\documentclass[10pt]{article}

\usepackage{fullpage}
\usepackage{setspace}
\usepackage{parskip}
\usepackage{titlesec}
\usepackage[section]{placeins}
\usepackage{xcolor}
\usepackage{breakcites}
\usepackage{lineno}
\usepackage{hyphenat}





\PassOptionsToPackage{hyphens}{url}
\usepackage[colorlinks = true,
            linkcolor = blue,
            urlcolor  = blue,
            citecolor = blue,
            anchorcolor = blue]{hyperref}
\usepackage{etoolbox}
\makeatletter
\patchcmd\@combinedblfloats{\box\@outputbox}{\unvbox\@outputbox}{}{%
  \errmessage{\noexpand\@combinedblfloats could not be patched}%
}%
\makeatother


\usepackage{natbib}




\renewenvironment{abstract}
  {{\bfseries\noindent{\abstractname}\par\nobreak}\footnotesize}
  {\bigskip}

\titlespacing{\section}{0pt}{*3}{*1}
\titlespacing{\subsection}{0pt}{*2}{*0.5}
\titlespacing{\subsubsection}{0pt}{*1.5}{0pt}


\usepackage{authblk}


\usepackage{graphicx}
\usepackage[space]{grffile}
\usepackage{latexsym}
\usepackage{textcomp}
\usepackage{longtable}
\usepackage{tabulary}
\usepackage{booktabs,array,multirow}
\usepackage{amsfonts,amsmath,amssymb}
\providecommand\citet{\cite}
\providecommand\citep{\cite}
\providecommand\citealt{\cite}
% You can conditionalize code for latexml or normal latex using this.
\newif\iflatexml\latexmlfalse
\providecommand{\tightlist}{\setlength{\itemsep}{0pt}\setlength{\parskip}{0pt}}%

\AtBeginDocument{\DeclareGraphicsExtensions{.pdf,.PDF,.eps,.EPS,.png,.PNG,.tif,.TIF,.jpg,.JPG,.jpeg,.JPEG}}

\usepackage[utf8]{inputenc}
\usepackage[english]{babel}



\usepackage{float}








\begin{document}

\title{Short Sleep Duration and Physical and Psychological Health Outcomes
Among Adult Survivors of Childhood Cancer}



\author[1]{Margaret Lubas}%
\author[2]{Belinda Mandrell}%
\author[2]{Kirsten Ness}%
\author[3]{Kumar Srivastava}%
\author[1]{Matthew Ehrhardt}%
\author[1]{Zhaoming Wang}%
\author[4]{Melissa Hudson}%
\author[2]{Leslie Robison}%
\author[2]{Kevin Krull}%
\author[2]{Tara Brinkman}%
\affil[1]{St Jude Children's Research Hospital}%
\affil[2]{St. Jude Children's Research Hospital}%
\affil[3]{St. Jude Children}%
\affil[4]{St. Jude Children’s Research Hospital}%


\vspace{-1em}



  
  \date{June 18, 2024}


\begingroup
\let\center\flushleft
\let\endcenter\endflushleft
\maketitle
\endgroup





\selectlanguage{english}
\begin{abstract}
Background: To examine associations between phenotypes of short sleep
duration and clinically-assessed health conditions in long-term
survivors of childhood cancer. Methods: Survivors recruited from the St.
Jude Lifetime Cohort (n=911; 52\% female; mean age 34 years; 26 years
post-diagnosis) completed behavioral health surveys and underwent
comprehensive physical examinations. Sleep was assessed with the
Pittsburgh Sleep Quality Index. Short sleep was defined as \textless{}7
hours per night with phenotypes of short sleep including poor sleep
efficiency (\textless{}85\%), prolonged sleep onset latency ([?]30
minutes), and wake after sleep onset ([?]3 times per week). Covariates
included childhood cancer treatment exposures, demographics, body mass
index, and physical inactivity. Separate modified Poisson regression
models were computed for each health category to estimate relative risks
(RR) and 95\% confidence intervals (CI). Multinomial logistic regression
models examined associations between sleep and an aggregated burden of
chronic health conditions. Results: Short sleep duration was reported
among 44\% (95\% CI 41\%-47\%) of survivors. In multivariable models,
short sleep duration alone was associated with pulmonary (RR=1.35, 95\%
CI 1.08-1.69), endocrine (RR=1.22, 95\% CI 1.06-1.39) and
gastrointestinal/hepatic conditions (RR=1.46, 95\% CI 1.18-1.79), and
anxiety (RR 3.24, 95\% CI 1.64-6.41) and depression (RR=2.33, 95\% CI
1.27-4.27). Short sleep with prolonged SOL was associated with a
high/severe burden of health conditions (OR=2.35, 95\% CI 1.12-4.94).
Conclusions: Short sleep duration was associated with multiple
clinically-ascertained adverse health conditions. Although the
temporality of these associations cannot be determined in this
cross-sectional study, sleep is modifiable, and improving sleep may
improve long-term health in survivors.%
\end{abstract}%



\sloppy




\textbf{Introduction}

Despite advances in cancer therapy and survival, childhood cancer
survivors experience a lifelong risk for treatment-related late
effects.\textsuperscript{1} Compared to the general population,
long-term survivors have an increased risk of cardiovascular
disease,\textsuperscript{2} metabolic syndrome,\textsuperscript{2} and
obesity.\textsuperscript{2} Compared to sibling comparisons or
non-cancer controls, long-term survivors have a higher prevalence of
cerebrovascular events,\textsuperscript{3} gastrointestinal
complications,\textsuperscript{4} and pulmonary
deficits.\textsuperscript{5} Adult survivors of childhood cancer
experience a high and variable burden of chronic health
conditions\textsuperscript{6} increasing their risk of early
mortality.\textsuperscript{7}

While risk of adverse health outcomes in survivors is largely driven by
treatment exposures, chronic health conditions can be exacerbated by
poor health behaviors. Among a large cohort of adult survivors of
childhood cancer, the observed association between unhealthy lifestyle
behaviors (e.g. diet, physical activity) and metabolic syndrome was
stronger than the association between cranial radiation and metabolic
syndrome.\textsuperscript{8} Adherence to a Mediterranean diet has been
associated with lower body mass index and lower risk of metabolic
syndrome among leukemia survivors.\textsuperscript{9} Moreover, physical
activity has been associated with decreased mortality risk among
childhood cancer survivors.\textsuperscript{10} Identifying and
promoting modifiable lifestyle behaviors may be essential to improving
the health outcomes and quality of life of long-term survivors.

Associations between sleep and health have not been fully elucidated in
survivors; however, in the general population sleep duration is widely
associated with several chronic health conditions. In cross-sectional
examinations of national samples, short and long sleep durations have
been associated with metabolic
syndrome,\textsuperscript{11}cardiovascular disease,\textsuperscript{12}
and chronic kidney disease.\textsuperscript{13} Moreover, prospective
associations between sleep disturbances and
diabetes,\textsuperscript{14}depression,\textsuperscript{15}
gastrointestinal disease\textsuperscript{16}, and progression to
end-stage renal disease\textsuperscript{17} have also been reported. The
high prevalence of self-reported sleep disturbances among survivors of
childhood cancer has been well characterized;\textsuperscript{18,19}
however, few studies have examined health status and poor sleep among
childhood cancer survivors. The purpose of this study was to examine
associations between short sleep duration and clinically-assessed health
conditions among adult survivors of childhood cancer.

\textbf{Methods}

\textbf{Study Participants}

Study participants were recruited from the St. Jude Lifetime Cohort
Study (SJLIFE),\textsuperscript{20} a retrospective cohort of childhood
cancer survivors who participate in prospective medical assessments. The
cohort was initiated in 2007 and includes survivors of childhood cancer
who are [?]5 years post-diagnosis of a pediatric cancer treated at St.
Jude Children's Research Hospital. For the current study, survivors
enrolled in SJLIFE who were [?]18 years of age and [?]10 years post
diagnosis were recruited for a randomized controlled trial focused on
sleep and cognition. We identified and screened 3,348 potentially
eligible SJLIFE participants. Among these survivors, 562 refused
participation in the intervention and 1,875 did not meet initial study
specific inclusion/exclusion criteria (see Supplementary Table S1
intervention inclusion/exclusion criteria). This resulted in 911
participants who completed baseline evaluations to confirm eligibility
for the intervention study and who form the study population for the
current analysis. All participants provided written informed consent and
the study was approved by the Institutional Review Board at St. Jude
Children's Research Hospital.

\textbf{Measures}

\emph{Health outcomes}

\emph{Physical health outcomes.} Clinically-assessed health conditions
were evaluated during on-campus medical evaluations and defined using
modified Common Terminology Criteria for Adverse Events (CTCAE) version
4.03 criteria adapted for childhood cancer
survivors.\textsuperscript{21} Comprehensive medical assessments
included diagnostic procedures, an assessment of neuromuscular function,
and a physical evaluation with a standardized laboratory battery. At the
time of assessment, if survivors reported any chronic health conditions
previously diagnosed, medical records were obtained to validate these
diagnoses. The following organ systems were evaluated during the medical
assessment and included as outcome variables: cardiac, pulmonary, renal,
endocrine, gastrointestinal/hepatic, neurologic and musculoskeletal.
CTCAE grades range from 1-4 (mild {[}grade 1{]}, moderate {[}grade 2{]},
severe or disabling {[}grade 3{]}, life-threatening {[}grade 4{]}), and
adverse health conditions were defined as grade [?]2 for each condition
(i.e. moderate to life threatening). Supplemental Tables S2a-g present
the frequency of grade 2-4 conditions for study participants, classified
by each organ system. Chronic health conditions were included if they
were diagnosed prior to and up to three months following the sleep
assessment.

In addition to evaluating health conditions by each organ system, we
created a composite measure assessing the burden/severity of the
survivor's physical health. A method developed by Geenen et
al.\textsuperscript{22} was employed to aggregate chronic health
conditions across organ systems (cardiovascular, pulmonary, endocrine,
neurologic, gastrointestinal, musculoskeletal, and renal), taking into
account the frequency and grade of conditions. For survivors who had
multiple chronic health conditions within the same organ system, the
highest grade within that organ system was utilized. This chronic health
burden score was classified via the following categories: none, low
(only grade 1 events), medium (having [?]1 grade 2 event and/or 1 grade 3
event), high (having [?] 2 grade 3 events or 1 grade 4 event and at most 1
grade 3 event), and severe (\textgreater{}1 grade 4 events or [?] 2 grade
3 events and 1 grade 4 event).

\emph{Psychological health outcomes.} The Brief Symptom Inventory-18
(BSI-18)\textsuperscript{23} was administered at the time of the
participant's sleep evaluation to assess clinically significant anxiety
and depression. Using sex-specific normative data, survivors with a
T-score [?]63 (90\textsuperscript{th} percentile) on either subscale were
classified with clinically significant anxiety and/or depression. The
BSI-18 has been previously validated in childhood cancer
survivors.\textsuperscript{24}

\emph{Self-reported sleep and short sleep duration (primary predictor).}

Phenotypes of self-reported short sleep were defined by utilizing
questions from The Pittsburgh Sleep Quality Index (PSQI), which measures
sleep quality and quantity over the previous month. Individual questions
were used to operationalize phenotypes of habitual short sleep duration.
Sleep duration was assessed via the question, ``during the past month,
how many hours of actual sleep did you get a night?'' Short sleep was
defined as self-reported sleep duration of \textless{} 7 hours per
night. Questions about sleep onset latency (SOL), wake after sleep onset
(WASO), and sleep efficiency (SE) were also utilized to examine short
sleepers with an additional sleep disturbance. Short sleepers with a
prolonged SOL were defined as individuals who reported a SOL [?] 30
minutes. Short sleepers with a WASO impairment were defined as
individuals who reported waking up late at night or early in the morning
at least three times a week. Short sleepers with poor SE were defined by
a SE \textless{} 85\% which was calculated from the PSQI as the ratio of
total sleep time compared to total time spent in bed. These
classifications were not mutually exclusive and were defined as
additional sleep disturbances among short sleepers.

\emph{Covariates}

Treatment exposures (e.g. individual chemotherapeutic agents and
radiation) known to increase the risk of chronic health conditions in
survivors were selected \emph{a priori} and informed by Children's
Oncology Group guidelines version 5.0.\textsuperscript{26} Specific
treatment exposures were selected for each health outcome in order to
provide adequate adjustment for treatment exposures in separate models
(see Table 1 for a description of treatment exposures included for each
health outcome). Age at evaluation, age at cancer diagnosis, sex,
race/ethnicity, body mass index (BMI) and physical inactivity were
included as covariates in all models. Physical inactivity was defined as
not meeting Centers for Disease Control recommendation for physical
activity (75 minutes of vigorous or 150 minutes of moderate activity per
week).\textsuperscript{27} Weekly moderate and vigorous activities were
converted into metabolic equivalents (METS), individuals who reported
\textless{}450 METS per week were classified as inactive. Age at
evaluation, BMI and physical activity were assessed at the time of the
sleep survey.

\textbf{Statistical analysis}

Descriptive statistics were calculated for all exposures, outcomes, and
covariates. Differences between study variables by short sleep duration
were reported by using Chi-square statistics for categorical variables
and t-tests for continuous variables. Modified Poisson regression models
with robust error variance\textsuperscript{28} were used to examine
associations between phenotypes of short sleep duration and health
outcomes. Separate models were conducted for each phenotype of short
sleep and each health outcome, while adjusting for age at evaluation,
sex, race/ethnicity, age at diagnosis, BMI, physical inactivity and
condition-specific treatment exposures. When examining the associations
between phenotypes of short sleep duration and the composite burden
score of physical health outcomes, multinomial logistic regression was
employed. Burden models were adjusted for age at evaluation, sex,
race/ethnicity, BMI, and physical inactivity. All analyses were
completed using SAS v9.4. All tests were two-sided and a p-value [?] .05
was considered statistically significant.

\textbf{Results}

\textbf{Self-Reported Sleep Characteristics}

Self-reported sleep characteristics of the study participants are shown
in Table 2. On average participants reported a sleep duration of 6 hours
and 38 minutes. Forty-four percent of the sample were classified as
short sleepers, reporting a sleep duration of \textless{} 7 hours per
night. Only 14 participants reported a long sleep duration, defined as
\textgreater{} 9 hours per night. As previous research identifies a
u-shaped relationship between sleep duration and adverse health
outcomes\textsuperscript{12,13,29}, the fourteen participants reporting
long sleep duration were removed from subsequent analyses due to the
inability to examine long sleepers separately.

\textbf{Demographic, Survivorship, and Health Characteristics}

Demographic, treatment exposures, and chronic health conditions among
survivors with short and typical sleep duration are summarized in Table
3. Survivors were 51.8\% female, predominately non-Hispanic white
(84.1\%), an average of 34 years of age, and 26 years from their cancer
diagnosis. Leukemia (41.4\%), non-central nervous system solid tumors
(23.4\%), and Hodgkin lymphoma (13.2\%) were the most common diagnoses
among participants. Grade 2 or higher cardiac (40.8\%), endocrine
(50.0\%), neurologic (31.0\%), gastrointestinal/hepatic (31.1 \%),
musculoskeletal (30.1\%) and pulmonary (26.3\%) conditions were
prevalent in the sample. Grade 2 or higher renal conditions (9.9\%),
anxiety (6.7\%) and depression (7.6\%) were less common among survivors.
Several health outcomes were more prevalent among short sleepers
(\textless{} 7 hours) compared to those with typical sleep duration (7
to 9 hours) such as: anxiety 10.6\% vs. 3.4\% (p\textless{}0.0001),
depression 10.3\% vs. 5.2\% (p=0.0100), endocrine 55.8\% vs. 45.5\%
(p=0.0022), pulmonary 30.3\% vs. 23.0\% (p=0.0147), and
gastrointestinal/hepatic conditions 37.0\% vs. 26.3\% (p=0.0006) (Table
3).

\textbf{Multivariable Analyses}

\emph{Health Outcomes}

In multivariable models adjusted for condition-specific treatment
exposures, demographic factors, BMI, and physical inactivity, all
phenotypes of short sleep duration were associated with grade 2-4
pulmonary, endocrine, and gastrointestinal/hepatic conditions (Table 4).
For example, short sleep duration alone was associated with a 22-46\%
increased prevalence of pulmonary, (RR 1.35, 95\% CI 1.08-1.69),
endocrine (RR 1.22, 95\% CI 1.06-1.39), and gastrointestinal/hepatic
conditions (RR 1.46, 95\% CI 1.18-1.79) (Table 4). Short sleep with a
prolonged SOL was associated with neurologic conditions (RR 1.32, 95\%
CI 1.04-1.68) and short sleep with prolonged WASO with cardiac (RR 1.21,
95\% CI 1.02-1.42) and neurologic conditions (RR 1.25, 95\% CI
1.01-1.57) (Table 4). All phenotypes of short sleep duration were
associated with anxiety (e.g. short sleep duration RR 3.24, 95\% CI
1.64-6.41) and depression (e.g. short sleep duration, RR 2.33, 95\% CI
1.27-4.27) (Table 4).

\emph{Severity/Burden}

When aggregating physical health conditions to assess the burden of
conditions, 34\% of participants (n=307) were classified as having a
high to severe burden score, 56\% were classified as having a medium
burden and 10\% (n=90) were classified in the none to low reference
group (Supplemental Table S3). In models adjusted for age, sex,
race/ethnicity, BMI, and physical inactivity, short sleep duration with
a prolonged SOL was associated with a high/severe burden of chronic
health conditions (OR 2.35, 95\% CI 1.12-4.94) compared to those with a
low to none burden. No other measures of short sleep duration were
significantly associated with medium or high/severe burden of health
conditions (Figure 1, Supplemental Table S4).

\textbf{Discussion}

In a large heterogeneous sample of adult survivors of childhood cancer,
we found associations between phenotypes of short sleep duration and
clinically assessed physical and psychological health outcomes. Short
sleep duration with prolonged sleep onset latency increased risk of
high/serve burden of chronic health conditions greater than 2-fold.
Associations between all phenotypes of short sleep duration and
psychological health outcomes ranged from 2 to 3-fold in strength. While
we did not observe large differences in the strength of associations
between our phenotypes of short sleep duration and health outcomes,
short sleep with prolonged SOL or WASO yielded consistent and strong
associations to several health outcomes, including pulmonary, endocrine,
gastrointestinal, neurologic, anxiety, and depression.

In our sample, 44\% of survivors reported a habitual short sleep
duration of less than seven hours per night. Among survivors with a
short sleep duration, 21-27\% also reported a prolonged SOL and/or WASO,
and nearly 30\% of short sleepers met criteria for a poor sleep
efficiency defined as \textless{}85\%. Overall, 57\% of the sample
scored above the PSQI clinical cut-off for poor sleep quality.
Consistent with previous literature,\textsuperscript{18,19} these
findings underscore the severity and prevalence of sleep disturbances
among survivors. Additionally, sleep disturbances\textsuperscript{30}and
fatigue are associated with reduced quality of life\textsuperscript{19},
neurocognitive impairment,\textsuperscript{30}and
depression\textsuperscript{19} among cross-sectional studies of
childhood cancer survivors. One longitudinal study reported associations
between dimensions of self-reported sleep and new onset psychological
distress and new onset migraines.\textsuperscript{18} However, this
study relied on self-reported health conditions. The current study
utilized clinically-ascertained health conditions and highlights the
range in which sleep duration relates to many biological systems (i.e.
cardiac, pulmonary, gastrointestinal, and neurologic) and dimensions of
psychological health.

There are several physiological pathways through which sleep duration
could relate to adverse health conditions or overall poorer physical
functioning. For example, sleep and immune functioning are
bidirectionally related. Immune activation can alter sleep quality and
patterns, while changes in sleep patterns can also impact the body's
inflammatory response.\textsuperscript{31} Sleep patterns and duration
are associated with the release of several hormones that regulate
appetite, metabolism, and glucose tolerance.\textsuperscript{32,33}Other
physiological processes follow diurnal patterns and may be disrupted by
sleep disturbances. For instance, blood pressure often decreases at
night (i.e. nocturnal dipping) and lack of decrease (i.e. non-dipping),
which is associated with increased risk of cardiovascular
disease,\textsuperscript{33} is more prevalent among individuals with
sleep disturbances, such as obstructive sleep apnea and advanced sleep
cycles.\textsuperscript{34} While there are several biological pathways
through which sleep patterns and sleep disturbances could affect chronic
health conditions, these relationships and their directions have not
been fully elucidated. However, the potential causal significance of
poor sleep and its associations with adverse health outcomes are
reinforced by several prospective
studies\textsuperscript{15-17}/reviews\textsuperscript{14,29}.

Understanding associations between sleep duration and chronic health
conditions in childhood cancer survivors is important because sleep may
serve as a modifiable point of intervention to improve the health of
this vulnerable population. In survivorship, excess risk of chronic
conditions is driven by treatment exposures; however, intervening on
lifestyle factors can improve health outcomes in this
population\textsuperscript{35}. Several behavioral sleep interventions
in non-cancer samples have been successful in improving sleep quantity
and quality\textsuperscript{36,37} and some provide preliminary support
for health improvements\textsuperscript{38-40} and thus, merit further
study among cancer survivors.

The results of our study should be considered within the context of
several limitations. Because our analyses were cross-sectional and sleep
was measured at only one time point, we cannot assess the temporality of
associations between sleep and health outcomes. In addition, chronic
health conditions were assessed from the time of cohort participation up
to three months after the sleep assessment. Although we acknowledge
short sleep duration may have been chronic as well, we were unable to
assess this in the current study. While there are several prospective
studies identifying sleep preceding chronic health conditions, there is
also strong potential for bidirectional associations. Moreover, as we
examined a range of health conditions, it is possible that some chronic
conditions could cause or contribute to sleep disturbances, while for
others, sleep may be the antecedent. Despite our inability to ascertain
the directionality of our found associations, sleep is modifiable and
may serve as an important component of lifestyle interventions that aim
to improve health among survivors. Interventions targeting sleep may be
necessary irrespective of whether it is an antecedent or consequent of
chronic health conditions.

The present study of long-term survivors of childhood cancer identifies
associations between short sleep duration and several physical and
psychological health conditions. While short sleep duration alone was
consistently associated with several health conditions (e.g. pulmonary,
endocrine, gastrointestinal/hepatic), short sleepers with prolonged SOL
and/or WASO were associated with two additional health conditions (e.g.,
cardiac and neurologic conditions). Examining additional sleep
disturbances among short sleepers may serve as a sensitive measure
between sleep and health outcomes. In addition, SOL and/or WASO may
severe as additional points of interventions when targeting sleep
extension.

\textbf{Conflict of interest statement:} The authors have declared no
conflicts of interest.

\textbf{Acknowledgements:} This work was supported by the National
Cancer Institute at the National Institutes of Health (CA195547, M.
Hudson and L. Robison, Principal Investigators; CA239689, T. Brinkman
and K. Krull, Principal Investigators) and by the National Cancer
Institute Training in Pediatric Cancer Care Survivorship award
(5T32CA225590, K. Krull, Principal Investigator). The content is solely
the responsibility of the authors and does not necessarily represent the
official views of the National Institutes of Health. Support to St. Jude
Children's Research Hospital was also provided by the Cancer Center
Support (CORE) grant (CA21765, C. Roberts, Principal Investigator) and
the American Lebanese Syrian Associated Charities (ALSAC).

\textbf{Data sharing statement:} The data that support the findings of
this study are available from the corresponding author upon reasonable
request



\textbf{References}

1. Hudson MM, Ness KK, Gurney JG, et al. Clinical ascertainment of
health outcomes among adults treated for childhood cancer.
\emph{JAMA.}2013;309(22):2371-2381.

2. Nottage KA, Ness KK, Li C, Srivastava D, Robison LL, Hudson MM.
Metabolic syndrome and cardiovascular risk among long-term survivors of
acute lymphoblastic leukaemia - From the St. Jude Lifetime
Cohort.\emph{Br J Haematol.} 2014;165(3):364-374.

3. Bowers DC, McNeil DE, Liu Y, et al. Stroke as a late treatment effect
of Hodgkin's Disease: a report from the Childhood Cancer Survivor
Study.\emph{J Clin Oncol.} 2005;23(27):6508-6515.

4. Goldsby R, Chen Y, Raber S, et al. Survivors of childhood cancer have
increased risk of gastrointestinal complications later in
life.\emph{Gastroenterology.} 2011;140(5):1464-1471 e1461.

5. Armenian SH, Landier W, Francisco L, et al. Long-term pulmonary
function in survivors of childhood cancer. \emph{J Clin
Oncol.}2015;33(14):1592-1600.

6. Bhakta N, Liu Q, Ness KK, et al. The cumulative burden of surviving
childhood cancer: an initial report from the St Jude Lifetime Cohort
Study (SJLIFE). \emph{Lancet.} 2017;390(10112):2569-2582.

7. Bagnasco F, Caruso S, Andreano A, et al. Late mortality and causes of
death among 5-year survivors of childhood cancer diagnosed in the period
1960-1999 and registered in the Italian Off-Therapy Registry. \emph{Eur
J Cancer.} 2019;110:86-97.

8. Smith WA, Li C, Nottage KA, et al. Lifestyle and metabolic syndrome
in adult survivors of childhood cancer: a report from the St. Jude
Lifetime Cohort Study. \emph{Cancer.} 2014;120(17):2742-2750.

9. Tonorezos ES, Robien K, Eshelman-Kent D, et al. Contribution of diet
and physical activity to metabolic parameters among survivors of
childhood leukemia. \emph{Cancer Causes Control.} 2013;24(2):313-321.

10. Scott JM, Li N, Liu Q, et al. Association of Exercise With Mortality
in Adult Survivors of Childhood Cancer. \emph{JAMA
Oncol.}2018;4(10):1352-1358.

11. Smiley A, King D, Bidulescu A. The Association between Sleep
Duration and Metabolic Syndrome: The NHANES 2013/2014.
\emph{Nutrients.}2019;11(11).

12. Sabanayagam C, Shankar A. Sleep duration and cardiovascular disease:
results from the National Health Interview Survey.
\emph{Sleep.}2010;33(8):1037-1042.

13. Salifu I, Tedla F, Pandey A, et al. Sleep duration and chronic
kidney disease: analysis of the national health interview
survey.\emph{Cardiorenal Med.} 2014;4(3-4):210-216.

14. Shan Z, Ma H, Xie M, et al. Sleep duration and risk of type 2
diabetes: a meta-analysis of prospective studies. \emph{Diabetes
Care.}2015;38(3):529-537.

15. Szklo-Coxe M, Young T, Peppard PE, Finn LA, Benca RM. Prospective
associations of insomnia markers and symptoms with depression. \emph{Am
J Epidemiol.} 2010;171(6):709-720.

16. Ananthakrishnan AN, Long MD, Martin CF, Sandler RS, Kappelman MD.
Sleep disturbance and risk of active disease in patients with Crohn's
disease and ulcerative colitis. \emph{Clin Gastroenterol
Hepatol.}2013;11(8):965-971.

17. Yamamoto R, Shinzawa M, Isaka Y, et al. Sleep Quality and Sleep
Duration with CKD are Associated with Progression to ESKD. \emph{Clin J
Am Soc Nephrol.} 2018;13(12):1825-1832.

18. Daniel LC, Wang M, Mulrooney DA, et al. Sleep, emotional distress,
and physical health in survivors of childhood cancer: A report from the
Childhood Cancer Survivor Study.
\emph{Psychooncology.}2019;28(4):903-912.

19. Mulrooney DA, Ness KK, Neglia JP, et al. Fatigue and sleep
disturbance in adult survivors of childhood cancer: a report from the
childhood cancer survivor study (CCSS). \emph{Sleep.}2008;31(2):271-281.

20. Hudson MM, Ness KK, Nolan VG, et al. Prospective medical assessment
of adults surviving childhood cancer: study design, cohort
characteristics, and feasibility of the St. Jude Lifetime Cohort
study.\emph{Pediatric blood \& cancer.} 2011;56(5):825-836.

21. Hudson MM, Ehrhardt MJ, Bhakta N, et al. Approach for Classification
and Severity Grading of Long-term and Late-Onset Health Events among
Childhood Cancer Survivors in the St. Jude Lifetime Cohort. \emph{Cancer
Epidemiol Biomarkers Prev.} 2017;26(5):666-674.

22. Geenen MM, Cardous-Ubbink MC, Kremer LC, et al. Medical assessment
of adverse health outcomes in long-term survivors of childhood
cancer.\emph{JAMA.} 2007;297(24):2705-2715.

23. Derogatis LR. \emph{Brief Symptom Inventory (BSI): Administration,
scoring, and procedures manual.} Minneapolis, MN: NCS Pearson; 2000.

24. Recklitis CJ, Parsons SK, Shih MC, Mertens A, Robison LL, Zeltzer L.
Factor structure of the brief symptom inventory--18 in adult survivors
of childhood cancer: results from the childhood cancer survivor
study.\emph{Psychol Assess.} 2006;18(1):22-32.

25. Buysse DJ, Reynolds CF, 3rd, Monk TH, Berman SR, Kupfer DJ. The
Pittsburgh Sleep Quality Index: a new instrument for psychiatric
practice and research. \emph{Psychiatry research.} 1989;28(2):193-213.

26. Children's Oncology Group. Long-term follow-up guidelines for
survivors of childhood, adolescent and young adult cancers, Version 5.0.
Available from
http://www.survivorshipguidelines.org/pdf/2018/COG\_LTFU\_Guidelines\_v5.pdf.
Published 2018. Accessed.

27. U.S. Department of Health and Human Services. \emph{Physical
Activity Guidelines for Americans, 2nd edition.} Washington, DC: U.S. :
Department of Health and Human Services;2018.

28. Zou G. A modified poisson regression approach to prospective studies
with binary data. \emph{Am J Epidemiol.} 2004;159(7):702-706.

29. Cappuccio FP, D'Elia L, Strazzullo P, Miller MA. Sleep duration and
all-cause mortality: a systematic review and meta-analysis of
prospective studies. \emph{Sleep.} 2010;33(5):585-592.

30. Tonning Olsson I, Lubas MM, Li C, et al. Insomnia and Neurocognitive
Functioning in Adult Survivors of Childhood Cancer. \emph{JNCI Cancer
Spectr.} 2020;4(3):pkaa008.

31. Besedovsky L, Lange T, Haack M. The Sleep-Immune Crosstalk in Health
and Disease. \emph{Physiol Rev.} 2019;99(3):1325-1380.

32. Leproult R, Van Cauter E. Role of sleep and sleep loss in hormonal
release and metabolism. \emph{Endocr Dev.} 2010;17:11-21.

33. Cappuccio FP, Miller MA. Sleep and Cardio-Metabolic
Disease.\emph{Curr Cardiol Rep.} 2017;19(11):110.

34. Thomas SJ, Booth JN, 3rd, Jaeger BC, et al. Association of Sleep
Characteristics With Nocturnal Hypertension and Nondipping Blood
Pressure in the CARDIA Study. \emph{J Am Heart Assoc.}2020;9(7):e015062.

35. Golubic M, Schneeberger D, Kirkpatrick K, et al. Comprehensive
Lifestyle Modification Intervention to Improve Chronic Disease Risk
Factors and Quality of Life in Cancer Survivors. \emph{J Altern
Complement Med.} 2018;24(11):1085-1091.

36. Murawski B, Wade L, Plotnikoff RC, Lubans DR, Duncan MJ. A
systematic review and meta-analysis of cognitive and behavioral
interventions to improve sleep health in adults without sleep
disorders.\emph{Sleep Med Rev.} 2018;40:160-169.

37. Redeker NS, Caruso CC, Hashmi SD, Mullington JM, Grandner M,
Morgenthaler TI. Workplace Interventions to Promote Sleep Health and an
Alert, Healthy Workforce. \emph{J Clin Sleep Med.} 2019;15(4):649-657.

38. Al Khatib HK, Hall WL, Creedon A, et al. Sleep extension is a
feasible lifestyle intervention in free-living adults who are habitually
short sleepers: a potential strategy for decreasing intake of free
sugars? A randomized controlled pilot study. \emph{Am J Clin
Nutr.}2018;107(1):43-53.

39. Baron KG, Duffecy J, Richardson D, Avery E, Rothschild S, Lane J.
Technology Assisted Behavior Intervention to Extend Sleep Among Adults
With Short Sleep Duration and Prehypertension/Stage 1 Hypertension: A
Randomized Pilot Feasibility Study. \emph{J Clin Sleep
Med.}2019;15(11):1587-1597.

40. Chaput JP, Despres JP, Bouchard C, Tremblay A. Longer sleep duration
associates with lower adiposity gain in adult short sleepers. \emph{Int
J Obes (Lond).} 2012;36(5):752-756.

{[}dataset{]} Brinkman TB, Lubas ML, Mandrell BN, Ness KK, Srivastava
DK, Ehrhardt MJ, Wang Z, Hudson MM, Robison LL; 2020; MIND; available
upon request.



\textbf{Figures}

\textbf{Figure 1. Multivariable Associations between Phenotypes of Short
Sleep and Severity/Burden of Physical Health Conditions}

Figure Caption

Reference group = low burden/none; models adjusted for age, sex,
race/ethnicity, body mass index, physical inactivity; long sleepers
removed from analyses.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Figure-1-(1)/Figure-1-(1)}

\end{center}
\end{figure}

\selectlanguage{english}
\FloatBarrier
\end{document}

