Relation between sleep quality and glycemic control among type 2 diabetic patients

Diabetes mellitus (DM) is a main public health burden with significant morbidity and mortality worldwide. Egypt is the eighth leading country regarding the prevalence of DM. In 2017, it was estimated that >8 million adults live with DM in Egypt, which represents a prevalence of almost 15%.¹

Glycemic control is the adjustment and maintenance of blood glucose levels within the normal range and is best evaluated by glycated hemoglobin A1c (HbA1c). HbA1c is an indicator of the overall glucose level for the past 2–3 months and has been widely used as the “gold standard” for evaluating glycemic control. In people with type 2 diabetes mellitus (T2DM), glycemic control is cardinal for maintaining health and reducing the risks of diabetes complications, including retinopathy, neuropathy, and nephropathy. Glycemic control may be affected by multiple biological, psychological, and behavioral factors; sleep plays a possible role among these factors.²

Sleep is very crucial and can influence every facet of our daily life. Poor sleep quality also affects our health and well-being. People who sleep well have better cognitive function, good memory, healthier immune systems, increased attentiveness, and show better performance throughout the day. Epidemiologic studies revealed that shorter sleep duration and poor sleep quality can raise the risk of obesity and lifestyle-related diseases such as diseases of the cardiovascular system, T2DM, poor glycemic control, and poor quality of life.³

Previous studies have shown that diabetic patients need to have proper sleep periods to better control their diabetes because sleep is one of the most essential factors in life, and it has influences many metabolic aspects including glucose tolerance.⁴

Community health nurses should be provided health education to maintain good sleep quality such as sleeping in a quiet place and preventing drinking caffeine sources.⁵ And refer any patient with sleep disturbances for treatment to achieve good glycemic control.⁶

Study results reveal that 61.6% of diabetic patients’ ages were >50 years with mean age ±SD 49.6 ± 8.4 and 74.4% were females and married. Concerning education, 39.2% of diabetic patients had secondary education, 54.4% of them had insufficient income, and additionally, of the 64.8% of patients diagnosed with diabetes for 5 years and more, about two-thirds of them were on oral treatment and 68.8% of patients had a family history. Additionally, 68% of them were obese and nearly half of the patients had dyslipidemia (48%).

Table 1 displays the components of the PSQI, including sleep duration, subjective sleep quality, and sleep disturbance were the highest mean score (4.0 ± 0.7, 2.5 ± 0.8, 2.4–0.6) respectively. That is to say, the higher the mean score, the poorer the quality of sleep.

Table 2 demonstrates that according to the PSQI score, 96.8% of diabetic patients had poor sleep quality ≥5. This shows that the higher the score, the poorer the quality of sleep.

Table 3 points to female gender and income that were statistically significant independent positive predictors of PSQI score and the duration of DM, oral + insulin treatment, smoking, and dyslipidemia were independent positive predictors. The regression model explains a 0.27% variation in change of this score as indicated by the r-square value.

Table 4 illustrates that 90.4% of diabetic patients had poor glycemic control HbA1c ≥7. This means the higher the score of 7%, the poorer glycemic control.

Table 5 illustrates that PSQI was a statistically significant independent positive predictor of HbA1c level while income, duration of DM, and smoking were independent positive predictors. The female gender was a statistically significant independent negative predictor of HbA1c level. The regression model explains a 0.10% variation in change of this level as indicated by the r-square value.

Table 6 illustrates that the PSQI score was a statistically significant independent positive predictor of control of DM. And controlled hypertension was an independent positive predictor. The regression model explains a 0.372% variation in DM control as indicated by the r-square value.

Table 7 illustrates the statistically significant relation between glycemic control and sleep efficiency, sleep disturbance, subjective sleep quality, and daytime dysfunction factors (P = 0.046, P = 0.02, P = 0.03, P = 0.001) respectively. It is noticed that patients who had insufficient sleep, sleep disturbance, bad sleep, and daytime dysfunction suffer from poor glycemic control compared to good glycemic control.

Table 8 reveals that a statistically significant relation was found between HbA1c and sleep quality (P = 0.003), It is noticed patients with poor sleep quality had poor glycemic control compared to patients with good sleep quality.

The incidence of sleep disturbance is common among people with type 2 diabetes.¹³ Sleep disturbance could be one of the determinants that impair glycemic control.¹⁴

Concerning characteristics of the study sample, the results showed that the mean age of diabetic patients was 49.6 ± 8.4, and more than two-thirds of them had a positive family history, especially in Tamil Nadu in India. Geetha et al.¹⁵ found that the mean age of the participants was 56.08 ± 10.04 and nearly 68.8% of T2DM patients had a family history of the disease. On the other hand, the majority of diabetic patients were obese and overweight, similar to what was reported from Saudi Arabia by AlShahrani,¹⁶ obesity and overweight prevalence in type II diabetes patients was 85.8%; additionally, about two-thirds of patients were on oral treatment. Similarly, in Mansoura District, Egypt Azzam et al.¹⁷ found that 60% of the subjects were taking oral hypoglycemic agents.

Concerning sleep quality components, the study results revealed that sleep duration, subjective sleep quality, and sleep disturbance were the highest mean score. That is to say, the higher the mean score, the poorer the quality of sleep. As in Japan, where Sakamoto et al.¹⁸ found that sleep duration, subjective sleep quality, and sleep latency had the highest mean score among diabetic patients.

About sleep quality score among diabetic patients, the results showed that most of the diabetic patients had poor sleep quality ≥5. Faulty lifestyle might play an important role in sleep quality such as sleep insufficiency, sleep latency, and short sleep duration. There is confirmation showing that a lack of 3 h of sleep leads to increases in sleep quality score by 5.¹³ In Jordan, this result is similar to Barakat et al.’s finding⁴ which showed that the majority of T2DM patients (81.0%) suffer from poor sleep quality.

Concerning factors affecting PSQI score including female gender was a statistically significant independent positive predictor of PSQI score. This might be due to sleep disorders such as restless legs syndrome (RLS), obstructive sleep apnea (OSA), and insomnia which are more common in women during distinct hormonal and physical changes at specific time points of women’s life span such as menopause, puberty, and pregnancy can influence sleep health and lead to gender-specific clinical disorders.¹⁹

In India, such finding was in agreement with Babu et al.²⁰ who reported that females suffered poor sleep quality when compared to males and this relation was statistically significant.

Also, income was a statistically significant independent positive predictor of the PSQI score. This is perhaps due to differences in personality traits and thinking in life matters. Conversely, a study done by Wu et al.²¹ in China found that lower income was associated with an increased risk of poor sleep quality, and this might be due to cultural differences.

The duration of DM was an independent positive predictor of the PSQI score. This might be due to the longer duration of diabetes connected with complications. Moreover, diabetes patients with poor glycemic control will develop nocturia, resulting in frequent awakenings, which leads to poor sleep quality²² In Ethiopia, this resulted in the same context as Jemere et al.²² clarified that longer duration of diabetes since diagnosis was a factor significantly associated with poor sleep quality.

Also oral and insulin treatments were independent positive predictors of PSQI score. This might be due to nocturnal hypoglycemia leading to sleep disruption and is considered one of the many factors that cause poor sleep quality among diabetics. Longer intervals between self-monitoring glycemia are generally seen during the night and this period is associated with the highest sensitivity to treatment of diabetes²³ In Jordan, in the same context, Barakata et al.⁴ found that poor sleep quality was significantly associated with insulin use while in Sinamangal Khakurel and Shakya²⁴ diabetic patients receiving oral hypoglycemic agents were more likely to have poor sleep quality versus patients receiving insulin only. On the contrary, Rajendran et al.²⁵ did not establish significant relation between sleep quality and the type of treatment of diabetes.

Smoking was an independent positive predictor of PSQI score. This was due to the effect of nicotine consumption in the brain, as nicotine is a mild stimulant to the central nervous system This association might be explained by the effect of snoring resulting from a reduction in breathing (hypopnea) and decrease in oxygen saturation because of smoking.⁴ This finding was in the same context as Liao et al.²⁶ who carried out a study in China, and found that smokers who were diabetic patients had statistically significant and had poor sleep quality and sleep disturbances compared to non-smokers.

Finally, dyslipidemia was an independent positive predictor of the PSQI score. This might be due to statin therapy which is the most common drug for lowering cholesterol levels associated with an increased risk of sleep disturbances including insomnia. In other studies, statin therapy might cause hallucinations and nightmares. Few clinical trials are on evaluating the effect of statins on sleep as a primary outcome. Three of them suggested an essential effect of statins on sleep quality²⁷ In the same line, in China, Zhan et al.²⁸ found that a higher prevalence of dyslipidemia was associated with frequent insomnia compared to those who had no insomnia. A recent study suggested that short sleep duration was associated with higher risks of hypercholesterolemia in adults. Furthermore, according to Mahmood et al.²⁹ subjects with poor sleep quality had higher total cholesterol and triglycerides compared to those with good sleep quality.

Regarding HbA1c level, the study results showed that most of the diabetic patients had poor glycemic control ≥7. This can be explained that patients with DM have less experience regarding risk factors associated with poor glycemic control including poor diet habits and sedentary lifestyle, poor sleep, treatment, and follow-up.³⁰ In Taif Alsaeudia, a similar result was proved by Obaid et al.¹⁴ who found that according to HbA1c, the majority of patients were having uncontrolled DM (83.3%).

Concerning factors affecting the HbA1c level, the study results revealed that income was a statistically significant independent positive predictor of HbA1c level. On the contrary Rutte et al.’s³¹ systematic reviews and meta-analyses showed that there was an inverse association between socioeconomic status and HbA1c levels in people with type 2 diabetes. People of low socioeconomic status have higher HbA1c levels than people of high socioeconomic status. This discrepancy might be because most of the study participants were residing in rural areas and had low income characterized by good sleep habits that help in glycemic control than those who had high income.

The duration of DM was an independent positive predictor of HbA1c level. This is explained by a study done by Khattab et al.³² who reported that a longer duration of diabetes was associated with insulin metabolism disturbance and poor glycemic control. In the same context, In India, Mammoo and Girija³³ realized that the duration of diabetes is one of the reasons for poor glycemic control; there is a statistically significant association between the duration of diabetes for >5 years and uncontrolled DM.

Also, smoking was an independent positive predictor of HbA1c level, and the explanation of this finding is perhaps that smoking is one cause of type 2 diabetes. The more cigarettes a person smokes, the higher the risk for type 2 diabetes forms. In fact, people with diabetes who smoke are more likely than those who don’t smoke to have trouble with insulin dosing and managing their condition resulting in poor glycemic control (U.S. Department of Health and Human Services, 2014).³⁴ This result was in the same line with Choi et al.³⁵ who carried out research in Korea and found that persons who smoke cigarettes had significantly higher HbA1c levels than non-smokers. Additionally, in Japan, Hu et al.³⁶ found that smoking was correlated with poor glycemic control.

While the female gender was a statistically significant independent negative predictor of HbA1c level. From the researcher’s point of view, psychological factors and treatment responses of females play an important role in lowering HbA1c. This result was consistent with that of Yuan et al.³⁷ in Taiwan, China who reported that there was no significant change in HbA1c in males, but there was a 0.10% reduction in females. On the contrary, in Brazil Duarte et al.³⁸ found that HbA1c levels in women were higher than in men and this difference was statistically significant.

Regarding factors that control DM, the results showed that controlled hypertension was an independent positive predictor of control of DM and the explanation might be due to high blood pressure leading to Insulin resistance syndrome.³⁹ So the more control of blood pressure, the lower insulin resistance that leads to control of diabetes. In Ethiopia, in the same line, Muleta et al.⁴⁰ found that uncontrolled blood glucose was an independent predictor of uncontrolled blood pressure. Bad glycemic control was more likely to have hypertension. Therefore, more effort ought to be devoted to controlling the blood pressure in diabetics.

And results showed PSQI score was a statistically significant independent positive predictor of control of DM. From the researcher’s point of view the good sleep quality, the more control of diabetes. Similarly, Zaraspe et al.⁴¹ in the Philippines glucose control is directly associated with sleep quality score. Patients with bad glucose control were more likely to have bad sleep quality.

Concerning the relation between sleep quality and glycemic control, the research results displayed that there was a statistically significant relation between glycemic control and subjective sleep quality, sleep efficiency, sleep disturbance, and daytime dysfunction components. It is noticed that patients who had bad sleep, sleep inefficiency, and the presence of sleep disturbance and daytime dysfunction suffered from poor glycemic control compared to good glycemic control. This reflected that the importance of improving sleep quality components will lead to control of HbA1C and inversely. These findings were supported by a study done by Tsai et al.⁴² in Taiwan which showed that there was a significant association between sleep efficiency and HbA1c these findings propose that low sleep efficiency is strongly associated with poorer glycemic control and in China, Zhu et al.¹³ found that risk factors for poor glycemic control were sleep disturbance and daytime dysfunction. The risk for poor glycemic control would increase when one increases the score of sleep disturbance and daytime dysfunction. Additionally, In Amsterdam, Brouwer et al.⁴³ found that subjective sleep quality was significantly associated with higher HbA1c in individuals with lower efficiency and worse quality.

Also, the current results revealed that a statistically significant relation was established between HbA1c and sleep quality, and it is noticed that patients with poor sleep quality have poor glycemic control compared to patients with good sleep quality. The rationale of this phenomenon might be due to 2 possible causes to explain this relation. First, the cerebral cortex, cerebral limbic system, and hypothalamus, which induce the secretion of catecholamines from the sympathetic ganglion and adrenal medulla and of cortisol from the pituitary–adrenal system is stimulated by sleep deprivation. These hormones may function to raise the plasma glucose level.⁴² Second, activation of the sympathetic nervous system promotes insulin resistance due to elevation of the levels of cortisol and IL-6 resulting from poor sleep quality.³³ The previous finding was supported by several studies carried out by Khakurel and Shakya²⁴ in Sinamangal. There was a significant relation between sleep quality with glycemic control. Mammoo and Girija³³ in Sri Manakula showed a positive correlation between PSQI score and HbA1c. In Iraq Al-Humairi and Hassan³⁰ found a highly statistically significant relationship between the level of HbA1c and sleep quality. There was also a significant increase in the level of HbA1c among patients with type 2 diabetics with poor sleep quality.

The study results bring about the conclusion that poor sleep quality and poor glycemic control were very common among type 2 diabetic patients. There was a highly statistically significant relation between sleep quality and glycemic control.