Journal of health research in community

Introduction
Diabetes mellitus is one of the leading causes of morbidity and premature mortality worldwide, with type 2 diabetes mellitus (T2DM) accounting for nearly 90% of all cases [1]. The prevalence of diabetes has been steadily increasing in developing countries, including Iran, creating a substantial public health burden [4]. Beyond well-recognized microvascular and macrovascular complications, sleep disturbances have emerged as an important yet underrecognized problem among patients with T2DM. Growing evidence suggests a bidirectional relationship between sleep quality and glycemic control. Poor sleep may impair glucose metabolism, increase insulin resistance, and alter neuroendocrine regulation, while hyperglycemia-related symptoms, such as nocturia and discomfort may disrupt sleep continuity [9]. Some previous Iranian studies have reported a high prevalence of poor sleep quality among individuals with diabetes [12]. Considering that sleep quality is regarded as a significant challenge in patients with T2DM, this study aimed to investigate sleep quality in T2DM patients in Khalkhal city and its relationship with blood glucose levels and demographic factors.

Methods 
This cross-sectional study was conducted on patients with confirmed T2DM who attended health centers in Khalkhal city, Iran. The sample size was calculated using the formula N= (Z 1-α/2)2σ2/d2 based on a previous study, with a 95% confidence level, Z 1-α/2=1.96, σ=3.7, and d=0.55, resulting in 174 participants. Considering approximately 10% attrition rate, the final sample size was increased to 190. Cluster random sampling was applied to ensure representation from different regions of the city. Khalkhal city was divided into four geographical regions; one health center from each region was randomly selected. Eligible patients were identified from the diabetes registry of each center, and participants were randomly recruited proportionate to the population covered by each center (47 participants from regions 1 and 2, and 48 participants from regions 3 and 4). Inclusion criteria were a confirmed diagnosis of T2DM, willingness to participate, and availability of a documented fasting blood glucose (FBG) result within the past month. Exclusion criteria included diagnosed psychiatric disorders (e.g., depression, anxiety, and bipolar disorder), the use of sedative or antidepressant medications, and incomplete questionnaires.
Data were collected using a demographic and clinical checklist (age, sex, marital status, education level, occupation, place of residence, duration of diabetes, medications, and FBG levels) and the Pittsburgh Sleep Quality Index (PSQI). The PSQI consists of 19 self-rated items generating seven component scores assessing sleep quality over the past month. The global score ranges from 0 to 21, with higher scores indicating poorer sleep quality; a global score of >5 is commonly used to define poor sleep quality.
Data analysis was performed using SPSS software, version 26. Independent t-tests and chi-square tests compared baseline characteristics between men and women. Linear regression analyses assessed the associations between FBG levels, age, duration of diabetes, and PSQI score, while logistic regression analysis was used to determine the odds ratio (OR) of sleep disturbance (dependent variable) according to FBG levels (independent variable) in three models (Model 1: crude; Model 2: adjusted for age and sex; Model 3: additionally adjusted for marital status, place of residence, education level, occupation, duration of illness, and type of medication).

Results
The mean age of participants was 53.08±16.59 years. Men were significantly older than women (P=0.005). Significant differences were observed between men and women regarding occupational status and marital status (P<0.05). Overall, 84.2% (n=160) of participants had poor sleep quality (PSQI >5).
Linear regression analysis showed a significant positive association between FBG levels and PSQI score in all models. Regarding the duration of diabetes, a significant association with PSQI score was observed in the crude model (P<0.001) and in Model 2 (P=0.01). However, in the fully adjusted model, the association was attenuated and was no longer statistically significant (P=0.10). Age showed a significant association with PSQI score in the crude model (P<0.001), but this relationship disappeared after full adjustment (P=0.37). Multivariable logistic regression confirmed the positive significant association between FBG levels and poor sleep quality. In the crude model, each unit increase in FBG levels increased the odds of poor sleep quality by 13% (OR=1.13; 95% CI: 1.06–1.20; P<0.001). This association remained significant in the age- and sex-adjusted model (OR=1.13; 95% CI: 1.06–1.21; P<0.001) and in the fully adjusted model (OR=1.12; 95% CI: 1.05–1.20; P<0.001). 

Conclusion 
The present study demonstrated a high prevalence of poor sleep quality among patients with T2DM in Khalkhal city, consistent with previous Iranian findings [12]. Importantly, FBG levels were independently associated with sleep quality across all regression models, supporting the evidence that hyperglycemia and sleep disturbances may have a reciprocal relationship [9]. Poor glycemic control may disrupt sleep through metabolic and neuroendocrine mechanisms, while impaired sleep may worsen insulin resistance. Additionally, duration of diabetes was associated with sleep quality in crude analyses. It is suggested to investigate the relationship between other variables of blood glucose status, including glycosylated hemoglobin and insulin resistance, and both the quality and quantity of sleep in patients with diabetes in future studies.

Ethical Considerations
Compliance with ethical guidelines
This study was approved by the Ethics Committee of Khalkhal University of Medical Sciences (Code: IR.KHALUMS.REC.1403.013). 

Funding
This study was supported by the Student Research and Technology Committee of Khalkhal University of Medical Sciences.

Authors contributions
Study design, data analysis, and manuscript drafting: Vahideh Aghamohammadi; Study design and manuscript drafting: Khadijeh Nasiri; Study design and data analysis and interpretation: Elahe Mohammadi; Study design, data analysis, and manuscript drafting: Hadi Bazyar; Data collection: Roxana Rahmani, Neda Gheidel, Mohadeseh Toloui and Haniyeh Saghi; All authors read and approved the final version of the manuscript.

Conflicts of interest
The authors declared no conflicts of interest.

Acknowledgments
The authors sincerely thank all participants and the staff of health centers in Khalkhal city for their valuable cooperation.


References

1. Smith J, Lee K, Zhao H, Patel M, Nguyen T, Garcia L, et al. The Description and Prediction of Incidence, Prevalence, Mortality, DisabilityAdjusted Life Years Cases, and Corresponding AgeStandardized Rates for Global Diabetes. Diabetes Res Clin Pract. 2024; 205:110231.
2. Sah AK, Srinivasarao D, David N, Agarwal S, Simha V, Mishra P, et al. A review on type 2 diabetes mellitus: Pathophysiology, risk factors, and vascular complications. Biomed Pharmacol J. 2025; 18(4):171-182. [DOI:10.13005/bpj/3283]
3. Aamodt KI, Powers AC, Miller LM, Johnson CK, Lee SY, Wu J, et al. The pathophysiology, presentation and classification of Type 1 diabetes. Diabetes Obes Metab. 2025; 27(Suppl 6):15-27. [DOI:10.1111/dom.16628] [PMID]
4. NCD Risk Factor Collaboration (NCD-RisC). Worldwide trends in diabetes prevalence and treatment from 1990 to 2022: a pooled analysis of 1108 population-representative studies with 141 million participants. Lancet. 2024; 404(10467):2077-93. [DOI:10.1016/s0140-6736(24)02317-1] [PMID]
5. Duncan BB MD, Boyko EJ. IDF diabetes atlas 11th edition 2025: Global prevalence and projections for 2050. Nephrol Dial Transplant. 2025; gfaf177. [DOI:10.1093/ndt/gfaf177] [PMID]
6. Peimani M, Esfahani Z, Bandarian F, Esmaeili S, Moghaddam SS, Namazi N, et al. The Burden of Type 2 Diabetes Mellitus and Attributable Risk Factors in Iran, 1990-2019: Results from the Global Burden of Disease Study 2019. Iran J Public Health. 2024; 53(4):913-23. [DOI:10.18502/ijph.v53i4.15569] [PMID]
7. No Author. Atlas of STEPwise approach to noncommunicable disease (NCD) risk factor surveillance (STEPs) 2021. 2022. Available from: [Link]
8. Kunutsor SK, Balasubramanian VG, Zaccardi F, Gillies CL, Aroda VR, Seidu S, et al. Glycaemic control and macrovascular and microvascular outcomes: A systematic review and meta-analysis of trials investigating intensive glucose-lowering strategies in people with type 2 diabetes. Diabetes Obes Metab. 2024; 26(6):2069-81. [DOI:10.1111/dom.15511] [PMID]
9. Van Someren EJW. Brain mechanisms of insomnia: New perspectives on causes and consequences. Physiol Rev. 2021; 101(3):995-1046. [DOI:10.1152/physrev.00046.2019] [PMID]
10. Direksunthorn T. Sleep and cardiometabolic health: A narrative review of epidemiological evidence, mechanisms, and interventions. Int J Gen Med. 2025; 18:5831-43. [DOI:10.2147/IJGM.S563616] [PMID]
11. Shah AS, Pant MR, Bommasamudram T, Nayak KR, Roberts SSH, Gallagher C, et al. Effects of sleep deprivation on physical and mental health outcomes: An umbrella review. Am J Lifestyle Med. 2025; 15598276251346752. [DOI:10.1177/15598276251346752] [PMID]
12. Khorasani ZM, Ravan VR, Hejazi S. Evaluation of the Prevalence of Sleep Disorder Among Patients with Type 2 Diabetes Mellitus Referring to Ghaem Hospital from 2016 to 2017. Curr Diabetes Rev. 2021; 17(2):214-21. [DOI:10.2174/1573399816666200527140340] [PMID]
13. Borzouei S, Ahmadi A, Pirdehghan A. Sleep quality and glycemic control in adults with type 2 diabetes mellitus. J Fam Med Prim Care. 2024; 13(8):3398-402. [DOI:10.4103/jfmpc.jfmpc_118_24] [PMID]
14. Ahmadiyan M, Ziaeirad M. The relationship between sleep quality and metabolic control indicators in patients with diabetes. Nurs Midwifery J. 2023; 20(12):1024-34. [DOI:10.52547/unmf.20.12.1024]
15. No Author. International Diabetes Federation [Internet]. 2026 [Updated 11 Aril 2026]. Available from: [Link]
16. Shamshirgaran SM, Ataei J, Malek A, Iranparvar-Alamdari M, Aminisani N. Quality of sleep and its determinants among people with type 2 diabetes mellitus in Northwest of Iran. World J Diabetes. 2017; 8(7):358-64. [DOI:10.4239/wjd.v8.i7.358] [PMID]
17. Kia NS, Gharib E, Doustmohamadian S, Mansori K, Ghods E. Factors affecting sleep quality in patients with type 2 diabetes: A cross-sectional study in Iran. Middle East Curr Psychiatry. 2023; 30(1):40. [DOI:10.1186/s43045-023-00310-8]
18. Torabi M, Izadi A, Naderifar M, Shamsaei F. Sleep Quality and Quality of Life in Adults with Type 2 Diabetes. J Diabetes Nurs. 2014; 2(1):51-61. [Link]
19. Buysse DJ, Reynolds III CF, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: A new instrument for psychiatric practice and research. Psychiatry Res. 1989; 28(2):193-213. [DOI:10.1016/0165-1781(89)90047-4] [PMID]
20. Kakouei H, Zare S, Akhlagi AA, Panahi D. Evaluation of Sleep Quality in Bus Drivers in Tehran. Traffic Manage Stud. 2010; 5(16):1-10. [Link]
21. Barakat S, Abujbara M, Banimustafa R, Batieha A, Ajlouni K. Sleep quality in patients with type 2 diabetes mellitus. J Clin Med Res. 2019; 11(4):261-70. [DOI:10.14740/jocmr2947w] [PMID]
22. Tsai YW, Kann NH, Tung TH, Chao YJ, Lin CJ, Chang KC, et al. Impact of subjective sleep quality on glycemic control in type 2 diabetes mellitus. Fam Pract. 2012; 29(1):30-5. [DOI:10.1093/fampra/cmr041] [PMID]
23. Cho EH, Lee H, Ryu OH, Choi MG, Kim SW. Sleep disturbances and glucoregulation in patients with type 2 diabetes. J Korean Med Sci. 2014; 29(2):243. [DOI:10.3346/jkms.2014.29.2.243] [PMID]
24. Jemere T, Mossie A, Berhanu H, Yeshaw Y. Poor sleep quality and its predictors among type 2 diabetes mellitus patients attending Jimma University Medical Center, Jimma, Ethiopia. BMC Res Notes. 2019; 12:1-6. [DOI:10.1186/s13104-019-4531-6] [PMID]
25. Sargolzaei MS, Kohestani D. Sleep quality in diabetic patients in Iran: A review. Payesh (Health Monitor). 2020; 19(4):391-404. [DOI:10.29252/payesh.19.4.391]
26. Sadeghi Sedeh B, Talaei A, Parham M, Sadeghi A, Sadeghi Sedeh S. Comparison of quality and type of sleep disorders in good control and uncontroled diabetic type2 patients. J Shahrekord Univ Med Sci. 2017; 19(3):65-75. [Link]
27. Wan Mahmood WA, Draman Yusoff MS, Behan LA, Di Perna A, Kyaw Tun T, McDermott J, et al. Association between sleep disruption and levels of lipids in Caucasians with type 2 diabetes. Int J Endocrinol. 2013; 2013(1):341506. [DOI:10.1155/2013/341506] [PMID]
28. Kuo CP, Lu SH, Huang CN, Liao WC, Lee MC. Sleep quality and associated factors in adults with type 2 diabetes: A retrospective cohort study. Int Jf Environ Res Public Health. 2021; 18(6):3025. [DOI:10.3390/ijerph18063025] [PMID]