Evidence mapPaperPMID 41250757Full record

ArticlePeerJ2025

Prevalence of poor sleep quality and its associated factors in patients with concurrent type 2 diabetes mellitus and hypertension.

Ziling Feng, Hongying Liu, Ni Xiong, Leyao Tang, Wenjie Dai, Fang Yang

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Article in PeerJ, 2025. 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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5 · Who and what money

Authors and funding

6 authors.

Ziling FengDepartment of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, Hunan Province, China.
Hongying LiuMedical Department, Hunan Prevention and Treatment Institute for Occupational Diseases, Affiliated Prevention and Treatment Institute for Occupational Diseases of University of South China, Changsha, Hunan Province, China.
Ni XiongDepartment of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, Hunan Province, China.
Leyao TangDepartment of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, Hunan Province, China.
Wenjie DaiDepartment of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, Hunan Province, China.
Fang YangMedical Simulation Center, 921 Hospital, Changsha, Hunan Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The coexistence of type 2 diabetes mellitus (T2DM) and hypertension can impair sleep quality, potentially leading to a wide range of adverse health outcomes. Therefore, this study aimed to evaluate sleep quality and its associated factors in patients with concurrent T2DM and hypertension in Hunan, China. Methods: This cross-sectional study recruited patients with concurrent T2DM and hypertension who visited the Department of Endocrinology at the First People's Hospital of Ruanjiang City, Hunan Province, China, between July 2022 and February 2023. Trained investigators conducted face-to-face interviews to collect data on sociodemographic, lifestyle, and disease-related factors, and assessed anxiety and sleep quality using the Generalized Anxiety Disorder-7 scale and the Pittsburgh Sleep Quality Index, respectively. Multivariable logistic regression analysis was performed to identify factors independently associated with sleep quality. A receiver operating characteristic (ROC) curve was generated to evaluate the predictive ability of the model, and the Hosmer-Lemeshow test was used to assess model calibration. Subgroup analyses were conducted by sex, educational level, and number of T2DM complications to test model robustness. Results: A total of 475 patients with concurrent T2DM and hypertension were included. The prevalence of poor sleep quality was 59.4% (95% confidence interval (CI) [54.9%-63.9%]). Multivariable logistic regression analysis showed that advanced age (adjusted odds ratio (aOR) = 2.12, 95% CI [1.29-3.48]), history of stroke (aOR = 2.16, 95% CI [1.15-4.06]), and anxiety (aOR = 4.24, 95% CI [2.58-6.98]) were associated with higher odds of poor sleep quality. Regular physical activity was associated with lower odds (aOR = 0.53, 95% CI [0.34-0.84]). The area under the receiver operating characteristic (ROC) curve was 0.776 (95% CI [0.735-0.818]), and the Hosmer-Lemeshow test ( Conclusions: Nearly three-fifths of patients with concurrent T2DM and hypertension exhibited poor sleep quality. Age, regular physical activity, history of stroke, and anxiety were significantly associated with sleep quality. However, due to the cross-sectional design, causal relationships cannot be established.

Indexed as

Diabetes Mellitus, Type 2HypertensionSleep QualitySleep Wake DisordersAdultAgedAnxietyChinaCross-Sectional StudiesFemaleHumansMaleMiddle AgedPrevalenceRisk FactorsAssociated factorsHypertensionPrevalenceSleep qualityType 2 diabetes mellitus

Identifiers

PMID41250757
PMCPMC12619938

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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 Socratic graph.