Literature DB >> 28650674

Variation in actigraphy-estimated rest-activity patterns by demographic factors.

Jonathan A Mitchell1,2, Mirja Quante3,4, Suneeta Godbole5, Peter James6,7, J Aaron Hipp8, Catherine R Marinac9, Sara Mariani3, Elizabeth M Cespedes Feliciano10, Karen Glanz11, Francine Laden6,7, Rui Wang3, Jia Weng3, Susan Redline3,12, Jacqueline Kerr5.   

Abstract

Rest-activity patterns provide an indication of circadian rhythmicity in the free-living setting. We aimed to describe the distributions of rest-activity patterns in a sample of adults and children across demographic variables. A sample of adults (N = 590) and children (N = 58) wore an actigraph on their nondominant wrist for 7 days and nights. We generated rest-activity patterns from cosinor analysis (MESOR, acrophase and magnitude) and nonparametric circadian rhythm analysis (IS: interdaily stability; IV: intradaily variability; L5: least active 5-hour period; M10: most active 10-hour period; and RA: relative amplitude). Demographic variables included age, sex, race, education, marital status, and income. Linear mixed-effects models were used to test for demographic differences in rest-activity patterns. Adolescents, compared to younger children, had (1) later M10 midpoints (β = 1.12 hours [95% CI: 0.43, 1.18] and lower M10 activity levels; (2) later L5 midpoints (β = 1.6 hours [95% CI: 0.9, 2.3]) and lower L5 activity levels; (3) less regular rest-activity patterns (lower IS and higher IV); and 4) lower magnitudes (β = -0.95 [95% CI: -1.28, -0.63]) and relative amplitudes (β = -0.1 [95% CI: -0.14, -0.06]). Mid-to-older adults, compared to younger adults (aged 18-29 years), had (1) earlier M10 midpoints (β = -1.0 hours [95% CI: -1.6, -0.4]; (2) earlier L5 midpoints (β = -0.7 hours [95% CI: -1.2, -0.2]); and (3) more regular rest-activity patterns (higher IS and lower IV). The magnitudes and relative amplitudes were similar across the adult age categories. Sex, race and education level rest-activity differences were also observed. Rest-activity patterns vary across the lifespan, and differ by race, sex and education. Understanding population variation in these patterns provides a foundation for further elucidating the health implications of rest-activity patterns across the lifespan.

Entities:  

Keywords:  actigraphy; demographics; epidemiology; rest-activity patterns

Mesh:

Year:  2017        PMID: 28650674      PMCID: PMC6101244          DOI: 10.1080/07420528.2017.1337032

Source DB:  PubMed          Journal:  Chronobiol Int        ISSN: 0742-0528            Impact factor:   2.877


  44 in total

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