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Nawrin SS, Inada H, Momma H, Nagatomi R. Twenty-four-hour physical activity patterns associated with depressive symptoms: a cross-sectional study using big data-machine learning approach. BMC Public Health 2024; 24:1254. [PMID: 38714982 PMCID: PMC11075341 DOI: 10.1186/s12889-024-18759-5] [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: 02/02/2024] [Accepted: 05/02/2024] [Indexed: 05/12/2024] Open
Abstract
BACKGROUND Depression is a global burden with profound personal and economic consequences. Previous studies have reported that the amount of physical activity is associated with depression. However, the relationship between the temporal patterns of physical activity and depressive symptoms is poorly understood. In this exploratory study, we hypothesize that a particular temporal pattern of daily physical activity could be associated with depressive symptoms and might be a better marker than the total amount of physical activity. METHODS To address the hypothesis, we investigated the association between depressive symptoms and daily dominant activity behaviors based on 24-h temporal patterns of physical activity. We conducted a cross-sectional study on NHANES 2011-2012 data collected from the noninstitutionalized civilian resident population of the United States. The number of participants that had the whole set of physical activity data collected by the accelerometer is 6613. Among 6613 participants, 4242 participants had complete demography and Patient Health Questionnaire-9 (PHQ-9) questionnaire, a tool to quantify depressive symptoms. The association between activity-count behaviors and depressive symptoms was analyzed using multivariable logistic regression to adjust for confounding factors in sequential models. RESULTS We identified four physical activity-count behaviors based on five physical activity-counting patterns classified by unsupervised machine learning. Regarding PHQ-9 scores, we found that evening dominant behavior was positively associated with depressive symptoms compared to morning dominant behavior as the control group. CONCLUSIONS Our results might contribute to monitoring and identifying individuals with latent depressive symptoms, emphasizing the importance of nuanced activity patterns and their probability of assessing depressive symptoms effectively.
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Affiliation(s)
- Saida Salima Nawrin
- Laboratory of Health and Sports Sciences, Tohoku University Graduate School of Biomedical Engineering, Sendai, Miyagi, Japan
| | - Hitoshi Inada
- Laboratory of Health and Sports Sciences, Tohoku University Graduate School of Biomedical Engineering, Sendai, Miyagi, Japan.
- Present Address: Department of Biochemistry & Cellular Biology, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan.
| | - Haruki Momma
- Department of Medicine and Science in Sports and Exercise, Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan
| | - Ryoichi Nagatomi
- Laboratory of Health and Sports Sciences, Tohoku University Graduate School of Biomedical Engineering, Sendai, Miyagi, Japan.
- Department of Medicine and Science in Sports and Exercise, Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan.
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Yeung CHC, Lu J, Soltero EG, Bauer C, Xiao Q. U.S. Adolescent Rest-Activity patterns: insights from functional principal component analysis (NHANES 2011-2014). Int J Behav Nutr Phys Act 2023; 20:125. [PMID: 37833691 PMCID: PMC10571346 DOI: 10.1186/s12966-023-01520-3] [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: 06/05/2023] [Accepted: 09/26/2023] [Indexed: 10/15/2023] Open
Abstract
BACKGROUND Suboptimal rest-activity patterns in adolescence are associated with worse health outcomes in adulthood. Understanding sociodemographic factors associated with rest-activity rhythms may help identify subgroups who may benefit from interventions. This study aimed to investigate the association of rest-activity rhythm with demographic and socioeconomic characteristics in adolescents. METHODS Using cross-sectional data from the nationally representative National Health and Nutrition Examination Survey (NHANES) 2011-2014 adolescents (N = 1814), this study derived rest-activity profiles from 7-day 24-hour accelerometer data using functional principal component analysis. Multiple linear regression was used to assess the association between participant characteristics and rest-activity profiles. Weekday and weekend specific analyses were performed in addition to the overall analysis. RESULTS Four rest-activity rhythm profiles were identified, which explained a total of 82.7% of variance in the study sample, including (1) High amplitude profile; (2) Early activity window profile; (3) Early activity peak profile; and (4) Prolonged activity/reduced rest window profile. The rest-activity profiles were associated with subgroups of age, sex, race/ethnicity, and household income. On average, older age was associated with a lower value for the high amplitude and early activity window profiles, but a higher value for the early activity peak and prolonged activity/reduced rest window profiles. Compared to boys, girls had a higher value for the prolonged activity/reduced rest window profiles. When compared to Non-Hispanic White adolescents, Asian showed a lower value for the high amplitude profile, Mexican American group showed a higher value for the early activity window profile, and the Non-Hispanic Black group showed a higher value for the prolonged activity/reduced rest window profiles. Adolescents reported the lowest household income had the lowest average value for the early activity window profile. CONCLUSIONS This study characterized main rest-activity profiles among the US adolescents, and demonstrated that demographic and socioeconomic status factors may shape rest-activity behaviors in this population.
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Affiliation(s)
- Chris Ho Ching Yeung
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, 1200 Pressler St., Houston, TX, USA
| | - Jiachen Lu
- Department of Biostatistics and Data Science, School of Public Health, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
- Center for Spatial‑Temporal Modeling for Applications in Population Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Erica G Soltero
- United States Department of Agriculture/Agricultural Research Services Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Cici Bauer
- Department of Biostatistics and Data Science, School of Public Health, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA.
- Center for Spatial‑Temporal Modeling for Applications in Population Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA.
| | - Qian Xiao
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, 1200 Pressler St., Houston, TX, USA.
- Center for Spatial‑Temporal Modeling for Applications in Population Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA.
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3
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Stein MJ, Baurecht H, Sedlmeier AM, Konzok J, Bohmann P, Fontvieille E, Peruchet-Noray L, Bowden J, Friedenreich CM, Fervers B, Ferrari P, Gunter MJ, Freisling H, Leitzmann MF, Viallon V, Weber A. Association between circadian physical activity patterns and mortality in the UK Biobank. Int J Behav Nutr Phys Act 2023; 20:102. [PMID: 37653438 PMCID: PMC10472628 DOI: 10.1186/s12966-023-01508-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 08/28/2023] [Indexed: 09/02/2023] Open
Abstract
BACKGROUND The benefit of physical activity (PA) for increasing longevity is well-established, however, the impact of diurnal timing of PA on mortality remains poorly understood. We aimed to derive circadian PA patterns and investigate their associations with all-cause mortality. METHODS We used 24 h PA time series from 96,351 UK Biobank participants aged between 42 and 79 years at accelerometry in 2013-2015. Functional principal component analysis (fPCA) was applied to obtain circadian PA patterns. Using multivariable Cox proportional hazard models, we related the loading scores of these fPCs to estimate risk of mortality. RESULTS During 6.9 years of follow-up, 2,850 deaths occurred. Four distinct fPCs accounted for 96% of the variation of the accelerometry data. Using a loading score of zero (i.e., average overall PA during the day) as the reference, a fPC1 score of + 2 (high overall PA) was inversely associated with mortality (Hazard ratio, HR = 0.91; 95% CI: 0.84-0.99), whereas a score of -2 (low overall PA) was associated with higher mortality (1.69; 95% CI: 1.57-1.81; p for non-linearity < 0.001). Significant inverse linear associations with mortality were observed for engaging in midday PA instead of early and late PA (fPC3) (HR for a 1-unit increase 0.88; 95% CI: 0.83-0.93). In contrast, midday and nocturnal PA instead of early and evening PA (fPC4) were positively associated with mortality (HR for a 1-unit increase 1.16; 95% CI: 1.08-1.25). CONCLUSION Our results suggest that it is less important during which daytime hours one is active but rather, to engage in some level of elevated PA for longevity.
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Affiliation(s)
- Michael J Stein
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Franz-Josef-Strauss Allee 11, 93057, Regensburg, Germany.
| | - Hansjörg Baurecht
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Franz-Josef-Strauss Allee 11, 93057, Regensburg, Germany
| | - Anja M Sedlmeier
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Franz-Josef-Strauss Allee 11, 93057, Regensburg, Germany
| | - Julian Konzok
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Franz-Josef-Strauss Allee 11, 93057, Regensburg, Germany
| | - Patricia Bohmann
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Franz-Josef-Strauss Allee 11, 93057, Regensburg, Germany
| | - Emma Fontvieille
- Nutrition and Metabolism Branch, International Agency for Research On Cancer (IARC/WHO), Lyon, France
| | - Laia Peruchet-Noray
- Nutrition and Metabolism Branch, International Agency for Research On Cancer (IARC/WHO), Lyon, France
- Department of Clinical Sciences, Faculty of Medicine, University of Barcelona, Barcelona, Spain
| | - Jack Bowden
- University of Exeter Medical School, Exeter, UK
- Novo Nordisk Research Center Oxford, Oxford, UK
| | - Christine M Friedenreich
- Department of Cancer Epidemiology and Prevention Research, Cancer Care Alberta, Alberta Health Services, Calgary, AB, Canada
- Departments of Oncology and Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Béatrice Fervers
- Département Prévention Cancer Environnement, Centre Léon Bérard, Lyon, France
- INSERM U1296 Radiation: Defense, Health, Environment, Lyon, France
| | - Pietro Ferrari
- Nutrition and Metabolism Branch, International Agency for Research On Cancer (IARC/WHO), Lyon, France
| | - Marc J Gunter
- Nutrition and Metabolism Branch, International Agency for Research On Cancer (IARC/WHO), Lyon, France
| | - Heinz Freisling
- Nutrition and Metabolism Branch, International Agency for Research On Cancer (IARC/WHO), Lyon, France
| | - Michael F Leitzmann
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Franz-Josef-Strauss Allee 11, 93057, Regensburg, Germany
| | - Vivian Viallon
- Nutrition and Metabolism Branch, International Agency for Research On Cancer (IARC/WHO), Lyon, France
| | - Andrea Weber
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Franz-Josef-Strauss Allee 11, 93057, Regensburg, Germany
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Majcherek D, Kowalski AM, Lewandowska MS. Lifestyle, Demographic and Socio-Economic Determinants of Mental Health Disorders of Employees in the European Countries. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:11913. [PMID: 36231214 PMCID: PMC9565551 DOI: 10.3390/ijerph191911913] [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: 07/30/2022] [Revised: 09/16/2022] [Accepted: 09/18/2022] [Indexed: 06/16/2023]
Abstract
Ensuring the health and well-being of workers should be a top priority for employers and governments. The aim of the article is to evaluate and rank the importance of mental health determinants: lifestyle, demographic factors and socio-economic status. The research study is based on EHIS 2013-2015 data for a sample of N = 140,791 employees from 30 European countries. The results obtained using machine learning techniques such as gradient-boosted trees and SHAPley values show that the mental health of European employees is strongly determined by the BMI, age and social support from close people. The next vital features are alcohol consumption, an unmet need for health care and sports activity, followed by the affordability of medicine or treatment, income and occupation. The wide range of variables clearly indicates that there is an important role for governments to play in order to minimize the risk of mental disorders across various socio-economic groups. It is also a signal for businesses to help boost the mental health of their employees by creating holistic, mentally friendly working conditions, such as offering time-management training, implementing morning briefings, offering quiet areas, making employees feel valued, educating them about depression and burnout symptoms, and promoting a healthy lifestyle.
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Affiliation(s)
- Dawid Majcherek
- Department of International Management, Collegium of World Economy, SGH Warsaw School of Economics, al. Niepodległości 162, 02-554 Warsaw, Poland
| | - Arkadiusz Michał Kowalski
- World Economy Research Institute, Collegium of World Economy, SGH Warsaw School of Economics, al. Niepodległości 162, 02-554 Warsaw, Poland
| | - Małgorzata Stefania Lewandowska
- Department of International Management, Collegium of World Economy, SGH Warsaw School of Economics, al. Niepodległości 162, 02-554 Warsaw, Poland
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Gianfredi V, Ferrara P, Pennisi F, Casu G, Amerio A, Odone A, Nucci D, Dinu M. Association between Daily Pattern of Physical Activity and Depression: A Systematic Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19116505. [PMID: 35682090 PMCID: PMC9180107 DOI: 10.3390/ijerph19116505] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 05/24/2022] [Accepted: 05/25/2022] [Indexed: 01/27/2023]
Abstract
Recent research suggested that daily pattern of physical activity (PA) may have an important association with depression, but findings are limited and contradictory. Our aim was to conduct a systematic review of the literature to summarize the literature evidence on the association between timing of PA and depression. A comprehensive search of PubMed/Medline and Scopus databases has been performed, and a total of five manuscripts have been thoroughly reviewed. The performed descriptive analysis shows lower levels of PA among individuals with depression or depressive symptoms, although evidence on the 24 h pattern of PA and depression is limited. An interesting finding is the association between lower PA during the morning, higher PA late in the evening (night), and depression or depressive symptoms. However, definitive conclusions could not be drawn due to the observational nature of the studies, their limited number, the high heterogeneity in the sample populations, and the studies’ differing outcome definitions and exposure assessments. Future studies considering not only the level of PA but also its daily variability might be important to further explore this novel area of research.
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Affiliation(s)
- Vincenza Gianfredi
- Department of Biomedical Sciences for Health, University of Milan, Via Pascal 36, 20133 Milan, Italy;
- CAPHRI Care and Public Health Research Institute, Maastricht University, 6200 MD Maastricht, The Netherlands
| | - Pietro Ferrara
- Department of Public Health, Experimental and Forensic Medicine, University of Pavia, 27100 Pavia, Italy; (P.F.); (A.O.)
- Center for Public Health Research, University of Milan-Bicocca, 20900 Monza, Italy
| | - Flavia Pennisi
- School of Medicine, Vita-Salute San Raffaele University, Via Olgettina 58, 20132 Milan, Italy; (F.P.); (G.C.)
| | - Giulia Casu
- School of Medicine, Vita-Salute San Raffaele University, Via Olgettina 58, 20132 Milan, Italy; (F.P.); (G.C.)
| | - Andrea Amerio
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), Section of Psychiatry, University of Genoa, 16146 Genoa, Italy;
- IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy
- Department of Psychiatry, Tufts University, Boston, MA 02155, USA
| | - Anna Odone
- Department of Public Health, Experimental and Forensic Medicine, University of Pavia, 27100 Pavia, Italy; (P.F.); (A.O.)
| | - Daniele Nucci
- Nutritional Support Unit, Veneto Institute of Oncology IOV-IRCCS, 35128 Padua, Italy
- Correspondence:
| | - Monica Dinu
- Department of Experimental and Clinical Medicine, University of Florence, 50121 Florence, Italy;
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Xiao Q, Lu J, Zeitzer JM, Matthews CE, Saint-Maurice PF, Bauer C. Rest-activity profiles among U.S. adults in a nationally representative sample: a functional principal component analysis. Int J Behav Nutr Phys Act 2022; 19:32. [PMID: 35331274 PMCID: PMC8944104 DOI: 10.1186/s12966-022-01274-4] [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: 09/15/2021] [Accepted: 03/04/2022] [Indexed: 11/30/2022] Open
Abstract
Background The 24-h rest and activity behaviors (i.e., physical activity, sedentary behaviors and sleep) are fundamental human behaviors essential to health and well-being. Functional principal component analysis (fPCA) is a flexible approach for characterizing rest-activity rhythms and does not rely on a priori assumptions about the activity shape. The objective of our study is to apply fPCA to a nationally representative sample of American adults to characterize variations in the 24-h rest-activity pattern, determine how the pattern differs according to demographic, socioeconomic and work characteristics, and examine its associations with general health status. Methods The current analysis used data from adults 25 or older in the National Health and Nutrition Examination Survey (NHANES, 2011–2014). Using 7-day 24-h actigraphy recordings, we applied fPCA to derive profiles for overall, weekday and weekend rest-activity patterns. We examined the association between each rest-activity profile in relation to age, gender, race/ethnicity, education, income and working status using multiple linear regression. We also used multiple logistic regression to determine the relationship between each rest-activity profile and the likelihood of reporting poor or fair health. Results We identified four distinct profiles (i.e., high amplitude, early rise, prolonged activity window, biphasic pattern) that together accounted for 86.8% of total variation in the study sample. We identified numerous associations between each rest-activity profile and multiple sociodemographic characteristics. We also found evidence suggesting the associations differed between weekdays and weekends. Finally, we reported that the rest-activity profiles were associated with self-rated health. Conclusions Our study provided evidence suggesting that rest-activity patterns in human populations are shaped by multiple demographic, socioeconomic and work factors, and are correlated with health status. Supplementary Information The online version contains supplementary material available at 10.1186/s12966-022-01274-4.
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Affiliation(s)
- Qian Xiao
- Department of Epidemiology, Human Genetics and Environmental Health, School of Public Health, the University of Texas Health Science Center at Houston, 1200 Pressler St., TX, Houston, USA.
| | - Jiachen Lu
- Department of Biostatistics and Data Science, The University of Texas Health Science Center at Houston, 1200 Pressler St., TX, Houston, USA
| | - Jamie M Zeitzer
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Charles E Matthews
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Pedro F Saint-Maurice
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Cici Bauer
- Department of Biostatistics and Data Science, The University of Texas Health Science Center at Houston, 1200 Pressler St., TX, Houston, USA.
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Pastre M, Lopez-Castroman J. Actigraphy monitoring in anxiety disorders: A mini-review of the literature. Front Psychiatry 2022; 13:984878. [PMID: 35990052 PMCID: PMC9381974 DOI: 10.3389/fpsyt.2022.984878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Accepted: 07/15/2022] [Indexed: 11/13/2022] Open
Abstract
Sleep disturbances and changes of activity patterns are not uncommon in anxiety disorders, but they are rarely the object of attention. Actigraphic monitoring of day and night activity patterns could provide useful data to detect symptom worsening, prevent risk periods, and evaluate treatment efficacy in those disorders. Thus, we have conducted a systematic search of the scientific literature to find any original study using actigraphic monitoring to investigate activity and sleep patterns in patients affected by any type of anxiety disorder according to the definition of the DSM-5. We found only six studies fulfilling these criteria. Three studies report significant findings in patients suffering from anxiety disorders. Overall, the samples and methods are heterogeneous. Although the authors support the interest of actigraphic monitoring in anxiety disorders, the evidence to date is very limited.
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Affiliation(s)
| | - Jorge Lopez-Castroman
- Department of Psychiatry, CHU Nimes, Nimes, France.,Institut de Génomique Fonctionnelle (IGF), Université de Montpellier, CNRS, INSERM, Montpellier, France.,Centro de Investigacion Biomedical en Salud Mental (CIBERSAM), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
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