Dataset Information

Sleeping More Hours Per Day Than Working Can Prevent New-Onset Diabetes.

ABSTRACT: Objectives: We expressed the combined effect by the ratio of daily sleep time to daily work time. The aim of this study was to discussed the predictive ability of daily sleep hours/work hours (SH/WH) ratio for diabetes risk. Methods: Cox proportional hazards regression was used to calculate the hazard ratios (HRs) of new-onset diabetes. Restricted cubic spline analyses were performed to visualize the influence trend of SH/WH ratio and diabetes risk. Results: The RCS model revealed a non-linear and L-shaped correlation between SH/WH ratio and diabetes risk. Compared with the participates with SH/WH ratio <1, those with a ratio ≥1 had a lower risk of developing diabetes. The multivariable adjusted hazard ratios (HRs) with 95% confidence intervals (CIs) of new-onset diabetes in Q2, Q3, Q4 and Q5 groups compared with Q1 group were 0.82 (0.57, 1.19), 1.05 (0.69, 1.59), 0.57 (0.36, 0.91), 0.66 (0.42, 1.06). The Kaplan-Meier curve showed that Q4 group had lower cumulative incidence. Conclusion: Sleeping longer than working (SH/WH ratio ≥1) can reduce risk for developing diabetes. A minimal risk observed at 1.10-<1.37 (the fourth quintile) of SH/WH ratio.

SUBMITTER: Yu H

PROVIDER: S-EPMC10739384 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Sleeping More Hours Per Day Than Working Can Prevent New-Onset Diabetes.

Yu Haiyan H Zhao Xiaoyu X Zhang Xiaodong X Wei Haishan H Zuo Anju A Guo Yuan Y

International journal of public health 20231208

Objectives: We expressed the combined effect by the ratio of daily sleep time to daily work time. The aim of this study was to discussed the predictive ability of daily sleep hours/work hours (SH/WH) ratio for diabetes risk. Methods: Cox proportional hazards regression was used to calculate the hazard ratios (HRs) of new-onset diabetes. Restricted cubic spline analyses were performed to visualize the influence trend of SH/WH ratio and diabetes risk. Results: The RCS model re ...[more]

PMID: 38144394

Similar Datasets

Project description:BackgroundThe prevalence of smokers among blood donors and the effect of smoking on the quality of donated blood have not been extensively explored. In the present study, we determined the prevalence of smoker donors in a large blood bank in Southern Brazil and evaluated the quality of packed red blood cells (RBCs) from these donors through recommended quality control tests and measurement of carboxyhemoglobin (COHb) levels. We then assessed the influence of smoking habits and abstinence before donation on these parameters.Material and methodsAn observational study was conducted to determine the prevalence of smoking donors, while a prospective cohort study compared conventional hematological and serological parameters and COHb levels at 0, 15, and 30 days after donation in RBCs donated by smokers (N = 31) and nonsmokers (N = 31) and their association with smoking habits and abstinence before donation.ResultsOf 14,428 blood donations received in 1 year, 5.9% were provided by smokers. Storage over time slightly altered some quality parameters, such as hematocrit, hemoglobin, hemolysis, and COHb levels, in RBC packs. COHb levels were higher in RBC packs from smokers (8%) than from non-smokers (2%), and increased as a function of the number of cigarettes smoked daily and time elapsed since the last cigarette smoked before donation. Lower levels were found in RBC packs from donors who smoked fewer than 20 cigarettes per day or remained abstinent for more than 12h before giving blood.ConclusionAlthough cigarette smoke had no significant effect on blood quality parameters such as hematocrit, hemoglobin, or hemolysis, it quadrupled COHb levels in packed RBCs. Abstinence from smoking for more than 12h or smoking fewer than 20 cigarettes daily helped decrease COHb levels.ImplicationsGiven the increasing prevalence of tobacco use worldwide, we suggest blood banks recommend 12h of tobacco abstinence before donation and analyze COHb levels in donated blood as an approach to reduce risk for high-risk recipients.

Project description:BackgroundIt has been posited that high workload and long work hours for trainees could affect the quality and efficiency of patient care. Duty hour restrictions seek to balance patient care and resident education by limiting resident work hours. Through a retrospective cohort study, we investigated whether patient care on an inpatient general medicine service at a large academic medical center is impacted when housestaff work more than 80 hours per week.MethodsWe identified all admissions to a housestaff-run general medicine service between June 25, 2013 and June 29, 2014. Each hospitalization was classified by whether the patient was admitted by housestaff who have worked more than 80 hours per week during their hospitalization. Housestaff computer activity and duty hours were calculated by institutional electronic heath record audit, as well as length of stay and a composite of in-hospital mortality, intensive care unit (ICU) transfer rate, and 30-day readmission rate.ResultsWe identified 4767 hospitalizations by 3450 unique patients; of which 40.9% of hospitalizations were managed by housestaff who worked more than 80 hours that week during their hospitalization. There was a significantly higher rate of the composite outcome (19.2% vs 16.7%, P = .031) for patients admitted by housestaff working more than 80 hours per week during their hospitalization. We found a statistically significant higher length of stay (5.12 vs 4.66 days, P = .048) and rate of ICU transfer (3.53% vs 2.38%, P = .029). There was no statistically significant difference in 30-day readmission rate (13.7% vs 12.8%, P = .395) or in-hospital mortality rate (3.18% vs 2.42%, P = .115). There was no correlation with team census on admission and patient outcomes.ConclusionsPatients taken care of by housestaff working more than 80 hours per week had increased length of stay and number of ICU transfers. There was no association between resident work-hours and patient in-hospital mortality or 30-day readmission rate.

Dataset Information

Sleeping More Hours Per Day Than Working Can Prevent New-Onset Diabetes.

Publications

Sleeping More Hours Per Day Than Working Can Prevent New-Onset Diabetes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets