TY - JOUR
T1 - Jointly modeling of sleep variables that are objectively measured by wrist actigraphy
AU - Xue, Xiaonan
AU - Hua, Simin
AU - Weber, Kathleen
AU - Qi, Qibin
AU - Kaplan, Robert
AU - Gustafson, Deborah R.
AU - Sharma, Anjali
AU - French, Audrey
AU - Burgess, Helen J.
N1 - Funding Information:
The contents of this publication are solely the responsibility of the authors and do not represent the official views of the National Institutes of Health (NIH). MWCCS (Principal Investigators): Atlanta CRS (Ighovwerha Ofotokun, Anandi Sheth, and Gina Wingood), U01‐HL146241; Baltimore CRS (Todd Brown and Joseph Margolick), U01‐HL146201; Bronx CRS (Kathryn Anastos and Anjali Sharma), U01‐HL146204; Brooklyn CRS (Deborah Gustafson and Tracey Wilson), U01‐HL146202; Data Analysis and Coordination Center (Gypsyamber D'Souza, Stephen Gange and Elizabeth Golub), U01‐HL146193; Chicago‐Cook County CRS (Mardge Cohen and Audrey French), U01‐HL146245; Chicago‐Northwestern CRS (Steven Wolinsky), U01‐HL146240; Northern California CRS (Bradley Aouizerat, Jennifer Price, and Phyllis Tien), U01‐HL146242; Los Angeles CRS (Roger Detels and Matthew Mimiaga), U01‐HL146333; Metropolitan Washington CRS (Seble Kassaye and Daniel Merenstein), U01‐HL146205; Miami CRS (Maria Alcaide, Margaret Fischl, and Deborah Jones), U01‐HL146203; Pittsburgh CRS (Jeremy Martinson and Charles Rinaldo), U01‐HL146208; UAB‐MS CRS (Mirjam‐Colette Kempf, Jodie Dionne‐Odom, and Deborah Konkle‐Parker), U01‐HL146192; UNC CRS (Adaora Adimora), U01‐HL146194. The MWCCS is funded primarily by the National Heart, Lung, and Blood Institute (NHLBI), with additional co‐funding from the National Institute of Child Health & Human Development (NICHD), National Institute on Aging (NIA), National Institute of Dental & Craniofacial Research (NIDCR), National Institute of Allergy and Infectious Diseases (NIAID), National Institute of Neurological Disorders and Stroke (NINDS), National Institute of Mental Health (NIMH), National Institute on Drug Abuse (NIDA), National Institute of Nursing Research (NINR), National Cancer Institute (NCI), National Institute on Alcohol Abuse and Alcoholism (NIAAA), National Institute on Deafness and Other Communication Disorders (NIDCD), National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institute on Minority Health and Health Disparities (NIMHD), and in coordination and alignment with the research priorities of the National Institutes of Health, Office of AIDS Research (OAR). MWCCS data collection is also supported by UL1‐TR000004 (UCSF CTSA), UL1‐TR003098 (JHU ICTR), UL1‐TR001881 (UCLA CTSI), P30‐AI‐050409 (Atlanta CFAR), P30‐AI‐073961 (Miami CFAR), P30‐AI‐050410 (UNC CFAR), P30‐AI‐027767 (UAB CFAR), and P30‐MH‐116867 (Miami CHARM). Eunice Kennedy Shriver
Funding Information:
This work is supported by National Heart, Lung, and Blood Institute (NHLBI) 1R01HL142116‐01 (2018‐2022) entitled “The Indoleamine 2, 3‐dioxygenase (IDOZe) Study” (Audrey, Burgess).
Funding Information:
information National Heart, Lung, and Blood Institute, Grant/Award Number: 1R01HL142116-01The contents of this publication are solely the responsibility of the authors and do not represent the official views of the National Institutes of Health (NIH). MWCCS (Principal Investigators): Atlanta CRS (Ighovwerha Ofotokun, Anandi Sheth, and Gina Wingood), U01-HL146241; Baltimore CRS (Todd Brown and Joseph Margolick), U01-HL146201; Bronx CRS (Kathryn Anastos and Anjali Sharma), U01-HL146204; Brooklyn CRS (Deborah Gustafson and Tracey Wilson), U01-HL146202; Data Analysis and Coordination Center (Gypsyamber D'Souza, Stephen Gange and Elizabeth Golub), U01-HL146193; Chicago-Cook County CRS (Mardge Cohen and Audrey French), U01-HL146245; Chicago-Northwestern CRS (Steven Wolinsky), U01-HL146240; Northern California CRS (Bradley Aouizerat, Jennifer Price, and Phyllis Tien), U01-HL146242; Los Angeles CRS (Roger Detels and Matthew Mimiaga), U01-HL146333; Metropolitan Washington CRS (Seble Kassaye and Daniel Merenstein), U01-HL146205; Miami CRS (Maria Alcaide, Margaret Fischl, and Deborah Jones), U01-HL146203; Pittsburgh CRS (Jeremy Martinson and Charles Rinaldo), U01-HL146208; UAB-MS CRS (Mirjam-Colette Kempf, Jodie Dionne-Odom, and Deborah Konkle-Parker), U01-HL146192; UNC CRS (Adaora Adimora), U01-HL146194. The MWCCS is funded primarily by the National Heart, Lung, and Blood Institute (NHLBI), with additional co-funding from the Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD), National Institute on Aging (NIA), National Institute of Dental & Craniofacial Research (NIDCR), National Institute of Allergy and Infectious Diseases (NIAID), National Institute of Neurological Disorders and Stroke (NINDS), National Institute of Mental Health (NIMH), National Institute on Drug Abuse (NIDA), National Institute of Nursing Research (NINR), National Cancer Institute (NCI), National Institute on Alcohol Abuse and Alcoholism (NIAAA), National Institute on Deafness and Other Communication Disorders (NIDCD), National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institute on Minority Health and Health Disparities (NIMHD), and in coordination and alignment with the research priorities of the National Institutes of Health, Office of AIDS Research (OAR). MWCCS data collection is also supported by UL1-TR000004 (UCSF CTSA), UL1-TR003098 (JHU ICTR), UL1-TR001881 (UCLA CTSI), P30-AI-050409 (Atlanta CFAR), P30-AI-073961 (Miami CFAR), P30-AI-050410 (UNC CFAR), P30-AI-027767 (UAB CFAR), and P30-MH-116867 (Miami CHARM). The authors gratefully acknowledge the contributions of the study participants and dedication of the staff at the MWCCS sites. This work is supported by National Heart, Lung, and Blood Institute (NHLBI) 1R01HL142116-01 (2018-2022) entitled “The Indoleamine 2, 3-dioxygenase (IDOZe) Study” (Audrey, Burgess). The authors would also want to thank the two anonymous referees whose constructive suggestions have resulted in significant improvement of the article.
Publisher Copyright:
© 2022 John Wiley & Sons Ltd.
PY - 2022/7/10
Y1 - 2022/7/10
N2 - Recently developed actigraphy devices have made it possible for continuous and objective monitoring of sleep over multiple nights. Sleep variables captured by wrist actigraphy devices include sleep onset, sleep end, total sleep time, wake time after sleep onset, number of awakenings, etc. Currently available statistical methods to analyze such actigraphy data have limitations. First, averages over multiple nights are used to summarize sleep activities, ignoring variability over multiple nights from the same subject. Second, sleep variables are often analyzed independently. However, sleep variables tend to be correlated with each other. For example, how long a subject sleeps at night can be correlated with how long and how frequent he/she wakes up during that night. It is important to understand these inter-relationships. We therefore propose a joint mixed effect model on total sleep time, number of awakenings, and wake time. We develop an estimating procedure based upon a sequence of generalized linear mixed effects models, which can be implemented using existing software. The use of these models not only avoids computational intensity and instability that may occur by directly applying a numerical algorithm on a complicated joint likelihood function, but also provides additional insights on sleep activities. We demonstrated in simulation studies that the proposed estimating procedure performed well in estimating both fixed and random effects' parameters. We applied the proposed model to data from the Women's Interagency HIV Sleep Study to examine the association of employment status and age with overall sleep quality assessed by several actigraphy measured sleep variables.
AB - Recently developed actigraphy devices have made it possible for continuous and objective monitoring of sleep over multiple nights. Sleep variables captured by wrist actigraphy devices include sleep onset, sleep end, total sleep time, wake time after sleep onset, number of awakenings, etc. Currently available statistical methods to analyze such actigraphy data have limitations. First, averages over multiple nights are used to summarize sleep activities, ignoring variability over multiple nights from the same subject. Second, sleep variables are often analyzed independently. However, sleep variables tend to be correlated with each other. For example, how long a subject sleeps at night can be correlated with how long and how frequent he/she wakes up during that night. It is important to understand these inter-relationships. We therefore propose a joint mixed effect model on total sleep time, number of awakenings, and wake time. We develop an estimating procedure based upon a sequence of generalized linear mixed effects models, which can be implemented using existing software. The use of these models not only avoids computational intensity and instability that may occur by directly applying a numerical algorithm on a complicated joint likelihood function, but also provides additional insights on sleep activities. We demonstrated in simulation studies that the proposed estimating procedure performed well in estimating both fixed and random effects' parameters. We applied the proposed model to data from the Women's Interagency HIV Sleep Study to examine the association of employment status and age with overall sleep quality assessed by several actigraphy measured sleep variables.
KW - Poisson distribution with over-dispersion
KW - Tweedie distribution
KW - compound Poisson gamma distribution
KW - generalized linear mixed effects model
UR - http://www.scopus.com/inward/record.url?scp=85128007429&partnerID=8YFLogxK
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U2 - 10.1002/sim.9385
DO - 10.1002/sim.9385
M3 - Article
C2 - 35417078
AN - SCOPUS:85128007429
VL - 41
SP - 2804
EP - 2821
JO - Statistics in Medicine
JF - Statistics in Medicine
SN - 0277-6715
IS - 15
ER -