behaviors that influence circadian rhythms are managed.
Collapse
Affiliation(s)
- Velarie Ansu Baidoo
- Center for Circadian and Sleep Medicine, Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Kristen L Knutson
- Center for Circadian and Sleep Medicine, Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| |
Collapse
|
14
|
Yang YD, Zeng Y, Li J, Zhou JH, He QY, Zheng CJ, Reichetzeder C, Krämer BK, Hocher B. Association of BMAL1 clock gene polymorphisms with fasting glucose in children. Pediatr Res 2023:10.1038/s41390-023-02467-8. [PMID: 36732647 PMCID: PMC10382306 DOI: 10.1038/s41390-023-02467-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 11/02/2022] [Accepted: 12/18/2022] [Indexed: 02/04/2023]
Abstract
BACKGROUND The brain and muscle Arnt-like protein-1 (BMAL1) gene is an important circadian clock gene and previous studies have found that certain polymorphisms are associated with type 2 diabetes in adults. However, it remains unknown if such polymorphisms can affect fasting glucose in children and if other factors modify the associations. METHODS A school-based cross-sectional study with 947 Chinese children was conducted. A multivariable linear regression model was used to analyze the association between BMAL1 gene polymorphisms and fasting glucose level. RESULTS After adjusting for age, sex, body mass index (BMI), physical activity, and unhealthy diet, GG genotype carriers of BMAL1 rs3789327 had higher fasting glucose than AA/GA genotype carriers (b = 0.101, SE = 0.050, P = 0.045). Adjusting for the same confounders, rs3816358 was shown to be significantly associated with fasting glucose (b = 0.060, SE = 0.028, P = 0.032). Furthermore, a significant interaction between rs3789327 and nutritional status on fasting glucose was identified (Pinteraction = 0.009); rs3789327 was associated with fasting glucose in the overweight/obese subgroup (b = 0.353, SE = 0.126, P = 0.006), but not in non-overweight/non-obese children. CONCLUSIONS BMAL1 polymorphisms were significantly associated with the fasting glucose level in children. Additionally, the observed interaction between nutritional status and BMAL1 supports promoting an optimal BMI in children genetically predisposed to higher glucose level. IMPACT Polymorphisms in the essential circadian clock gene BMAL1 were associated with fasting blood glucose levels in children. Additionally, there was a significant interaction between nutritional status and BMAL1 affecting fasting glucose levels. BMAL1 rs3789327 was associated with fasting glucose only in overweight/obese children. This finding could bring novel insights into mechanisms by which nutritional status influences fasting glucose in children.
Collapse
Affiliation(s)
- Yi-De Yang
- Department of Child and Adolescent Health, School of Medicine, Hunan Normal University, 410006, Changsha, China.,Key Laboratory of Molecular Epidemiology of Hunan Province, School of Medicine, Hunan Normal University, 410081, Changsha, China
| | - Yuan Zeng
- Department of Child and Adolescent Health, School of Medicine, Hunan Normal University, 410006, Changsha, China.,Key Laboratory of Molecular Epidemiology of Hunan Province, School of Medicine, Hunan Normal University, 410081, Changsha, China
| | - Jian Li
- Key Laboratory of Study and Discovery of Small Targeted Molecules of Hunan Province, School of Medicine, Hunan Normal University, 410013, Changsha, China
| | - Jun-Hua Zhou
- Key Laboratory of Molecular Epidemiology of Hunan Province, School of Medicine, Hunan Normal University, 410081, Changsha, China
| | - Quan-Yuan He
- Key Laboratory of Molecular Epidemiology of Hunan Province, School of Medicine, Hunan Normal University, 410081, Changsha, China
| | - Chan-Juan Zheng
- Department of Child and Adolescent Health, School of Medicine, Hunan Normal University, 410006, Changsha, China.,Key Laboratory of Molecular Epidemiology of Hunan Province, School of Medicine, Hunan Normal University, 410081, Changsha, China
| | - Christoph Reichetzeder
- Institute of Nutritional Science, University of Potsdam, Potsdam, Germany.,HMU - Health and Medical University, Potsdam, Germany
| | - Bernhard K Krämer
- Fifth Department of Medicine (Nephrology/Endocrinology/Rheumatology), University Medical Centre Mannheim, University of Heidelberg, Mannheim, Germany
| | - Berthold Hocher
- Key Laboratory of Study and Discovery of Small Targeted Molecules of Hunan Province, School of Medicine, Hunan Normal University, 410013, Changsha, China. .,Fifth Department of Medicine (Nephrology/Endocrinology/Rheumatology), University Medical Centre Mannheim, University of Heidelberg, Mannheim, Germany. .,Reproductive and Genetic Hospital of CITIC-Xiangya, Changsha, China. .,Institute of Medical Diagnostics, IMD Berlin, Berlin, Germany.
| |
Collapse
|
15
|
Timing of Meals and Sleep in the Mediterranean Population: The Effect of Taste, Genetics, Environmental Determinants, and Interactions on Obesity Phenotypes. Nutrients 2023; 15:nu15030708. [PMID: 36771415 PMCID: PMC9921798 DOI: 10.3390/nu15030708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 01/20/2023] [Accepted: 01/26/2023] [Indexed: 01/31/2023] Open
Abstract
Circadian rhythms regulate the sleep-wake and feeding-fasting cycles. Sleep and feeding constitute a complex cycle that is determined by several factors. Despite the importance of sleep duration and mealtimes for many obesity phenotypes, most studies on dietary patterns have not investigated the contribution of these variables to the phenotypes analyzed. Likewise, they have not investigated the factors related to sleep or mealtimes. Thus, our aims were to investigate the link between taste perception and eating/sleep patterns and to analyze the effect of the interactions between sleep/meal patterns and genetic factors on obesity phenotypes. We conducted a cross-sectional analysis on 412 adults from the Mediterranean population. We measured taste perception (bitter, sweet, salty, sour, and umami) and assessed sleep duration and waketime. The midpoint of sleep and social jetlag was computed. From the self-reported timing of meals, we estimated the eating window, eating midpoint, and eating jetlag. Adherence to the Mediterranean diet was measured with a validated score. Selected polymorphisms in the TAS2R38, CLOCK, and FTO genes were determined, and their associations and interactions with relevant phenotypes were analyzed. We found various associations between temporal eating, sleep patterns, and taste perception. A higher bitter taste perception was associated with an earlier eating midpoint (p = 0.001), breakfast time (p = 0.043), dinner time (p = 0.009), waketime (p < 0.001), and midpoint of sleep (p = 0.009). Similar results were observed for the bitter taste polymorphism TAS2R38-rs713598, a genetic instrumental variable for bitter perception, increasing the causality of the associations. Moreover, significant gene-sleep interactions were detected between the midpoint of sleep and the TAS2R38-rs713598 (p = 0.032), FTO-rs9939609 (p = 0.037), and CLOCK-rs4580704 (p = 0.004) polymorphisms which played a role in determining obesity phenotypes. In conclusion, our study provided more information on the sleep and mealtime patterns of the general Spanish Mediterranean population than on their main relationships. Moreover, we were able to show significant associations between taste perception, specifically bitter taste; sleep time; and mealtimes as well as an interaction between sleep time and several genetic variants linked to obesity phenotypes. However, additional research is needed to better characterize the causality and mechanisms behind these associations.
Collapse
|
16
|
Matricciani L, Paquet C, Dumuid D, Lushington K, Olds T. Multidimensional Sleep and Cardiometabolic Risk Factors for Type 2 Diabetes: Examining Self-Report and Objective Dimensions of Sleep. DIABETES EDUCATOR 2022; 48:533-545. [DOI: 10.1177/26350106221137896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Purpose: The purpose of the study was to determine the association between objective and self-report measures of sleep and cardiometabolic risk factors for type 2 diabetes. Methods: This study examines data on Australian adults, collected as part of the Child Health CheckPoint study. Sleep was examined in terms of actigraphy-derived sleep duration, timing, efficiency and variability; and self-report trouble sleeping. Cardiometabolic risk factors for type 2 diabetes were examined in terms of body mass index and biomarkers of inflammation and dyslipidemia. Generalized estimating equations, adjusted for geographic clustering, were used to determine the association between measures of sleep and cardiometabolic risk factors. Results: Complete case analysis was conducted for 1017 parents (87% mothers). Both objective and self-report measures of sleep were significantly but weakly associated with cardiometabolic risk factors. Conclusion: Both objective and self-report measures of sleep are significantly associated with cardiometabolic risk factors for type 2 diabetes. Self-report troubled sleep is associated with poorer cardiometabolic health, independent of actigraphy-derived sleep parameters.
Collapse
Affiliation(s)
- Lisa Matricciani
- Clinical & Health Sciences, University of South Australia, Adelaide, Australia
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, Adelaide, Australia
| | - Catherine Paquet
- Faculté des Sciences Administratives, Université Laval; Centre Nutrition, santé et société (NUTRISS), INAF, Université Laval; Centre de Recherche, Centre Hospitalier Universitaire de Québec - Université Laval
| | - Dorothea Dumuid
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, Adelaide, Australia
- Allied Health and Human Performance (AHHP), University of South Australia, Adelaide, Australia
- Murdoch Children’s Research Institute, Parkville, Victoria, Australia
| | - Kurt Lushington
- Discipline of Psychology, Justice and Society Unit, University of South Australia
| | - Tim Olds
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, Adelaide, Australia
- Murdoch Children’s Research Institute, Parkville, Victoria, Australia
| |
Collapse
|
17
|
Vidmar AP, Cáceres NA, Schneider-Worthington CR, Shirazipour C, Buman MP, de la Haye K, Salvy SJ. Integration of Time-Based Recommendations with Current Pediatric Health Behavior Guidelines: Implications for Obesity Prevention and Treatment in Youth. Curr Obes Rep 2022; 11:236-253. [PMID: 36348216 PMCID: PMC9742346 DOI: 10.1007/s13679-022-00491-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/11/2022] [Indexed: 11/09/2022]
Abstract
PURPOSE OF REVIEW Youth-onset obesity is associated with negative health outcomes across the lifespan including cardiovascular diseases, type 2 diabetes, obstructive sleep apnea, dyslipidemias, asthma, and several cancers. Pediatric health guidelines have traditionally focused on the quality and quantity of dietary intake, physical activity, and sleep. RECENT FINDINGS Emerging evidence suggests that the timing (time of day when behavior occurs) and composition (proportion of time spent allocated to behavior) of food intake, movement (i.e., physical activity, sedentary time), and sleep may independently predict health trajectories and disease risks. Several theoretically driven interventions and conceptual frameworks feature behavior timing and composition (e.g., 24 h movement continuum, circadian science and chronobiology, intermittent fasting regimens, structured day hypothesis). These literatures are, however, disparate, with little crosstalk across disciplines. In this review, we examine dietary, sleep, and movement guidelines and recommendations for youths ages 0-18 in the context of theoretical models and empirical findings in support of time-based approaches. The review aims to inform a unifying framework of health behaviors and guide future research on the integration of time-based recommendations into current quantity and quality-based health guidelines for children and adolescents.
Collapse
Affiliation(s)
- Alaina P Vidmar
- Department of Pediatrics, Center for Endocrinology, Diabetes and Metabolism, Children's Hospital Los Angeles and Keck School of Medicine of USC, 4650 Sunset Boulevard, Mailstop #61, Los Angeles, CA, 90027, USA.
| | - Nenette A Cáceres
- Cancer Research Center On Health Equity, Cedars-Sinai Medical Center, West Hollywood, CA, USA
| | | | - Celina Shirazipour
- Cancer Research Center On Health Equity, Cedars-Sinai Medical Center, West Hollywood, CA, USA
| | - Matthew P Buman
- College of Health Solutions, Arizona State University, Tempe, USA
| | - Kayla de la Haye
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | - Sarah-Jeanne Salvy
- Cancer Research Center On Health Equity, Cedars-Sinai Medical Center, West Hollywood, CA, USA
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| |
Collapse
|
18
|
Liu H, Yang L, Wan C, Li Z, Yan G, Han Y, Sun H, Wang X. Exploring potential mechanism of ciwujia tablets for insomnia by UPLC-Q-TOF-MS/MS, network pharmacology, and experimental validation. Front Pharmacol 2022; 13:990996. [PMID: 36110515 PMCID: PMC9468710 DOI: 10.3389/fphar.2022.990996] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 08/08/2022] [Indexed: 11/24/2022] Open
Abstract
Insomnia, whether chronic or intermittent, is a common central nervous system disease. Ciwujia Tablet (CWT) is a well-known traditional Chinese medicine (TCM) made from the extract of Eleutherococcus senticosus (Rupr. & Maxim.) Maxim. This medication is commonly used for treating insomnia in China, but the lack of in-depth research focused on the chemical ingredients of CWT creates a gap in knowledge regarding its effective constituents against insomnia. Considering that the therapeutic material basis, targets, and pathways related to this drug have not been fully investigated by scholars in the field, the focus of this study is on identifying the chemical ingredients or structural characteristics of CWT by the UPLC-Q-TOF-MS/MS technique. Besides, concepts of network pharmacology were also used to investigate the targets and pathways of CWT. An insomnia rat model was established by intraperitoneal injection of p-chlorophenylalanine, and the results were verified through various experiments. A total of 46 ingredients were identified in CWT, such as eleutheroside B, eleutheroside E, isofraxidin, and chlorogenic acid. Among them, 17 ingredients with good solubility, favorable gastrointestinal absorption, and high bioavailability were selected for network pharmacological analysis. It was concluded that CWT participated in the regulation of neurotransmitter levels, modulation of ion transport, neurotransmitter receptor activity, synaptic transmission, dopaminergic transmission and other essential processes. Results from the animal experiments showed that CWT can increase the content of inhibitory neurotransmitters 5-HT and GABA in the brain, reduce the synthesis of excitatory escalating transmitters DA and NE, shorten the sleep latency and prolong the sleep duration of insomnia rats. Furthermore, CWT could significantly alleviate the symptoms of insomnia in model rats. Identifying the chemical ingredients of CWT in this experiment is of great significance for exploring its potential curative effects, which provides a solid basis for further understanding the therapeutic value of this medication.
Collapse
Affiliation(s)
- Hongda Liu
- National Chinmedomics Research Center, National TCM Key Laboratory of Serum Pharmacochemistry, Metabolomics Laboratory, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Le Yang
- State Key Laboratory of Dampness Syndrome of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Chunlei Wan
- National Chinmedomics Research Center, National TCM Key Laboratory of Serum Pharmacochemistry, Metabolomics Laboratory, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Zhineng Li
- National Chinmedomics Research Center, National TCM Key Laboratory of Serum Pharmacochemistry, Metabolomics Laboratory, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Guangli Yan
- National Chinmedomics Research Center, National TCM Key Laboratory of Serum Pharmacochemistry, Metabolomics Laboratory, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Ying Han
- National Chinmedomics Research Center, National TCM Key Laboratory of Serum Pharmacochemistry, Metabolomics Laboratory, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Hui Sun
- National Chinmedomics Research Center, National TCM Key Laboratory of Serum Pharmacochemistry, Metabolomics Laboratory, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Xijun Wang
- National Chinmedomics Research Center, National TCM Key Laboratory of Serum Pharmacochemistry, Metabolomics Laboratory, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
- State Key Laboratory of Dampness Syndrome of Chinese Medicine, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
- State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Taipa, Macau SAR, China
- *Correspondence: Xijun Wang,
| |
Collapse
|
19
|
Maghsoudipour M, Allison MA, Patel SR, Talavera GA, Daviglus M, Zee PC, Reid KJ, Makarem N, Malhotra A. Associations of chronotype and sleep patterns with metabolic syndrome in the Hispanic community health study/study of Latinos. Chronobiol Int 2022; 39:1087-1099. [PMID: 35509113 PMCID: PMC9177706 DOI: 10.1080/07420528.2022.2069030] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Sleep duration, sleep efficiency, and sleep timing have been shown to have potential effects on metabolic functions relevant to circadian rhythms. It is not clear if the impact of sleep patterns on metabolic risk factors is through sociocultural and environmental factors or circadian misalignment. We investigated the associations of sleep patterns, chronotype, and social jet lag with metabolic syndrome among non-shift worker Hispanic/Latino adults. We used cross-sectional data from the Sueño Ancillary Study of The Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Data from a subsample of 2189 participants aged 18-64 years were used in the analysis. Mean nightly sleep duration, mean sleep onset time, mean sleep offset time, mean sleep midpoint time, sleep efficiency, sleep variability (standard deviation (SD) of sleep duration, and SD of sleep midpoint), and time spent above light exposure threshold (1000 lux) in a day were assessed by wrist actigraphy (Acti-watch Spectrum). Chronotype was determined by the reduced Morningness-Eveningness Questionnaire. Medical conditions including dyslipidemia, hypertension, and diabetes mellitus were determined from a fasting blood specimen and physical exam at the baseline visit. To determine whether sleep patterns, light levels, chronotype, and social jetlag are associated with metabolic syndrome, multivariable logistic regression models were fitted, including variables with P < .15 in the univariate analysis. The results of the multivariable analysis demonstrated that in participants older than 40 years, intermediate chronotype (vs early) was significantly associated with a higher risk of metabolic syndrome (Odds ratio (95%CI): 1.33 (1.04,1.7)), while later chronotype (vs. early) in participants younger than 40 years was significantly associated with a lower risk of metabolic syndrome (Odds ratio (95%CI): 0.37 (0.14, 0.96)). Also, higher sleep efficiency was significantly associated with decreased odds of metabolic syndrome (Odds ratio (95%CI): 0.98 (0.96, 0.99)). Nightly sleep duration was not significantly different between two groups of participants with and without metabolic syndrome in multivariable analyses. There was no significant association between social jet lag and metabolic syndrome in multivariable analysis (p = .286). Moreover, there was no significant association between chronotype and social jet lag in multivariable analysis. The association between metabolic syndrome and chronotype is age-dependent. While early chronotype is associated with metabolic syndrome in younger individuals, it tended to be associated with lower odds for metabolic syndrome in older individuals.
Collapse
Affiliation(s)
- Maryam Maghsoudipour
- Department of Medicine, University of California San Diego, La Jolla, California, USA
| | - Matthew A. Allison
- Department of Family Medicine, University of California San Diego, La Jolla, California, USA
| | - Sanjay R. Patel
- Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Gregory A. Talavera
- Department of Psychology, San Diego State University, San Diego, California, USA
| | - Martha Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, College of Medicine, Chicago, Illinois, USA
| | - Phyllis C. Zee
- Center for Circadian and Sleep Medicine, Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Kathryn J. Reid
- Center for Circadian and Sleep Medicine, Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Nour Makarem
- Department of Epidemiology, Mailman School of Public Health, Columbia University Irving Medical Center, New York, USA
| | - Atul Malhotra
- Department of Medicine, University of California San Diego, La Jolla, California, USA
| |
Collapse
|
20
|
Meng M, Jiang Y, Lin J, Zhang J, Wang G, Zhu Q, Lin Q, Jiang F. The mediating effect of DNA methylation in the association between maternal sleep during pregnancy and offspring adiposity status: a prospective cohort study. Clin Epigenetics 2022; 14:66. [PMID: 35596190 PMCID: PMC9123687 DOI: 10.1186/s13148-022-01284-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Accepted: 04/23/2022] [Indexed: 11/23/2022] Open
Abstract
Background Childhood overweight/obesity is a global public health concern. It is important to identify its early-life risk factors. Maternal poor sleep is common in late pregnancy, and previous studies indicated that poor sleep may influence the offspring’s adiposity status. However, very few studies in humans investigated the effect of the different sleep parameters (sleep quantity, quality, and timing) on the offspring’s adiposity indicators, and long-term studies are even more scarce. In addition, the underlying mechanism remains unclear. The present study therefore aimed to examine the association between the three maternal sleep dimensions in the late pregnancy and the offspring adiposity indicators and to explore the potential mediating effect of the cord blood DNA methylation in the above association. Methods Included participants in the current study were 2211 healthy pregnant women with singleton gestation from the Shanghai Birth Cohort (SBC) and Shanghai Sleep Birth Cohort (SSBC). Maternal nighttime sleep duration, quality, and midpoint (an indicator of circadian rhythm) were assessed by the same instrument in both cohorts during late pregnancy, and the offspring’s body mass index (BMI) and subcutaneous fat (SF) were measured at 2 years old. Additionally, in 231 SSBC samples, the genome-wide DNA methylation levels were measured using the Illumina Infinium Methylation EPIC BeadChip. The multivariate linear regression was used to determine the associations between the maternal sleep parameters and the offspring adiposity indicators. The epigenome-wide association study was conducted to identify the maternal sleep-related CpG sites. The mediation analysis was performed to evaluate the potential intermediate role of DNA methylation in the association between maternal sleep and offspring adiposity indicators. Results The mean maternal nighttime sleep duration and the sleep midpoint for combined cohorts were 9.24 ± 1.13 h and 3.02 ± 0.82, respectively, and 24.5% of pregnant women experienced poor sleep quality in late pregnancy. After adjusting for the covariates, the maternal later sleep midpoint was associated with the increased SF in offspring (Coef. = 0.62, 95% CI 0.37–0.87, p < 0.001) at 2 years old. However, no significant associations of the nighttime sleep duration or sleep quality with the offspring adiposity indicators were found. In the SSBC sample, 45 differential methylated probes (DMPs) were associated with the maternal sleep midpoint, and then, we observed 10 and 3 DMPs that were also associated with the offspring’s SF and BMI at 2 years, of which cg04351668 (MARCH9) and cg12232388 significantly mediated the relationship of sleep midpoint and SF and cg12232388 and cg12225226 mediated the sleep midpoint–BMI association, respectively. Conclusions Maternal later sleep timing in late pregnancy was associated with higher childhood adiposity in the offspring. Cord blood DNA methylation may play a mediation role in that relationship. Supplementary Information The online version contains supplementary material available at 10.1186/s13148-022-01284-w.
Collapse
Affiliation(s)
- Min Meng
- Department of Developmental and Behavioral Pediatrics, Pediatric Translational Medicine Institute, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, 1678 Dong Fang Road, Shanghai, 200127, China.,Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200092, China
| | - Yanrui Jiang
- Department of Developmental and Behavioral Pediatrics, Pediatric Translational Medicine Institute, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, 1678 Dong Fang Road, Shanghai, 200127, China.,Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200092, China
| | - Jianfei Lin
- Department of Developmental and Behavioral Pediatrics, Pediatric Translational Medicine Institute, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, 1678 Dong Fang Road, Shanghai, 200127, China.,Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200092, China
| | - Jun Zhang
- Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200092, China.,School of Public Health, Shanghai Jiao Tong University, Shanghai, 200025, China
| | - Guanghai Wang
- Department of Developmental and Behavioral Pediatrics, Pediatric Translational Medicine Institute, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, 1678 Dong Fang Road, Shanghai, 200127, China.,Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200092, China.,Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai, 201602, China
| | - Qi Zhu
- Department of Developmental and Behavioral Pediatrics, Pediatric Translational Medicine Institute, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, 1678 Dong Fang Road, Shanghai, 200127, China.,Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200092, China
| | - Qingmin Lin
- School of Life Science and Biotechnology, Shanghai Jiao Tong University, 800 Dong Chuan Road, Shanghai, 200240, China.
| | - Fan Jiang
- Department of Developmental and Behavioral Pediatrics, Pediatric Translational Medicine Institute, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, 1678 Dong Fang Road, Shanghai, 200127, China. .,Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200092, China. .,Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai, 201602, China.
| |
Collapse
|
21
|
Liang Z, Liu J. Sleep Behavior and Self-Reported Infertility: A Cross-Sectional Analysis Among U.S. Women. Front Endocrinol (Lausanne) 2022; 13:818567. [PMID: 35620388 PMCID: PMC9127231 DOI: 10.3389/fendo.2022.818567] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Accepted: 04/06/2022] [Indexed: 11/13/2022] Open
Abstract
OBJECTIVE To investigate the associations between sleep behaviors and female infertility. METHODS We conducted a cross-sectional study composed of 2175 U.S. women 18-44 years of age from the National Health and Nutrition Examination Survey (NHANES) (2015-2018). Bedtime/waketime and sleep duration were extracted from the sleep disorder questionnaire. Self-reported infertility was defined as a binary variable based on the participants' response to the question, "Have you ever attempted to become pregnant over a period of at least a year without becoming pregnant?". Multivariate logistic regression analyses were done to explore the relationship between sleep behaviors and female infertility. RESULTS Bedtime (OR=1.24; 95% CI, 1.10-1.40, P = 0.001) and waketime (OR=1.14; 95% CI, 1.01-1.28, P = 0.037) were associated with infertility. Waketime of 08:00 was the inflection point, above which the probability of infertility increased rapidly (OR=1.41; 95% CI, 1.11-1.79, P = 0.004). Sleep-wake behavior was significantly associated with infertility (OR=1.34; 95% CI, 1.16-1.53, P < 0.001) and participants with early-bed/early-rise behavior had the lowest risk. CONCLUSIONS Among U.S. women 18-44 years of age, bedtime and waketime were significantly linearly and non-linearly correlated with infertility, respectively. Early-bed/early-rise behavior was associated with the lowest infertility rate. Further study is needed because the timing of sleep behaviors are modifiable factors and could be a novel strategy to cope with infertility.
Collapse
Affiliation(s)
- Zhu Liang
- Department of Obstetrics and Gynecology, Center for Reproductive Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Key Laboratory for Reproductive Medicine of Guangdong Province, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Jianqiao Liu
- Department of Obstetrics and Gynecology, Center for Reproductive Medicine, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Key Laboratory for Reproductive Medicine of Guangdong Province, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- *Correspondence: Jianqiao Liu,
| |
Collapse
|
22
|
Zatońska K, Basiak-Rasała A, Połtyn-Zaradna K, Kinastowski K, Szuba A. Sleep Duration and Bedtime in the PURE Poland Cohort Study and the Link with Noncommunicable Diseases. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 19:403. [PMID: 35010663 PMCID: PMC8744841 DOI: 10.3390/ijerph19010403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 12/18/2021] [Accepted: 12/28/2021] [Indexed: 06/14/2023]
Abstract
(1) Background: The objective was to investigate the association between sleep duration, bedtime, and noncommunicable diseases in the PURE Poland cohort study. (2) Methods: The baseline study was conducted in 2007-2010. The study group comprised 2023 adult inhabitants of urban and rural areas in Lower Silesia, Poland. The study protocol included questionnaires, blood pressure measurements, blood draws, and anthropometric measurements. Sleep duration and bedtime were self-reported. (3) Results: The median sleep duration of women was 30 min longer than men (8 h vs. 7.5 h; p = 0.001). The average time of sleep increased along with the age of the participants. A sleep duration of >8 h was more common in rural than in urban participants (40.2% vs. 27.1%; respectively; p < 0.001). The relative risk of diabetes, stroke, hypertension, cardiovascular diseases (CVD), and obesity was significantly higher in participants who went to bed between 6 p.m. and 10 p.m. in comparison to those who went to bed between 10 p.m. and 12 a.m. (RR 2.23, 95% CI 1.06-4.67; RR 2.52, 95% CI 1.28 to 4.97; RR 1.12, 95% CI 1.04-1.20; RR 1.36; 95% CI 1.1-1.68; RR 1.38; 95% CI 1.15-1.66, respectively). The relative risk of respiratory diseases was two-fold higher in those who went to bed after midnight in comparison to those who went to bed between 10 p.m. and 12 a.m. (RR 2.24; 95% CI 1.19-4.22). (4) Conclusions: In our study, an earlier bedtime was associated with a higher risk of diabetes, stroke, obesity, hypertension, and CVD.
Collapse
Affiliation(s)
- Katarzyna Zatońska
- Department of Population Health, Wroclaw Medical University, 50-345 Wroclaw, Poland; (K.Z.); (K.P.-Z.)
| | - Alicja Basiak-Rasała
- Department of Population Health, Wroclaw Medical University, 50-345 Wroclaw, Poland; (K.Z.); (K.P.-Z.)
| | - Katarzyna Połtyn-Zaradna
- Department of Population Health, Wroclaw Medical University, 50-345 Wroclaw, Poland; (K.Z.); (K.P.-Z.)
| | | | - Andrzej Szuba
- Department of Angiology, Hypertension and Diabetology, Wroclaw Medical University, 50-529 Wroclaw, Poland;
| |
Collapse
|
23
|
The Association between Temperament, Chronotype, Depressive Symptoms, and Disease Activity among Patients with Inflammatory Bowel Disease-A Cross-Sectional Pilot Study. Life (Basel) 2021; 11:life11121347. [PMID: 34947878 PMCID: PMC8706576 DOI: 10.3390/life11121347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Revised: 11/29/2021] [Accepted: 12/04/2021] [Indexed: 11/18/2022] Open
Abstract
The psychological aspect may play an important role in ulcerative colitis (UC) and Crohn’s disease (CD). The aims of this study were to explore the differences between patients with UC and CD regarding chronotype, temperament and depression, and to assess the psychological factors mentioned as predictors of disease activity. In total, n = 37 patients with UC and n = 47 patients with CD were included in the study. They underwent a clinical assessment, including the Mayo score or Crohn Disease Activity Index (CDAI), and completed questionnaires: a sociodemographic survey, Formal Characteristics of Behavior–Temperament Inventory (FCB-TI), Chronotype Questionnaire (CQ), and the Beck Depression Index II (BDI). The Sensory Sensitivity score was higher among patients with CD than UC (p = 0.04). The emotional reactivity and endurance scores were higher among women than men with CD (p = 0.028 and p = 0.012 respectively). CQ Morningness–Eveningness (ME) correlated with Endurance (p = 0.041), Emotional Reactivity (p = 0.016), and Activity (p = 0.004). ME correlated with Rhythmicity among CD patients (p = 0.002). The Mayo score was predicted by Perseverance. The CDAI score was predicted by the BDI score. The pattern of the relationship between chronotype and temperament may differentiate patients with UC and CD. Personal disposition may play a role in the clinical assessment of patients with IBD.
Collapse
|
24
|
Mokros Ł, Witusik A, Szydłowska D, Jankowski KS, Kuna P, Pietras T. Mental health indices may fully mediate the relationship between morningness-eveningness and disease control among adult asthma patients. J Asthma 2021; 59:1923-1932. [PMID: 34606405 DOI: 10.1080/02770903.2021.1989463] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Objective: The aim of this study was to assess the association between morningness-eveningness and disease control with consideration of mental state as a mediator and the control of confounding factors among adult asthma patients.Methods: This is a cross-sectional study, which included a nonrandom sample of N = 66 patients from an outpatient unit with a confirmed asthma diagnosis, who gave an informed consent and completed a set of questionnaires: a survey comprising questions about sociodemographic and clinical characteristics, the Asthma Control Test (ACT), the Composite Scale of Morningness (CSM), and the General Health Questionnaire (GHQ-28). Mediation models were created separately for each GHQ-28 dimension (somatic symptoms, anxiety/insomnia, social dysfunction and depressive symptoms), for a total score and for four GHQ-28 dimensions together, considered as mediators.Results: Low morning affect was related to poor disease symptom control among patients with asthma. The effect was fully mediated by non-psychotic mental health indices. Evening-time preference was associated with a rise in asthma control, and mediated by somatic symptoms and anxiety/insomnia, when controlled for morning affect.Conclusions: The current study underlines the significance of assessment of both individual morningness-eveningness preference and mental health in the management of asthma symptoms.
Collapse
Affiliation(s)
- Łukasz Mokros
- Department of Clinical Pharmacology, Medical University of Lodz, Lodz, Poland
| | - Andrzej Witusik
- Faculty of Composition, Theory of Music, Conducting, Eurhythmics and Music Education, Music Therapy Course, Grazyna and Kiejstut Bacewicz Memorial Academy of Music in Lodz, Lodz, Poland
| | - Dorota Szydłowska
- Clinical Department of Internal Medicine, Asthma and Allergy, Medical University of Lodz, Lodz, Poland
| | | | - Piotr Kuna
- Clinical Department of Internal Medicine, Asthma and Allergy, Medical University of Lodz, Lodz, Poland
| | - Tadeusz Pietras
- Second Department of Psychiatry, Institute of Psychiatry and Neurology, Warsaw, Poland
| |
Collapse
|
25
|
Abstract
Circadian disruption is pervasive and can occur at multiple organizational levels, contributing to poor health outcomes at individual and population levels. Evidence points to a bidirectional relationship, in that circadian disruption increases disease severity and many diseases can disrupt circadian rhythms. Importantly, circadian disruption can increase the risk for the expression and development of neurologic, psychiatric, cardiometabolic, and immune disorders. Thus, harnessing the rich findings from preclinical and translational research in circadian biology to enhance health via circadian-based approaches represents a unique opportunity for personalized/precision medicine and overall societal well-being. In this Review, we discuss the implications of circadian disruption for human health using a bench-to-bedside approach. Evidence from preclinical and translational science is applied to a clinical and population-based approach. Given the broad implications of circadian regulation for human health, this Review focuses its discussion on selected examples in neurologic, psychiatric, metabolic, cardiovascular, allergic, and immunologic disorders that highlight the interrelatedness between circadian disruption and human disease and the potential of circadian-based interventions, such as bright light therapy and exogenous melatonin, as well as chronotherapy to improve and/or modify disease outcomes.
Collapse
Affiliation(s)
- Anna B Fishbein
- Department of Pediatrics, Division of Pediatric Allergy and Immunology, Ann & Robert H. Lurie Children's Hospital, and
| | - Kristen L Knutson
- Department of Neurology and Center for Circadian and Sleep Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Phyllis C Zee
- Department of Neurology and Center for Circadian and Sleep Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| |
Collapse
|
26
|
Petrov ME, Pituch KA, Kasraeian K, Jiao N, Mattingly J, Hasanaj K, Youngstedt SD, Buman MP, Epstein DR. Impact of the COVID-19 pandemic on change in sleep patterns in an exploratory, cross-sectional online sample of 79 countries. Sleep Health 2021; 7:451-458. [PMID: 34193394 DOI: 10.1016/j.sleh.2021.05.007] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Revised: 05/05/2021] [Accepted: 05/11/2021] [Indexed: 10/21/2022]
Abstract
OBJECTIVES To describe changes in sleep patterns during the coronavirus disease 2019 (COVID-19) pandemic, develop profiles according to these patterns, and assess sociodemographic, economic, COVID-19 related, and sleep and mental health factors associated with these profiles. DESIGN, SETTING, AND PARTICIPANTS A 25-minute online survey was distributed worldwide through social media from 5/21/2020 to 7/1/2020. MEASUREMENTS Participants reported sociodemographic/economic information, the impact of the pandemic on major life domains, insomnia and depressive symptoms, and changes in sleep midpoint, time-in-bed, total sleep time (TST), sleep efficiency (SE), and nightmare and nap frequency from prior to during the pandemic. Sleep pattern changes were subjected to latent profile analysis. The identified profiles were compared to one another on all aforementioned factors using probit regression analyses. RESULTS The sample of 991 participants (ages: 18-80 years; 72.5% women; 60.3% residing outside of the United States) reported significantly delayed sleep midpoint, reductions in TST and SE, and increases in nightmares and naps. Over half reported significant insomnia symptoms, and almost two-thirds reported significant depressive symptoms. Latent profile analysis revealed 4 sleep pattern change profiles that were significantly differentiated by pre-pandemic sleep patterns, gender, and various COVID-19-related impacts on daily living such as severity of change in routines, and family stress and discord. CONCLUSIONS In an international online sample, poor sleep and depressive symptoms were widespread, and negative shifts in sleep patterns from pre-pandemic patterns were common. Differences in sleep pattern response to the COVID-19 crisis suggest potential and early targets for behavioral sleep health interventions.
Collapse
Affiliation(s)
- Megan E Petrov
- Edson College of Nursing and Health Innovation, Arizona State University, Phoenix, Arizona, USA.
| | - Keenan A Pituch
- Edson College of Nursing and Health Innovation, Arizona State University, Phoenix, Arizona, USA
| | - Kimiya Kasraeian
- College of Health Solutions, Arizona State University, Phoenix, Arizona, USA
| | - Nana Jiao
- Edson College of Nursing and Health Innovation, Arizona State University, Phoenix, Arizona, USA
| | - Jennifer Mattingly
- Edson College of Nursing and Health Innovation, Arizona State University, Phoenix, Arizona, USA
| | - Kristina Hasanaj
- Edson College of Nursing and Health Innovation, Arizona State University, Phoenix, Arizona, USA; College of Health Solutions, Arizona State University, Phoenix, Arizona, USA
| | - Shawn D Youngstedt
- Edson College of Nursing and Health Innovation, Arizona State University, Phoenix, Arizona, USA; College of Health Solutions, Arizona State University, Phoenix, Arizona, USA
| | - Matthew P Buman
- College of Health Solutions, Arizona State University, Phoenix, Arizona, USA
| | - Dana R Epstein
- Edson College of Nursing and Health Innovation, Arizona State University, Phoenix, Arizona, USA; College of Health Solutions, Arizona State University, Phoenix, Arizona, USA
| |
Collapse
|
27
|
Abstract
Sleep is essential for healthy being and healthy functioning of human body as a whole, as well as each organ and system. Sleep disorders, such as sleep-disordered breathing, insomnia, sleep fragmentation, and sleep deprivation are associated with the deterioration in human body functioning and increased cardiovascular risks. However, owing to the complex regulation and heterogeneous state sleep per se can be associated with cardiovascular dysfunction in susceptible subjects. The understanding of sleep as a multidimensional concept is important for better prevention and treatment of cardiovascular diseases.
Collapse
Affiliation(s)
- Lyudmila Korostovtseva
- Sleep Laboratory, Research Department for Hypertension, Department for Cardiology, Almazov National Medical Research Centre, 2 Akkuratov Street, St Petersburg 197341, Russia.
| | - Mikhail Bochkarev
- Sleep Laboratory, Research Department for Hypertension, Almazov National Medical Research Centre, 2 Akkuratov Street, St Petersburg 197341, Russia
| | - Yurii Sviryaev
- Research Department for Hypertension, Almazov National Medical Research Centre, 2 Akkuratov Street, St Petersburg 197341, Russia
| |
Collapse
|
28
|
Tse LA, Wang C, Rangarajan S, Liu Z, Teo K, Yusufali A, Avezum Á, Wielgosz A, Rosengren A, Kruger IM, Chifamba J, Calik KBT, Yeates K, Zatońska K, AlHabib KF, Yusoff K, Kaur M, Ismail N, Seron P, Lopez-Jaramillo P, Poirier P, Gupta R, Khatib R, Kelishadi R, Lear SA, Choudhury T, Mohan V, Li W, Yusuf S. Timing and Length of Nocturnal Sleep and Daytime Napping and Associations With Obesity Types in High-, Middle-, and Low-Income Countries. JAMA Netw Open 2021; 4:e2113775. [PMID: 34190997 PMCID: PMC8246307 DOI: 10.1001/jamanetworkopen.2021.13775] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
IMPORTANCE Obesity is a growing public health threat leading to serious health consequences. Late bedtime and sleep loss are common in modern society, but their associations with specific obesity types are not well characterized. OBJECTIVE To assess whether sleep timing and napping behavior are associated with increased obesity, independent of nocturnal sleep length. DESIGN, SETTING, AND PARTICIPANTS This large, multinational, population-based cross-sectional study used data of participants from 60 study centers in 26 countries with varying income levels as part of the Prospective Urban Rural Epidemiology study. Participants were aged 35 to 70 years and were mainly recruited during 2005 and 2009. Data analysis occurred from October 2020 through March 2021. EXPOSURES Sleep timing (ie, bedtime and wake-up time), nocturnal sleep duration, daytime napping. MAIN OUTCOMES AND MEASURES The primary outcomes were prevalence of obesity, specified as general obesity, defined as body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) of 30 or greater, and abdominal obesity, defined as waist circumference greater than 102 cm for men or greater than 88 cm for women. Multilevel logistic regression models with random effects for study centers were performed to calculate adjusted odds ratios (AORs) and 95% CIs. RESULTS Overall, 136 652 participants (81 652 [59.8%] women; mean [SD] age, 51.0 [9.8] years) were included in analysis. A total of 27 195 participants (19.9%) had general obesity, and 37 024 participants (27.1%) had abdominal obesity. The mean (SD) nocturnal sleep duration was 7.8 (1.4) hours, and the median (interquartile range) midsleep time was 2:15 am (1:30 am-3:00 am). A total of 19 660 participants (14.4%) had late bedtime behavior (ie, midnight or later). Compared with bedtime between 8 pm and 10 pm, late bedtime was associated with general obesity (AOR, 1.20; 95% CI, 1.12-1.29) and abdominal obesity (AOR, 1.20; 95% CI, 1.12-1.28), particularly among participants who went to bed between 2 am and 6 am (general obesity: AOR, 1.35; 95% CI, 1.18-1.54; abdominal obesity: AOR, 1.38; 95% CI, 1.21-1.58). Short nocturnal sleep of less than 6 hours was associated with general obesity (eg, <5 hours: AOR, 1.27; 95% CI, 1.13-1.43), but longer napping was associated with higher abdominal obesity prevalence (eg, ≥1 hours: AOR, 1.39; 95% CI, 1.31-1.47). Neither going to bed during the day (ie, before 8pm) nor wake-up time was associated with obesity. CONCLUSIONS AND RELEVANCE This cross-sectional study found that late nocturnal bedtime and short nocturnal sleep were associated with increased risk of obesity prevalence, while longer daytime napping did not reduce the risk but was associated with higher risk of abdominal obesity. Strategic weight control programs should also encourage earlier bedtime and avoid short nocturnal sleep to mitigate obesity epidemic.
Collapse
Affiliation(s)
- Lap Ah Tse
- Jockey Club School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China
| | - Chuangshi Wang
- Medical Research and Biometrics Center, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China
| | - Sumathy Rangarajan
- Population Health Research Institute, McMaster University, Hamilton, Canada
| | - Zhiguang Liu
- Division of Occupational and Environmental Health, Jockey Club School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China
| | - Koon Teo
- Population Health Research Institute, McMaster University, Hamilton, Canada
| | - Afzalhussein Yusufali
- Dubai Medical University, Hatta Hospital, Dubai Health Authority, Dubai, United Arab Emirates
| | - Álvaro Avezum
- Research Division, Dante Pazzanese Institute of Cardiology, São Paulo, Brazil
| | | | - Annika Rosengren
- Department of Molecular and Clinical Medicine, Sahlgrenska Academy, University of Gothenburg and Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Iolanthé M. Kruger
- Africa Unit for Transdisciplinary Health Research, North-West University, Potcehfstroom, South Africa
| | - Jephat Chifamba
- Department of Physiology, University of Zimbabwe College of Health Sciences, Harare, Zimbabwe
| | - K. Burcu Tumerdem Calik
- Department of Health Management, Faculty of Health Sciences, Marmara University, Istanbul, Turkey
| | - Karen Yeates
- Department of Medicine, Faculty of Health Sciences, Queen’s University, Kingston, Canada
| | - Katarzyna Zatońska
- Department of Social Medicine, Wroclaw Medical University, Wroclaw Poland
| | - Khalid F. AlHabib
- Department of Cardiac Sciences, King Fahad Cardiac Center, King Saud University College of Medicine, Riyadh, Saudi Arabia
| | - Khalid Yusoff
- Universiti Teknologi MARA, Selayang, Malaysia
- UCSI University, Kuala Lumpur, Malaysia
| | - Manmeet Kaur
- Department of Community Medicine and School of Public Health, Postgraduate Institute of Medical Education and Research, Chandigarh, India
| | - Noorhassim Ismail
- Department of Community Health, Faculty of Medicine, University Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - Pamela Seron
- Dpto Medicina Interna, Facultad de Medicina, Universidad de La Frontera, Temuco, Chile
| | | | - Paul Poirier
- Faculté de pharmacie, Université Laval, Québec, Canada
| | - Rajeev Gupta
- Eternal Heart Care Centre and Research Institute, Jaipur, India
| | - Rasha Khatib
- Institute of Community and Public Health, Birzeit University, Birzeit, Palestine
| | - Roya Kelishadi
- Isfahan Cardiovascular Research Center, Cardiovascular Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Scott A. Lear
- Faculty of Health Sciences, Simon Fraser University, Burnaby, Canada
| | | | - Viswanathan Mohan
- Madras Diabetes Research Foundation, Dr Mohan’s Diabetes Specialities Centre, Chennai, India
| | - Wei Li
- Medical Research and Biometrics Center, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China
| | - Salim Yusuf
- Population Health Research Institute, McMaster University, Hamilton, Canada
| |
Collapse
|
29
|
Zhai Z, Liu X, Zhang H, Dong X, He Y, Niu M, Pan M, Wang C, Wang X, Li Y. Associations of midpoint of sleep and night sleep duration with type 2 diabetes mellitus in Chinese rural population: the Henan rural cohort study. BMC Public Health 2021; 21:879. [PMID: 33962597 PMCID: PMC8106181 DOI: 10.1186/s12889-021-10833-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Accepted: 04/13/2021] [Indexed: 01/18/2023] Open
Abstract
Background The study aimed to investigate the independent and combined effects of midpoint of sleep and night sleep duration on type 2 diabetes mellitus (T2DM) in areas with limited resources. Methods A total of 37,276 participants (14,456 men and 22,820 women) were derived from the Henan Rural Cohort Study. Sleep information was assessed based on the Pittsburgh Sleep Quality Index. Logistic regression models and restricted cubic splines were used to estimate the relationship of the midpoint of sleep and night sleep duration with T2DM. Results Of the 37,276 included participants, 3580 subjects suffered from T2DM. The mean midpoint of sleep among the Early, Intermediate and Late groups were 1:05 AM ±23 min, 1:56 AM ±14 min, and 2:57 AM ±34 min, respectively. Compared to the Intermediate group, adjusted odds ratios (ORs) and 95% confidence interval (CI) of T2DM were 1.13 (1.04–1.22) and 1.14 (1.03–1.26) in the Early group and the Late group. Adjusted OR (95% CI) for T2DM compared with the reference (7- h) was 1.28 (1.08–1.51) for longer (≥ 10 h) night sleep duration. The combination of late midpoint of sleep and night sleep duration (≥ 9 h) increased 38% (95% CI 10–74%) prevalence of T2DM. These associations were more obvious in women than men. Conclusions Late and early midpoint of sleep and long night sleep duration were all associated with higher prevalence of T2DM. Meanwhile, midpoint of sleep and night sleep duration might have combined effects on the prevalence of T2DM, which provided potential health implications for T2DM prevention, especially in rural women. Trial registration The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). Date of registration: 2015-07-06. Supplementary Information The online version contains supplementary material available at 10.1186/s12889-021-10833-6.
Collapse
Affiliation(s)
- Zhihan Zhai
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, PR China
| | - Xiaotian Liu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, PR China
| | - Haiqing Zhang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, PR China
| | - Xiaokang Dong
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, PR China
| | - Yaling He
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, PR China
| | - Miaomiao Niu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, PR China
| | - Mingming Pan
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, PR China.,Department of Preventive Medicine, Henan University of Chinese Medicine, 156 East Jinshui, Zhengzhou, Henan, 450046, PR China
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, PR China
| | - Xiaoqiong Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, PR China. .,Department of Economics, Business School, Zhengzhou University, Zhengzhou, Henan, PR China.
| | - Yuqian Li
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, PR China. .,Department of Clinical Pharmacology, School of Pharmaceutical Science, Zhengzhou University, Zhengzhou, Henan, PR China.
| |
Collapse
|
30
|
Dashti HS, Cade BE, Stutaite G, Saxena R, Redline S, Karlson EW. Sleep health, diseases, and pain syndromes: findings from an electronic health record biobank. Sleep 2021; 44:5909423. [PMID: 32954408 DOI: 10.1093/sleep/zsaa189] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Revised: 08/28/2020] [Indexed: 02/02/2023] Open
Abstract
STUDY OBJECTIVES Implementation of electronic health record biobanks has facilitated linkage between clinical and questionnaire data and enabled assessments of relationships between sleep health and diseases in phenome-wide association studies (PheWAS). In the Mass General Brigham Biobank, a large health system-based study, we aimed to systematically catalog associations between time in bed, sleep timing, and weekly variability with clinical phenotypes derived from ICD-9/10 codes. METHODS Self-reported habitual bed and wake times were used to derive variables: short (<7 hours) and long (≥9 hours) time in bed, sleep midpoint, social jetlag, and sleep debt. Logistic regression and Cox proportional hazards models were used to test cross-sectional and prospective associations, respectively, adjusted for age, gender, race/ethnicity, and employment status and further adjusted for body mass index. RESULTS In cross-sectional analysis (n = 34,651), sleep variable associations were most notable for circulatory system, mental disorders, and endocrine/metabolic phenotypes. We observed the strongest associations for short time in bed with obesity, for long time in bed and sleep midpoint with major depressive disorder, for social jetlag with hypercholesterolemia, and for sleep debt with acne. In prospective analysis (n = 24,065), we observed short time in bed associations with higher incidence of acute pain and later sleep midpoint and higher sleep debt and social jetlag associations with higher incidence of major depressive disorder. CONCLUSIONS Our analysis reinforced that sleep health is a multidimensional construct, corroborated robust known findings from traditional cohort studies, and supported the application of PheWAS as a promising tool for advancing sleep research. Considering the exploratory nature of PheWAS, careful interrogation of novel findings is imperative.
Collapse
Affiliation(s)
- Hassan S Dashti
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA.,Broad Institute, Cambridge, MA.,Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | - Brian E Cade
- Broad Institute, Cambridge, MA.,Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA.,Division of Sleep Medicine, Harvard Medical School, Boston, MA
| | - Gerda Stutaite
- Mass General Brigham Personalized Medicine, Mass General Brigham, Boston, MA
| | - Richa Saxena
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA.,Broad Institute, Cambridge, MA.,Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA.,Division of Sleep Medicine, Harvard Medical School, Boston, MA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA.,Division of Sleep Medicine, Harvard Medical School, Boston, MA.,Department of Medicine, Brigham and Women's Hospital and Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA
| | - Elizabeth W Karlson
- Mass General Brigham Personalized Medicine, Mass General Brigham, Boston, MA.,Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital, Boston, MA
| |
Collapse
|
31
|
Fritz J, Phillips AJK, Hunt LC, Imam A, Reid KJ, Perreira KM, Mossavar-Rahmani Y, Daviglus ML, Sotres-Alvarez D, Zee PC, Patel SR, Vetter C. Cross-sectional and prospective associations between sleep regularity and metabolic health in the Hispanic Community Health Study/Study of Latinos. Sleep 2021; 44:5937003. [PMID: 33095850 DOI: 10.1093/sleep/zsaa218] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Revised: 09/19/2020] [Indexed: 12/23/2022] Open
Abstract
STUDY OBJECTIVES Sleep is an emergent, multi-dimensional risk factor for diabetes. Sleep duration, timing, quality, and insomnia have been associated with diabetes risk and glycemic biomarkers, but the role of sleep regularity in the development of metabolic disorders is less clear. METHODS We analyzed data from 2107 adults, aged 19-64 years, from the Sueño ancillary study of the Hispanic Community Health Study/Study of Latinos, followed over a mean of 5.7 years. Multivariable-adjusted complex survey regression methods were used to model cross-sectional and prospective associations between the sleep regularity index (SRI) in quartiles (Q1-least regular, Q4-most regular) and diabetes (either laboratory-confirmed or self-reported antidiabetic medication use), baseline levels of insulin resistance (HOMA-IR), beta-cell function (HOMA-β), hemoglobin A1c (HbA1c), and their changes over time. RESULTS Cross-sectionally, lower SRI was associated with higher odds of diabetes (odds ratio [OR]Q1 vs. Q4 = 1.64, 95% CI: 0.98-2.74, ORQ2 vs. Q4 = 1.12, 95% CI: 0.70-1.81, ORQ3 vs. Q4 = 1.00, 95% CI: 0.62-1.62, ptrend = 0.023). The SRI effect was more pronounced in older (aged ≥ 45 years) adults (ORQ1 vs. Q4 = 1.88, 95% CI: 1.14-3.12, pinteraction = 0.060) compared to younger ones. No statistically significant associations were found between SRI and diabetes incidence, as well as baseline HOMA-IR, HOMA-β, and HbA1c values, or their changes over time among adults not taking antidiabetic medication. CONCLUSIONS Our results suggest that sleep regularity represents another sleep dimension relevant for diabetes risk. Further research is needed to elucidate the relative contribution of sleep regularity to metabolic dysregulation and pathophysiology.
Collapse
Affiliation(s)
- Josef Fritz
- Circadian and Sleep Epidemiology Laboratory, Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO
| | - Andrew J K Phillips
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
| | - Larissa C Hunt
- Circadian and Sleep Epidemiology Laboratory, Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO
| | - Akram Imam
- Circadian and Sleep Epidemiology Laboratory, Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO
| | - Kathryn J Reid
- Center for Circadian and Sleep Medicine, Department of Neurology, Northwestern University, Chicago, IL
| | - Krista M Perreira
- Department of Social Medicine, University of North Carolina School of Medicine, Chapel Hill, NC
| | - Yasmin Mossavar-Rahmani
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY
| | - Martha L Daviglus
- College of Medicine, Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL
| | - Daniela Sotres-Alvarez
- Collaborative Studies Coordinating Center, Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Phyllis C Zee
- Center for Circadian and Sleep Medicine, Department of Neurology, Northwestern University, Chicago, IL
| | - Sanjay R Patel
- Center for Sleep and Cardiovascular Outcomes Research, University of Pittsburgh, Pittsburgh, PA
| | - Céline Vetter
- Circadian and Sleep Epidemiology Laboratory, Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO
| |
Collapse
|
32
|
Wu IH, Heredia N, Dong Q, McNeill LH, Balachandran DD, Lu Q, Chang S. Sleep duration and type 2 diabetes risk: A prospective study in a population-based Mexican American cohort. Sleep Health 2021; 7:168-176. [PMID: 33582048 DOI: 10.1016/j.sleh.2020.12.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 12/03/2020] [Accepted: 12/09/2020] [Indexed: 12/20/2022]
Abstract
STUDY OBJECTIVES The primary aim of the study was to estimate the effect of sleep duration on prospective type 2 diabetes (T2D) risk across demographic characteristics and follow-up periods, and test body mass index (BMI) as a mediator and moderator. METHODS Data included adults (Mage = 39.0 ± 12.7 years) born in the United States or Mexico recruited from 2001 to 2012 in a Mexican American cohort study conducted in Houston, TX (n = 15,779). Participants completed self-reported questionnaires at baseline related to health, health behaviors (sleep duration, physical activity, smoking, drinking), and sociocultural factors and were followed up annually. RESULTS Cox proportional hazard models estimated hazard ratios (HR) for the effect of sleep duration on T2D diagnosis at follow-up. Of the participants, 10.3% were diagnosed with T2D. Self-reported ≤5 hours of sleep, compared to 7-8 hours, at baseline predicted greater risk for T2D (HR = 1.32, P = .001), yet was no longer significant after adjusting for sociodemographic characteristics and BMI. Notably, those with BMI <25 kg/m2 reporting ≤5 hours of sleep were at significant risk for T2D at 3 (HR = 4.13, P = .024) and 5-year follow-up (HR = 3.73, P = .008) compared to 7-8 hours. Obesity status accounted for 31.6% and 27.3% of the variance in the association between ≤5 and 6 hours of sleep and increased T2D risk, respectively. CONCLUSIONS Results highlighted the mediating and moderating role of BMI, and its effect on T2D risk at earlier follow-up among those without obesity. T2D prevention and control for Mexican American adults should consider the role of chronic sleep loss.
Collapse
Affiliation(s)
- Ivan Hc Wu
- Department of Health Disparities Research, University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
| | - Natalia Heredia
- Department of Health Promotion & Behavioral Sciences, The University of Texas Health Science Center at Houston, School of Public Health, Houston, Texas, USA
| | - Qiong Dong
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Lorna H McNeill
- Department of Health Disparities Research, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Diwakar D Balachandran
- Department of Pulmonary Medicine, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Qian Lu
- Department of Health Disparities Research, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Shine Chang
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| |
Collapse
|
33
|
Association of bedtime with mortality and major cardiovascular events: an analysis of 112,198 individuals from 21 countries in the PURE study. Sleep Med 2021; 80:265-272. [PMID: 33610073 DOI: 10.1016/j.sleep.2021.01.057] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2020] [Accepted: 01/28/2021] [Indexed: 12/13/2022]
Abstract
OBJECTIVES This study aimed to examine the association of bedtime with mortality and major cardiovascular events. METHODS Bedtime was recorded based on self-reported habitual time of going to bed in 112,198 participants from 21 countries in the Prospective Urban Rural Epidemiology (PURE) study. Participants were prospectively followed for 9.2 years. We examined the association between bedtime and the composite outcome of all-cause mortality, non-fatal myocardial infarction, stroke and heart failure. Participants with a usual bedtime earlier than 10PM were categorized as 'earlier' sleepers and those who reported a bedtime after midnight as 'later' sleepers. Cox frailty models were applied with random intercepts to account for the clustering within centers. RESULTS A total of 5633 deaths and 5346 major cardiovascular events were reported. A U-shaped association was observed between bedtime and the composite outcome. Using those going to bed between 10PM and midnight as the reference group, after adjustment for age and sex, both earlier and later sleepers had a higher risk of the composite outcome (HR of 1.29 [1.22, 1.35] and 1.11 [1.03, 1.20], respectively). In the fully adjusted model where demographic factors, lifestyle behaviors (including total sleep duration) and history of diseases were included, results were greatly attenuated, but the estimates indicated modestly higher risks in both earlier (HR of 1.09 [1.03-1.16]) and later sleepers (HR of 1.10 [1.02-1.20]). CONCLUSION Early (10 PM or earlier) or late (Midnight or later) bedtimes may be an indicator or risk factor of adverse health outcomes.
Collapse
|
34
|
Marhuenda J, Villaño D, Arcusa R, Zafrilla P. Melatonin in Wine and Beer: Beneficial Effects. Molecules 2021; 26:molecules26020343. [PMID: 33440795 PMCID: PMC7827953 DOI: 10.3390/molecules26020343] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 01/04/2021] [Accepted: 01/05/2021] [Indexed: 12/15/2022] Open
Abstract
Melatonin is a hormone secreted in the pineal gland with several functions, especially regulation of circadian sleep cycle and the biological processes related to it. This review evaluates the bioavailability of melatonin and resulting metabolites, the presence of melatonin in wine and beer and factors that influence it, and finally the different benefits related to treatment with melatonin. When administered orally, melatonin is mainly absorbed in the rectum and the ileum; it has a half-life of about 0.45–1 h and is extensively inactivated in the liver by phase 2 enzymes. Melatonin (MEL) concentration varies from picograms to ng/mL in fermented beverages such as wine and beer, depending on the fermentation process. These low quantities, within a dietary intake, are enough to reach significant plasma concentrations of melatonin, and are thus able to exert beneficial effects. Melatonin has demonstrated antioxidant, anticarcinogenic, immunomodulatory and neuroprotective actions. These benefits are related to its free radical scavenging properties as well and the direct interaction with melatonin receptors, which are involved in complex intracellular signaling pathways, including inhibition of angiogenesis and cell proliferation, among others. In the present review, the current evidence on the effects of melatonin on different pathophysiological conditions is also discussed.
Collapse
|
35
|
Li R, Zhang J, Gao Y, Zhang Y, Lan X, Dong H, Wu C, Yu C, Peng M, Zeng G. Duration and quality of sleep during pregnancy are associated with preterm birth and small for gestational age: A prospective study. Int J Gynaecol Obstet 2021; 155:505-511. [PMID: 33421108 DOI: 10.1002/ijgo.13584] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 09/30/2020] [Accepted: 01/06/2021] [Indexed: 11/08/2022]
Abstract
OBJECTIVE To explore the associations of duration and quality of sleep during pregnancy with preterm birth and small for gestational age (SGA). METHODS A prospective study was carried out on 1082 healthy women with singleton pregnancies from Chengdu, China. Self-report questionnaires, including duration and quality of sleep and other information, were administered at 8-12, 24-28, and 32-36 weeks of pregnancy. Data on gestational age and weight and length of the neonates were recorded after delivery. After controlling the potential confounders, a multivariable logistic regression model was performed to evaluate whether duration and quality of sleep were associated with preterm birth and SGA. RESULTS Participants with short duration of sleep during the third trimester were more likely to report preterm birth (odds ratio [OR] 2.16, 95% confidence interval [CI] 1.26-4.81) and SGA (OR 2.67, 95% CI 1.18-6.54). Participants with poor quality of sleep during the third trimester were at high risk for preterm birth (OR 2.26, 95% CI 1.29-5.84) and SGA (OR 2.08, 95% CI 1.19-5.38). CONCLUSION Short duration and poor quality of sleep during pregnancy are associated with an increased risk of preterm birth and SGA. Sleep characteristics should be assessed during prenatal evaluations to decrease adverse maternal and fetal outcomes.
Collapse
Affiliation(s)
- Run Li
- Department of Clinical Nutrition, Sichuan Provincial Hospital for Women and Children, Chengdu, China
| | - Ju Zhang
- Department of Clinical Nutrition, Sichuan Provincial Hospital for Women and Children, Chengdu, China
| | - Yan Gao
- Department of Obstetrics, Sichuan Provincial Hospital for Women and Children, Chengdu, China
| | - Yiqi Zhang
- Department of Nutrition, Food Safety and Toxicology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Xi Lan
- Department of Nutrition, Food Safety and Toxicology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Hongli Dong
- Department of Nutrition, Food Safety and Toxicology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Cheng Wu
- Department of Clinical Nutrition, Sichuan Provincial Hospital for Women and Children, Chengdu, China
| | - Chengwei Yu
- Department of Clinical Nutrition, Sichuan Provincial Hospital for Women and Children, Chengdu, China
| | - Min Peng
- Department of Clinical Nutrition, Sichuan Provincial Hospital for Women and Children, Chengdu, China
| | - Guo Zeng
- Department of Nutrition, Food Safety and Toxicology, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| |
Collapse
|
36
|
Risk of mortality among patients with moderate to severe obstructive sleep apnea and diabetes mellitus: results from the SantOSA cohort. Sleep Breath 2021; 25:1467-1475. [PMID: 33394326 DOI: 10.1007/s11325-020-02283-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 11/28/2020] [Accepted: 12/21/2020] [Indexed: 10/22/2022]
Abstract
INTRODUCTION Patients with obstructive sleep apnea (OSA) and comorbid diabetes mellitus (DM) are reported to have an increased risk of cardiovascular (CV) outcomes; however, data on CV mortality are scant. AIM This study aimed to evaluate if patients with comorbid OSA and DM have an increased risk of CV mortality that is higher than the two diseases in isolation. METHODS In this prospective cohort study, we included patients referred for a sleep study with and without DM at baseline. We developed four study groups as follows: group 1 (reference group), OSA (-) DM (-); group 2, OSA (-) DM (+); group 3, OSA (+) DM (-); group 4, OSA (+) DM (+). Intergroup differences were evaluated using the t test and χ2 test, and multivariate analysis was performed using logistic regression. The incidence rates of CV mortality were calculated using the Kaplan-Meier (log-rank) model, and adjusted HRs were calculated using the Cox regression model. RESULTS A total of 1447 patients were included in the analysis-group 1: 441 participants; group 2: 141 participants; group 3: 736 participants; group 4: 151 participants. The mean follow-up was 5 years. The association between OSA + DM showed an independent risk of incident CV mortality (HR 2.37, CI 1.16-4.82, p = 0.02) and an increased prevalence of coronary heart disease (OR 3.44, CI 1.73-5.59, p < 0.01). In addition, T90% was also associated with CV mortality. CONCLUSION The coexistence of OSA + DM was associated with an independent risk of CV mortality. In addition, T90% was also associated with CV mortality.
Collapse
|
37
|
Mahdavinia M, Kapil A, Bernstein JS, Lastra AC, LoSavio PS. Race as a risk factor for sleep timing shift and disruption in chronic rhinosinusitis. Ann Allergy Asthma Immunol 2020; 126:429-431. [PMID: 33144267 DOI: 10.1016/j.anai.2020.10.019] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 10/14/2020] [Accepted: 10/27/2020] [Indexed: 10/23/2022]
Affiliation(s)
- Mahboobeh Mahdavinia
- Division of Allergy and Immunology, Department of Internal Medicine, Rush University Medical Center, Chicago, Illinois
| | - Anuja Kapil
- Division of Allergy and Immunology, Department of Internal Medicine, Rush University Medical Center, Chicago, Illinois.
| | - Joshua S Bernstein
- Department of Internal Medicine, Rush University Medical Center, Chicago, Illinois
| | - Alejandra C Lastra
- Sleep Disorders Service and Research Center, Rush University Medical Center, Chicago, Illinois
| | - Phillip S LoSavio
- Department of Otorhinolaryngology-Head and Neck Surgery, Rush University Medical Center, Chicago, Illinois
| |
Collapse
|
38
|
Chaput JP, Dutil C, Featherstone R, Ross R, Giangregorio L, Saunders TJ, Janssen I, Poitras VJ, Kho ME, Ross-White A, Zankar S, Carrier J. Sleep timing, sleep consistency, and health in adults: a systematic review. Appl Physiol Nutr Metab 2020; 45:S232-S247. [DOI: 10.1139/apnm-2020-0032] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
The objective of this systematic review was to examine the associations between sleep timing (e.g., bedtime/wake-up time, midpoint of sleep), sleep consistency/regularity (e.g., intra-individual variability in sleep duration, social jetlag, catch-up sleep), and health outcomes in adults aged 18 years and older. Four electronic databases were searched in December 2018 for articles published in the previous 10 years. Fourteen health outcomes were examined. A total of 41 articles, including 92 340 unique participants from 14 countries, met inclusion criteria. Sleep was assessed objectively in 37% of studies and subjectively in 63% of studies. Findings suggest that later sleep timing and greater sleep variability were generally associated with adverse health outcomes. However, because most studies reported linear associations, it was not possible to identify thresholds for “late sleep timing” or “large sleep variability”. In addition, social jetlag was associated with adverse health outcomes, while weekend catch-up sleep was associated with better health outcomes. The quality of evidence ranged from “very low” to “moderate” across study designs and health outcomes using GRADE. In conclusion, the available evidence supports that earlier sleep timing and regularity in sleep patterns with consistent bedtimes and wake-up times are favourably associated with health. (PROSPERO registration no.: CRD42019119534.) Novelty This is the first systematic review to examine the influence of sleep timing and sleep consistency on health outcomes. Later sleep timing and greater variability in sleep are both associated with adverse health outcomes in adults. Regularity in sleep patterns with consistent bedtimes and wake-up times should be encouraged.
Collapse
Affiliation(s)
- Jean-Philippe Chaput
- Healthy Active Living and Obesity Research Group, Children’s Hospital of Eastern Ontario Research Institute, Ottawa, ON K1H 8L1, Canada
| | - Caroline Dutil
- Healthy Active Living and Obesity Research Group, Children’s Hospital of Eastern Ontario Research Institute, Ottawa, ON K1H 8L1, Canada
| | - Ryan Featherstone
- Healthy Active Living and Obesity Research Group, Children’s Hospital of Eastern Ontario Research Institute, Ottawa, ON K1H 8L1, Canada
| | - Robert Ross
- School of Kinesiology and Health Studies, Queen’s University, Kingston, ON K7L 3N6, Canada
| | - Lora Giangregorio
- Department of Kinesiology, University of Waterloo, Waterloo, ON N2L 3G1, Canada
| | - Travis J. Saunders
- Department of Applied Human Sciences, University of Prince Edward Island, Charlottetown, PE C1A 4P3, Canada
| | - Ian Janssen
- School of Kinesiology and Health Studies, Queen’s University, Kingston, ON K7L 3N6, Canada
| | | | - Michelle E. Kho
- School of Rehabilitation Sciences, McMaster University, Hamilton, ON L8S 1C7, Canada
| | - Amanda Ross-White
- Queen’s University Library, Queen’s University, Kingston, ON K7L 3N6, Canada
| | - Sarah Zankar
- Healthy Active Living and Obesity Research Group, Children’s Hospital of Eastern Ontario Research Institute, Ottawa, ON K1H 8L1, Canada
| | - Julie Carrier
- Départment de psychologie, Université de Montréal, Montreal, QC H2V 2S9, Canada
| |
Collapse
|
39
|
Hu C, Zhang Y, Wang S, Lin L, Peng K, Du R, Qi H, Zhang J, Wang T, Zhao Z, Li M, Xu Y, Xu M, Li D, Bi Y, Wang W, Chen Y, Lu J. Association of bedtime with the risk of non-alcoholic fatty liver disease among middle-aged and elderly Chinese adults with pre-diabetes and diabetes. Diabetes Metab Res Rev 2020; 36:e3322. [PMID: 32268002 DOI: 10.1002/dmrr.3322] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Revised: 01/27/2020] [Accepted: 03/30/2020] [Indexed: 12/13/2022]
Abstract
BACKGROUND Emerging evidence indicated that sleep characteristics may play important roles in the development of metabolic disorders. However, little is known as to the association between bedtime and the risk of non-alcoholic fatty liver disease (NAFLD) in individuals with pre-diabetes and diabetes. METHODS In a prospective cohort of 10 375 adults aged ≥40 years, 1960 of 3484 eligible pre-diabetic and diabetic individuals were identified for the current study. NAFLD was diagnosed using liver ultrasonography at baseline and at follow-up. Information on bedtime was obtained at baseline using a standard questionnaire. RESULTS We documented 433 incident cases of NAFLD among this study population. In multivariable-adjusted logistic regression model, later bedtime was associated with increased risk of NAFLD (29% increased risk per hour of later bedtime). Compared to individuals with bedtime ≤20:00, the odds ratios (95% confidence intervals) of NAFLD for bedtime of 20:00-22:00 and ≥22:00 were 1.56 (1.04-2.34) and 2.05 (1.31-3.20), respectively. In the subgroup analysis, significant associations were observed among those who were overweight or physically inactive, or those with metabolic syndrome or elevated 10-year risks for atherosclerotic cardiovascular disease. When estimating the joint effect of bedtime and other sleep characteristics, higher risk of incident NAFLD was observed in groups of late bed/early rise, late bed/napping (yes), late bed/bad sleeper, or late bed/shorter sleep durations. CONCLUSIONS Later bedtime was significantly associated with an increased risk of incident NAFLD in adults with pre-diabetes and diabetes, underscoring the importance of sleep behaviour management in the prevention of NAFLD.
Collapse
Affiliation(s)
- Chunyan Hu
- Shanghai National Clinical Research Center for Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Shanghai, China
| | - Yi Zhang
- Shanghai National Clinical Research Center for Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Shanghai, China
| | - Shuangyuan Wang
- Shanghai National Clinical Research Center for Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Shanghai, China
| | - Lin Lin
- Shanghai National Clinical Research Center for Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Shanghai, China
| | - Kui Peng
- Shanghai National Clinical Research Center for Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Shanghai, China
| | - Rui Du
- Shanghai National Clinical Research Center for Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Shanghai, China
| | - Hongyan Qi
- Shanghai National Clinical Research Center for Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Shanghai, China
| | - Jie Zhang
- Shanghai National Clinical Research Center for Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Shanghai, China
| | - Tiange Wang
- Shanghai National Clinical Research Center for Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Shanghai, China
| | - Zhiyun Zhao
- Shanghai National Clinical Research Center for Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Shanghai, China
| | - Mian Li
- Shanghai National Clinical Research Center for Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Shanghai, China
| | - Yu Xu
- Shanghai National Clinical Research Center for Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Shanghai, China
| | - Min Xu
- Shanghai National Clinical Research Center for Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Shanghai, China
| | - Donghui Li
- Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Yufang Bi
- Shanghai National Clinical Research Center for Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Shanghai, China
| | - Weiqing Wang
- Shanghai National Clinical Research Center for Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Shanghai, China
| | - Yuhong Chen
- Shanghai National Clinical Research Center for Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Shanghai, China
| | - Jieli Lu
- Shanghai National Clinical Research Center for Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Institute of Endocrine and Metabolic Diseases, Shanghai, China
| |
Collapse
|
40
|
Association between Sleep Timing and Weight Status among 14- to 19-Year-Old Adolescents in Wuhan, China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17165703. [PMID: 32784581 PMCID: PMC7460288 DOI: 10.3390/ijerph17165703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 07/13/2020] [Accepted: 07/14/2020] [Indexed: 11/30/2022]
Abstract
This study examined the cross-sectional and longitudinal association of sleep timing with weight status in 14- to 19-year-old adolescents in Wuhan, China. A prospective school-based study was conducted in Wuhan, China between 28 May and 29 September 2019. Data on sociodemographic information, academic performance, diet, mental health status, physical activity, sleep characteristics, body weight, and height were collected. A linear regression model and binary logistic regression model were performed. A total of 1194 adolescents were included in the analysis. Adolescents who woke up before 05:45 had higher body mass index (BMI) Z-score (odds ratio (OR) with 95% confidence interval (CI) = 1.28 (1.05, 1.57), p = 0.02) and higher odds of overweight/obesity (odds ratio (OR) with 95% confidence interval (CI) = 1.74 (1.10, 2.76), p = 0.02) at baseline after fully adjustment for covariates, compared with those who woke up after 05:45. Longitudinal data showed a nonsignificant association between waking up time and change in BMI Z-score (p = 0.18). No association of bedtime with weight status was observed in this sample after full adjustment (p > 0.1). Earlier waking up time might contribute to overweight and obesity in adolescents; however, more data are needed to test and elucidate this relationship.
Collapse
|
41
|
Zheng R, Niu J, Wu S, Wang T, Wang S, Xu M, Chen Y, Dai M, Zhang D, Yu X, Tang X, Hu R, Ye Z, Shi L, Su Q, Yan L, Qin G, Wan Q, Chen G, Gao Z, Wang G, Shen F, Luo Z, Qin Y, Chen L, Huo Y, Li Q, Zhang Y, Liu C, Wang Y, Wu S, Yang T, Deng H, Chen L, Zhao J, Mu Y, Xu Y, Li M, Lu J, Wang W, Zhao Z, Xu Y, Bi Y, Ning G. Gender and age differences in the association between sleep characteristics and fasting glucose levels in Chinese adults. DIABETES & METABOLISM 2020; 47:101174. [PMID: 32659495 DOI: 10.1016/j.diabet.2020.07.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Revised: 06/24/2020] [Accepted: 07/01/2020] [Indexed: 01/19/2023]
Abstract
AIM The present study examined the associations between night-time sleep duration, midday napping duration and bedtime, and fasting glucose levels, and whether or not such associations are dependent on gender and age. METHODS This study was a cross-sectional analysis of 172,901 adults aged≥40 years living in mainland China. Sleep duration was obtained by self-reports of bedtime at night, waking-up time the next morning and average napping duration at midday. Fasting plasma glucose (FPG)≥7.0mmol/L was defined as hyperglycaemia. Independent associations between night-time sleep duration, midday naptime duration and bedtime with hyperglycaemia were evaluated using regression models. RESULTS Compared with night-time sleep durations of 6-7.9h, both short (<6h) and long (≥8h) night-time sleep durations were significantly associated with an increased risk of hyperglycaemia in women [odds ratio (OR): 1.12, 95% confidence interval (CI): 1.01-1.29 and OR: 1.14, 95% CI: 1.08-1.21, respectively], and revealed a U-shaped distribution of risk in women and no significant association in men. Long midday nap durations (≥1h) were significantly but weakly associated with hyperglycaemia (OR: 1.04, 95% CI: 1.01-1.09) compared with no napping without interactions from gender or age, whereas the association between bedtime and fasting glucose levels did vary according to gender and age. CONCLUSION Night-time sleep duration, midday napping duration and bedtime were all independently associated with the risk of hyperglycaemia, and some of the associations between these sleep characteristics and hyperglycaemia were gender- and age-dependent.
Collapse
Affiliation(s)
- R Zheng
- Shanghai National Clinical Research Centre for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of China, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Shanghai 200025, China
| | - J Niu
- Shanghai National Clinical Research Centre for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of China, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Shanghai 200025, China
| | - S Wu
- Shanghai National Clinical Research Centre for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of China, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Shanghai 200025, China
| | - T Wang
- Shanghai National Clinical Research Centre for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of China, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Shanghai 200025, China
| | - S Wang
- Shanghai National Clinical Research Centre for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of China, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Shanghai 200025, China
| | - M Xu
- Shanghai National Clinical Research Centre for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of China, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Shanghai 200025, China
| | - Y Chen
- Shanghai National Clinical Research Centre for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of China, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Shanghai 200025, China
| | - M Dai
- Shanghai National Clinical Research Centre for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of China, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Shanghai 200025, China
| | - D Zhang
- Shanghai National Clinical Research Centre for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of China, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Shanghai 200025, China
| | - X Yu
- Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - X Tang
- First Hospital of Lanzhou University, Lanzhou, China
| | - R Hu
- Zhejiang Provincial Centre for Disease Control and Prevention, Zhejiang, China
| | - Z Ye
- Zhejiang Provincial Centre for Disease Control and Prevention, Zhejiang, China
| | - L Shi
- Affiliated Hospital of Guiyang Medical College, Guiyang, China
| | - Q Su
- Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - L Yan
- Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - G Qin
- First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Q Wan
- Affiliated Hospital of Luzhou Medical College, Luzhou, China
| | - G Chen
- Fujian Provincial Hospital, Fujian Medical University, Fuzhou, China
| | - Z Gao
- Dalian Municipal Central Hospital, Dalian Medical University, Dalian, China
| | - G Wang
- First Hospital of Jilin University, Changchun, China
| | - F Shen
- First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Z Luo
- First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Y Qin
- First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - L Chen
- Qilu Hospital of Shandong University, Jinan, China
| | - Y Huo
- Jiangxi Provincial People's Hospital Affiliated to Nanchang University, Nanchang, China
| | - Q Li
- Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Y Zhang
- Central Hospital of Shanghai Jiading District, Shanghai, China
| | - C Liu
- Jiangsu Province Hospital on Integration of Chinese and Western Medicine, Nanjing, China
| | - Y Wang
- First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - S Wu
- Karamay Municipal People's Hospital, Xinjiang, China
| | - T Yang
- First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - H Deng
- First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - L Chen
- Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - J Zhao
- Shandong Provincial Hospital affiliated to Shandong University, Jinan, China
| | - Y Mu
- Chinese People's Liberation Army General Hospital, Beijing, China
| | - Y Xu
- Clinical Trials Centre, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - M Li
- Shanghai National Clinical Research Centre for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of China, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Shanghai 200025, China
| | - J Lu
- Shanghai National Clinical Research Centre for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of China, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Shanghai 200025, China
| | - W Wang
- Shanghai National Clinical Research Centre for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of China, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Shanghai 200025, China
| | - Z Zhao
- Shanghai National Clinical Research Centre for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of China, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Shanghai 200025, China.
| | - Y Xu
- Shanghai National Clinical Research Centre for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of China, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Shanghai 200025, China.
| | - Y Bi
- Shanghai National Clinical Research Centre for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of China, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Shanghai 200025, China.
| | - G Ning
- Shanghai National Clinical Research Centre for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of China, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, 197 Ruijin 2nd Road, Shanghai 200025, China
| | | |
Collapse
|
42
|
Brindle RC, Yu L, Buysse DJ, Hall MH. Empirical derivation of cutoff values for the sleep health metric and its relationship to cardiometabolic morbidity: results from the Midlife in the United States (MIDUS) study. Sleep 2020; 42:5488780. [PMID: 31083710 DOI: 10.1093/sleep/zsz116] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2018] [Revised: 03/15/2019] [Indexed: 12/27/2022] Open
Abstract
STUDY OBJECTIVES Emerging evidence supports a multidimensional perspective of sleep in the context of health. The sleep health model, and composite sleep health score, are increasingly used in research. However, specific cutoff values that differentiate "good" from "poor" sleep, have not been empirically derived and its relationship to cardiometabolic health is less-well understood. We empirically derived cutoff values for sleep health dimensions and examined the relationship between sleep health and cardiometabolic morbidity. METHODS Participants from two independent Biomarker Studies in the MIDUS II (N = 432, 39.8% male, age = 56.92 ± 11.45) and MIDUS Refresher (N = 268, 43.7% male, age = 51.68 ± 12.70) cohorts completed a 1-week study where sleep was assessed with daily diaries and wrist actigraphy. Self-reported physician diagnoses, medication use, and blood values were used to calculate total cardiometabolic morbidity. Receiver operating characteristic (ROC) curves were generated in the MIDUS II cohort for each sleep health dimension to determine cutoff values. Using derived cutoff values, logistic regression was used to examine the relationship between sleep health scores and cardiometabolic morbidity in the MIDUS Refresher cohort, controlling for traditional risk factors. RESULTS Empirically derived sleep health cutoff values aligned reasonably well to cutoff values previously published in the sleep health literature and remained robust across physical and mental health outcomes. Better sleep health was significantly associated with a lower odds of cardiometabolic morbidity (OR [95% CI] = 0.901 [0.814-0.997], p = .044). CONCLUSIONS These results contribute to the ongoing development of the sleep health model and add to the emerging research supporting a multidimensional perspective of sleep and health.
Collapse
Affiliation(s)
- Ryan C Brindle
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA.,Department of Psychology and Neuroscience Program, Washington and Lee University, Lexington, VA
| | - Lan Yu
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA
| | - Daniel J Buysse
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA
| | - Martica H Hall
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA
| |
Collapse
|
43
|
Muilwijk M, Stenvers DJ, Nicolaou M, Kalsbeek A, van Valkengoed IG. Behavioral Circadian Timing System Disruptors and Incident Type 2 Diabetes in a Nonshift Working Multiethnic Population. Obesity (Silver Spring) 2020; 28 Suppl 1:S55-S62. [PMID: 32438513 PMCID: PMC7496413 DOI: 10.1002/oby.22777] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Accepted: 12/20/2019] [Indexed: 01/01/2023]
Abstract
OBJECTIVE This study aimed to describe distributions of behavioral circadian disruptors in a free-living setting among a nonshift working multiethnic population, estimate the associated risk of type 2 diabetes (T2D), and determine whether disruptors account for ethnic differences in T2D. METHODS Participants from six ethnic groups were included (Amsterdam, the Netherlands; n = 1,347-3,077 per group). Multinomial logistic regression was used to estimate ethnic differences in disruptors, such as skipping breakfast, eating erratically, and sleep duration. Associations between disruptors and incident T2D and the interaction by ethnicity were studied by Cox regression. RESULTS Ethnic minority populations skipped breakfast more often, timed meals differently, had longer periods of fasting, ate more erratically, and had more short/long sleep durations than the Dutch. Night snacking from 4 am to 6 am (HR: 5.82; 95% CI: 1.42-23.91) and both short (HR: 1.48; 95% CI: 1.03-2.12) and long sleep (HR: 3.09; 95% CI: 1.54-6.22), but no other disruptors, were associated with T2D. The higher T2D risk among ethnic minority populations compared with Dutch did not decrease after adjustment for last snack or length of sleep. CONCLUSIONS Although prevalence of circadian disruptors was higher among ethnic minority populations and some disruptors were associated with T2D, disruptors did not account for ethnic differences in T2D risk.
Collapse
Affiliation(s)
- Mirthe Muilwijk
- Department of Public HealthAmsterdam Public Health Research InstituteAmsterdam UMCUniversity of AmsterdamAmsterdamThe Netherlands
| | - Dirk Jan Stenvers
- Department of Endocrinology and MetabolismAmsterdam UMCUniversity of AmsterdamAmsterdamThe Netherlands
| | - Mary Nicolaou
- Department of Public HealthAmsterdam Public Health Research InstituteAmsterdam UMCUniversity of AmsterdamAmsterdamThe Netherlands
| | - Andries Kalsbeek
- Department of Endocrinology and MetabolismAmsterdam UMCUniversity of AmsterdamAmsterdamThe Netherlands
- Netherlands Institute for NeuroscienceAmsterdamThe Netherlands
| | - Irene G.M. van Valkengoed
- Department of Public HealthAmsterdam Public Health Research InstituteAmsterdam UMCUniversity of AmsterdamAmsterdamThe Netherlands
| |
Collapse
|
44
|
Seo JA, Lee DY, Yu JH, Cho H, Lee SK, Suh S, Kim SG, Choi KM, Baik SH, Shin C, Kim NH. Habitual late sleep initiation is associated with increased incidence of type 2 diabetes mellitus in Korean adults: the Korean Genome and Epidemiology Study. Sleep 2020; 42:5473601. [PMID: 30994171 DOI: 10.1093/sleep/zsz090] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2018] [Revised: 03/04/2019] [Indexed: 12/21/2022] Open
Abstract
STUDY OBJECTIVES Although sleep duration and quality were significant risk factors of type 2 diabetes (T2D), the impact of sleep initiation time on the development of T2D has not been studied in large longitudinal studies. METHODS A total of 3689 participants without diabetes aged 40-69 years at baseline were enrolled from the Korean Genome and Epidemiology Study and followed up for 12 years. Participants were categorized based on habitual sleep initiation time by questionnaire as follows: 20:00-22:59 (early sleepers, ES, n = 766), 23:00-00:59 (usual sleepers, US, n = 2407), and 1:00-5:59 (late sleepers, LS, n = 516). Incident T2D was identified biennially by fasting plasma glucose or 2-hour glucose after 75-g oral glucose loading or use of anti-diabetes medication. RESULTS During follow-up, 820 cases of T2D were documented and the LS group showed the highest increase in insulin resistance. Hazard ratio (HR) (95% confidence interval) for T2D of LS compared to ES was 1.34 (1.04-1.74) after adjustment for covariates including sleep duration. The impact of late sleep on the development of T2D was more evident in older individuals (≥65 years at baseline) (HR = 4.24 [1.42-12.68] in older LS vs. older ES, HR = 1.27 [1.00-1.62] in younger LS vs. younger ES, pinteraction = 0.002). In addition, LS with low insulin secretion and sensitivity showed an approximately fivefold increased risk for T2D compared to ES with high insulin secretion and sensitivity. CONCLUSIONS/INTERPRETATION Habitual late sleep initiation is a significant risk factor for T2D in Koreans, especially in people with lower insulin sensitivity, lower β-cell function, and older age.
Collapse
Affiliation(s)
- Ji A Seo
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Korea
| | - Da Young Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Korea
| | - Ji Hee Yu
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Korea
| | - Hyunjoo Cho
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Korea
| | - Seung Ku Lee
- Institute of Human Genomic Study, Korea University Ansan Hospital, Ansan, Korea
| | - Sooyeon Suh
- Department of Psychology, Sungshin Women's University, Seoul, Korea
| | - Sin Gon Kim
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Korea
| | - Kyung Mook Choi
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Korea
| | - Sei Hyun Baik
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Korea
| | - Chol Shin
- Institute of Human Genomic Study, Korea University Ansan Hospital, Ansan, Korea.,Division of Respiratory and Critical Care Medicine, Department of Internal Medicine, Korea University College of Medicine, Seoul, Korea
| | - Nan Hee Kim
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Korea
| |
Collapse
|
45
|
Wang L, Li J, Du Y, Sun T, Na L, Wang Z. The relationship between sleep onset time and cardiometabolic biomarkers in Chinese communities: a cross-sectional study. BMC Public Health 2020; 20:374. [PMID: 32197597 PMCID: PMC7085179 DOI: 10.1186/s12889-020-08516-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2018] [Accepted: 03/12/2020] [Indexed: 11/17/2022] Open
Abstract
Background Late sleep onset time (SOT) is a common social phenomenon in modern society, and it was associated with a higher risk of obesity. However, the literature gap exists about the SOT and cardiometabolic biomarkers which closely associated with obesity. The present study aimed to explore the association of SOT with cardiometabolic biomarkers in Chinese communities. Methods A cross-sectional study enrolled a total of 2418 participants was conducted in Ningxia province of China. The cardiometabolic biomarkers included triglyceride, total cholesterol, high-density lipoprotein, low-density lipoprotein and fasting plasma glucose were measured quantitatively using the standard method. The SOT and sleep duration were acquired by a self-report questionnaire. The multiple mixed-effect linear regression model was employed to examine the association. Results Binary analysis found an inverse association of SOT with high-density lipoprotein (β = − 0.05, 95%CI: − 0.06, − 0.03), with 1 h delayed in SOT the high-density lipoprotein decreased 0.05 mmol/L. After controlling for demographic variables, health-related behaviors, and physical health covariates, late SOT was associated with a higher level of triglyceride (β = 0.12, 95%CI: 0.06, 0.18), a higher level of low-density lipoprotein (β = 0.06, 95% CI: 0.02, 0.09), and a lower level of high-density lipoprotein (β = − 0.05, 95% CI: − 0.06, − 0.03). when stratified by sleep duration (less than eight hours vs. eight and longer hours), a positive association between SOT and LDL (β = 0.08, 95% CI: 0.04, 0.12) was found among participants with sleep duration eight hours and longer. Conclusion Late sleep onset time with the negative effect on the cardiometabolic biomarkers, and individuals with late SOT coupled with longer sleep duration may take risk of a higher level of low-density lipoprotein which in turn lead to increase the risk of cardiovascular disease.
Collapse
Affiliation(s)
- Liqun Wang
- School of Public Health and Management, Ningxia Medical University, Yinchuan, 750004, China
| | - Jiangping Li
- School of Public Health and Management, Ningxia Medical University, Yinchuan, 750004, China
| | - Yong Du
- Surgical Laboratory of General Hospital, Ningxia Medical University, Yinchuan, 750004, China.,School of Clinical Medicine, Ningxia Medical University, Yinchuan, 750004, China
| | - Ting Sun
- Surgical Laboratory of General Hospital, Ningxia Medical University, Yinchuan, 750004, China
| | - Li Na
- Surgical Laboratory of General Hospital, Ningxia Medical University, Yinchuan, 750004, China
| | - Zhizhong Wang
- School of Public Health and Management, Ningxia Medical University, Yinchuan, 750004, China.
| |
Collapse
|
46
|
The Elapsed Time between Dinner and the Midpoint of Sleep is Associated with Adiposity in Young Women. Nutrients 2020; 12:nu12020410. [PMID: 32033292 PMCID: PMC7071164 DOI: 10.3390/nu12020410] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Revised: 01/27/2020] [Accepted: 02/03/2020] [Indexed: 12/22/2022] Open
Abstract
Meal timing relative to sleep/wake schedules is relevant in the search for obesity risk factors. However, clock time does not accurately characterize the timing of food intake in the context of internal circadian timing. Therefore, we studied elapsed between dinner and the midpoint of sleep (TDM) as a practical approach to evaluate meal timing relative to internal timing, and its implications on obesity. To do so, adiposity, sleep, diet, physical activity, and TDM were measured in 133 women. The participants were grouped into four categories according to their sleep timing behavior (early-bed/early-rise; early-bed/late-rise; late-bed/early-rise; late-bed/late-rise). Differences among the categories were tested using ANOVA, while restricted cubic splines were calculated to study the association between TDM and adiposity. Our results show that, although participants had dinner at about the same time, those that had the shortest TDM (early-bed/early-rise group) were found to have significantly higher BMI and waist circumference values (2.3 kg/m2 and 5.2 cm) than the other groups. In addition, a TDM of 6 h was associated with the lowest values of adiposity. The TDM could be a practical approach to personalizing meal timing based on individual sleep/wake schedules. Thus, according to our findings, dining 6 h before the midpoint of sleep is an important finding and could be vital for future nutritional recommendations and for obesity prevention and treatment.
Collapse
|
47
|
Lu K, Zhao Y, Chen J, Hu D, Xiao H. Interactive association of sleep duration and sleep quality with the prevalence of metabolic syndrome in adult Chinese males. Exp Ther Med 2019; 19:841-848. [PMID: 32010244 PMCID: PMC6966124 DOI: 10.3892/etm.2019.8290] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Accepted: 10/03/2019] [Indexed: 12/02/2022] Open
Abstract
The present study aimed to examine the separate and combined association of self-reported sleep duration and quality with the prevalence of metabolic syndrome (MetS) in adult Chinese males. A total of 4,144 subjects were enrolled in the present crossed-sectional study. All participants were subjected to anthropometric measurements, blood tests and a survey based on a standardized questionnaire. Multivariate logistic regression was used to assess the influence of sleep duration and quality on the prevalence of MetS. The group that had 7 h of sleep had the best results as compared with those with shorter or longer sleep durations, and the prevalence of MetS was the lowest in this group. In addition, poor vs. good sleep quality was associated with an increased risk of MetS. Further analysis suggested that sleep duration and quality had an additive effect on the prevalence of MetS. In conclusion, sleep duration as well as quality should be considered when exploring the potential association between sleep and other conditions.
Collapse
Affiliation(s)
- Kai Lu
- Department of Cardiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, P.R. China
| | - Yue Zhao
- Department of Cardiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, P.R. China
| | - Jia Chen
- Department of Clinical Nutrition, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, P.R. China
| | - Dayi Hu
- Department of Cardiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, P.R. China
| | - Hua Xiao
- Department of Cardiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, P.R. China
| |
Collapse
|
48
|
Neighborhoods to Nucleotides - Advances and gaps for an obesity disparities systems epidemiology model. CURR EPIDEMIOL REP 2019; 6:476-485. [PMID: 36643055 PMCID: PMC9839192 DOI: 10.1007/s40471-019-00221-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Purpose of Review Disparities in obesity rates in the US continue to increase. Here we review progress and highlight gaps in understanding disparities in obesity with a focus on the Hispanic/Latino population from a systems epidemiology framework. We review seven domains: environment, behavior, biomarkers, nutrition, microbiome, genomics, and epigenomics/transcriptomics. We focus on recent advances that include at least two or more of these domains, and then provide a real world example of data collection efforts that reflect these domains. Recent Findings Research into DNA methylation related to discrimination and microbiome relating to eating behaviors and food content is furthering understanding of why disparities in obesity persist. Environmental and neighborhood level research is uncovering the importance of exposures such as air and noise pollution and systematic or structural racism for obesity and related outcomes through behaviors such as sleep.
Collapse
|
49
|
Reid KJ, Weng J, Ramos AR, Zee PC, Daviglus M, Mossavar-Rahmani Y, Sotres-Alvarez D, Gallo LC, Chirinos DA, Patel SR. Impact of shift work schedules on actigraphy-based measures of sleep in Hispanic workers: results from the Hispanic Community Health Study/Study of Latinos ancillary Sueño study. Sleep 2019; 41:5053098. [PMID: 30010969 DOI: 10.1093/sleep/zsy131] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2017] [Indexed: 12/15/2022] Open
Abstract
Study Objectives To describe sleep characteristics of shift workers compared with day workers from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) Sueño ancillary study and test the hypothesis that shift work is associated with shorter sleep duration, worse sleep quality, greater sleep variability, and other sleep/health-related factors. Methods Employed adults (N = 1253, mean age 46.3 years, 36.3% male) from the Sueño study were included. Measures of sleep duration, timing, regularity, and continuity were calculated from 7 days of wrist-activity monitoring. Participants provided information on demographics, employment, work schedule (day, afternoon, night, split, irregular, and rotating), sleepiness, depressive symptoms, medications, caffeine, and alcohol use. Survey linear regression adjusting for age, sex, background, site, number of jobs, and work hours was used. Results In age and sex-adjusted models, all shift work schedules were associated with delayed sleep timing. Night and irregular schedules were associated with shorter sleep duration, greater napping, and greater variability of sleep. Afternoon and rotating shifts were associated with lower sleep regularity. In fully adjusted models, night and irregular schedules remained associated with shorter sleep duration, later sleep midpoint, and greater variability in sleep measures compared with day schedules. Split schedules were associated with, less time in bed, less sleep fragmentation, and less wake during the sleep period than day schedules. Conclusions Work schedule significantly affects sleep-wake with substantial differences between day work and other types of schedule. Detailed assessment of work schedule type not just night shift should be considered as an important covariate when examining the association between sleep and health outcomes.
Collapse
Affiliation(s)
- Kathryn J Reid
- Department of Neurology, Northwestern University, Chicago, IL
| | - Jia Weng
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA
| | - Alberto R Ramos
- Department of Neurology, University of Miami, Miller School of Medicine, Miami, FL
| | - Phyllis C Zee
- Department of Neurology, Northwestern University, Chicago, IL
| | | | - Yasmin Mossavar-Rahmani
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY
| | - Daniela Sotres-Alvarez
- Department of Biostatistics, Collaborative Studies Coordinating Center, University of North Carolina, Chapel Hill, NC
| | - Linda C Gallo
- Department of Psychology, San Diego State University, San Diego, CA
| | | | - Sanjay R Patel
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA
| |
Collapse
|
50
|
Liu B, Song L, Zhang L, Wang L, Wu M, Xu S, Wang Y. Sleep patterns and the risk of adverse birth outcomes among Chinese women. Int J Gynaecol Obstet 2019; 146:308-314. [DOI: 10.1002/ijgo.12878] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Revised: 01/30/2019] [Accepted: 05/31/2019] [Indexed: 12/31/2022]
Affiliation(s)
- Bingqing Liu
- Department of Maternal and Child HealthSchool of Public HealthTongji Medical CollegeHuazhong University of Science and Technology Wuhan China
| | - Lulu Song
- Department of Maternal and Child HealthSchool of Public HealthTongji Medical CollegeHuazhong University of Science and Technology Wuhan China
| | - Lina Zhang
- Department of Maternal and Child HealthSchool of Public HealthTongji Medical CollegeHuazhong University of Science and Technology Wuhan China
| | - Lulin Wang
- Department of Maternal and Child HealthSchool of Public HealthTongji Medical CollegeHuazhong University of Science and Technology Wuhan China
| | - Mingyang Wu
- Department of Maternal and Child HealthSchool of Public HealthTongji Medical CollegeHuazhong University of Science and Technology Wuhan China
| | - Shunqing Xu
- Key Laboratory of Environment and HealthMinistry of Education & Ministry of Environmental ProtectionHuazhong University of Science and Technology Wuhan China
- State Key Laboratory of Environmental HealthSchool of Public HealthTongji Medical CollegeHuazhong University of Science and Technology Wuhan China
| | - Youjie Wang
- Department of Maternal and Child HealthSchool of Public HealthTongji Medical CollegeHuazhong University of Science and Technology Wuhan China
| |
Collapse
|