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Muhammad T, Srivastava S, Muneera K, Kumar M, Kelekar U. Treatment for Insomnia Symptoms is Associated with Reduced Depression Among Older Adults: A Propensity Score Matching Approach. Clin Gerontol 2024; 47:436-451. [PMID: 37153958 DOI: 10.1080/07317115.2023.2208582] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
OBJECTIVES The study aimed to investigate the effect of utilization of treatment for insomnia symptoms on the prevalence of major depressive disorder among older adults in India. METHODS We used the data from the Longitudinal Ageing Study in India (LASI), 2017-18. The sample included 10,911 older individuals who reported insomnia symptoms. The propensity score matching (PSM) approach was used to compare the depressive disorder among those who received vs. not received treatment. RESULTS Only 5.7% of older adults reporting insomnia symptoms received treatment. On average, prevalence of depressive disorder among men and women who received treatment for insomnia symptoms was lesser by 0.79 and 0.33 points, respectively, than those who did not receive treatment. In the matched sample, treatment for insomnia symptoms was significantly associated with lesser prevalence of depression for both older men (β= -0.68, p < .001) and older women (β= -0.62, p < .001). CONCLUSIONS The current findings suggest that treatment for insomnia symptoms can reduce the risk of depressive disorder among older adults and the effects are higher among older men than women.
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Affiliation(s)
- T Muhammad
- Department of Family & Generations, International Institute for Population Sciences, Mumbai, India
| | - Shobhit Srivastava
- Department of Survey Research & Data Analytics, International Institute for Population Sciences, Mumbai, India
| | - K Muneera
- School of Management Studies, National Institute of Technology, Calicut, Kerala, India
| | - Manish Kumar
- Population Research Centre, Dharwad, Karnataka, India
| | - Uma Kelekar
- School of Business, College of Business, Innovation, Leadership and Technology
- Marymount Center for Optimal Aging, Marymount University, Arlington-VA, USA
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Bolstad CJ, Cui R, Fiske A, Nadorff MR. Age Moderates the Relation between Sleep Problems and Suicide Risk. Clin Gerontol 2024; 47:408-415. [PMID: 35209805 DOI: 10.1080/07317115.2022.2044951] [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] [Indexed: 11/03/2022]
Abstract
OBJECTIVES This cross-sectional study examined whether age moderates the relation between sleep problems and suicide risk and investigated whether sleep problems are differentially associated with suicide risk in younger (18-40) and older (60+) adults. METHODS MTurk workers (N = 733) completed the Pittsburgh Sleep Quality Index, Suicidal Behavior Questionnaire-Revised, Patient Health Questionnaire, and demographic questions. Analysis of variance and linear regressions were utilized. RESULTS Older adults scored lower on four PSQI components, symptoms of depression, and suicide risk than younger adults. Age significantly moderated the relation between sleep problems and suicide risk after controlling for gender and depressive symptoms, F(5, 635) = 72.38, p < .001. Sleep problems significantly related to suicide risk in younger adults (t = 6.47, p < .001) but not in older adults (t = 0.57, p = .57). Sleep medication use was related to suicide risk in both groups, whereas daytime dysfunction was related to suicide risk in older adults and sleep disturbances were related to suicide risk in younger adults. CONCLUSIONS The relation between sleep problems and suicide risk differs between younger and older adults. This study adds to the literature suggesting that sleep medications may not be appropriate for older adults. CLINICAL IMPLICATIONS Sleep problems are significantly related to suicide risk in younger adults but not older adults. Sleep medication use is associated with suicide risk regardless of age.
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Affiliation(s)
- Courtney J Bolstad
- Department of Psychology, Mississippi State University, Mississippi State, Mississippi, USA
| | - Ruifeng Cui
- Department of Psychology, West Virginia University, Morgantown, West Virginia, USA
| | - Amy Fiske
- Department of Psychology, West Virginia University, Morgantown, West Virginia, USA
- Injury Control Research Center, West Virginia University, Morgantown, West Virginia, USA
| | - Michael R Nadorff
- Department of Psychology, Mississippi State University, Mississippi State, Mississippi, USA
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas, USA
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Huang Y, Fleury J. Socially-supported sleep in older adults aged 50 and older: a concept analysis. Front Public Health 2024; 12:1364639. [PMID: 38645458 PMCID: PMC11027164 DOI: 10.3389/fpubh.2024.1364639] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Accepted: 03/25/2024] [Indexed: 04/23/2024] Open
Abstract
Introduction The population of older adults is growing disproportionately, constituting 13% of the global population in 2022, and is expected to double by 2050. One of public health's priorities is healthy aging, the maintenance of functional ability aligned with well-being. As many as 50% of older adults report poor sleep quality, leading to an increased risk of morbidity and mortality. The quality and quantity of social relationships may broadly benefit sleep in older adults. However, the concept of socially-supported sleep is underdeveloped as a basis for intervention. Methods Existing literature was searched without time restriction in PubMed, CINAHL, PsycINFO, and Scopus ending in August 2022. Thematic analysis was used to determine the defining attributes, antecedents, and consequences of socially-supported sleep guided by Rodgers' evolutionary concept analysis. Results Twenty-nine articles written in English, peer-reviewed, and examined social support and sleep in participants aged ≥50 were included. The defining attributes reflect dimensions of sleep quality. The antecedents are safe and secure, belonging and connection, and warmth and comfort. The consequences of socially-supported sleep include improved regulatory capabilities, physical and emotional well-being, and quality of life. Conclusion Socially-supported sleep has the potential to inform interventions that promote sleep in older adults. Ongoing research is needed to address the antecedents and mechanisms through which socially-supported sleep may promote sleep quality for healthy aging.
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Affiliation(s)
- Yingyan Huang
- Edson College of Nursing and Health Innovation, Arizona State University, Phoenix, AZ, United States
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Yang SY, Lin PH, Wang JY, Fu SH. Effectiveness of binaural beat music combined with rhythmical photic stimulation on older people with depressive symptoms in long-term care institution: a quasi-experimental pilot study. Aging Clin Exp Res 2024; 36:86. [PMID: 38558209 PMCID: PMC10984885 DOI: 10.1007/s40520-024-02737-3] [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: 02/14/2024] [Accepted: 03/17/2024] [Indexed: 04/04/2024]
Abstract
BACKGROUND Many older adults residing in long-term care often face issues like poor sleep, reduced vitality, and depression. Non-pharmacological approaches, specifically Binaural Beat Music (BBM) and Rhythmic Photic Stimulation (RPS), may alleviate these symptoms, yet their efficacy in this demographic has not been extensively explored. AIMS This study investigated the effects of combined BBM and RPS interventions on sleep quality, vitality, and depression among older residents with depressive symptoms in long-term care facilities. METHODS Using a quasi-experimental design, a total of 88 older adults with depressive symptoms from Taiwanese daytime care centers were divided into the BBM with RPS, and Sham groups (44 each). They underwent 20-minute daily sessions of their assigned treatment for two weeks. The BBM with RPS group listened to 10 Hz binaural beat music with 10 Hz photic stimulation glasses, and the Sham group received non-stimulating music and glasses. RESULTS After the intervention, participants in the BBM with RPS groups showed significant improvements in vitality and depressive mood, with a notable increase in sympathetic nervous system activity. Conversely, the Sham group exhibited significant deterioration in vitality and mental health, with a significant increase in parasympathetic activity. Additionally, compared with the Sham group, the BBM and RPS groups showed significant improvements in vitality, mental health, and depression, with a significant increase in sympathetic nervous activity. CONCLUSION The two-week intervention suggests that the combination of BBM and RPS, as a non-invasive intervention, can potentially improve vitality, mental health, and depressive mood among older adults in long-term care institutions.
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Affiliation(s)
- Shang-Yu Yang
- Department of Healthcare Administration, College of Medical and Health Science, Asia University, 500, Lioufeng Rd, 41354, Wufeng, Taichung, Taiwan, R.O.C..
| | - Pin-Hsuan Lin
- Department of Health and Beauty, Shu Zen Junior College of Medicine and Management, Kaohsiung, 821, Taiwan
| | - Jiun-Yi Wang
- Department of Healthcare Administration, College of Medical and Health Science, Asia University, 500, Lioufeng Rd, 41354, Wufeng, Taichung, Taiwan, R.O.C
- Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, 404, Taiwan
| | - Shih-Hau Fu
- Department of Acupressure Technology, Chung Hwa University of Medical Technology, Tainan 717, Tainan, Taiwan
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Banks SJ, Yhang E, Tripodis Y, Su Y, Protas H, Adler CH, Balcer LJ, Bernick C, Mez JB, Palmisano J, Barr WB, Wethe JV, Dodick DW, Mcclean MD, Martin B, Hartlage K, Turner A, Turner RW, Malhotra A, Colman M, Pasternak O, Lin AP, Koerte IK, Bouix S, Cummings JL, Shenton ME, Reiman EM, Stern RA, Alosco ML. Clinical Outcomes and Tau Pathology in Retired Football Players: Associations With Diagnosed and Witnessed Sleep Apnea. Neurol Clin Pract 2024; 14:e200263. [PMID: 38425491 PMCID: PMC10900387 DOI: 10.1212/cpj.0000000000200263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 11/30/2023] [Indexed: 03/02/2024]
Abstract
Background and Objectives Obstructive sleep apnea (SA) is common in older men and a contributor to negative cognitive, psychiatric, and brain health outcomes. Little is known about SA in those who played contact sports and are at increased risk of neurodegenerative disease(s) and other neuropathologies associated with repetitive head impacts (RHI). In this study, we investigated the frequency of diagnosed and witnessed SA and its contribution to clinical symptoms and tau pathology using PET imaging among male former college and former professional American football players. Methods The sample included 120 former National Football League (NFL) players, 60 former college players, and 60 asymptomatic men without exposure to RHI (i.e., controls). Diagnosed SA was self-reported, and all participants completed the Mayo Sleep Questionnaire (MSQ, informant version), the Epworth Sleepiness Scale (ESS), neuropsychological testing, and tau (flortaucipir) PET imaging. Associations between sleep indices (diagnosed SA, MSQ items, and the ESS) and derived neuropsychological factor scores, self-reported depression (Beck Depression Inventory-II [BDI-II]), informant-reported neurobehavioral dysregulation (Behavior Rating Inventory of Executive Function-Adult Version [BRIEF-A] Behavioral Regulation Index [BRI]), and tau PET uptake, were tested. Results Approximately 36.7% of NFL players had diagnosed SA compared with 30% of the former college football players and 16.7% of the controls. Former NFL players and college football players also had higher ESS scores compared with the controls. Years of football play was not associated with any of the sleep metrics. Among the former NFL players, diagnosed SA was associated with worse Executive Function and Psychomotor Speed factor scores, greater BDI-II scores, and higher flortaucipir PET standard uptake value ratios, independent of age, race, body mass index, and APOE ε4 gene carrier status. Higher ESS scores correlated with higher BDI-II and BRIEF-A BRI scores. Continuous positive airway pressure use mitigated all of the abovementioned associations. Among the former college football players, witnessed apnea and higher ESS scores were associated with higher BRIEF-A BRI and BDI-II scores, respectively. No other associations were observed in this subgroup. Discussion Former elite American football players are at risk of SA. Our findings suggest that SA might contribute to cognitive, neuropsychiatric, and tau outcomes in this population. Like all neurodegenerative diseases, this study emphasizes the multifactorial contributions to negative brain health outcomes and the importance of sleep for optimal brain health.
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Affiliation(s)
- Sarah J Banks
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - Eukyung Yhang
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - Yorghos Tripodis
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - Yi Su
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - Hillary Protas
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - Charles H Adler
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - Laura J Balcer
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - Charles Bernick
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - Jesse B Mez
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - Joseph Palmisano
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - William B Barr
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - Jennifer V Wethe
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - David W Dodick
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - Michael D Mcclean
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - Brett Martin
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - Kaitlin Hartlage
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - Arlener Turner
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - Robert W Turner
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - Atul Malhotra
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - Michael Colman
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - Ofer Pasternak
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - Alexander P Lin
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - Inga K Koerte
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - Sylvain Bouix
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - Jeffrey L Cummings
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - Martha E Shenton
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - Eric M Reiman
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - Robert A Stern
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
| | - Michael L Alosco
- Departments of Neuroscience and Psychiatry (SJB), University of California, San Diego; Department of Biostatistics (EY, YT), Boston University School of Public Health; Boston University Alzheimer's Disease Research Center (YT, JBM, RAS, MLA), Boston University CTE Center, Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, MA; Banner Alzheimer's Institute (YS), Arizona State University,; Banner Alzheimer's Institute (HP), Arizona Alzheimer's Consortium, Phoenix; Department of Neurology (CHA, DWD), Mayo Clinic College of Medicine, Mayo Clinic Arizona, Scottsdale; Departments of Neurology (LJB), Population Health and Ophthalmology, NYU Grossman School of Medicine, New York; Cleveland Clinic Lou Ruvo Center for Brain Health (CB), Las Vegas, NV; Biostatistics and Epidemiology Data Analytics Center (BEDAC) (JP, BM, KH), Boston University School of Public Health, MA; Department of Neurology (WBB), NYU Grossman School of Medicine, New York; Department of Psychiatry and Psychology (JVW), Mayo Clinic School of Medicine, Mayo Clinic Arizona, Scottsdale; Department of Environmental Health (MDM), Boston University School of Public Health, MA; Department of Psychiatry and Behavioral Sciences (AT), University of Miami; Department of Clinical Research and Leadership (RWT), The George Washington University School of Medicine and Health Sciences, Washington, DC; Department of Medicine (AM), UCSD, San Diego, CA; Psychiatry Neuroimaging Laboratory (MC, OP, APL, IKK, SB), Department of Psychiatry, Brigham and Women's Hospital; Massachusetts General Hospital (IKK), Boston, MA; cBRAIN (IKK), Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy; Graduate School of Systemic Neurosciences (IKK); NICUM (NeuroImaging Core Unit Munich) (IKK), Ludwig Maximilians University, Munich, Germany; Chambers-Grundy Center for Transformative Neuroscience (JLC), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; Psychiatry Neuroimaging Laboratory (MES), Department of Psychiatry, Department of Radiology, Brigham and Women's Hospital, Boston, MA; Department of Software Engineering and Information Technology (SB), École de technologie supérieure, Montreal, QC; Banner Alzheimer's Institute (EMR), University of Arizona, Arizona State University, Translational Genomics Research Institute, and Arizona Alzheimer's Consortium, Phoenix; Department of Anatomy and Neurobiology (RAS); and Department of Neurosurgery (RAS), Boston University Chobanian and Avedisian School of Medicine, Boston, MA
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6
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Wang X, Yan X, Li M, Cheng L, Qi X, Zhang J, Pan S, Xu X, Wei W, Li Y. U-shaped association between sleep duration and biological aging: Evidence from the UK Biobank study. Aging Cell 2024:e14159. [PMID: 38556842 DOI: 10.1111/acel.14159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 03/11/2024] [Accepted: 03/12/2024] [Indexed: 04/02/2024] Open
Abstract
Previous research on sleep and aging largely has failed to illustrate the optimal dose-response curve of this relationship. We aimed to analyze the associations between sleep duration and measures of predicted age. In total, 241,713 participants from the UK Biobank were included. Habitual sleep duration was collected from the baseline questionnaire. Four indicators, homeostatic dysregulation (HD), phenoAge (PA), Klemera-Doubal method (KDM), and allostatic load (AL), were chosen to assess predicted age. Multivariate linear regression models were utilized. The association of sleep duration and predicted age followed a U-shape (All p for nonlinear <0.05). Compared with individuals who sleep for 7 h/day, the multivariable-adjusted beta of ≤5 and ≥9 h/day were 0.05 (95% CI 0.03, 0.07) and 0.03 (95% CI 0.02, 0.05) for HD, 0.08 (95% CI 0.01, 0.14) and 0.36 (95% CI 0.31, 0.41) for PA, and 0.21 (95% CI 0.12, 0.30) and 0.30 (95% CI 0.23, 0.37) for KDM. Significant independent and joint effects of sleep and cystatin C (CysC) and gamma glutamyltransferase (GGT) on predicted age metrics were future found. Similar results were observed when conducting stratification analyses. Short and long sleep duration were associated with accelerated predicted age metrics mediated by CysC and GGT.
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Affiliation(s)
- Xuanyang Wang
- Department of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, Harbin, Heilongjiang, China
| | - Xuemin Yan
- Department of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, Harbin, Heilongjiang, China
| | - Mengdi Li
- Department of Endodontics, The First Hospital, Harbin Medical University, Harbin, China
| | - Licheng Cheng
- Department of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, Harbin, Heilongjiang, China
| | - Xiang Qi
- Department of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, Harbin, Heilongjiang, China
| | - Jia Zhang
- Department of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, Harbin, Heilongjiang, China
| | - Sijia Pan
- Department of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, Harbin, Heilongjiang, China
| | - Xiaoqing Xu
- Department of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, Harbin, Heilongjiang, China
| | - Wei Wei
- Department of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, Harbin, Heilongjiang, China
- Department of Pharmacology, College of Pharmacy, Key Laboratory of Cardiovascular Research, Ministry of Education, Harbin Medical University, Harbin, China
| | - Ying Li
- Department of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, Harbin, Heilongjiang, China
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7
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Wang H, Li J, Liu Q, Zhang Y, Wang Y, Li H, Sun L, Hu B, Zhang D, Liang C, Lei J, Wang P, Sheng J, Tao F, Chen G, Yang L. Physical activity attenuates the association of long-term exposure to nitrogen dioxide with sleep quality and its dimensions in Chinese rural older adults. J Affect Disord 2024; 349:187-196. [PMID: 38199389 DOI: 10.1016/j.jad.2024.01.036] [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: 09/20/2023] [Revised: 12/05/2023] [Accepted: 01/03/2024] [Indexed: 01/12/2024]
Abstract
BACKGROUND Joint impacts of air pollution and physical activity (PA) on sleep quality remain unaddressed. We aimed to investigate whether PA attenuates the association of long-term exposure to nitrogen dioxide (NO2) with sleep quality and its dimensions in older adults. METHODS This study included 3408 Chinese rural older adults. Annual NO2 was estimated using the Space-Time Extra-Trees model. PA was assessed by International Physical Activity Questionnaire. Sleep quality was evaluated using Pittsburgh Sleep Quality Index (PSQI) scale. Linear regression models were used to assess the associations of long-term NO2 exposure and PA with sleep quality and its dimensions, and interaction plots were used to depict the attenuating effect of PA on associations of NO2 with sleep quality and its dimensions. RESULTS Three-year (3-y) average NO2 (per 0.64-μg/m3 increment) was positively associated with global PSQI (β = 0.41, 95 % CI: 0.23, 0.59), sleep duration (β = 0.16, 95 % CI: 0.11, 0.21), and habitual sleep efficiency (β = 0.22, 95 % CI: 0.17, 0.27), while PA was negatively associated with global PSQI (β = -0.33, 95 % CI: -0.46, -0.20) and five domains of PSQI other than sleep duration and sleep disturbances. The associations of NO2 with global PSQI, sleep duration, and habitual sleep efficiency were attenuated with increased PA (Pinteraction were 0.037, 0.020, and 0.079, respectively). CONCLUSIONS PA attenuates the adverse impacts of long-term NO2 exposure on sleep quality, especially on sleep duration, and habitual sleep efficiency, in Chinese rural elderly people. Participating in PA should be encouraged in this population, and continued efforts are still needed to reduce air pollution.
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Affiliation(s)
- Hongli Wang
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Hefei 230032, Anhui, China; Center for Big Data and Population Health of IHM, Hefei 230032, Anhui, China
| | - Junzhe Li
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Hefei 230032, Anhui, China; Center for Big Data and Population Health of IHM, Hefei 230032, Anhui, China
| | - Qiang Liu
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Hefei 230032, Anhui, China; Center for Big Data and Population Health of IHM, Hefei 230032, Anhui, China
| | - Yan Zhang
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Hefei 230032, Anhui, China
| | - Yuan Wang
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Hefei 230032, Anhui, China
| | - Huaibiao Li
- Fuyang Center for Diseases Prevention and Control, Fuyang 236069, Anhui, China
| | - Liang Sun
- Fuyang Center for Diseases Prevention and Control, Fuyang 236069, Anhui, China
| | - Bing Hu
- Fuyang Center for Diseases Prevention and Control, Fuyang 236069, Anhui, China
| | - Dongmei Zhang
- School of Health Services Management, Anhui Medical University, Hefei 230032, Anhui, China
| | - Chunmei Liang
- School of Public Health, Department of Hygiene Inspection and Quarantine, Anhui Medical University, Hefei 230032, Anhui, China
| | - Jingyuan Lei
- School of Public Health, Department of Hygiene Inspection and Quarantine, Anhui Medical University, Hefei 230032, Anhui, China
| | - Panpan Wang
- School of Public Health, Department of Hygiene Inspection and Quarantine, Anhui Medical University, Hefei 230032, Anhui, China
| | - Jie Sheng
- Scientific Research Center in Preventive Medicine, School of Public Health, Anhui Medical University, Hefei 230032, Anhui, China
| | - Fangbiao Tao
- Anhui Provincial Key Laboratory of Population Health and Aristogenics, Hefei 230032, Anhui, China
| | - Guimei Chen
- School of Health Services Management, Anhui Medical University, Hefei 230032, Anhui, China
| | - Linsheng Yang
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Hefei 230032, Anhui, China; Center for Big Data and Population Health of IHM, Hefei 230032, Anhui, China.
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8
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Wang H, Zhang Y, Li H, Li J, Liu Q, Wang Y, Sun L, Hu B, Chen G, Zhang D, Liang C, Lei J, Wang P, Tao F, Yang L. The Association Between Essential Metal Element Mixture and Sleep Quality in Chinese Community-Dwelling Older Adults. Biol Trace Elem Res 2024; 202:900-912. [PMID: 37340210 DOI: 10.1007/s12011-023-03729-6] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 06/10/2023] [Indexed: 06/22/2023]
Abstract
Previous studies have related single essential metal elements (EMEs) to sleep quality among older adults, however, the association of the EME mixture with sleep quality remained poorly understood. This study aimed to investigate the relationships between single EMEs and the EME mixture and sleep quality in older adults living in Chinese communities. This study consisted of 3957 older adults aged 60 years or over. Urinary concentrations of cobalt (Co), vanadium (V), selenium (Se), molybdenum (Mo), strontium (Sr), calcium (Ca), and magnesium (Mg) were detected using inductively coupled plasma mass spectrometry. Sleep quality was evaluated using Pittsburgh Sleep Quality Index (PSQI). The associations of single EMEs and EME mixture with sleep quality were assessed using logistic regression and Bayesian kernel machine regression (BKMR) models, respectively. Adjusted single-element logistic regression models showed that Mo (OR = 0.927, 95%CI:0.867-0.990), Sr (OR = 0.927, 95%CI:0.864-0.994), and Mg (OR = 0.934, 95%CI:0.873-0.997) were negatively related to poor sleep quality. BKMR models exhibited similar results. Also, higher levels of the EME mixture in urine were inversely related to the odds of poor sleep quality after adjustment for covariates, and Mo had the largest conditional posterior inclusion probability (condPIP) value in the mixture. Mo, Sr, and Mg were negatively related to poor sleep quality, separately and as the mixture. The EME mixture in urine was associated with decreased odds of poor sleep quality in older adults, and Mo was the greatest contributor within the mixture. Additional cohort research is warranted to clarify the relationship of multiple EMEs with sleep quality.
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Affiliation(s)
- Hongli Wang
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Meishan Road 81, Hefei, 230032, Anhui, China
- Anhui Provincial Key Laboratory of Population Health and Aristogenics, Hefei, 230032, Anhui, China
| | - Yan Zhang
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Meishan Road 81, Hefei, 230032, Anhui, China
- Anhui Provincial Key Laboratory of Population Health and Aristogenics, Hefei, 230032, Anhui, China
| | - Huaibiao Li
- Fuyang Center for Diseases Prevention and Control, Fuyang, 236069, Anhui, China
| | - Junzhe Li
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Meishan Road 81, Hefei, 230032, Anhui, China
| | - Qiang Liu
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Meishan Road 81, Hefei, 230032, Anhui, China
| | - Yuan Wang
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Meishan Road 81, Hefei, 230032, Anhui, China
| | - Liang Sun
- Fuyang Center for Diseases Prevention and Control, Fuyang, 236069, Anhui, China
| | - Bing Hu
- Fuyang Center for Diseases Prevention and Control, Fuyang, 236069, Anhui, China
| | - Guimei Chen
- Anhui Provincial Key Laboratory of Population Health and Aristogenics, Hefei, 230032, Anhui, China
- School of Health Services Management, Anhui Medical University, Hefei, 230032, Anhui, China
| | - Dongmei Zhang
- Anhui Provincial Key Laboratory of Population Health and Aristogenics, Hefei, 230032, Anhui, China
- School of Health Services Management, Anhui Medical University, Hefei, 230032, Anhui, China
| | - Chunmei Liang
- School of Public Health, Department of Hygiene Inspection and Quarantine, Anhui Medical University, Hefei, 230032, Anhui, China
- Key Laboratory of Population Health Across Life Cycle, Anhui Medical University, Ministry of Education of the People's Republic of China, Hefei, 230032, Anhui, China
- NHC Key Laboratory of Study On Abnormal Gametes and Reproductive Tract, Anhui Medical University, Hefei, 230032, Anhui, China
| | - Jingyuan Lei
- School of Public Health, Department of Hygiene Inspection and Quarantine, Anhui Medical University, Hefei, 230032, Anhui, China
| | - Panpan Wang
- School of Public Health, Department of Hygiene Inspection and Quarantine, Anhui Medical University, Hefei, 230032, Anhui, China
| | - Fangbiao Tao
- Anhui Provincial Key Laboratory of Population Health and Aristogenics, Hefei, 230032, Anhui, China
- Key Laboratory of Population Health Across Life Cycle, Anhui Medical University, Ministry of Education of the People's Republic of China, Hefei, 230032, Anhui, China
| | - Linsheng Yang
- School of Public Health, Department of Epidemiology and Health Statistics, Anhui Medical University, Meishan Road 81, Hefei, 230032, Anhui, China.
- Anhui Provincial Key Laboratory of Population Health and Aristogenics, Hefei, 230032, Anhui, China.
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9
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Hawley AL, Baum JI. Nutrition as the foundation for successful aging: a focus on dietary protein and omega-3 polyunsaturated fatty acids. Nutr Rev 2024; 82:389-406. [PMID: 37319363 DOI: 10.1093/nutrit/nuad061] [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] [Indexed: 06/17/2023] Open
Abstract
Skeletal muscle plays a critical role throughout the aging process. People living with sarcopenia, a progressive and generalized loss of skeletal muscle mass and function, often experience diminished quality of life, which can be attributed to a long period of decline and disability. Therefore, it is important to identify modifiable factors that preserve skeletal muscle and promote successful aging (SA). In this review, SA was defined as (1) low cardiometabolic risk, (2) preservation of physical function, and (3) positive state of wellbeing, with nutrition as an integral component. Several studies identify nutrition, specifically high-quality protein (eg, containing all essential amino acids), and long-chain omega-3 polyunsaturated fatty acids (n-3 PUFAs), eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA), as positive regulators of SA. Recently, an additive anabolic effect of protein and n-3 PUFAs has been identified in skeletal muscle of older adults. Evidence further suggests that the additive effect of protein and n-3 PUFAs may project beyond skeletal muscle anabolism and promote SA. The key mechanism(s) behind the enhanced effects of intake of protein and n-3 PUFAs needs to be defined. The first objective of this review is to evaluate skeletal muscle as a driver of cardiometabolic health, physical function, and wellbeing to promote SA. The second objective is to examine observational and interventional evidence of protein and n-3 PUFAs on skeletal muscle to promote SA. The final objective is to propose mechanisms by which combined optimal intake of high-quality protein and n-3 PUFAs likely play a key role in SA. Current evidence suggests that increased intake of protein above the Recommended Dietary Allowance and n-3 PUFAs above the Dietary Guidelines for Americans recommendations for late middle-aged and older adults is required to maintain skeletal muscle mass and to promote SA, potentially through the mechanistical target of rapamycin complex 1 (mTORC1).
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Affiliation(s)
- Aubree L Hawley
- School of Human and Environmental Sciences, University of Arkansas, Fayetteville, AR, USA
| | - Jamie I Baum
- Center for Human Nutrition, Department of Food Science, University of Arkansas System Division of Agriculture, Fayetteville, AR, USA
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10
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Zhang D, Li S. Family Members' Abuse of Older Adults, Psychological Well-Being, and Sleep Quality Among Older Women and Men in China. J Appl Gerontol 2024; 43:205-214. [PMID: 37747794 DOI: 10.1177/07334648231203835] [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] [Indexed: 09/27/2023] Open
Abstract
Despite the well-documented detrimental health effects of elder abuse, scholars have rarely considered whether and how family members' abuse of older adults is associated with sleep. Data from the 2018 China Longitudinal Aging Social Survey (N = 8110) were used to assess the association between elder abuse committed by family members and sleep quality, and how psychological well-being (depression and loneliness) mediates and gender moderates the above association. Results indicated that those who experienced family members' abuse were more likely to report poor sleep quality than their non-abused counterparts. Depression and loneliness partially mediated the elder abuse-sleep relationship. Furthermore, among those who experienced one elder abuse, older women had a higher risk of poor sleep quality than their male counterparts. However, two or more elder abuse experiences had similar negative effects on older women and men. Preventing elder abuse and improving psychological well-being is critical to promoting late-life sleep.
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Affiliation(s)
- Dan Zhang
- School of Public Administration, Hohai University, Nanjing, China
| | - Shuzhuo Li
- Institute for Population and Development Studies, School of Public Policy and Administration, Xi'an Jiaotong University, Xi'an, China
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11
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Matynia A, Recio BS, Myers Z, Parikh S, Goit RK, Brecha NC, Pérez de Sevilla Müller L. Preservation of Intrinsically Photosensitive Retinal Ganglion Cells (ipRGCs) in Late Adult Mice: Implications as a Potential Biomarker for Early Onset Ocular Degenerative Diseases. Invest Ophthalmol Vis Sci 2024; 65:28. [PMID: 38224335 PMCID: PMC10793389 DOI: 10.1167/iovs.65.1.28] [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: 06/29/2023] [Accepted: 11/27/2023] [Indexed: 01/16/2024] Open
Abstract
Purpose Intrinsically photosensitive retinal ganglion cells (ipRGCs) play a crucial role in non-image-forming visual functions. Given their significant loss observed in various ocular degenerative diseases at early stages, this study aimed to assess changes in both the morphology and associated behavioral functions of ipRGCs in mice between 6 (mature) and 12 (late adult) months old. The findings contribute to understanding the preservation of ipRGCs in late adults and their potential as a biomarker for early ocular degenerative diseases. Methods Female and male C57BL/6J mice were used to assess the behavioral consequences of aging to mature and old adults, including pupillary light reflex, light aversion, visual acuity, and contrast sensitivity. Immunohistochemistry on retinal wholemounts from these mice was then conducted to evaluate ipRGC dendritic morphology in the ganglion cell layer (GCL) and inner nuclear layer (INL). Results Morphological analysis showed that ipRGC dendritic field complexity was remarkably stable through 12 months old of age. Similarly, the pupillary light reflex, visual acuity, and contrast sensitivity were stable in mature and old adults. Although alterations were observed in ipRGC-independent light aversion distinct from the pupillary light reflex, aged wild-type mice continuously showed enhanced light aversion with dilation. No effect of sex was observed in any tests. Conclusions The preservation of both ipRGC morphology and function highlights the potential of ipRGC-mediated function as a valuable biomarker for ocular diseases characterized by early ipRGC loss. The consistent stability of ipRGCs in mature and old adult mice suggests that detected changes in ipRGC-mediated functions could serve as early indicators or diagnostic tools for early-onset conditions such as Alzheimer's disease, Parkinson's disease, and diabetes, where ipRGC loss has been documented.
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Affiliation(s)
- Anna Matynia
- Department of Ophthalmology, Jules Stein Eye Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States
- Brain Research Institute, University of California, Los Angeles, Los Angeles, California, United States
| | - Brandy S. Recio
- Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States
| | - Zachary Myers
- Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States
| | - Sachin Parikh
- Department of Ophthalmology, Jules Stein Eye Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States
- Brain Research Institute, University of California, Los Angeles, Los Angeles, California, United States
| | - Rajesh Kumar Goit
- Department of Ophthalmology, Jules Stein Eye Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States
- Brain Research Institute, University of California, Los Angeles, Los Angeles, California, United States
| | - Nicholas C. Brecha
- Department of Ophthalmology, Jules Stein Eye Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States
- Brain Research Institute, University of California, Los Angeles, Los Angeles, California, United States
- Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States
| | - Luis Pérez de Sevilla Müller
- Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States
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12
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Sankar K, Shanmugasundram N, Baskaran B, Anabalagan D, Sivaraman V, Santhiyagu X, Muhasaparur Ganesan R. Effectiveness of High-dose Clonazepam Versus Low-Dose Clonazepam With Cognitive Behavioral Therapy in Older Adults With Moderately Severe Insomnia: A Prospective Cohort Study. Clin Ther 2024; 46:69-73. [PMID: 37940498 DOI: 10.1016/j.clinthera.2023.10.010] [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: 04/03/2023] [Revised: 09/15/2023] [Accepted: 10/10/2023] [Indexed: 11/10/2023]
Abstract
PURPOSE To evaluate the effectiveness of high-dose clonazepam (1 mg) versus low-dose clonazepam (0.5 mg) with cognitive behavioral therapy for insomnia (CBT-i) in older adults with moderately severe insomnia. METHODS A prospective cohort study was conducted in patients who did not respond to low-dose clonazepam for insomnia secondary to chronic medical conditions. After starting with 0.25 mg of clonazepam, their dose was increased to 0.5 mg, then to 1 mg (Group A), or to the same dose with additional CBT-i (Group B). They were followed for 24 weeks, and scores of the insomnia severity index (ISI) and subjective units of distress scale (SUDS) were recorded. Patient adverse drug reactions (ADRs) were documented and assessed for their causality. ISI and SUDS scores were considered primary outcome measures. FINDINGS Between-group analysis revealed a significant decline in the mean score of ISI at week 16 (P < 0.05) and for SUDS at week 20 (P < 0.05) in group B compared to group A. Similarly, within-group analysis also revealed a statistically significant reduction of the mean score in ISI and SUDS scores at week 4 and 8 (P < 0.05) in both groups. ADRs occurred more frequently in group A (14%) than in group B (5%). Assessments of causality showed that the majority of cases were possible. IMPLICATIONS For individuals who were resistant to 0.5 mg of clonazepam, adding CBT-i with low-dose clonazepam is a viable alternative to increasing the dose to 1 mg.
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Affiliation(s)
- Karthik Sankar
- Department of Pharmacy Practice, Sri Ramachandra Faculty of Pharmacy, Sri Ramachandra Institute of Higher Education and Research, Chennai, Tamil Nadu, India
| | - Natrajan Shanmugasundram
- Department of Psychiatry, Sri Ramachandra Medical College and Research Institute, Sri Ramachandra Institute of Higher Education and Research, Chennai, Tamil Nadu, India
| | - Balaswetha Baskaran
- Department of Pharmacy Practice, Sri Ramachandra Faculty of Pharmacy, Sri Ramachandra Institute of Higher Education and Research, Chennai, Tamil Nadu, India
| | - Deepika Anabalagan
- Department of Pharmacy Practice, Sri Ramachandra Faculty of Pharmacy, Sri Ramachandra Institute of Higher Education and Research, Chennai, Tamil Nadu, India
| | - Varadharajan Sivaraman
- Department of Clinical Psychology, Sri Ramachandra Institute of Higher Education and Research, Chennai, Tamil Nadu, India
| | - Xavier Santhiyagu
- Department of Statistics, Loyola College, Chennai, Tamil Nadu, India
| | - Rajanandh Muhasaparur Ganesan
- Department of Pharmacy Practice, SRM College of Pharmacy, SRM Institute of Science and Technology, Chennai, Tamil Nadu, India.
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13
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Watanabe D, Yoshida T, Watanabe Y, Yamada Y, Miyachi M, Kimura M. Combined Use of Sleep Quality and Duration Is More Closely Associated With Mortality Risk Among Older Adults: A Population-based Kyoto-Kameoka Prospective Cohort Study. J Epidemiol 2023; 33:591-599. [PMID: 36155361 PMCID: PMC10635816 DOI: 10.2188/jea.je20220215] [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: 07/22/2022] [Accepted: 09/12/2022] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Whether sleep quality and duration assessed from multiple domains, either individually or in combination, are strongly associated with mortality risk in older adults remains unelucidated. We aimed to clarify these relationships. METHODS We enrolled 7,668 older (age ≥65 years) Japanese adults in the Kyoto-Kameoka prospective cohort study who provided valid responses to the Pittsburgh Sleep Quality Index (PSQI) in a mail-in survey. Sleep quality and duration were classified into six groups using the previously validated PSQI: short sleep duration (SSD: <360 min/day)/sleep disturbance (SD: ≥5.5 PSQI points), n = 701; SSD/non-sleep disturbance (NSD: <5.5 PSQI points), n = 100; optimal sleep duration (OSD: 360-480 min/day)/NSD, n = 1,863; OSD/SD, n = 2,113; long sleep duration (LSD: >480 min/day)/NSD, n = 1,972; LSD/SD, n = 919. Mortality data were collected from February 15, 2012, to November 30, 2016. We evaluated the relationship between all-cause mortality risk and sleep quality and duration (and their combinations) using a multivariable Cox proportional hazards model that included baseline covariates. RESULTS The median follow-up period was 4.75 years (34,826 person-years), with a total of 616 deaths. After adjusting for confounders, compared with other groups, SSD/SD and LSD/SD had the highest hazard ratio (HR) of mortality (SSD/SD: HR 1.56; 95% confidence interval [CI], 1.10-2.19; SSD/NSD: HR 1.27; 95% CI, 0.47-3.48; OSD/NSD: reference; OSD/SD: HR 1.20; 95% CI, 0.91-1.59; LSD/NSD: HR 1.35; 95% CI, 1.03-1.77; LSD/SD: HR 1.83; 95% CI, 1.37-2.45). However, mortality risk was not associated with the interaction between sleep quality and duration. CONCLUSION Older adults with sleep disturbances involving SSD and LSD have a strong positive association with mortality risk, suggesting an additive effect between sleep quality and duration.
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Affiliation(s)
- Daiki Watanabe
- Faculty of Sport Sciences, Waseda University, Saitama, Japan
- National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan
- Institute for Active Health, Kyoto University of Advanced Science, Kyoto, Japan
| | - Tsukasa Yoshida
- National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan
- Institute for Active Health, Kyoto University of Advanced Science, Kyoto, Japan
- Senior Citizen’s Welfare Section, Kameoka City Government, Kyoto, Japan
| | - Yuya Watanabe
- National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan
- Institute for Active Health, Kyoto University of Advanced Science, Kyoto, Japan
- Physical Fitness Research Institute, Meiji Yasuda Life Foundation of Health and Welfare, Tokyo, Japan
| | - Yosuke Yamada
- National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan
- Institute for Active Health, Kyoto University of Advanced Science, Kyoto, Japan
| | - Motohiko Miyachi
- Faculty of Sport Sciences, Waseda University, Saitama, Japan
- National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan
| | - Misaka Kimura
- Institute for Active Health, Kyoto University of Advanced Science, Kyoto, Japan
- Department of Nursing, Doshisha Women’s College of Liberal Arts, Kyoto, Japan
- Laboratory of Applied Health Sciences, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - the Kyoto-Kameoka Study Group
- National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan
- Institute for Active Health, Kyoto University of Advanced Science, Kyoto, Japan
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14
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Brossoit RM, Stark HP, Crain TL, Bodner TE, Hammer LB, Mohr CD, Shea SA. Multidimensionality of the PROMIS sleep disturbance 8b short form in working adult populations. Sleep Health 2023; 9:925-932. [PMID: 37770251 PMCID: PMC10888491 DOI: 10.1016/j.sleh.2023.08.001] [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: 11/23/2022] [Revised: 07/25/2023] [Accepted: 08/04/2023] [Indexed: 09/30/2023]
Abstract
OBJECTIVES The Patient-Reported Outcomes Measurement Information System sleep disturbance measures were developed using item response theory assumptions of unidimensionality and local independence. Given that sleep health is multidimensional, we evaluate the factor structure of the Patient-Reported Outcomes Measurement Information System sleep disturbance 8b short form to examine whether it reflects a unidimensional or multidimensional construct. METHODS Six full-time working adult samples were collected from civilian and military populations. Exploratory and confirmatory factor analyses were conducted. Single-factor and two-factor models were performed to evaluate the dimensionality of sleep disturbance using the 8b short form. Sleep duration and subjective health were examined as correlates of the sleep disturbance dimensions. RESULTS Across six working adult samples, single-factor models consistently demonstrated poor fit, whereas the two-factor models, with insomnia symptoms (ie, trouble sleeping) and dissatisfaction with sleep (ie, subjective quality of sleep) dimensions demonstrated sufficient fit that was significantly better than the single-factor models. Across each sample, dissatisfaction with sleep was more strongly correlated with sleep duration and subjective health than insomnia symptoms, providing additional evidence for distinguishability between the two sleep disturbance factors. CONCLUSIONS In working adult populations, the Patient-Reported Outcomes Measurement Information System sleep disturbance 8b short form is best modeled as two distinguishable factors capturing insomnia symptoms and dissatisfaction with sleep, rather than as a unidimensional sleep disturbance construct.
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Affiliation(s)
- Rebecca M Brossoit
- Louisiana State University, Department of Psychology, Baton Rouge, Louisiana, USA.
| | - Hannah P Stark
- Louisiana State University, Department of Psychology, Baton Rouge, Louisiana, USA
| | - Tori L Crain
- Portland State University, Department of Psychology, Portland, Oregon, USA
| | - Todd E Bodner
- Portland State University, Department of Psychology, Portland, Oregon, USA
| | - Leslie B Hammer
- Oregon Health & Science University, Oregon Institute of Occupational Health Sciences, Portland, Oregon, USA
| | - Cynthia D Mohr
- Portland State University, Department of Psychology, Portland, Oregon, USA
| | - Steven A Shea
- Oregon Health & Science University, Oregon Institute of Occupational Health Sciences, Portland, Oregon, USA
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15
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Hoteit M, Al-Masry A, Elbejjani M, Aoun M, Abu-Dargham R, Medawar W, Abou Zeinab H, Farhood L, Koubar SH. Sleepiness and Health-Related Quality of Life Among Kidney Transplant Recipients in a Low-Middle Income Country: A Cross-Sectional Study. Transpl Int 2023; 36:11547. [PMID: 38020749 PMCID: PMC10647915 DOI: 10.3389/ti.2023.11547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Accepted: 10/05/2023] [Indexed: 12/01/2023]
Abstract
This study aims to describe daytime sleepiness and health-related quality of life (HRQoL) among Lebanese kidney transplant (KT) recipients and to examine the medical, psychosocial and transplant factors related to them. It is a cross-sectional multi-center study involving KT recipients >18 years. Daytime sleepiness was assessed using ESS Questionnaire. HRQoL was measured using the SF-36 questionnaire. Social support was self-reported. A multivariable regression analysis evaluated factors associated with daytime sleepiness and HRQoL in our sample. 118 patients were recruited over a 2 years period. Excessive daytime sleepiness was prevalent in 12.7%. It was associated with Diabetes Mellitus (OR 3.97, 95% CI 0.94-16.81, p = 0.06) and obesity (OR 1.13, 95% CI 1.02, 1.27, p = 0.02). Social support and higher eGFR were associated with better scores on the MCS (β 24.13 p < 0.001 and β 0.26 p < 0.01) and the PCS (β 15.48 p < 0.01 and β 0.22 P 0.02). Conversely, depression and hospitalization were negatively associated with the MCS (β -27.44, p < 0.01 and β -9.87, p < 0.01) and the PCS (β -0.28.49, p < 0.01 and β -10.37, p < 0.01).
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Affiliation(s)
- Mayssaa Hoteit
- Division of Nephrology and Hypertension, Department of Internal Medicine, American University of Beirut, Beirut, Lebanon
| | - Ahmad Al-Masry
- Division of Nephrology and Hypertension, Department of Internal Medicine, University of Iowa Hospitals and Clinics, Iowa City, IA, United States
| | - Martine Elbejjani
- Clinical Research Institute, American University of Beirut, Beirut, Lebanon
| | - Mabel Aoun
- AUB Santé, Lorient, France
- Faculty of Medicine, Saint-Joseph University, Beirut, Lebanon
| | | | - Walid Medawar
- Division of Nephrology and Hypertension, Department of Internal Medicine, American University of Beirut, Beirut, Lebanon
| | - Hilal Abou Zeinab
- Division of Nephrology and Hypertension, Hammoud University Hospital, Saida, Lebanon
| | - Laila Farhood
- School of Nursing, American University of Beirut, Beirut, Lebanon
- Psychiatry Department, Faculty of Medicine, American University of Beirut, Beirut, Lebanon
| | - Sahar H. Koubar
- Division of Nephrology and Hypertension, Department of Internal Medicine, American University of Beirut, Beirut, Lebanon
- Division of Nephrology and Hypertension, University of Minnesota, Minneapolis, MN, United States
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16
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Mayer G, Stenmanns C, Doeppner TR, Hermann DM, Gronewold J. [Sleep and dementia]. Z Gerontol Geriatr 2023; 56:556-560. [PMID: 37676320 DOI: 10.1007/s00391-023-02237-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/10/2023] [Indexed: 09/08/2023]
Abstract
Aging is associated with changes in sleep structure and cerebral deposition of amyloid beta and tau proteins. Sleep disturbances precede the onset of dementia by years. Comorbid sleep disorders, such as insomnia and sleep-disordered breathing, a family history of dementia and epigenetic factors can contribute to the development of dementia. This article explores the question of the interaction between sleep and dementia based on the existing literature. Alterations caused by slow wave sleep lead to changes in the glymphatic clearance of amyloid beta, tau proteins and other proteins. Transient and chronic sleep disorders cause disturbances in the brain areas responsible for cognition and behavior. Sleep-regulating brain areas are the first to be affected in the neurodegenerative process and accelerate the risk of dementia. Circadian age-related changes in amyloid beta and tau proteins affect the amount and depth of sleep and vice versa. Amyloid beta in cerebrospinal fluid shows an inverse correlation with sleep. Orexins modulate amyloid beta and sleep.
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Affiliation(s)
- Geert Mayer
- Philipps-Universität Marburg, Marburg, Deutschland.
- , Privatweg 2, 34582, Borken, Deutschland.
| | - Carla Stenmanns
- Klinik für Orthopädie und Unfallchirurgie, Altersmedizin, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Deutschland
| | - Thorsten R Doeppner
- Klinik für Neurologie, Universitätsklinkum Gießen und Marburg, Gießen, Deutschland
| | - Dirk M Hermann
- Klinik für Neurologie, Universitätsklinikum Essen, Essen, Deutschland
| | - Janine Gronewold
- Klinik für Neurologie, Universitätsklinikum Essen, Essen, Deutschland
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17
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Kundu S, Acharya SS. Linkage of premature and early menopause with psychosocial well-being: a moderated multiple mediation approach. BMC Psychol 2023; 11:228. [PMID: 37559104 PMCID: PMC10413596 DOI: 10.1186/s40359-023-01267-3] [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: 03/14/2023] [Accepted: 07/26/2023] [Indexed: 08/11/2023] Open
Abstract
PURPOSE Menopause occurring before the age of 40 is premature and between 40 and 44 years age is early, since the natural age of menopause lies between 45 and 50. The endocrine changes that come with menopause include an erratic decline in estrogen levels which affects the brain. Thus, leading to changes in cognitive function in the longer term due to the menopausal transition. The study aims to explore the effect of premature and early menopause on cognitive health, and psychosocial well-being. The moderated multiple mediation hypothesis of the study is that the effect of premature or early menopause is mediated by depression and insomnia, while all the pathways are moderated by smoking habits. DATA AND METHODS The study utilized Longitudinal Aging Study in India (LASI), 2017-2018, Wave 1 data. The sample of 31,435 women were aged 45 and above and did not undergo hysterectomy. A moderated multiple mediation model was used to understand the association between premature or early menopause (X), insomnia (M1), depression (M2), moderator (W), and cognitive health (Y), while controlling for possible confounders. RESULTS Premature menopause was negatively associated with cognition (β:-0.33; SE:0.12; p < 0.05), whereas positively associated with insomnia (β:0.18; SE:0.03; p < 0.001) and depression (β:0.25; SE:0.04; p < 0.001). There is a moderating effect of smoking or tobacco consumption has a significant moderating effect on the pathways among premature menopause, depression, insomnia and cognition. When the same model was carried out for early menopause (40-44 years), the results were not significant. CONCLUSIONS The findings emphasize the fact that smoking is associated with premature menopause, depression and insomnia. Women who experienced premature menopause has lower cognitive scores, depressive symptoms and insomnia symptoms, which were higher among those who consumed tobacco. The study, strongly recommends the dissemination of information on the negative effects of tobacco consumption and making more informed choices to maintain a healthy life. More research into various methods and therapy is needed to determine the relationship between the age of early menopause and their psychosocial well-being.
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Affiliation(s)
- Sampurna Kundu
- Centre of Social Medicine and Community Health, School of Social Sciences, Jawaharlal Nehru University, Delhi, 110067, India.
| | - Sanghmitra Sheel Acharya
- Centre of Social Medicine and Community Health, School of Social Sciences, Jawaharlal Nehru University, Delhi, 110067, India
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18
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Nutakor JA, Zhou L, Larnyo E, Gavu AK, Chohan IM, Addai-Dansoh S, Tripura D. The Relationship Between Social Capital and Sleep Duration Among Older Adults in Ghana: A Cross-Sectional Study. Int J Public Health 2023; 68:1605876. [PMID: 37457843 PMCID: PMC10338686 DOI: 10.3389/ijph.2023.1605876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 06/20/2023] [Indexed: 07/18/2023] Open
Abstract
Objective: This study aims to investigate the connection between social capital and sleep duration among older adults in Ghana, as limited research has been conducted to explore this relationship. Methods: This study utilized Wave 2 data from a sample of Ghanaian older adults from the World Health Organization Study on Global AGEing and Adult Health (SAGE). Self-reported data on social capital and sleep duration were compiled. Using ordered logistic regression, the relationship between social capital and sleep duration was examined. Results: Older adults who did not participate in social activities showed the strongest association with the risk of short sleep (p < 0.05). Our study found that older adults who sleep for shorter periods tend to report better sleep quality. There was no correlation between medium and long sleep durations and social capital. Conclusion: This study underscores the importance of more research to truly understand the complex connections between older adults' social participation, sleep, and health. It also has important implications for the promotion of good sleep in aging populations.
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Affiliation(s)
| | - Lulin Zhou
- School of Management, Jiangsu University, Zhenjiang, China
| | - Ebenezer Larnyo
- Center for Black Studies Research, University of California, Santa Barbara, CA, United States
| | - Alexander Kwame Gavu
- Department of Educational Administration, College of Education, University of Saskatchewan, Saskatoon, SK, Canada
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Montesino-Goicolea S, Nin O, Gonzalez BM, Sawczuk NJ, Nodarse CL, Valdes-Hernandez PA, Jackson E, Huo Z, Somerville JET, Porges EC, Smith C, Fillingim RB, Cruz-Almeida Y. Protocol for a pilot and feasibility randomized-controlled trial of four weeks of oral γ-aminobutyric acid (GABA) intake and its effect on pain and sleep in middle-to-older aged adults. Contemp Clin Trials Commun 2023; 32:101066. [PMID: 36712186 PMCID: PMC9876833 DOI: 10.1016/j.conctc.2023.101066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Revised: 12/05/2022] [Accepted: 01/14/2023] [Indexed: 01/22/2023] Open
Abstract
Approximately 1.71 billion people globally live with musculoskeletal pain conditions, including low back pain, knee pain, and neck pain Cieza et al. (2020). In the US, an estimated 20.4% of U.S. adult had chronic pain and 8.0% of U.S. adults had high-impact chronic pain, with higher prevalence associated with advancing age Dahlhamer et al. (2018). On the other hand, between 50 and 70 million US adults have a sleep disorder (American Sleep Association). Although the link between sleep and pain is widely established, the neurobiological mechanisms underlying this relationship have yet to be fully elucidated, specifically within an aged population. As currently available sleep and chronic pain therapies are only partially effective, novel treatment approaches are urgently needed. Given the potential mechanistic role of γ-aminobutyric acid (GABA) in both conditions, and the availability of GABA supplements over the counter, the present proposal will determine the feasibility and acceptability of oral GABA administration in middle-to-older aged adults with chronic pain and sleep disorders as well as characterize the potential neurobiological mechanisms involved in both conditions. Results from the present investigation using a parallel, double-blinded, placebo-controlled study will provide novel preliminary information needed for future translational pain and sleep research.
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Affiliation(s)
- Soamy Montesino-Goicolea
- Pain Research & Intervention Center of Excellence, University of Florida, Gainesville, FL, USA
- Department of Community Dentistry & Behavioral Science, College of Dentistry, University of Florida, Gainesville, FL, USA
- Institute on Aging, University of Florida, Gainesville, FL, USA
| | - Olga Nin
- Department of Anesthesiology, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Barbara M. Gonzalez
- Pain Research & Intervention Center of Excellence, University of Florida, Gainesville, FL, USA
- Department of Community Dentistry & Behavioral Science, College of Dentistry, University of Florida, Gainesville, FL, USA
| | - Nathalie J. Sawczuk
- Pain Research & Intervention Center of Excellence, University of Florida, Gainesville, FL, USA
- Department of Community Dentistry & Behavioral Science, College of Dentistry, University of Florida, Gainesville, FL, USA
| | - Chavier Laffitte Nodarse
- Pain Research & Intervention Center of Excellence, University of Florida, Gainesville, FL, USA
- Department of Community Dentistry & Behavioral Science, College of Dentistry, University of Florida, Gainesville, FL, USA
| | - Pedro Antonio Valdes-Hernandez
- Pain Research & Intervention Center of Excellence, University of Florida, Gainesville, FL, USA
- Department of Community Dentistry & Behavioral Science, College of Dentistry, University of Florida, Gainesville, FL, USA
| | - Elijah Jackson
- Pain Research & Intervention Center of Excellence, University of Florida, Gainesville, FL, USA
- Department of Community Dentistry & Behavioral Science, College of Dentistry, University of Florida, Gainesville, FL, USA
| | - Zhiguang Huo
- Department of Biostatistics, College of Public Health & Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA
| | - Jessie Elise T. Somerville
- Pain Research & Intervention Center of Excellence, University of Florida, Gainesville, FL, USA
- Department of Community Dentistry & Behavioral Science, College of Dentistry, University of Florida, Gainesville, FL, USA
| | - Eric C. Porges
- Center for Cognitive Aging & Memory, McKnight Brain Foundation, University of Florida, Gainesville, FL, USA
- Department of Clinical and Health Psychology College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Cameron Smith
- Department of Anesthesiology, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Roger B. Fillingim
- Pain Research & Intervention Center of Excellence, University of Florida, Gainesville, FL, USA
- Department of Community Dentistry & Behavioral Science, College of Dentistry, University of Florida, Gainesville, FL, USA
- Institute on Aging, University of Florida, Gainesville, FL, USA
| | - Yenisel Cruz-Almeida
- Pain Research & Intervention Center of Excellence, University of Florida, Gainesville, FL, USA
- Center for Cognitive Aging & Memory, McKnight Brain Foundation, University of Florida, Gainesville, FL, USA
- Department of Community Dentistry & Behavioral Science, College of Dentistry, University of Florida, Gainesville, FL, USA
- Institute on Aging, University of Florida, Gainesville, FL, USA
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20
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Associations between objectively measured sleep parameters and cognition in healthy older adults: A meta-analysis. Sleep Med Rev 2023; 67:101734. [PMID: 36577339 DOI: 10.1016/j.smrv.2022.101734] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 11/03/2022] [Accepted: 12/05/2022] [Indexed: 12/14/2022]
Abstract
Multiple studies have examined associations between sleep and cognition in older adults, but a majority of these depend on self-reports on sleep and utilize cognitive tests that assess overall cognitive function. The current meta-analysis involved 72 independent studies and sought to quantify associations between objectively measured sleep parameters and cognitive performance in healthy older adults. Both sleep macrostructure (e.g., sleep duration, continuity, and stages) and microstructure (e.g., slow wave activity and spindle activity) were evaluated. For macrostructure, lower restlessness at night was associated with better memory performance (r = 0.43, p = 0.02), while lower sleep onset latency was associated with better executive functioning (r = 0.28, p = 0.03). Greater relative amount of N2 and REM sleep, but not N3, positively correlated with cognitive performance. The association between microstructure and cognition in older adults was marginally significant. This relationship was moderated by age (z = 0.07, p < 0.01), education (z = 0.26, p = 0.03), and percentage of female participants (z = 0.01, p < 0.01). The current meta-analysis emphasizes the importance of considering objective sleep measures to understand the relationship between sleep and cognition in healthy older adults. These results also form a base from which researchers using wearable sleep technology and measuring behavior through computerized testing tools can evaluate their findings.
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21
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Sabot D, Baumann O. Neuroimaging Correlates of Cognitive Behavioral Therapy for Insomnia (CBT-I): A Systematic Literature Review. J Cogn Psychother 2023; 37:82-101. [PMID: 36787999 DOI: 10.1891/jcpsy-d-21-00006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Cognitive behavioral therapy for insomnia (CBT-I) is the gold-standard non-pharmacological treatment for insomnia, a complex disorder that comprises psychological, behavioral, and physiological components. This systematic literature review aimed to evaluate a growing body of exploratory studies that have examined CBT-I treatment effects using neuroimaging assessment. Nine studies met current review selection criteria, of which six studies compared insomnia groups with good sleepers, waitlist, and/or control groups. CBT-I administration varied in treatment length and duration across the studies, as did neuroimaging assessment, which included task-based and resting-state functional magnetic resonance imaging (fMRI), and structural magnetic resonance imaging (MRI). Functional connectivity abnormalities were observed in participants, including reduced engagement in task-related brain regions and apparent difficulties in regulating default mode brain areas that appeared to reverse following CBT-I treatment. Taken together, the neuroimaging results complement behavioral measures of treatment efficacy, indicating support for the effectiveness of CBT-I treatment in the recovery of brain function and structure.
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Affiliation(s)
- Debbie Sabot
- School of Psychology, Bond University, Robina QLD 4226 Australia
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22
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Enam N, Grampurohit N, Farber RS. Sleep Management within Skilled Nursing Facilities: A Practice Survey. Occup Ther Health Care 2023; 37:1-17. [PMID: 33228469 DOI: 10.1080/07380577.2020.1846234] [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] [Indexed: 01/05/2023]
Abstract
A cross-sectional descriptive survey of 105 occupational therapy practitioners examined the practice patterns in sleep management within skilled nursing facilities. All participants viewed sleep as essential to address in their settings, since clients frequently reported inadequate sleep, daytime sleepiness, difficulty staying asleep, and situational interruption. Majority of the practitioners reported not screening, assessing, treating, or documenting sleep issues and lack the use of standardized assessments and evidence-based interventions for sleep. Results suggest that practitioners need more training, education, and advocacy skills to promote the role of occupational therapy in addressing sleep management in skilled nursing facilities.
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Affiliation(s)
- Nabila Enam
- Occupational Therapy, University of the Sciences, Philadelphia, PA, USA
| | - Namrata Grampurohit
- Occupational Therapy, Thomas Jefferson University - Center City Campus, Philadelphia, PA, USA
| | - Ruth S Farber
- Rehabilitation Sciences/Occupational Therapy, Temple University, Philadelphia, PA, USA
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23
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Cohen ZL, Eigenberger PM, Sharkey KM, Conroy ML, Wilkins KM. Insomnia and Other Sleep Disorders in Older Adults. Psychiatr Clin North Am 2022; 45:717-734. [PMID: 36396275 DOI: 10.1016/j.psc.2022.07.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Sleep disruption is common in older adults and is associated with many poor health outcomes. It is vital for providers to understand insomnia and other sleep disorders in this population. This article outlines age-related changes in sleep, and medical, psychiatric, environmental, and psychosocial factors that may impact sleep. It addresses the evaluation of sleep symptoms and diagnosis of sleep disorders. It aims to examine the evidence for non-pharmacological and pharmacologic treatment options for insomnia while weighing factors particularly germane to the aging adult..
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Affiliation(s)
- Zachary L Cohen
- Department of Psychiatry, University of North Carolina at Chapel Hill, 101 Manning Drive, Campus Box #7160, Chapel Hill, NC, 27599, USA.
| | - Paul M Eigenberger
- Yale University School of Medicine, 300 George Street, Suite #901, New Haven, CT, 06511, USA
| | - Katherine M Sharkey
- Department of Medicine, The Warren Alpert Medical School of Brown University, 233 Richmond Street, Suite 242, Providence, RI 02903, USA; Department of Psychiatry and Human Behavior, The Warren Alpert Medical School of Brown University, 233 Richmond Street, Suite 242, Providence, RI 02903, USA
| | - Michelle L Conroy
- Yale University School of Medicine, 300 George Street, Suite #901, New Haven, CT, 06511, USA; VA Connecticut Healthcare System, West Haven, CT, USA
| | - Kirsten M Wilkins
- Yale University School of Medicine, 300 George Street, Suite #901, New Haven, CT, 06511, USA; VA Connecticut Healthcare System, West Haven, CT, USA
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24
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Aliabadi S, Zarghami F, Farhadi A, Sharifi F, Moodi M. Effect of Physical Activity on Sleep Outcomes among Iranian Older Adults: A Cross-Sectional Study. ADVANCES IN GERONTOLOGY 2022. [DOI: 10.1134/s2079057022040038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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Perceived stress, recent stressors, and distress in relation to sleep disturbance and duration among middle-aged and older Asian immigrants. Sleep Health 2022; 9:211-217. [PMID: 36572577 PMCID: PMC10122696 DOI: 10.1016/j.sleh.2022.11.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 11/10/2022] [Accepted: 11/14/2022] [Indexed: 12/25/2022]
Abstract
OBJECTIVE This study aimed to examine the associations of perceived stress, stressors, and distress with sleep disturbance and duration among Asian immigrants. DESIGN/SETTING/PARTICIPANTS The sample included 400 Asian immigrants aged 50-75 years old recruited from primary care physicians' clinics. METHODS We fit multivariable regression models to examine the associations of perceived stress, stressors, and distress with self-reported sleep disturbance and duration. We tested effect modifications by language proficiency, years in the United States, acculturative stress, and social support. RESULTS A total of 73 (18.3%) participants reported any sleep disturbance, and the average time in bed was 7.25 hours (SD = 1.17). Higher perceived stress (PR = 1.15, 95% CI = 1.06, 1.26), stressors (PR = 1.32, 95% CI = 1.13, 1.59), and distress (PR = 1.36, 95% CI = 1.21, 1.57) were associated with a higher prevalence of any sleep disturbance. These associations were not modified by language proficiency, years in the United States, acculturative stress, and social support. On the other hand, the associations of perceived stress and distress with time in bed were modified by years in the United States. Specifically, higher levels of distress were associated with shorter times in bed only among adults who have resided in the United States for less than 10 years. CONCLUSION Perceived stress, stressors, and distress were associated with a higher prevalence of sleep disturbance. Moreover, perceived stress and distress had stronger associations with times in bed among recent immigrants. Future sleep health research in Asian Americans should consider the important role of stress and distress, especially among recent immigrants.
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26
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Yang E, Ismail A, Kim Y, Erdogmus E, Boron J, Goldstein F, DuBose J, Zimring C. Multidimensional Environmental Factors and Sleep Health for Aging Adults: A Focused Narrative Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:15481. [PMID: 36497555 PMCID: PMC9739530 DOI: 10.3390/ijerph192315481] [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: 08/28/2022] [Revised: 10/28/2022] [Accepted: 11/10/2022] [Indexed: 06/17/2023]
Abstract
The timing, amount, and quality of sleep are critical for an individual's health and quality of life. This paper provides a focused narrative review of the existing literature around multidimensional environments and sleep health for aging adults. Five electronic databases, Scopus, Web of Science, PubMed/Medline; EBSCOhost, PsycINFO (ProQuest), and Google Scholar yielded 54,502 total records. After removing duplicates, non-peer reviewed academic articles, and nonrelevant articles, 70 were included for review. We were able to categorize environmental factors into housing security, home environment, and neighborhood environment, and, within each environmental category, specific elements/aspects are discussed. This paper provides a comprehensive map connecting identified levels of influence (individual, home/house, and neighborhood-level) in which subfactors are listed under each level of influence/category with the related literature list. Our review highlights that multidimensional environmental factors can affect aging adults' sleep health and eventually their physical, mental, and cognitive health and that sleep disparities exist in racial minorities in socioeconomically disadvantaged communities in which cumulative environmental stressors coexist. Based on this focused narrative review on the multidimensional sleep environments for aging adults, knowledge gaps are identified, and future research directions are suggested.
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Affiliation(s)
- Eunhwa Yang
- School of Building Construction, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Aliaa Ismail
- School of Building Construction, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Yujin Kim
- School of Building Construction, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Ece Erdogmus
- School of Building Construction, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Julie Boron
- Department of Gerontology, University of Nebraska Omaha, Omaha, NE 68182, USA
| | - Felicia Goldstein
- Department of Neurology, School of Medicine, Emory University, Atlanta, GA 30322, USA
| | - Jennifer DuBose
- SimTigrate Design Lab, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Craig Zimring
- SimTigrate Design Lab, Georgia Institute of Technology, Atlanta, GA 30332, USA
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Sleep Problems and Psychological Well-Being: Baseline Findings from the Canadian Longitudinal Study on Aging. Can J Aging 2022; 42:230-240. [PMID: 36408684 DOI: 10.1017/s0714980822000368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Abstract
International studies have demonstrated associations between sleep problems and poor psychological well-being; however, Canadian data are limited. This study investigated this association using cross-sectional baseline data from the Canadian Longitudinal Study on Aging, a national survey of 30,097 community-dwelling adults, 45–85 years of age. Short sleep duration, sleep dissatisfaction, insomnia symptoms, and daytime impairment were consistently associated with a higher prevalence of dissatisfaction with life, psychological distress, and poor self-reported mental health. Long sleep duration was associated with a higher prevalence of psychological distress and poor self-reported mental health, but not with dissatisfaction with life. Associations between sleep problems and psychological distress were 11–18 per cent stronger in males. With each 10-year increase in age, the association between daytime impairment and life dissatisfaction increased by 11 per cent, and insomnia symptoms and poor mental health decreased by 11 per cent. Sleep problems in middle-aged and older adults warrant increased attention as a public health problem in Canada.
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28
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Qin F, Luo M, Xiong Y, Zhang N, Dai Y, Kuang W, Cen X. Prevalence and associated factors of cognitive impairment among the elderly population: A nationwide cross-sectional study in China. Front Public Health 2022; 10:1032666. [PMID: 36466480 PMCID: PMC9713248 DOI: 10.3389/fpubh.2022.1032666] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 10/31/2022] [Indexed: 11/18/2022] Open
Abstract
Background Cognitive impairments are associated with increased risk for progression to dementia. In China, limited surveys have been conducted to estimate the national prevalence and risk factors associated with cognitive impairment in China. This study aims to assess the national prevalence and modifiable risk factors for cognitive impairments in the Chinese elderly population. Methods This cross-sectional study was based on the 2018 China Health and Retirement Longitudinal Study. The Mini Mental State Examination (MMSE) is recommended to test for cognitive impairment. Univariate and multivariate logistic regression models were used in assessing risk factors for cognitive impairments in the Chinese elderly population. Results A total of 3768 participants aged 60 years or older were enrolled in this study. The national prevalence of cognitive impairments was 22.24% in China, and the prevalence of cognitive impairment was higher in the south-west region than in the north region (29.94 vs. 16.53%, p < 0.05). The risk for cognitive impairments was higher in the following participants: not married or not living with spouse relative to married with spouse present (OR = 1.39, 95% CI, 1.15-1.70; p = 0.001), nap duration of ≥ 90 min relative to 30-60 min (OR = 1.54, 95% CI, 1.20-1.98; p = 0.001), sleep duration of ≥ 8 h relative to 6-8 h (OR = 1.73, 95% CI, 1.29-2.31; p < 0.001), and depression relative to no depression (OR = 1.67, 95% CI, 1.41-1.97; p < 0.001). The risk of cognitive impairment was lower in participants living in the urban areas relative to the rural areas (OR = 0.57, 95% CI, 0.47-0.69; p < 0.001) and consuming alcohol once a month relative to never consuming alcohol (OR = 0.69, 95% CI, 0.51-0.94; p = 0.02). Conclusion Cognitive impairment prevalence was high in the Chinese elderly population. The potentially modifiable risk factors for cognitive impairment should be further assessed in the development of interventions for the elderly Chinese population.
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Affiliation(s)
- Feng Qin
- National Chengdu Center for Safety Evaluation of Drugs, State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, West China Hospital, Sichuan University, Chengdu, China,Department of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Min Luo
- Department of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Yang Xiong
- Department of Urology, West China Hospital, Sichuan University, Chengdu, China
| | - Ni Zhang
- Department of Psychiatry, West China Hospital, Sichuan University, Chengdu, China,Department of Nuclear Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Yanping Dai
- National Chengdu Center for Safety Evaluation of Drugs, State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, West China Hospital, Sichuan University, Chengdu, China
| | - Weihong Kuang
- Department of Psychiatry, West China Hospital, Sichuan University, Chengdu, China,Department of Nuclear Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Xiaobo Cen
- National Chengdu Center for Safety Evaluation of Drugs, State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, West China Hospital, Sichuan University, Chengdu, China,*Correspondence: Xiaobo Cen
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Souabni M, Souabni MJ, Hammouda O, Romdhani M, Trabelsi K, Ammar A, Driss T. Benefits and risks of napping in older adults: A systematic review. Front Aging Neurosci 2022; 14:1000707. [PMID: 36337699 PMCID: PMC9634571 DOI: 10.3389/fnagi.2022.1000707] [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: 07/22/2022] [Accepted: 09/27/2022] [Indexed: 11/29/2022] Open
Abstract
A growing body of evidence indicates that napping is common among older adults. However, a systematic review on the effect of napping on the elderly is lacking. The aim of this systematic review was to (i) determine how studies evaluated napping behavior in older adults (frequency, duration and timing); (ii) explore how napping impacts perceptual measures, cognitive and psychomotor performance, night-time sleep and physiological parameters in the elderly (PROSPERO CRD42022299805). A total of 738 records were screened by two researchers using the PICOS criteria. Fifteen studies met our inclusion criteria with a mean age ranging from 60.8 to 78.3 years and a cumulative sample size of n = 326. Daytime napping had an overall positive impact on subjective measures (i.e., sleepiness and fatigue), psychomotor performances (i.e., speed and accuracy) and learning abilities (i.e., declarative and motor learning). Additionally, studies showed (i) consistency between nap and control conditions regarding sleep duration, efficiency and latency, and proportion of sleep stages, and (ii) increase of 24 h sleep duration with nap compared to control condition. Based on the findings of the present review, there is minimal evidence to indicate that napping is detrimental for older adults' nighttime sleep. Future studies should consider involving repeated naps during a micro-cycle in order to investigate the chronic effect of napping on older adults.
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Affiliation(s)
- Maher Souabni
- Interdisciplinary Laboratory in Neurosciences, Physiology and Psychology Physical Activity, Health and Learning (LINP2), UFR STAPS (Faculty of Sport Sciences), UPL, Paris Nanterre University, Nanterre, France
| | - Mehdi J. Souabni
- Interdisciplinary Laboratory in Neurosciences, Physiology and Psychology Physical Activity, Health and Learning (LINP2), UFR STAPS (Faculty of Sport Sciences), UPL, Paris Nanterre University, Nanterre, France
| | - Omar Hammouda
- Interdisciplinary Laboratory in Neurosciences, Physiology and Psychology Physical Activity, Health and Learning (LINP2), UFR STAPS (Faculty of Sport Sciences), UPL, Paris Nanterre University, Nanterre, France
- Research Laboratory, Molecular Bases of Human Pathology, LR19ES13, Faculty of Medicine, University of Sfax, Sfax, Tunisia
| | - Mohamed Romdhani
- Physical Activity, Sport and Health, UR18JS01, National Observatory of Sports, Tunis, Tunisia
- Motricité-Interactions-Performance, MIP, UR4334, Le Mans Université, Le Mans, France
| | - Khaled Trabelsi
- High Institute of Sport and Physical Education of Sfax, University of Sfax, Sfax, Tunisia
- Research Laboratory: Education, Motricity, Sport and Health, EM2S, LR19JS01, University of Sfax, Sfax, Tunisia
| | - Achraf Ammar
- Interdisciplinary Laboratory in Neurosciences, Physiology and Psychology Physical Activity, Health and Learning (LINP2), UFR STAPS (Faculty of Sport Sciences), UPL, Paris Nanterre University, Nanterre, France
- High Institute of Sport and Physical Education of Sfax, University of Sfax, Sfax, Tunisia
- Department of Training and Movement Science, Institute of Sport Science, Johannes Gutenberg-University Mainz, Mainz, Germany
- *Correspondence: Achraf Ammar
| | - Tarak Driss
- Interdisciplinary Laboratory in Neurosciences, Physiology and Psychology Physical Activity, Health and Learning (LINP2), UFR STAPS (Faculty of Sport Sciences), UPL, Paris Nanterre University, Nanterre, France
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Huang J, Li M, McPhillips MV, Lukkahatai N, Li J. Association of Sleep and Physical Activity Among Older Adults and the Moderation of Chronotype. Int J Aging Hum Dev 2022; 97:35-51. [PMID: 36217729 DOI: 10.1177/00914150221128974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
This study aimed to examine the associations of both subjectively and objectively measured sleep with physical activity among older adults and to explore the possible moderating role of chronotype in these associations. We included baseline data of 116 community-dwelling older adults without dementia from three prior studies. Pittsburgh Sleep Quality Index and Actigraphy were used as subjective and objective sleep measures, respectively. Physical activity was assessed by the Physical Activity Scale for the Elderly. The Morningness-Eveningness Questionnaire was used to measure chronotype, which was further dichotomized into morning type and non-morning type. Multiple linear regressions were performed to examine the associations, controlling for demographic and health characteristics. We found that better subjective sleep quality, shorter actigraphy sleep duration, and higher actigraphy sleep efficiency were uniquely associated with greater physical activity. Being a morning type might alleviate the adverse association between poor subjective sleep quality and physical activity among older adults.
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Affiliation(s)
- Jing Huang
- School of Nursing, 1466John Hopkins University, Baltimore, MD, USA
| | - Mengchi Li
- School of Nursing, 1466John Hopkins University, Baltimore, MD, USA
| | | | - Nada Lukkahatai
- School of Nursing, 1466John Hopkins University, Baltimore, MD, USA
| | - Junxin Li
- School of Nursing, 1466John Hopkins University, Baltimore, MD, USA
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Hu K, Li W, Zhang Y, Chen H, Bai C, Yang Z, Lorenz T, Liu K, Shirai K, Song J, Zhao Q, Zhao Y, Zhang JJ, Wei J, Pan J, Qi J, Ye T, Zeng Y, Yao Y. Association between outdoor artificial light at night and sleep duration among older adults in China: A cross-sectional study. ENVIRONMENTAL RESEARCH 2022; 212:113343. [PMID: 35461841 DOI: 10.1016/j.envres.2022.113343] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 04/14/2022] [Accepted: 04/18/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND Light after dusk disrupts the circadian rhythms and shifts the timing of sleep later; but it is unknown whether outdoor artificial light at night (ALAN) affects sleep quality. This study aimed to explore the association between residential outdoor ALAN and sleep duration in a nationally representative sample of Chinese older adults. METHODS We examined the cross-sectional associations of outdoor ALAN with self-reported sleep duration in 13,474 older adults participating in the 2017-2018 wave of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Outdoor ALAN exposure was estimated at the residence level using satellite images. We applied generalized linear mixed models to investigate the association between ALAN exposure and sleep duration. We performed stratified analyses by age, sex, education, and household income levels. Moreover, we used multi-level logistic regression models to investigate the effects of ALAN on the short sleep duration (≤6 h) and the long sleep duration (>8 h), respectively, in reference to sleep for >6-8 h per day. RESULTS We found a significant association between outdoor ALAN intensity and sleep duration. The highest quartile of ALAN was associated with 17.04 (95% CI: 9.42-24.78) fewer minutes of sleep as compared to the lowest quartile. The reductions in sleep duration per quartile change in ALAN were greater in the young old (≥65-85 years) and in those with higher levels of education, and those with higher household income, respectively. We did not detect a sex difference. In addition, those in the highest quartile of ALAN were more likely to report a 25% (95% CI: 10%-42%) increase in short sleep (<6 h), and a 21% (95% CI: 9%-31%) decrease in long sleep (>8 h). CONCLUSIONS Increasing outdoor nighttime light intensity surrounding residences was associated with shorter sleep duration in older residents in China. This finding implies the importance of urban outdoor artificial light management as a potential means to lower the public health burden of sleep disorders.
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Affiliation(s)
- Kejia Hu
- Department of Big Data in Health Science, School of Public Health, Zhejiang University, Hangzhou, 310058, China
| | - Wanlu Li
- Department of Big Data in Health Science, School of Public Health, Zhejiang University, Hangzhou, 310058, China
| | - Yunquan Zhang
- School of Public Health, Wuhan University of Science and Technology, Wuhan, 430065, China
| | - Huashuai Chen
- Business School of Xiangtan University, Xiangtan, 411105, China
| | - Chen Bai
- School of Labor and Human Resources, Renmin University of China, Beijing, 100872, China
| | - Zhenchun Yang
- Global Health Institute and the Nicholas School of Environment, Duke University, Durham, 27708, USA
| | - Thiess Lorenz
- Department of Cardiology, University Heart and Vascular Center Hamburg, Hamburg, 20246, Germany
| | - Keyang Liu
- Public Health, Department of Social Medicine, Osaka University Graduate School of Medicine, Suita Shi, Osaka, 565-0871, Japan
| | - Kokoro Shirai
- Public Health, Department of Social Medicine, Osaka University Graduate School of Medicine, Suita Shi, Osaka, 565-0871, Japan
| | - Jinglu Song
- Department of Urban Planning and Design, Xi'an Jiaotong-Liverpool University, Suzhou, 215123, China
| | - Qi Zhao
- Department of Epidemiology, School of Public Health, Shandong University, Jinan, 250012, China
| | - Yali Zhao
- Central Laboratory, Hainan Hospital of Chinese People's Liberation Army General Hospital, Sanya, 572000, China
| | - Junfeng Jim Zhang
- Global Health Institute and the Nicholas School of Environment, Duke University, Durham, 27708, USA
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, 20742, USA
| | - Jiahao Pan
- Department of Big Data in Health Science, School of Public Health, Zhejiang University, Hangzhou, 310058, China
| | - Jin Qi
- Department of Big Data in Health Science, School of Public Health, Zhejiang University, Hangzhou, 310058, China
| | - Tingting Ye
- School of Public Health and Preventive Medicine, Monash University, Melbourne, 3004, Australia
| | - Yi Zeng
- Center for Healthy Aging and Development Studies, National School of Development, Peking University, Beijing, 100871, China.
| | - Yao Yao
- China Center for Health Development Studies, Peking University, Beijing, 100191, China.
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Hussain J, Ling L, Alonzo RT, Rodrigues R, Nicholson K, Stranges S, Anderson KK. Associations between sleep patterns, smoking, and alcohol use among older adults in Canada: Insights from the Canadian Longitudinal Study on Aging (CLSA). Addict Behav 2022; 132:107345. [PMID: 35526407 DOI: 10.1016/j.addbeh.2022.107345] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 02/12/2022] [Accepted: 04/26/2022] [Indexed: 11/29/2022]
Abstract
Poor sleep is associated with chronic health conditions among older adults. As substance use rates increase in this population, age-related physiological and cognitive declines may exacerbate its detrimental consequences, including sleep problems. We analyzed cross-sectional associations between sleep patterns, smoking, and alcohol use using baseline data from 30,097 community-dwelling Canadian adults aged 45-85 years from the Canadian Longitudinal Study on Aging. Insomnia symptoms (difficulties falling/staying asleep), sleep duration (short:<6h; long:>8h), and sleep satisfaction(dissatisfied/neutral/satisfied) were measured. Smoking and alcohol-use frequency (past 12 months), average daily amount (past 30 days), and binge drinking (past 12 months) were self-reported, and associations were examined using modified Poisson regression. Approximately 23% of participants had insomnia symptoms, and 26% reported sleep dissatisfaction. 91% of participants were current non-smokers, whereas 7% reported smoking daily. Over 50% drank ≤ 2 drinks daily, and 3% reported binge drinking. There was a higher adjusted prevalence of insomnia among daily smokers (PR = 1.10, 95% CI = 1.00-1.21) and binge drinkers (PR = 1.21, 95% CI = 1.02-1.43). Odds of short sleep duration were lower among regular drinkers (COR = 0.71, 95% CI = 0.56-0.90) and higher among daily smokers (COR = 1.19, 95% CI = 1.01-1.40). Heavy and frequent smoking and alcohol use are associated with both insomnia symptoms and sleep dissatisfaction, but not consistently with sleep duration. Further longitudinal investigation of this relationship in aging populations is needed in clinical and public health settings to infer the extent of causality and design effective public health interventions in this vulnerable population.
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Affiliation(s)
- Junayd Hussain
- Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada; School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ontario, Canada
| | - Linda Ling
- Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Rea T Alonzo
- Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Rebecca Rodrigues
- Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Kathryn Nicholson
- Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Saverio Stranges
- Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada; Department of Family Medicine, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada; Department of Medicine, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada; Department of Population Health, Luxembourg Institute of Health, Strassen, Luxembourg
| | - Kelly K Anderson
- Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada; Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada; Lawson Health Research Institute, Western University, London, Ontario, Canada.
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De Fazio R, Mattei V, Al-Naami B, De Vittorio M, Visconti P. Methodologies and Wearable Devices to Monitor Biophysical Parameters Related to Sleep Dysfunctions: An Overview. MICROMACHINES 2022; 13:mi13081335. [PMID: 36014257 PMCID: PMC9412310 DOI: 10.3390/mi13081335] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Revised: 08/15/2022] [Accepted: 08/16/2022] [Indexed: 06/13/2023]
Abstract
Sleep is crucial for human health from metabolic, mental, emotional, and social points of view; obtaining good sleep in terms of quality and duration is fundamental for maintaining a good life quality. Over the years, several systems have been proposed in the scientific literature and on the market to derive metrics used to quantify sleep quality as well as detect sleep disturbances and disorders. In this field, wearable systems have an important role in the discreet, accurate, and long-term detection of biophysical markers useful to determine sleep quality. This paper presents the current state-of-the-art wearable systems and software tools for sleep staging and detecting sleep disorders and dysfunctions. At first, the paper discusses sleep's functions and the importance of monitoring sleep to detect eventual sleep disturbance and disorders. Afterward, an overview of prototype and commercial headband-like wearable devices to monitor sleep is presented, both reported in the scientific literature and on the market, allowing unobtrusive and accurate detection of sleep quality markers. Furthermore, a survey of scientific works related the effect of the COVID-19 pandemic on sleep functions, attributable to both infection and lifestyle changes. In addition, a survey of algorithms for sleep staging and detecting sleep disorders is introduced based on an analysis of single or multiple biosignals (EEG-electroencephalography, ECG-electrocardiography, EMG-electromyography, EOG-electrooculography, etc.). Lastly, comparative analyses and insights are provided to determine the future trends related to sleep monitoring systems.
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Affiliation(s)
- Roberto De Fazio
- Department of Innovation Engineering, University of Salento, 73100 Lecce, Italy
| | - Veronica Mattei
- Department of Innovation Engineering, University of Salento, 73100 Lecce, Italy
| | - Bassam Al-Naami
- Department of Biomedical Engineering, Faculty of Engineering, The Hashemite University, Zarqa 13133, Jordan
| | - Massimo De Vittorio
- Department of Innovation Engineering, University of Salento, 73100 Lecce, Italy
- Center for Biomolecular Nanotechnologies, Italian Technology Institute IIT, 73010 Arnesano, Italy
| | - Paolo Visconti
- Department of Innovation Engineering, University of Salento, 73100 Lecce, Italy
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Smith L, Shin JI, Veronese N, Soysal P, López Sánchez GF, Pizzol D, Demurtas J, Tully MA, Barnett Y, Butler L, Koyanagi A. Sleep duration and sarcopenia in adults aged ≥ 65 years from low and middle-income countries. Aging Clin Exp Res 2022; 34:1573-1581. [PMID: 35103953 DOI: 10.1007/s40520-022-02074-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 01/06/2022] [Indexed: 12/13/2022]
Abstract
BACKGROUND Sleep duration may influence risk for sarcopenia but studies on this topic are scarce, especially from low and- middle-income countries (LMICs). Thus, the aim of the present study was to investigate the association between sleep duration and sarcopenia among adults aged ≥ 65 years from five LMICs (China, Ghana, India, Russia, South Africa). METHODS Cross-sectional, community-based data from the WHO study on global ageing and adult health (SAGE) were analysed. Sarcopenia was defined as having low skeletal muscle mass (SMM) and weak handgrip strength, while severe sarcopenia was defined as having low SMM, weak handgrip strength, and slow gait speed. Self-reported sleep duration in the past two nights were averaged and classified as ≤ 6, > 6 to ≤ 9, and ≥ 9 h/day. Multivariable logistic regression analysis was conducted. RESULTS Data on 13,210 adults aged ≥ 65 years [mean (SD) age 72.6 (11.3) years; 55.0% females] were analyzed. In the overall sample, compared to > 6 to ≤ 9 h/day of sleep duration, > 9 h/day was associated with 1.70 (95% CI 1.15-2.51) and 1.75 (95% CI 1.08-2.84) times higher odds for sarcopenia and severe sarcopenia, respectively. No significant associations were observed among males, but associations were particularly pronounced among females [i.e., OR = 2.19 (95% CI 1.26-3.81) for sarcopenia, and OR = 2.26 (95% CI 1.20-4.23) for severe sarcopenia]. CONCLUSIONS Long sleep duration was associated with an increased odds of sarcopenia and severe sarcopenia in LMICs, particularly in females. Future studies should investigate whether addressing long sleep duration among females can lead to lower risk for sarcopenia onset in LMICs.
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Affiliation(s)
- Lee Smith
- Centre for Health, Performand and Wellbeing, Anglia Ruskin University, Cambridge, CB1 1PT, UK
| | - Jae Il Shin
- Department of Pediatrics, Yonsei University College of Medicine, Yonsei-ro 50, Seodaemun-gu, 8044, Seoul, 120-752, Republic of Korea
| | - Nicola Veronese
- Department of Internal Medicine, Geriatrics Section, University of Palermo, Palermo, Italy
| | - Pinar Soysal
- Department of Geriatric Medicine, Faculty of Medicine, Bezmialem Vakif University, Istanbul, Turkey
| | - Guillermo F López Sánchez
- Division of Preventive Medicine and Public Health, Department of Public Health Sciences, School of Medicine, University of Murcia, 30100, Murcia, Espinardo, Spain.
| | - Damiano Pizzol
- Italian Agency for Development Cooperation, Jerusalem, Israel
| | - Jacopo Demurtas
- Clinical and Experimental Medicine PhD Program, University of Modena and Reggio Emilia, Modena, Italy
| | - Mark A Tully
- Institute of Mental Health Sciences, School of Health Sciences, Ulster University, Newtownabbey, BT15 1ED, Northern Ireland
| | - Yvonne Barnett
- Centre for Health, Performand and Wellbeing, Anglia Ruskin University, Cambridge, CB1 1PT, UK
| | - Laurie Butler
- Centre for Health, Performand and Wellbeing, Anglia Ruskin University, Cambridge, CB1 1PT, UK
| | - Ai Koyanagi
- Research and Development Unit, Parc Sanitari Sant Joan de Déu, CIBERSAM, Dr. Antoni Pujadas, 42, Sant Boi de Llobregat, 08830, Barcelona, Spain
- ICREA, Pg, Lluis Companys 23, 08010, Barcelona, Spain
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Bentham C, Eaves L. The Impact of Cognitive-Behavioral Interventions on Sleep Disturbance in Depressed and Anxious Community-dwelling Older Adults: A Systematic Review. Behav Sleep Med 2022; 20:477-499. [PMID: 34120539 DOI: 10.1080/15402002.2021.1933488] [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] [Indexed: 10/21/2022]
Abstract
INTRODUCTION Depression and anxiety are prevalent mental health conditions in older adulthood. Despite sleep disturbance being a common comorbidity in late-life depression and anxiety, it is often discounted as a target for treatment. The current review aims to establish whether cognitive-behavioral therapy (CBT) is effective in treating concomitant sleep disturbance in depressed and anxious older adults and to review evidence supporting whether CBT interventions targeting anxiety and depression, or concurrent sleep disturbance, have the greatest effectiveness in this client group. METHOD A systematic database search was conducted to identify primary research papers evaluating the effectiveness of CBT interventions, recruiting older adults with symptoms of depression and/or anxiety, and employing a validated measure of sleep disturbance. The identified papers were included in a narrative synthesis of the literature. RESULTS Eleven identified studies consistently support reductions in sleep disturbance in elderly participants with depression and anxiety in response to CBT. Most CBT interventions in the review included techniques specifically targeting sleep, and only one study directly compared CBT for insomnia (CBT-I) with a CBT-I intervention also targeting depressive symptoms, limiting the ability of the review to comment on whether interventions targeting sleep disturbance or mental health symptoms have superior effectiveness. CONCLUSION The extant research indicates that CBT interventions are effective in ameliorating sleep disturbance in late-life depression and anxiety. Future high-quality research is required to substantiate this finding and to compare the effectiveness of CBT-I and CBT for depression and anxiety in this group to inform clinical practice.
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Affiliation(s)
| | - Lucy Eaves
- Department of Psychological Services, Sheffield Teaching Hospitals, UK
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de Almondes KM, Castro EDAS, Paiva T. Morbidities Worsening Index to Sleep in the Older Adults During COVID-19: Potential Moderators. Front Psychol 2022; 13:913644. [PMID: 35832914 PMCID: PMC9271867 DOI: 10.3389/fpsyg.2022.913644] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 06/06/2022] [Indexed: 12/02/2022] Open
Abstract
Older adults were considered a vulnerable group for the COVID-19 infection and its consequences, including problems with sleep.
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Affiliation(s)
- Katie Moraes de Almondes
- Department of Psychology and Postgraduate Program in Psychobiology, AMBSONO Sleep Clinic, Onofre Lopes University Hospital, Federal University of Rio Grande do Norte, Natal, Brazil
- *Correspondence: Katie Moraes de Almondes,
| | | | - Teresa Paiva
- CENC –Sleep Medicine Center, Lisbon, Portugal
- ISAMB – Faculdade de Medicina, Universidade de Lisboa, Lisbon, Portugal
- Comprehensive Health Research Center (CHRC), Universidade Nova de Lisboa, Lisbon, Portugal
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Umar A, Khan MS, Sehgal SA, Jafar K, Ahmad S, Waheed A, Aslam MW, Wajid M, Rehman TU, Khan T, Ditta A, Akmal H, Ashfaq M, Javed T, Tahir R. Epidemiological studies of sleep disorder in educational community of Pakistani population, its major risk factors and associated diseases. PLoS One 2022; 17:e0266739. [PMID: 35446890 PMCID: PMC9022811 DOI: 10.1371/journal.pone.0266739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 03/25/2022] [Indexed: 11/18/2022] Open
Abstract
Sleep is one of the most important functions of the life. The disturbance in sleep or quality of sleep leads to several dysfunctions of the human body. This study aimed to investigate the prevalence of sleep disorders, their possible risk factors and their association with other health problems. The data was collected from the educational community of the Pakistani population. The Insomnia Severity Index (ISI) was used to evaluate the insomnia and the sleep apnea was evaluated through a simple questionnaire method. The blood samples were collected to perform significant blood tests for clinical investigations. Current research revealed that the individuals in the educational community had poor sleep quality. A total of 1998 individuals from the educational community were surveyed, 1584 (79.28%) of whom had a sleep disorders, including insomnia (45.20%) and sleep apnea (34.08%). The measured onset of age for males and females was 30.35 years and 31.07 years respectively. The Clinical investigations showed that the sleep had significant impact on the hematology of the patients. Higher levels of serum uric acid and blood sugar were recorded with a sleep disorder. The individuals of the educational community were using the sleeping pills. The other associated diseases were mild tension, headaches, migraines, depression, diabetes, obesity, and myopia. The use of beverage, bad mood, medical condition, mental stress, disturbed circadian rhythms, workload and extra use of smartphone were major risk factors of sleep disorders. It was concluded that the insomnia was more prevalent than the sleep apnea. Furthermore, life changes events were directly linked with disturbance of sleep. Tension, depression, headaches, and migraine were more associated with sleep disorders than all other health issues.
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Affiliation(s)
- Ali Umar
- Department of Zoology, Faculty of Life Sciences, University of Okara, Okara, Pakistan
| | - Muhammad Saleem Khan
- Department of Zoology, Faculty of Life Sciences, University of Okara, Okara, Pakistan
- * E-mail: (MSK); (SAS)
| | - Sheikh Arslan Sehgal
- Department of Bioinformatics, Faculty of Life Sciences, University of Okara, Okara, Pakistan
- * E-mail: (MSK); (SAS)
| | - Kamran Jafar
- Department of Zoology, Faculty of Life Sciences, University of Okara, Okara, Pakistan
| | - Shabbir Ahmad
- Department of Zoology, Faculty of Life Sciences, University of Okara, Okara, Pakistan
| | - Ahmad Waheed
- Department of Zoology, Faculty of Life Sciences, University of Okara, Okara, Pakistan
| | - Muhammad Waseem Aslam
- Department of Zoology, Faculty of Life Sciences, University of Okara, Okara, Pakistan
| | - Muhammad Wajid
- Department of Zoology, Faculty of Life Sciences, University of Okara, Okara, Pakistan
| | - Tanzil Ur Rehman
- Department of Zoology, Faculty of Life Sciences, University of Okara, Okara, Pakistan
| | - Tehmina Khan
- Department of Zoology, Faculty of Life Sciences, University of Okara, Okara, Pakistan
| | - Allah Ditta
- Department of Zoology, Faculty of Life Sciences, University of Okara, Okara, Pakistan
| | - Hasnain Akmal
- Department of Zoology, Faculty of Life Sciences, University of Okara, Okara, Pakistan
| | - Muhammad Ashfaq
- Department of Zoology, Faculty of Life Sciences, University of Okara, Okara, Pakistan
| | - Tariq Javed
- Department of Zoology, Faculty of Life Sciences, University of Okara, Okara, Pakistan
| | - Rida Tahir
- Department of Zoology, Faculty of Life Sciences, University of Okara, Okara, Pakistan
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Cheval B, Maltagliati S, Sieber S, Cullati S, Zou L, Ihle A, Kramer AF, Yu Q, Sander D, Boisgontier MP. Better Subjective Sleep Quality Partly Explains the Association Between Self-Reported Physical Activity and Better Cognitive Function. J Alzheimers Dis 2022; 87:919-931. [DOI: 10.3233/jad-215484] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
Background: Physical activity has been associated with better cognitive function and better sleep quality. Yet, whether the beneficial effect of physical activity on cognitive function can be explained by an indirect pathway involving better sleep quality is unclear. Objective: To investigate whether sleep quality mediates the association between physical activity and cognitive function in adults 50 years of age or older. Methods: 86,541 community-dwelling European adults were included in the study. Physical activity and sleep quality were self-reported. Indicators of cognitive function (immediate recall, delayed recall, verbal fluency) were assessed using objective tests. All measures were collected six times between 2004 and 2017. The mediation was tested using multilevel mediation analyses. Results: Results showed that self-reported physical activity was associated with better self-reported sleep quality, which was associated with better performance in all three indicators of cognitive function, demonstrating an indirect effect of physical activity on cognitive function through sleep quality. The mediating effect of sleep quality accounted for 0.41%, 1.46%, and 8.88% of the total association of physical activity with verbal fluency, immediate recall, and delayed recall, respectively. Conclusion: These findings suggest that self-reported sleep quality partly mediates the association between self-reported physical activity and cognitive function. These results need to be confirmed by device-based data of physical activity and sleep quality.
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Affiliation(s)
- Boris Cheval
- Swiss Center for Affective Sciences, University of Geneva, Switzerland
- Laboratory for the Study of Emotion Elicitation and Expression (E3Lab), Department of Psychology, University of Geneva, Switzerland
| | | | - Stefan Sieber
- Swiss NCCR “LIVES – Overcoming Vulnerability: Life Course Perspectives”, University of Geneva, Switzerland
- Center for the Interdisciplinary Study of Gerontology and Vulnerability, University of Geneva, Switzerland
| | - Stéphane Cullati
- Population Health Laboratory, University of Fribourg, Switzerland
- Department of Readaptation and Geriatrics, University of Geneva, Switzerland
| | - Liye Zou
- Institute of KEEP Collaborative Innovation, Shenzhen University, China
- Exercise Psychophysiology Laboratory, School of Psychology, Shenzhen University, China
| | - Andreas Ihle
- Swiss NCCR “LIVES – Overcoming Vulnerability: Life Course Perspectives”, University of Geneva, Switzerland
- Center for the Interdisciplinary Study of Gerontology and Vulnerability, University of Geneva, Switzerland
- Cognitive Aging Lab, Department of Psychology, University of Geneva, Geneva, Switzerland
| | - Arthur F. Kramer
- Center for Cognitive and Brain Health, Department of Psychology, Northeastern University, Boston, MA, USA
- Beckman Institute, University of Illinois at Urbana-Champaign, Champaign, IL, USA
| | - Qian Yu
- Institute of KEEP Collaborative Innovation, Shenzhen University, China
- Exercise Psychophysiology Laboratory, School of Psychology, Shenzhen University, China
| | - David Sander
- Swiss Center for Affective Sciences, University of Geneva, Switzerland
- Laboratory for the Study of Emotion Elicitation and Expression (E3Lab), Department of Psychology, University of Geneva, Switzerland
| | - Matthieu P. Boisgontier
- School of Rehabilitation Sciences, Faculty of Health Sciences, University of Ottawa, Canada
- Bruyère Research Institute, Ottawa, Canada
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Brouwer A, van de Ven PM, Kok A, Snoek FJ, Beekman ATF, Bremmer MA. Symptoms of depression and insomnia in older age: A within-individual analysis over 20 years. J Am Geriatr Soc 2022; 70:2051-2059. [PMID: 35383906 PMCID: PMC9541249 DOI: 10.1111/jgs.17765] [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: 02/14/2021] [Revised: 02/17/2022] [Accepted: 02/24/2022] [Indexed: 11/29/2022]
Abstract
Background Depression and insomnia often co‐occur, and precede one another. Possibly, insomnia gives rise to depression, and vice versa. We tested whether insomnia symptoms of an older individual are associated with later depressive symptoms in that older individual, and vice versa. Methods We performed a longitudinal analysis of data from a prospective cohort study in a large sample of community‐dwelling older people (N = 3081), with measurements every three years, over a time period of 20 years. The within‐individual longitudinal reciprocal relationship between symptoms of depression (Center for Epidemiological Studies Depression Scale), and symptoms of insomnia (three‐item questionnaire, including difficulty initiating sleep, nightly awakenings, and early morning awakening) was modeled by means of a bivariate linear growth model. We tested whether symptoms of insomnia were associated with symptoms of depression three years later, and vice versa. Results Severity of symptoms of depression and insomnia and their within‐individual average change over time were moderately correlated (correlation of intercepts: rho 0.41, 95% CI: 0.36 to 0.46 p < 0.001; correlation of slopes: rho 0.39, 95% CI: 0.25 to 0.52, p < 0.001). Symptoms of depression were not found to be associated with an additional risk of higher symptoms of insomnia three years later, and vice versa (p = 0.329 and p = 0.919, respectively). Similar results were found when analyses were corrected for covariates. Conclusions In older individuals, depression and insomnia are associated and tend to increase concurrently over time, but constitute no additional risk for one another over repeated three‐year intervals. These findings contradict previous research that suggests that depression and insomnia are risk factors for one another over time. The current study stands out due to the longitudinal within‐individual statistical approach, but is limited by the three‐year interval between measures.
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Affiliation(s)
- Annelies Brouwer
- Amsterdam UMC, Vrije Universiteit, Department of Psychiatry, Amsterdam Public Health research institute, Amsterdam, the Netherlands.,Department of Research and Innovation, GGZ inGeest Specialized Mental Health Care, Amsterdam, the Netherlands
| | - Peter M van de Ven
- Amsterdam UMC, Vrije Universiteit, Department of Epidemiology and Biostatistics, Amsterdam Public Health research institute, Amsterdam, the Netherlands
| | - Almar Kok
- Amsterdam UMC, Vrije Universiteit, Department of Epidemiology and Biostatistics, Amsterdam Public Health research institute, Amsterdam, the Netherlands.,Department of Sociology, VU University, Amsterdam, the Netherlands
| | - Frank J Snoek
- Amsterdam UMC, Vrije Universiteit and University of Amsterdam, Department of Medical Psychology, Amsterdam Public Health research institute, Amsterdam, the Netherlands
| | - Aartjan T F Beekman
- Amsterdam UMC, Vrije Universiteit, Department of Psychiatry, Amsterdam Public Health research institute, Amsterdam, the Netherlands.,Department of Research and Innovation, GGZ inGeest Specialized Mental Health Care, Amsterdam, the Netherlands
| | - Marijke A Bremmer
- Amsterdam UMC, Vrije Universiteit, Department of Psychiatry, Amsterdam Public Health research institute, Amsterdam, the Netherlands
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Lustenberger C, Ferster ML, Huwiler S, Brogli L, Werth E, Huber R, Karlen W. Auditory deep sleep stimulation in older adults at home: a randomized crossover trial. COMMUNICATIONS MEDICINE 2022; 2:30. [PMID: 35603302 PMCID: PMC9053232 DOI: 10.1038/s43856-022-00096-6] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 03/07/2022] [Indexed: 11/13/2022] Open
Abstract
Background Auditory stimulation has emerged as a promising tool to enhance non-invasively sleep slow waves, deep sleep brain oscillations that are tightly linked to sleep restoration and are diminished with age. While auditory stimulation showed a beneficial effect in lab-based studies, it remains unclear whether this stimulation approach could translate to real-life settings. Methods We present a fully remote, randomized, cross-over trial in healthy adults aged 62-78 years (clinicaltrials.gov: NCT03420677). We assessed slow wave activity as the primary outcome and sleep architecture and daily functions, e.g., vigilance and mood as secondary outcomes, after a two-week mobile auditory slow wave stimulation period and a two-week Sham period, interleaved with a two-week washout period. Participants were randomized in terms of which intervention condition will take place first using a blocked design to guarantee balance. Participants and experimenters performing the assessments were blinded to the condition. Results Out of 33 enrolled and screened participants, we report data of 16 participants that received identical intervention. We demonstrate a robust and significant enhancement of slow wave activity on the group-level based on two different auditory stimulation approaches with minor effects on sleep architecture and daily functions. We further highlight the existence of pronounced inter- and intra-individual differences in the slow wave response to auditory stimulation and establish predictions thereof. Conclusions While slow wave enhancement in healthy older adults is possible in fully remote settings, pronounced inter-individual differences in the response to auditory stimulation exist. Novel personalization solutions are needed to address these differences and our findings will guide future designs to effectively deliver auditory sleep stimulations using wearable technology.
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Affiliation(s)
- Caroline Lustenberger
- Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- Neuroscience Center Zurich (ZNZ), University of Zurich and ETH Zurich, Zurich, Switzerland
- Center of Competence Sleep & Health Zurich, University of Zurich, Zurich, Switzerland
| | - M. Laura Ferster
- Mobile Health Systems Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Stephanie Huwiler
- Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Luzius Brogli
- Mobile Health Systems Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- Institute of Biomedical Engineering, Universität Ulm, Ulm, Germany
| | - Esther Werth
- Neuroscience Center Zurich (ZNZ), University of Zurich and ETH Zurich, Zurich, Switzerland
- Center of Competence Sleep & Health Zurich, University of Zurich, Zurich, Switzerland
- Department of Neurology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Reto Huber
- Neuroscience Center Zurich (ZNZ), University of Zurich and ETH Zurich, Zurich, Switzerland
- Center of Competence Sleep & Health Zurich, University of Zurich, Zurich, Switzerland
- Child Development Centre, University Children’s Hospital, University of Zurich, Zurich, Switzerland
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Walter Karlen
- Center of Competence Sleep & Health Zurich, University of Zurich, Zurich, Switzerland
- Mobile Health Systems Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- Institute of Biomedical Engineering, Universität Ulm, Ulm, Germany
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Grandner MA. Sleep, Health, and Society. Sleep Med Clin 2022; 17:117-139. [DOI: 10.1016/j.jsmc.2022.03.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Sella E, Toffalini E, Canini L, Borella E. Non-pharmacological interventions targeting sleep quality in older adults: a systematic review and meta-analysis. Aging Ment Health 2022; 27:847-861. [PMID: 35352595 DOI: 10.1080/13607863.2022.2056879] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Abstract
Objectives: This review aimed to examine the available evidence about non-pharmacological interventions (NPIs) aimed at improving sleep quality in older adults without insomnia or dementia.Methods: Studies on NPIs targeting older adults' sleep were searched in the PsycInfo, PubMed and Scopus databases, with no restriction on publication year up to September 2021. Studies on NPIs for older adults with no diagnosed sleep disorders were included, while those on pharmacological therapies and/or concerning pathological samples were excluded. The risk of bias was assessed using tools based on Joanna Briggs' criteria. The data extracted were meta-analyzed using random effects models for subgroups of NPIs.Results: Of the 1,893 records identified, 31 studies on NPIs (N = 2,224; range of mean ages: 60-78 years) were analyzed. All NPIs improved self-reported sleep quality, albeit to a different extent (physical activity: d=.97 - 95% CI=.62, 1.32-; psychological/psychoeducational, or NPIs that combined more than one sleep-targeting activity: d range: .21 to .97). Only the NPIs based on physical activity improved objectively-measured sleep, d=.31 (.04, .57). The methodological quality of most studies was limited.Conclusion: The most often used NPIs targeting sleep rely on physical activity and sensory stimulation with promising results on sleep quality for the former. More data are needed on psychological/psychoeducational NPIs and combined interventions in order to test their effectiveness. The methodological weaknesses of the available studies suggest they their findings should be interpreted with caution.
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Affiliation(s)
- Enrico Sella
- Department of General Psychology, University of Padova, Padova, Italy
| | - Enrico Toffalini
- Department of General Psychology, University of Padova, Padova, Italy
| | - Luca Canini
- Department of General Psychology, University of Padova, Padova, Italy
| | - Erika Borella
- Department of General Psychology, University of Padova, Padova, Italy
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Bakhshandeh Bavarsad M, Foroughan M, Zanjari N, Ghaedamini Harouni G, Jorjoran Shushtari Z. Development and validation of the geriatrics health behavior questionnaire (GHBQ). BMC Public Health 2022; 22:526. [PMID: 35300652 PMCID: PMC8932145 DOI: 10.1186/s12889-022-12927-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Accepted: 03/07/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Considering the importance of health behaviors in health outcomes, it is necessary to assess health behaviors precisely. This study aimed to develop and validate The Geriatrics Health Behavior Questionnaire among Iranian older adults. METHODS This cross-sectional and methodological study was conducted on 420 community older adults (age ≥ 60) through random multi-stage sampling. The initial questionnaire has been developed with 22 items and seven subscales based on an extensive literature review, evaluation of related questionnaires, and experts' opinions. Face and content validity were evaluated by interviewing 10 older adults and 18 specialists. The construct validity was evaluated via Known-groups validity and convergent validity. The reliability of the questionnaire was calculated by internal consistency, test-retest, and absolute reliability. RESULTS The face validity was conducted by using interviews with older adults and gathering the specialists' opinions. The items were grammatically and lexically corrected accordingly. Two items were deleted due to CVR < 0.44. Modified Kappa statistic (K*) and I-CVI for all items were higher than 0.88. The average content validity index (S-CVI/Ave) value was 0.94. Three items were deleted to improve the internal consistency; the final GHBQ consisted of 17 items with Cronbach α = 0.72. Acceptable convergent validity was approved by a significant correlation between GHBQ and SF8™ health survey (r = 0.613, P value< 0.001). Independent t-test showed that older adults with education level ≥ high school have significantly higher health behavior scores than those with education level < high school (11.93 ± 2.27 vs. 9.87 ± 2.35, t = - 9.08, p < 0.001). Intra-class correlation coefficient (ICC) for the total questionnaire was 0.92 (95% CI =0.84 to 0.96). Standard Error Measurement (SEM) and Minimal Detectable Change (MDC95) were 0.71 and 1.98, respectively. CONCLUSION The present study results showed that the Geriatrics Health Behavior Questionnaire had suitable validity and reliability among Iranian older adults. It is recommended to consider its comprehensiveness and yet its briefness in other populations after passing validation.
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Affiliation(s)
- Maryam Bakhshandeh Bavarsad
- Iranian Research Center on Aging, Department of Aging, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | - Mahshid Foroughan
- Iranian Research Center on Aging, Department of Aging, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran.
| | - Nasibeh Zanjari
- Iranian Research Center on Aging, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
| | | | - Zahra Jorjoran Shushtari
- Ph.D., Social Determinants of Health Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
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The effects of a real-life lifestyle program on physical activity and objective and subjective sleep in adults aged 55+ years. BMC Public Health 2022; 22:353. [PMID: 35183133 PMCID: PMC8857863 DOI: 10.1186/s12889-022-12780-2] [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: 05/21/2021] [Accepted: 02/15/2022] [Indexed: 11/13/2022] Open
Abstract
Study objectives Age related changes in sleep result in an increasing prevalence of poor sleep in mid-aged and older adults. Although physical activity has shown to benefit sleep in studies in controlled settings, this has not yet been examined in a real-life lifestyle program. The aims of this study were to: 1) examine the effects of a lifestyle program on moderate-to-vigorous physical activity and objective and subjective sleep in adults aged 55+ years; and 2) examine if the effects differed between good and poor sleepers. Methods This controlled pretest-posttest trial examined the effects of the 12-week group-based real-life lifestyle program ‘Lekker Actief’ on moderate-to-vigorous physical activity (measured using accelerometers) and sleep (measured using accelerometers and the Pittsburgh Sleep quality Index, PSQI). The main component of the program was a 12-week progressive walking program, complemented by an optional muscle strengthening program and one educational session on healthy nutrition. Of the 451 participants who were tested pre-intervention, 357 participants completed the posttest assessment (200 in the intervention group and 157 in the control group). Effects on moderate-to-vigorous physical activity and on objective sleep (sleep efficiency, total sleep time, wake time after sleep onset (WASO) and number of awakenings) as well as subjective sleep (sleep quality) were examined in crude and in adjusted multiple regression models. An interaction term between program (control versus intervention) and sleep category (good and poor) was included in all models. Results Moderate-to-vigorous physical activity levels significantly increased in the intervention group compared with the control group (43,02 min per day; 95%CI: 12.83–73.22; fully adjusted model). The interaction terms revealed no differences between good and poor sleepers regarding the effect of the intervention on moderate-to-vigorous physical activity. There were no significant effects on sleep, except for good sleepers who showed an increase in number of awakenings/night by 1.44 (CI 95% 0.49; 2.24). Conclusions Although this program was effective in increasing physical activity, it did not improve sleep. Lifestyle programs should be promoted to increase physical activity, but more is needed to improve sleep as well. This trial was registered at ClinicalTrials.gov (Trial registration NCT03576209).
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Sun-Suslow N, Balon E, Montoya JL, Saloner R, Campbell LM, Serrano V, Ellis RJ, Moore DJ. Frailty Syndrome Is Associated with Poorer Self-Reported Sleep Quality Among Older Persons with Human Immunodeficiency Virus. AIDS Res Hum Retroviruses 2022; 38:87-96. [PMID: 34779233 PMCID: PMC8861916 DOI: 10.1089/aid.2020.0158] [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] [Indexed: 02/03/2023] Open
Abstract
Older people with HIV (PWH) experience heightened risk for the acquisition of cumulative, multisystem decline, that is, frailty syndrome. Frailty relates to poorer sleep quality in the general older adult population; however, this association has yet to be explored among PWH. A cross-sectional analysis of 285 PWH ≥50 years of age (mean age 60.5 ± 7.0) examined the relationship between frailty (Fried frailty phenotype) and self-reported sleep quality [Pittsburgh Sleep Quality Index (PSQI)]. Three separate multivariable linear regression models examined global PSQI as a function of (1) frailty phenotype, (2) total number of frailty symptoms, or (3) specific individual frailty symptoms. Models covaried for demographic and biopsychosocial risk factors, including age, sex, race/ethnicity, education, premorbid verbal IQ estimate, current depressive symptoms, and diagnosis of a substance abuse disorder. Compared to nonfrail (B = 0.151; p = .021) and prefrail (B = 0.144; p = .021), frail phenotype was related to poorer sleep quality (increased global PSQI; F(5,278) = 11.34, p < .001; R2 = 0.17). Increased number of frailty symptoms (B = 0.144; p = .019; F(4,276) = 12.719, p < .001; R2 = 0.16) and exhaustion was associated with increased global PSQI scores (B = 0.218, p < .001; F(6,247) = 10.436, p < .001; R2 = 0.19). In all models, older age, female sex, and elevated current depressive symptoms were associated with poorer sleep quality. In older PWH, greater frailty symptoms related to poorer sleep quality, independent of psychosocial risk factors for poor sleep. Frailty and poor sleep individually have adverse effects on health and everyday functioning; thus, establishing this association may better aid providers to screen for and treat problems with sleep quality and/or frailty among PWH.
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Affiliation(s)
- Ni Sun-Suslow
- Department of Psychiatry, University of California San Diego, San Diego, California, USA
| | - Emily Balon
- University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Jessica L. Montoya
- Department of Psychiatry, University of California San Diego, San Diego, California, USA
| | - Rowan Saloner
- San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, California, USA
| | - Laura M. Campbell
- San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, California, USA
| | - Vanessa Serrano
- San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, California, USA
| | - Ronald J. Ellis
- University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - David J. Moore
- University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
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Zhang D, Lin Z, Chen F, Li S. What Could Interfere with a Good Night's Sleep? The Risks of Social Isolation, Poor Physical and Psychological Health among Older Adults in China. Res Aging 2022; 44:519-530. [PMID: 34991389 DOI: 10.1177/01640275211065103] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
This study provides one of the first population-based investigations of the longitudinal association between social isolation and sleep difficulty among older adults in China. We analyzed three waves of longitudinal data from the China Longitudinal Aging Social Survey (2014-2018), in which 8456 respondents contributed 16,156 person-year observations. Results from multilevel logistic regression models showed that social isolation was related to a higher risk of sleep difficulty. We also found that socially isolated older adults were more likely to report higher levels of depressive symptoms, a greater prevalence of loneliness and pain, and more chronic diseases compared to their socially integrated counterparts, which in turn increased their risks of sleep difficulty. Moreover, socially isolated older adults with chronic diseases were particularly vulnerable to the risk of sleep difficulty. These findings provide helpful guidance for policymakers and practitioners to design effective intervention strategies to help older adults with sleep problems.
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Affiliation(s)
- Dan Zhang
- School of Public Policy and Administration, Institute for Population and Development Studies, 12480Xi'an Jiaotong University, Xi'an, China
| | - Zhiyong Lin
- Center on Aging and Population Sciences and Population Research Center, 12330The University of Texas at Austin, Austin, TX, USA
| | - Feinian Chen
- Department of Sociology and Maryland Population Research Center, 1068University of Maryland, College Park, MD, USA
| | - Shuzhuo Li
- School of Public Policy and Administration, Institute for Population and Development Studies, 12480Xi'an Jiaotong University, Xi'an, China
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Cardinali DP, Brown GM, Pandi-Perumal SR. Melatonin's Benefits and Risks as a Therapy for Sleep Disturbances in the Elderly: Current Insights. Nat Sci Sleep 2022; 14:1843-1855. [PMID: 36267165 PMCID: PMC9578490 DOI: 10.2147/nss.s380465] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 10/03/2022] [Indexed: 01/19/2023] Open
Abstract
Aging is accompanied by circadian changes, including disruptive alterations in the sleep/wake cycle, as well as the beginning of low-degree inflammation ("inflammaging"), a scenario that leads to several chronic illnesses, including cancer, and metabolic, cardiovascular, and neurological dysfunctions. As a result, any effective approach to healthy aging must consider both the correction of circadian disturbance and the control of low-grade inflammation. One of the most important prerequisites for healthy aging is the preservation of robust circadian rhythmicity (particularly of the sleep/wake cycle). Sleep disturbance disrupts various activities in the central nervous system, including waste molecule elimination. Melatonin is a chemical with extraordinary phylogenetic conservation found in all known aerobic creatures whose alteration plays an important role in sleep changes with aging. Every day, the late afternoon/nocturnal surge in pineal melatonin helps to synchronize both the central circadian pacemaker found in the hypothalamic suprachiasmatic nuclei (SCN) and a plethora of peripheral cellular circadian clocks. Melatonin is an example of an endogenous chronobiotic substance that can influence the timing and amplitude of circadian rhythms. Moreover, melatonin is also an excellent anti-inflammatory agent, buffering free radicals, down-regulating proinflammatory cytokines, and reducing insulin resistance, among other things. We present both scientific and clinical evidence that melatonin is a safe drug for treating sleep disturbances in the elderly.
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Affiliation(s)
- Daniel P Cardinali
- Faculty of Medical Sciences, Pontificia Universidad Católica Argentina, Buenos Aires, Argentina
| | - Gregory M Brown
- Molecular Brain Science Research Department, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
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Basta M, Vgontzas AN, Fernandez-Mendoza J, Antypa D, Li Y, Zaganas I, Panagiotakis S, Karagkouni E, Simos P. Basal Cortisol Levels Are Increased in Patients with Mild Cognitive Impairment: Role of Insomnia and Short Sleep Duration. J Alzheimers Dis 2022; 87:933-944. [PMID: 35404277 DOI: 10.3233/jad-215523] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
BACKGROUND Mild cognitive impairment (MCI) is frequent in elderly and a risk factor for dementia. Both insomnia and increased cortisol levels are risk factors for MCI. OBJECTIVE We examined cross-sectionally whether increased cortisol levels are associated with short sleep duration (SSD) and/or the insomnia short sleep duration (ISS) phenotype, in elderly with MCI. METHODS One hundred twenty-four participants with MCI and 84 cognitively non-impaired controls (CNI)≥60 years underwent medical history, physical examination, neuropsychiatric evaluation, neuropsychological testing, 3-day actigraphy, assessment of subjective insomnia symptoms, and a single morning plasma cortisol level. The short sleep phenotypes were defined by sleep efficiency below the median of the entire sample (i.e.,≤81%) with at least one insomnia symptom (ISS) or without (SSD). ANOVA models were used to compare the various sleep phenotypes to those who did not present either short sleep or insomnia symptoms [non-insomnia (NI)]. RESULTS MCI participants had higher cortisol levels compared to the CNI group (p = 0.009). MCI participants with insomnia (n = 44) or SSD (n = 38) had higher cortisol levels compared to the NI group (n = 42; p = 0.014 and p = 0.045, respectively). Furthermore, MCI participants with ISS phenotype but not those with insomnia with normal sleep duration had higher cortisol levels compared to NI (p = 0.011 and p = 0.4, respectively). Both linear trend analyses showed that cortisol reached the highest levels in the ISS phenotype. CONCLUSION The ISS and SSD phenotypes are associated with increased cortisol levels in elderly with MCI. Improving sleep quality and duration and decreasing cortisol levels may delay further cognitive decline.
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Affiliation(s)
- Maria Basta
- Department of Psychiatry, University Hospital of Heraklion, Heraklion, Crete, Greece
- Sleep Research and Treatment Center, Department of Psychiatry, Penn State University, Hershey, PA, USA
| | - Alexandros N Vgontzas
- Department of Psychiatry, University Hospital of Heraklion, Heraklion, Crete, Greece
- Sleep Research and Treatment Center, Department of Psychiatry, Penn State University, Hershey, PA, USA
| | - Julio Fernandez-Mendoza
- Sleep Research and Treatment Center, Department of Psychiatry, Penn State University, Hershey, PA, USA
| | - Despina Antypa
- Department of Psychiatry, University Hospital of Heraklion, Heraklion, Crete, Greece
| | - Yun Li
- Department of Sleep Medicine, Mental Health Center of Shantou University, Shantou, Guangdong, China
- Sleep Medicine Center, Shantou University Medical College, Shantou, Guangdong, China
| | - Ioannis Zaganas
- Department of Neurology, University Hospital of Heraklion, Heraklion, Crete, Greece
| | - Symeon Panagiotakis
- Department of Internal Medicine, University Hospital of Heraklion, Heraklion, Crete, Greece
| | - Efthalia Karagkouni
- Sleep Research and Treatment Center, Department of Psychiatry, Penn State University, Hershey, PA, USA
| | - Panagiotis Simos
- Department of Psychiatry, University Hospital of Heraklion, Heraklion, Crete, Greece
- Computational Biomedicine Laboratory, Institute of Computer Science, Foundation for Research and Technology-Hellas, Greece
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49
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Wang C, Zhang Z, Zheng Z, Chen X, Zhang Y, Li C, Chen H, Liao H, Zhu J, Lin J, Liang H, Yu Q, Chen R, Liang J. Relationship between obstructive sleep apnea-hypopnea syndrome and osteoporosis adults: A systematic review and meta-analysis. Front Endocrinol (Lausanne) 2022; 13:1013771. [PMID: 36465605 PMCID: PMC9712780 DOI: 10.3389/fendo.2022.1013771] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/07/2022] [Accepted: 10/26/2022] [Indexed: 11/19/2022] Open
Abstract
OBJECTIVE This study is undertaken to explore the relationship between obstructive sleep apnea-hypopnea syndrome (OSAHS) and osteoporosis, including the relationship between OSAHS and osteoporosis incidence, lumbar spine bone mineral density (BMD), and lumbar spine T-score. METHOD Cochrane Library, PubMed, Embase, Web of Science, and other databases are searched from their establishment to April 2022. Literature published in 4 databases on the correlation between OSAHS and osteoporosis,lumbar spine BMD,lumbar spine T-score is collected. Review Manager 5.4 software is used for meta-analysis. RESULTS A total of 15 articles are selected, including 113082 subjects. Compared with the control group, the OSAHS group has a higher incidence of osteoporosis (OR = 2.03, 95% CI: 1.26~3.27, Z = 2.90, P = 0.004), the lumbar spine BMD is significantly lower (MD = -0.05, 95% CI: -0.08~-0.02, Z = 3.07, P = 0.002), and the lumbar spine T-score is significantly decreased (MD = -0.47, 95% CI: -0.79~-0.14, Z = 2.83, P = 0. 005). CONCLUSION Compared with the control group, the OSAHS group has a higher incidence of osteoporosis and decreased lumbar spine BMD and T-score. In order to reduce the risk of osteoporosis, attention should be paid to the treatment and management of adult OSAHS, and active sleep intervention should be carried out.
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Affiliation(s)
- Chaoyu Wang
- Department of Pulmonary and Critical Care Medicine, The Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China
- Department of Pulmonary and Critical Care Medicine, Taishan Hospital of Traditional Chinese Medicine, Jiangmen, Guangdong, China
| | - Zhiping Zhang
- Department of Pulmonary and Critical Care Medicine, The People's Hospital of JiangMen (Jiangmen Hospital, Southern Medical University), Jiangmen, China
| | - Zhenzhen Zheng
- Department of Pulmonary and Critical Care Medicine, The Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China
| | - Xiaojuan Chen
- Medical College, Jiaying University, Meizhou, Guangdong, China
| | - Yu Zhang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Chunhe Li
- Department of Critical Care Medicine, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China
| | - Huimin Chen
- Department of Traditional Chinese Medicine, The Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China
| | - Huizhao Liao
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Jinru Zhu
- Department of Pulmonary and Critical Care Medicine, The Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China
| | - Junyan Lin
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Hongwei Liang
- Department of Pulmonary and Critical Care Medicine, The People's Hospital of JiangMen (Jiangmen Hospital, Southern Medical University), Jiangmen, China
| | - Qiuying Yu
- Department of Pulmonary and Critical Care Medicine, Taishan Hospital of Traditional Chinese Medicine, Jiangmen, Guangdong, China
- *Correspondence: Qiuying Yu, ; Riken Chen, ; Jinhua Liang,
| | - Riken Chen
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
- *Correspondence: Qiuying Yu, ; Riken Chen, ; Jinhua Liang,
| | - Jinhua Liang
- Department of Endocrinology, The Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, China
- *Correspondence: Qiuying Yu, ; Riken Chen, ; Jinhua Liang,
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50
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Kim JH, Song JH, Wee JH, Lee JW, Choi HG. Depressive Symptoms, Subjective Cognitive Decline, and Subjective Sleep Quality Are Associated with Slips and Falls: Data from the Community Health Survey in Korean Adults. Gerontology 2021; 68:518-528. [DOI: 10.1159/000518007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 06/19/2021] [Indexed: 11/19/2022] Open
Abstract
<b><i>Background:</i></b> Identifying the risk factors for falls among the elderly population is arguably one of the most imperative public health issues in the current aging society. <b><i>Objectives:</i></b> This study aimed to determine the associations between depressive symptoms, subjective cognitive decline (SCD), and poor subjective sleep quality and the risk of slips/falls in a Korean older population. <b><i>Methods:</i></b> This cross-sectional study involved 228,340 elderly individuals living in Korea. Measurements included self-reported depressive symptoms, SCD, and self-reported sleep quality. The risk of slips/falls was dichotomized depending on whether slips/falls had occurred during the past year, and the associations between different risk factors and slips/falls were explored. Multiple logistic regression was used to obtain the odds ratios (ORs) and 95% confidence intervals (CIs). Complex sampling methods were used to estimate the weighted value of each participant. <b><i>Results:</i></b> The risk of slips/falls was significantly associated with high levels of depressive symptoms (adjusted OR 1.06, 95% CI: 1.05–1.07) and SCD (adjusted OR 1.33, 95% CI: 1.19–1.50). Regarding each sleep quality component, the adjusted ORs for slips/falls were 1.85 for very poor sleep quality, 1.49 for long sleep latency, 1.04 for <5 h of sleep duration, 1.32 for low sleep efficiency, 2.78 for high sleep disturbance, 1.52 for the use of sleep medication ≥3 times a week, and 1.82 for high daytime dysfunction due to sleep problems compared to the respective good sleep conditions. <b><i>Conclusions:</i></b> Our results demonstrated that depressive symptoms, SCD, and poor subjective sleep quality are independent factors affecting the occurrence of slips/falls. Thus, efforts to manage depressive symptoms and cognitive decline early and to improve sleep quality can be an alternative strategy to decrease the likelihood of falls.
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