Evidence map›Paper›PMID 40042843›Full record

ArticleJAMA network open2025

Trajectories of Sleep Duration, Sleep Onset Timing, and Continuous Glucose Monitoring in Adults.

Luqi Shen, Bang-Yan Li, Wanglong Gou, Xinxiu Liang, Haili Zhong, Congmei Xiao, Ruiqi Shi, Zelei Miao, Yan Yan, Yuanqing Fu and 2 more

Abstract read
In one paragraph

Article in JAMA network open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Observational
  5. Advancing Precision Nutrition Through Multimodal Data and Artificial Intelligence.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  6. Observational
  7. Article
  8. Age-Associated Development of Sleep Disturbances inNature and science of sleep · 2026
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Luqi ShenWestlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China.
Bang-Yan LiGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Wanglong GouWestlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China.
Xinxiu LiangAffiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, China.
Haili ZhongGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Congmei XiaoAffiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, China.
Ruiqi ShiAffiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, China.
Zelei MiaoAffiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, China.
Yan YanGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Yuanqing FuAffiliated Hangzhou First People's Hospital, School of Medicine, Westlake University, Hangzhou, China.
Yu-Ming ChenGuangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Ju-Sheng ZhengWestlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Understanding the interplay between trajectories of sleep duration, sleep onset timing, and glycemic dynamics is crucial for improving preventive strategies against diabetes and related metabolic diseases. Objective: To examine the associations of sleep duration and onset timing trajectories with continuous glucose monitoring (CGM)-derived glycemic metrics in adults. Design, Setting, and Participants: This cohort study analyzed data collected from January 2014 to December 2023 in the Guangzhou Nutrition and Health Study, a prospective cohort in Guangdong province, China, among participants aged 46 to 83. Participants who had repeated sleep assessments at several study visits and were equipped with CGM devices at the last visit were included. Data analyses were conducted between January and June 2024. Exposures: The trajectories of sleep duration and onset timing were constructed using self-report sleep duration and sleep onset timing, recorded at multiple study visit points. Main Outcomes and Measures: Measurements of glycemic variability and glycemic control were collected using a masked CGM device worn by patients for 14 consecutive days. Huber robust regression models were used to assess the associations between sleep trajectories and CGM-derived metrics. Results: In this study of 1156 participants (mean [SD] age, 63.0 [5.1] years, 816 [70.6%] women), we identified 4 distinct sleep duration trajectory groups: severe inadequate, moderate inadequate, mild inadequate, and adequate. Severe sleep inadequacy was associated with an increment of glycemic variability indicators: 2.87% (95% CI, 1.23%-4.50%) for coefficient of variation and 0.06 (95% CI, 0.02-0.09) mmol/L for mean of daily differences. We found 2 trajectories of sleep onset timing: persistent early and persistent late groups. Late sleep onset was associated with larger coefficient of variation (β = 1.18%; 95% CI, 0.36%-2.01%) and mean of daily differences (β = 0.02 mmol/L; 95% CI, 0.01-0.04 mmol/L). Inappropriate sleep duration and timing trajectories in combination were associated with greater glycemic variability. Conclusions and Relevance: In this cohort study of middle-aged and older participants, persistent inadequate sleep duration and late sleep onset, whether alone or in combination, were associated with greater glycemic variability. These findings emphasize the importance of considering both sleep duration and timing for optimizing glycemic control in the general population.

Indexed as

Blood GlucoseBlood Glucose Self-MonitoringSleepAgedAged, 80 and overChinaContinuous Glucose MonitoringFemaleHumansMaleMiddle AgedProspective StudiesSleep DurationTime FactorsBlood Glucose

Identifiers

PMID40042843
PMCPMC11883496

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.