Evidence map›Paper›PMID 41134282›Full record

ArticleSleep2026

Sex differences in bidirectional associations between dimensions of Fitbit-derived sleep and emotional health across 1 year in American Life in Realtime, a nationally representative sample of U.S. adults.

Gina Marie Mathew, Wendy Troxel, Lauren Hale, Ritika R Chaturvedi

Abstract read
In one paragraph

Article in Sleep, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Gina Marie MathewProgram in Public Health, Department of Family, Population, and Preventive Medicine, Renaissance School of Medicine, Stony Brook University, 101 Nicolls Road, Health Sciences Center, Level 3, Room 071, Stony Brook, NY 11794-8338, United States.ORCID 0000-0002-9658-7154
Wendy TroxelRAND, Social and Economic Wellbeing, Pittsburgh, PA, United States.ORCID 0000-0002-2147-8041
Lauren HaleProgram in Public Health, Department of Family, Population, and Preventive Medicine, Renaissance School of Medicine, Stony Brook University, 101 Nicolls Road, Health Sciences Center, Level 3, Room 071, Stony Brook, NY 11794-8338, United States.ORCID 0000-0002-7530-2519
Ritika R ChaturvediCenter for Economic and Social Research, University of Southern California, Los Angeles, CA, United States.ORCID 0000-0002-0416-6134

Funding

Enhancing engagement and participation of marginalized community residents in the UASU01AG077280 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Arie Kapteyn · 2023 to 2026
$50.9M
Toward Next Generation Data on Health and Life Changes at Older Ages: Administrative Supplement to track the effects of the COVID-19 pandemic on American familiesU01AG054580 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI KAPTEYN, ARIE · 2017 to 2022
$27.3M
UAS-CLEAR: A new nationally representative longitudinal study of caregiving experiences and well-being across the lifecourseR01AG083097 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Marco Angrisani, KIRA S BIRDITT · 2023 to 2026
$3.8M
Using passively collected person-generated health data to explore population-specific relationships between social determinants of health, sleep patterns, and cognitive outcomesR01LM013237 · NLM · UNIVERSITY OF SOUTHERN CALIFORNIA · PI CHATURVEDI, RITIKA RATNAM · 2020 to 2023
$1.4M
National Library of Medicine at the National Institutes of Health R01LM013237NIA NIH HHS U01 AG054580NIA NIH HHS U01 AG077280NLM NIH HHS R01AG083097NLM NIH HHS R01 LM013237NLM NIH HHS R01LM013237NLM NIH HHS U01AG054580NLM NIH HHS U01AG077 280NLM NIH HHS U01AG077280-03S1A1Social Security Administration
6 · The paper itself

Abstract

STUDY

objectivesWe examined sex differences in within-person bidirectional and between-person associations between dimensions of Fitbit-measured sleep and multiple self-reported emotional health measures among a large sample of U.S. adults across ~1 year.

methodsData were from American Life in Realtime (ALiR), a probability-based cohort representative of U.S. adults. Participants wore Fitbits to measure sleep and answered monthly questionnaires on depression, anxiety, and stress symptoms. Linear mixed models examined bidirectional associations of nighttime Fitbit sleep measures (mean and SD of total sleep time [TST], clock time of sleep onset [CTSO], and sleep maintenance efficiency [SMEff]) across 14-day intervals that immediately preceded or succeeded each monthly report of emotional health and between-person associations. Analyses adjusted for sociodemographic variables and examined sex differences.

resultsThe sample (n = 733-754) had a mean age of 47.1 ± 14.6, 48.7%F. Generally, within-person findings indicated that shorter and longer TST, poorer SMEff, and greater variability in CTSO and SMEff than one's average predicted higher depression, anxiety, and stress scores in the subsequent monthly report. In reverse, worse-than-average emotional health for a given month predicted poorer sleep health in the succeeding 14 days, with fewer significant associations than models with sleep predicting emotional health. Between-person results consistently showed that, on average, adults with later CTSO and more sleep variability had poorer emotional health. Some findings were stronger in females.

conclusionsPoor sleep predicts worse emotional health and vice versa in a large representative sample, particularly among females, highlighting the need for tailored intervention strategies that consider sex-specific patterns in sleep-emotional health dynamics. Statement of Significance The present study examined bidirectional associations between sleep and emotional health in a population-based sample of several hundred U.S. adults using objective sleep measures (Fitbit-derived) across 1 year. Within-person findings indicated that poor sleep health (shorter and longer total sleep time, lower sleep maintenance efficiency, and more variability in these measures) predicted worse emotional health. Poor sleep more frequently predicted poor emotional health than vice versa. On average, in between-person findings, people with poorer sleep had worse emotional health. Some findings were stronger in females. Using novel longitudinal, high-frequency wearable data from a nationally representative cohort over a year, these findings highlight the need for tailored intervention strategies that consider sex-specific patterns in sleep-emotional health dynamics.

Indexed as

Fitness TrackersSleepAdultAnxietyDepressionFemaleHumansMaleMiddle AgedSelf ReportSex FactorsSleep QualityStress, PsychologicalSurveys and QuestionnairesUnited Statesactigraphyanxietydepressionemotional healthsexsleep maintenance efficiencysleep onsetsleep variabilitystresstotal sleep time

Identifiers

PMID41134282
PMCPMC12951524

What OpenQuestion holds

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LicenceCC BY-NC
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.