European Journal of Cardiovascular Medicine

Type 2 Diabetes Mellitus (T2DM) is a major non-communicable disease worldwide and is associated with substantial morbidity due to chronic hyperglycemia and its related complications. According to the International Diabetes Federation, approximately 589 million adults were living with diabetes globally in 2024, and this number is projected to rise sharply in the coming decades, with T2DM accounting for nearly 90% of all cases [1]. India represents one of the largest contributors to this burden, with national estimates suggesting nearly 90 million adults affected, placing a significant strain on healthcare systems, particularly in government tertiary care settings [2]. While long-term glycemic control assessed by HbA1c has traditionally been the cornerstone of diabetes management, increasing evidence suggests that glycemic variability (GV)—short-term fluctuations in blood glucose levels—plays an independent and clinically important role in the development of diabetic complications [3].

Glycemic variability has been linked to oxidative stress, endothelial dysfunction, inflammation, and activation of pro-atherogenic pathways, all of which contribute to both microvascular and macrovascular complications in patients with T2DM [4]. Studies have shown that patients with similar HbA1c levels may have markedly different degrees of glycemic variability, resulting in different risks for complications, highlighting the limitation of relying solely on average glycemic indices [5]. Therefore, identification of modifiable factors influencing glycemic variability has emerged as an important area of contemporary diabetes research.

Sleep is a vital physiological process that regulates metabolic, endocrine, and circadian functions. Poor sleep quality, short sleep duration, and sleep fragmentation have been increasingly recognized as important contributors to metabolic dysregulation. Epidemiological studies have demonstrated that individuals with poor sleep quality have a higher risk of insulin resistance, impaired glucose tolerance, and development of T2DM [6]. In patients already diagnosed with diabetes, disturbed sleep has been associated with suboptimal glycemic control, higher HbA1c levels, and increased risk of complications [7].

Mechanistically, poor sleep quality influences glucose metabolism through multiple pathways, including activation of the hypothalamic–pituitary–adrenal axis, increased sympathetic activity, altered cortisol secretion, and disruption of circadian rhythm–dependent insulin sensitivity [8]. Sleep deprivation and fragmented sleep have also been shown to increase nocturnal glucose excursions and impair counter-regulatory hormonal responses, thereby contributing to increased glycemic variability [9]. Recent studies using continuous glucose monitoring systems have reported that patients with poor sleep quality experience greater intraday and nocturnal glucose fluctuations compared to those with adequate sleep [10].

Despite growing international evidence linking sleep disturbances with glycemic variability, prospective data from Indian populations remain limited, particularly in routine clinical settings. Moreover, sleep quality assessment is often overlooked in standard diabetes care, especially in government hospitals where the focus is primarily on pharmacological glycemic control. Understanding the relationship between sleep quality and glycemic variability may provide an opportunity for low-cost, non-pharmacological interventions aimed at improving overall glycemic stability.

Therefore, the present prospective study titled “Association Between Sleep Quality and Glycemic Variability in Patients With Type 2 Diabetes Mellitus”, conducted at PDU Medical College and attached group of Hospital (Dedraj Bhartiya Hospital -Churu), with a study population of 100 patients over a period of one year, aims to evaluate the association between sleep quality and glycemic variability in patients with T2DM. The findings of this study may help emphasize the importance of sleep assessment as an integral component of comprehensive diabetes management.

The primary aim of this prospective study is to evaluate the association between sleep quality and glycemic variability in patients with Type 2 Diabetes Mellitus. The objectives of the study include assessing sleep quality using a standardized sleep assessment tool, analyzingglycemic variability through appropriate glycemic indices, and comparing glycemic variability parameters between patients with good and poor sleep quality. Additionally, the study aims to determine whether poor sleep quality is independently associated with increased glycemic fluctuations after accounting for routine clinical and metabolic factors.

The future outcomes of this study are expected to provide clinically relevant evidence supporting the role of sleep quality as a modifiable determinant of glycemic stability in patients with Type 2 Diabetes Mellitus. Establishing this association may encourage routine sleep assessment as part of comprehensive diabetes care and promote the incorporation of non-pharmacological sleep-focused interventions to improve glycemic variability. Ultimately, these findings may contribute to better individualized diabetes management strategies, reduction in complication risk, and overall improvement 

This prospective observational study was conducted at PDU Medical College and attached group of Hospital (Dedraj Bhartiya Hospital -Churu), over a period of one year. The study included 100 patients diagnosed with Type 2 Diabetes Mellitus attending the outpatient and inpatient services of the Department of Medicine during the study period. Adult patients aged 18 years and above with a confirmed diagnosis of Type 2 Diabetes Mellitus and willing to provide informed consent were enrolled consecutively. Patients with Type 1 diabetes mellitus, gestational diabetes, acute illness, chronic kidney disease stage 4 or above, known sleep disorders requiring treatment (such as obstructive sleep apnea on therapy), psychiatric illness, shift workers, and those on medications known to significantly affect sleep or glycemic variability were excluded to minimize confounding. Baseline demographic and clinical details including age, sex, duration of diabetes, treatment modality, and comorbid conditions were recorded. Sleep quality was assessed using a validated questionnaire, such as the Pittsburgh Sleep Quality Index (PSQI), with participants categorized into good and poor sleep quality based on standard cut-off scores. Glycemic variability was assessed using capillary blood glucose profiles and/or continuous glucose monitoring–derived parameters, including measures such as standard deviation of glucose values, coefficient of variation, and mean amplitude of glycemic excursions, recorded over a defined monitoring period. HbA1c levels were measured to assess overall glycemic control. All laboratory investigations were performed in the central laboratory following standard operating procedures and quality control measures. Data were entered into Microsoft Excel and analyzed using appropriate statistical software. Continuous variables were expressed as mean and standard deviation, while categorical variables were summarized as frequencies and percentages. The association between sleep quality and glycemic variability parameters was evaluated using Student’s t-test or Mann–Whitney U test for continuous variables and chi-square test for categorical variables, as appropriate. Multivariate analysis was planned to assess the independent association between poor sleep quality and glycemic variability. A p-value of less than 0.05 was considered statistically significant. Ethical approval was obtained from the Institutional Ethics Committee, and the study was conducted in accordance with the principles of the Declaration of Helsinki.

The present study evaluated sleep quality and its association with glycemic variability among patients with Type 2 Diabetes Mellitus. The mean global Pittsburgh Sleep Quality Index (PSQI) score of the study population was 9.42 ± 2.86, indicating an overall poor sleep quality among the participants. More than half of the patients were categorized as having poor sleep quality based on standard PSQI cut-off values. Among the PSQI components, higher mean scores were observed for sleep disturbances, subjective sleep quality, and daytime dysfunction, suggesting that frequent nocturnal disruptions and their daytime consequences were common in this population. In contrast, the use of sleeping medication showed a relatively lower mean score.

When glycemic parameters were analyzed according to sleep quality, patients with poor sleep quality demonstrated consistently higher fasting blood glucose levels and greater glycemic variability compared to those with good sleep quality. Measures of glycemic variability, including standard deviation of glucose values, coefficient of variation, and mean amplitude of glycemic excursions, were markedly elevated in patients with poor sleep quality. Additionally, mean HbA1c levels were higher among poor sleepers, reflecting suboptimal overall glycemic control.

A higher proportion of patients with poor sleep quality exhibited increased glycemic variability compared to those with good sleep quality. These findings indicate a clear association between impaired sleep quality and greater glucose fluctuations in patients with Type 2 Diabetes Mellitus. Overall, the results suggest that poor sleep quality is common in diabetic patients and is significantly associated with increased glycemic variability, underscoring the importance of incorporating sleep assessment into routine diabetes management.

Table 1. Demographic and Clinical Profile of Study Participants (n = 100)

Table 2. Distribution of Sleep Quality Among Study Participants

Table 3. Comparison of Glycemic Variability Parameters According to Sleep Quality

Table 4. Association Between Sleep Quality and Increased Glycemic Variability

The mean global PSQI score of the study population was 9.42 ± 2.86, indicating overall poor sleep quality. Higher mean scores were observed in components related to sleep disturbances, subjective sleep quality, and daytime dysfunction, suggesting that fragmented sleep and its daytime consequences were prominent among patients with Type 2 Diabetes Mellitus. Use of sleep medication showed a comparatively lower mean score.

Figure 1: Association Between Sleep Quality and Glycemic Variability

Figure 2: Mean PSQI Component Scores among T2DM

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In the present prospective study, poor sleep quality was observed in 54% of patients with Type 2 Diabetes Mellitus, with a mean global PSQI score of 9.42 ± 2.86, indicating a substantial burden of sleep disturbance in this population. These findings are comparable with reports from other clinical settings. A multicentric Asian study by Lee et al. reported poor sleep quality in 52–60% of patients with T2DM, with mean PSQI scores ranging between 8.6 and 10.1, closely mirroring the magnitude observed in this study [11]. Similarly, an Indian hospital-based study by Khandelwal et al. documented poor sleep quality in 57% of diabetic patients, reinforcing that sleep disturbance is highly prevalent among Indian patients with T2DM [12]. The consistency across studies suggests that sleep impairment is a common but under-recognized problem in routine diabetes care.

The present study demonstrated that patients with poor sleep quality had significantly higher glycemic variability, reflected by elevated fasting blood glucose, higher standard deviation of glucose values, increased coefficient of variation, and greater mean amplitude of glycemic excursions (MAGE). These findings align with evidence from continuous glucose monitoring–based studies. Reutrakul et al. reported that patients with fragmented or poor-quality sleep exhibited significantly higher nocturnal and intraday glucose fluctuations, independent of HbA1c levels [13]. Likewise, Kachi et al. observed that poor sleepers had higher glucose variability despite comparable mean glucose levels, supporting the concept that sleep quality affects short-term glucose dynamics beyond average glycemic control [14].

In this study, increased glycemic variability was present in 70.4% of patients with poor sleep quality, compared to only 30.4% among those with good sleep quality, indicating a strong association. Comparable proportions have been reported in prior studies. A Japanese prospective study by Ohkuma et al. found that patients with short or poor-quality sleep had nearly twofold higher odds of increased glycemic variability, measured using coefficient of variation and MAGE [15]. Similarly, Zhang et al. demonstrated that poor sleep quality was independently associated with higher glycemic variability indices even after adjusting for age, duration of diabetes, and treatment modality [16]. These findings collectively suggest that sleep quality is an important and independent determinant of glucose instability.

The higher HbA1c levels observed among poor sleepers in the present study further strengthen this association. Previous research has consistently shown that disturbed sleep is linked to worse long-term glycemic control. Shan et al., in a meta-analysis of prospective studies, reported that poor sleep quality and short sleep duration were associated with significantly higher HbA1c levels and poorer diabetes control [17]. Indian data also support this relationship; Srivastava et al. observed that diabetic patients with PSQI scores >5 had significantly higher HbA1c compared to those with better sleep quality [18]. The concurrence of increased glycemic variability and elevated HbA1c among poor sleepers highlights the dual impact of sleep disturbance on both short-term and long-term glycemic regulation.

From a pathophysiological perspective, the findings of this study are biologically plausible. Poor sleep quality leads to activation of the sympathetic nervous system, dysregulation of cortisol secretion, and disruption of circadian rhythms, all of which contribute to impaired insulin sensitivity and exaggerated glucose excursions. Experimental sleep restriction studies have shown increased insulin resistance and impaired glucose tolerance within days of sleep deprivation, supporting a causal link between sleep disturbance and glycemic instability [19]. Moreover, recurrent nocturnal arousals may blunt counter-regulatory hormonal responses, thereby increasing glucose variability, particularly during night-time and early morning hours [20].

Overall, the findings of this study are in concordance with existing international and Indian literature and add prospective evidence from a government tertiary care setting. The strong association between poor sleep quality and increased glycemic variability underscores the need to view sleep assessment as an integral component of diabetes management rather than an ancillary concern.

This prospective study demonstrates that poor sleep quality is highly prevalent among patients with Type 2 Diabetes Mellitus and is significantly associated with increased glycemic variability. Patients with impaired sleep quality exhibited greater short-term glucose fluctuations and higher HbA1c levels compared to those with good sleep quality, highlighting the adverse impact of sleep disturbance on both immediate and long-term glycemic control. These findings suggest that sleep quality is an important, yet often overlooked, modifiable factor influencing glycemic stability in patients with T2DM. Incorporating routine sleep assessment into diabetes care may help identify high-risk patients and improve overall metabolic outcomes. Limitations The study has certain limitations that should be acknowledged. The sample size was relatively modest and drawn from a single tertiary care center, which may limit the generalizability of the results. Sleep quality was assessed using a subjective questionnaire rather than objective sleep measures such as polysomnography or actigraphy. Glycemic variability was assessed over a limited monitoring period, which may not fully capture long-term glucose fluctuations. Additionally, potential confounders such as stress levels, physical activity, dietary patterns, and undiagnosed sleep disorders like obstructive sleep apnea were not comprehensively evaluated. Recommendations Based on the findings of this study, routine assessment of sleep quality should be considered as part of comprehensive diabetes management. Early identification of poor sleep quality may allow timely implementation of non-pharmacological interventions such as sleep hygiene counseling, lifestyle modification, and stress management strategies to improve glycemic variability. Larger multicentric studies with longer follow-up and incorporation of objective sleep assessments are recommended to further elucidate the causal relationship between sleep quality and glycemic variability. Future research should also explore whether targeted sleep-improvement interventions can lead to sustained improvements in glycemic control and reduction in diabetes-related complications.

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