Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder characterized by insulin resistance and hyperglycemia, affecting millions worldwide. Its prevalence is steadily rising due to sedentary lifestyles, unhealthy diets, and increasing obesity rates, posing a significant burden on healthcare systems globally (1). Glycemic control, commonly assessed by fasting plasma glucose (FPG), postprandial glucose (PPG), and glycated hemoglobin (HbA1c), is critical in reducing the risk of diabetes-related complications such as neuropathy, nephropathy, retinopathy, and cardiovascular disease (2).

Recent research has increasingly focused on the influence of non-traditional factors, such as sleep quality, on glycemic control. Sleep is a vital physiological process that plays a key role in metabolic regulation. Disturbances in sleep patterns, including poor sleep quality, short sleep duration, and sleep apnea, have been associated with insulin resistance, elevated inflammatory markers, and impaired glucose metabolism (3,4). The Pittsburgh Sleep Quality Index (PSQI) is a widely used and validated tool to assess sleep quality, incorporating aspects such as sleep duration, latency, disturbances, and daytime dysfunction (5).

Emerging evidence indicates that individuals with T2DM frequently experience sleep disturbances, which may contribute to poorer glycemic outcomes (6). However, the extent and nature of this association remain underexplored, particularly in diverse populations with varying sociocultural and clinical backgrounds. Therefore, this study aims to assess sleep quality in patients with T2DM and to evaluate its correlation with glycemic control indicators, thereby highlighting the potential role of sleep assessment in comprehensive diabetes management.

A total of 150 patients diagnosed with type 2 diabetes mellitus, aged between 35 and 65 years, were enrolled consecutively from the outpatient clinic. Inclusion criteria comprised individuals with a confirmed diagnosis of T2DM for at least one year and stable treatment regimen for the past three months. Patients with known psychiatric illness, diagnosed sleep disorders (e.g., obstructive sleep apnea), use of sedatives, or those with comorbid conditions such as chronic kidney disease or hepatic failure were excluded from the study.

Data Collection:

At baseline, a detailed history was taken including duration of diabetes, medication use, lifestyle habits (smoking, alcohol consumption), and body mass index (BMI) was calculated. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), a standardized questionnaire that evaluates seven domains of sleep over the past month. A global PSQI score >5 was indicative of poor sleep quality.

Glycemic Parameters:

Fasting plasma glucose (FPG), postprandial glucose (PPG), and glycated hemoglobin (HbA1c) were measured at baseline and at 6-month follow-up using standard laboratory techniques. Blood samples were collected following at least 8 hours of fasting. HbA1c was measured using high-performance liquid chromatography (HPLC).

Study Groups:

Based on the PSQI global score, participants were classified into two groups:

• Good Sleepers (PSQI ≤ 5)
• Poor Sleepers (PSQI > 5)

Statistical Analysis:

Data were entered and analyzed using SPSS version 25.0. Continuous variables were presented as mean ± standard deviation (SD), and categorical variables as percentages. Independent t-tests were used to compare glycemic parameters between groups. Pearson’s correlation coefficient was applied to assess the relationship between PSQI scores and HbA1c. A p-value <0.05 was considered statistically significant.

A total of 150 patients with type 2 diabetes mellitus were included in the study. The mean age of the participants was 52.6 ± 8.1 years, with 58% (n=87) being male and 42% (n=63) female. Based on PSQI scores, 88 participants (58.7%) were classified as poor sleepers, while 62 (41.3%) had good sleep quality.

Baseline Characteristics

Table 1 presents the demographic and clinical profiles of the study population. No significant difference was found between the groups in terms of age, gender distribution, BMI, or duration of diabetes (p>0.05).

Table 1: Baseline characteristics of study participants

Glycemic Parameters and Sleep Quality

A significant difference was observed in glycemic control between the two groups. Poor sleepers had higher mean fasting plasma glucose (FPG), postprandial glucose (PPG), and HbA1c values compared to good sleepers (p<0.01 for all comparisons), as shown in Table 2.

Table 2: Comparison of glycemic parameters between good and poor sleepers

Correlation Between Sleep Quality and Glycemic Control

A moderate positive correlation was observed between PSQI scores and HbA1c levels (r = 0.42, p < 0.01), as illustrated in Table 3. Similarly, PSQI showed positive correlations with FPG (r = 0.39, p < 0.01) and PPG (r = 0.35, p < 0.01), indicating that poorer sleep quality was associated with worse glycemic outcomes.

Table 3: Correlation between PSQI score and glycemic parameters

These findings suggest a statistically significant relationship between poor sleep quality and elevated glycemic markers in patients with T2DM (Tables 2 and 3).

The present prospective cohort study demonstrated a significant association between poor sleep quality and suboptimal glycemic control in patients with type 2 diabetes mellitus (T2DM). Our findings revealed that patients with poor sleep, as determined by PSQI scores >5, had significantly higher fasting plasma glucose, postprandial glucose, and HbA1c levels compared to those with good sleep quality. These results are consistent with the growing body of evidence linking sleep disturbances to impaired glucose metabolism and poor diabetes outcomes.

Sleep is increasingly recognized as an important determinant of metabolic health. It influences glucose homeostasis through neuroendocrine regulation involving cortisol, growth hormone, leptin, and insulin sensitivity (1). Experimental studies have shown that sleep restriction leads to decreased insulin sensitivity and increased sympathetic activity, which may contribute to poor glycemic control in individuals with T2DM (2,3). Our findings align with those of Knutson et al., who reported that shorter sleep duration and lower sleep quality were associated with higher HbA1c levels in diabetic patients (4).

In our study, poor sleepers constituted approximately 59% of the population, highlighting the high prevalence of sleep disturbances in T2DM patients. Similar rates have been reported in previous studies, where the prevalence of poor sleep in diabetic cohorts ranged between 50% and 70% (5,6). Factors such as nocturia, peripheral neuropathy, and psychological stress associated with chronic illness may contribute to disturbed sleep in this group (7).

The significant correlation observed between PSQI scores and HbA1c levels (r = 0.42) in our study reinforces the hypothesis that poor sleep quality is a modifiable risk factor for poor glycemic control. Buxton et al. demonstrated in a controlled setting that even partial sleep restriction could lead to increased insulin resistance, supporting a causal role for inadequate sleep in metabolic dysfunction (8). Furthermore, a meta-analysis by Lee et al. concluded that poor sleep quality is independently associated with elevated HbA1c levels in patients with T2DM (9).

In addition to glycemic indices, previous research has suggested that poor sleep may exacerbate systemic inflammation, contributing to insulin resistance and beta-cell dysfunction (10,11). Cytokines such as IL-6 and TNF-α are elevated in individuals with disrupted sleep, which may worsen diabetic outcomes (12). Sleep deprivation also leads to increased evening cortisol levels, which impairs insulin action and promotes gluconeogenesis, further contributing to hyperglycemia (13).

Interestingly, interventions aimed at improving sleep quality have shown promise in enhancing glycemic control. Studies on cognitive-behavioral therapy for insomnia and sleep hygiene education in diabetic populations have demonstrated reductions in HbA1c levels and improvements in sleep metrics (14). These findings support the integration of sleep assessments and interventions into routine diabetes care.

Despite the robust associations observed, our study has certain limitations. The reliance on self-reported sleep quality may introduce subjective bias. Objective assessments such as actigraphy or polysomnography could provide more precise sleep data. Additionally, we did not assess for comorbid sleep disorders such as obstructive sleep apnea, which are known to be prevalent among diabetic patients and may confound results (15).

In conclusion, this study reinforces the growing recognition of sleep quality as a critical but often overlooked factor in the management of T2DM. Addressing sleep disturbances may offer a novel and effective approach to optimizing glycemic control and reducing diabetes-related complications.

1. Borzouei S, Ahmadi A, Pirdehghan A. Sleep quality and glycemic control in adults with type 2 diabetes mellitus. J Family Med Prim Care. 2024;13(8):3398–402. doi:10.4103/jfmpc.jfmpc_118_24.
2. Bener A, Al-Hamaq AOAA, Agan AF, Öztürk M, Ömer A. Sleeping disturbances and predictor risk factors among type 2 diabetic mellitus patients. Ann Afr Med. 2020;19(4):230–6. doi:10.4103/aam.aam_51_19.
3. Shibabaw YY, Dejenie TA, Tesfa KH. Glycemic control and its association with sleep quality and duration among type 2 diabetic patients. Metabol Open. 2023;18:100246. doi:10.1016/j.metop.2023.100246.
4. Tang Y, Meng L, Li D, Yang M, Zhu Y, Li C, et al. Interaction of sleep quality and sleep duration on glycemic control in patients with type 2 diabetes mellitus. Chin Med J (Engl). 2014;127(20):3543–7.
5. Khakurel G, Shakya D, Chalise P, Chalise S. Association of subjective sleep quality and glycemic level in patients with type 2 diabetes mellitus: a cross sectional study. Kathmandu Univ Med J (KUMJ). 2020;18(70):107–10.
6. Swami V, Yadav SK, Saxena P, Sharma A, Dash CK, Gupta A. Study of glycemic variability in well-controlled type 2 diabetic patients using continuous glucose monitoring system. J Assoc Physicians India. 2024;72(1):18–21. doi:10.59556/japi.71.0441.
7. Denic-Roberts H, Costacou T, Orchard TJ. Subjective sleep disturbances and glycemic control in adults with long-standing type 1 diabetes: the Pittsburgh's Epidemiology of Diabetes Complications study. Diabetes Res Clin Pract. 2016;119:1–12. doi:10.1016/j.diabres.2016.06.013.
8. Gozashti MH, Eslami N, Radfar MH, Pakmanesh H. Sleep pattern, duration and quality in relation with glycemic control in people with type 2 diabetes mellitus. Iran J Med Sci. 2016;41(6):531–8.
9. Farooque R, Herekar F, Iftikhar S, Patel MJ. The frequency of poor sleep quality in patients with diabetes mellitus and its association with glycemic control. Cureus. 2020;12(11):e11608. doi:10.7759/cureus.11608.
10. 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):261–6. doi:10.14740/jocmr2947w.
11. 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.
12. Rusu A, Ciobanu D, Bala C, Cerghizan A, Roman G. Social jetlag, sleep-related parameters, and glycemic control in adults with type 1 diabetes: results of a cross-sectional study. J Diabetes. 2019;11(5):394–401. doi:10.1111/1753-0407.12867.
13. Muniyapillai T, Kulothungan K, Aswin A, R A, G G, Z HK, et al. Effect of self-care activities and behaviors on glycemic control in patients with diabetes at a tertiary care hospital in Perambalur, South India: a cross-sectional study. Cureus. 2024;16(1):e52188. doi:10.7759/cureus.52188.
14. Suteau V, Saulnier PJ, Wargny M, Gonder-Frederick L, Gand E, Chaillous L, et al. Association between sleep disturbances, fear of hypoglycemia and psychological well-being in adults with type 1 diabetes mellitus: data from cross-sectional VARDIA study. Diabetes Res Clin Pract. 2020;160:107988. doi:10.1016/j.diabres.2019.107988.
15. McAdam-Marx C, Bellows BK, Unni S, Wygant G, Mukherjee J, Ye X, et al. Impact of adherence and weight loss on glycemic control in patients with type 2 diabetes: cohort analyses of integrated medical record, pharmacy claims, and patient-reported data. J Manag Care Spec Pharm. 2014;20(7):691–700. doi:10.18553/jmcp.2014.20.7.691.