Blood sugar control and sleep quality -
We created a modified PSQI score by removing the sleep duration component to assess sleep quality independently from sleep quantity. The PSQI does not assess the presence of SRBD, which is frequent in type 2 diabetes.
Subjects were classified as at high risk of SRBD if they indicated on the PSQI that their sleep was disturbed 3 or more times per week because of difficulty breathing or coughing or snoring.
Subjects who responded that their bed partners had noticed loud snoring or pauses in breathing during sleep 1 or more times per week were also classified as at high risk.
Finally, this high-risk group included 12 patients who indicated during the interview that they had SRBD. All other subjects were classified as at low risk of SRBD. The interview included the item Center for Epidemiologic Studies Depression Scale CES-D.
We obtained total GHb or HbA 1c values from the medical charts. Midway through the study, the University of Chicago Laboratories switched from measuring GHb by Bio-Rad Variant Classic boronate affinity-automated high-performance liquid chromatography [HPLC] to HbA 1c by Bio-Rad Variant II ion exchange automated HPLC Bio-Rad Laboratories, Hercules, Calif.
The intra-assay coefficient of variation was 0. We converted GHb values to HbA 1c using the following equation:. All statistical analyses were computed using SPSS Hemoglobin A 1c had a right-skewed distribution.
Therefore, we used the natural log of HbA 1c lnHbA 1c in correlation and general linear model GLM analysis. Perceived sleep debt was used as the primary variable to quantify the impact of sleep duration because it incorporates individual differences in sleep need.
We also repeated the analyses using weekly sleep duration rather than perceived sleep debt. We used the modified PSQI score as a marker of sleep quality.
Finally, we calculated GLM for the dependent variable, lnHbA 1c , including both categorical and continuous variables. The first model included 2 sleep variables as well as covariates and all first-degree interactions. Because a significant interaction term that includes a sleep variable and a categorical variable indicates that the association between sleep and glycemic control is different for the different categories, we planned to stratify our regression analyses according to any significant interactions that included a categorical variable and a sleep variable.
The sample included 42 men and women. Table 2 provides descriptive statistics. The mean HbA 1c level was 8.
We separated the 39 patients who reported sleep frequently disrupted by pain from the remainder of the sample. Sleep quantity was lower in the group with pain, indicated by shorter sleep durations and greater perceived sleep debt Table 2. Modified PSQI scores were also higher in the group with frequent pain, even after excluding the pain question from the score.
The remainder of our analysis was restricted to patients without pain-disturbed sleep 35 men and 87 women. The only significant sex difference in sleep was for weekend sleep duration, which was significantly longer in women 6.
Body mass index, waist-hip ratio, frequency of exercise, frequency of checking glucose, and duration of diabetes were not significantly related to lnHbA 1c levels.
We performed a GLM analysis of variance, with lnHbA 1c level as the dependent variable and perceived sleep debt, modified PSQI score, age, sex, BMI, insulin use, presence of diabetic complications, and 6 first-degree interactions as predictors.
The depression score did not emerge as a significant predictor or have significant interactions with other predictors. Because of the significant interactions between the sleep variables and diabetic complications or insulin use, regression analyses were stratified by diabetic complications and by insulin use Table 3.
In patients without complications, perceived sleep debt but not subjective sleep quality was associated with lnHbA 1c levels. In contrast, in patients with at least 1 complication, modified PSQI score, but not perceived sleep debt, was a significant predictor after controlling for covariates.
Figure 1 presents bivariate associations between HbA 1c level and the 2 sleep variables in patients without and with diabetic complications. Since we used lnHbA 1c in regression analyses, the β coefficients of the GLM represent the proportional change in HbA 1c level for an absolute change in main effect.
For example, in patients without complications, a perceived sleep debt increase of 3 hours per night for an individual with an HbA 1c level of 7. In patients with at least 1 complication, a 5-point increase in PSQI for an individual with an HbA 1c of 8.
Because the β coefficient is proportional, changes in sleep variables have a larger effect at larger values of HbA 1c. Table 3 also presents results for patients stratified by insulin use. For patients not taking insulin, perceived sleep debt, but not PSQI, was a significant predictor.
For patients taking insulin, PSQI score, but not perceived debt, was significantly associated with lnHbA 1c level. This subgroup had a higher mean HbA 1c level compared with those at low risk of SRBD 9. Recent laboratory and epidemiologic studies have indicated that insufficient sleep may result in decreased glucose tolerance and increased diabetes risk.
To our knowledge, the present study is the first to address this hypothesis by examining self-reported sleep duration and quality and HbA 1c levels in patients with type 2 diabetes. Our analyses reveal that a higher perceived sleep debt or lower sleep quality are associated with poorer glucose control, after controlling for age, sex, BMI, insulin use, and the presence of major complications.
The direction of causality cannot be inferred from our analyses. Poor glycemic control in patients with diabetes could impair subjective sleep quality even in the absence of pain.
For example, nocturia could play a role in the observed relationship between sleep and glycemic control. Perceived sleep debt could partly reflect the inability to achieve sufficient sleep rather than a voluntary reduction of bedtime.
Thus, poor diabetes control could contribute both to a higher perceived sleep debt and lower sleep quality. On the other hand, evidence from previous laboratory and epidemiologic studies supports the opposite direction of causality, that is, that short or poor sleep impairs glucose control.
The prospective studies showing a relationship between sleep duration and the development of symptomatic diabetes are particularly relevant to the present findings. The strength of the associations in our sample suggests that such studies would be warranted from a clinical standpoint.
Our analyses indicated that in patients without complications, a perceived sleep debt of 3 hours per day was associated with an increase in HbA 1c level by 1. The magnitude of these effects is comparable to those of widely used oral antidiabetic agents. We verified that the results of the regression model would have been qualitatively similar had we used sleep duration rather than perceived sleep debt but noted that perceived sleep debt accounted for a larger proportion of the variance compared with sleep duration.
When patients classified as being at high risk for SRBD were excluded from our analysis, the associations between HbA 1c levels and sleep variables persisted, indicating that SRBD risk as estimated in our study is not the primary mediator of the relationship between glucose control and sleep.
The present study identifies sleep as a potential factor influencing glucose control in a specific population of patients with type 2 diabetes.
A cohort study that included mostly whites found a relationship between sleep duration and the development of symptomatic diabetes. Sleep curtailment has become increasingly prevalent in modern society, and it cannot be excluded that this behavior has contributed to the current epidemic of type 2 diabetes.
Correspondence: Eve Van Cauter, PhD, Department of Medicine, University of Chicago, S Maryland Ave, MC AMB M, Chicago, IL evcauter medicine.
Author Contributions: The senior author had full access to the study data and takes responsibility for its integrity and the accuracy of the analysis.
Role of the Sponsors: The sole role of the sponsors was financial support. full text icon Full Text. Download PDF Top of Article Abstract Methods Results Comment Article Information References.
Figure 1. View Large Download. Table 1. Summary of Epidemiologic Studies That Examined the Association Between Sleep and Diabetes.
Spiegel KLeproult RVan Cauter E Impact of sleep debt on metabolic and endocrine function. Lancet ; PubMed Google Scholar Crossref.
Spiegel KKnutson KLeproult RTasali ECauter EV Sleep loss: a novel risk factor for insulin resistance and type 2 diabetes. J Appl Physiol ; PubMed Google Scholar Crossref. Now, new findings from a team of sleep scientists at the University of California, Berkeley, are closer to an answer.
The researchers say this is an exciting advance because sleep is a modifiable lifestyle factor that could now be used as part of a therapeutic and painless adjunct treatment for those with high blood sugar or Type 2 diabetes.
For years, researchers have studied how the coupling of non-rapid eye movement sleep spindles and deep, slow brain waves corresponded to an entirely different function — that of learning and memory.
Indeed, the same team of UC Berkeley researchers previously found that deep-sleep brain waves improved the ability of the hippocampus — the part of the brain associated with learning — to retain information. But this new research builds on a rodent study and reveals a novel and previously unrecognized role for these combined brain waves in humans when it comes to the critical bodily function of blood sugar management.
The UC Berkeley researchers first examined sleep data in a group of individuals. They found that this particular coupled set of deep-sleep brain waves predicted next-day glucose control, even after controlling for other factors such as age, gender and the duration and quality of sleep.
Next, the team then set out to explore the descending pathway that might explain the connection between these deep-sleep brain waves sending a signal down into the body, ultimately predicting the regulation of blood glucose.
Sleep affects your hormone levels and your circadian rhythm. Your circadian rhythm naturally controls your sleep-wake cycle by responding to things like light and dark levels.
Most people have a reasonably consistent circadian rhythm as adults. This internal clock controls hormone secretion, temperature, eating habits, and digestion. When your circadian rhythms are out of sync, your body's metabolic health can decline—and a risk for diabetes can increase.
This leads your body to produce more insulin to stabilize blood glucose levels. The more insulin resistant your cells become, the greater the risk that your insulin and blood sugar levels will chronically rise. This eventually leads to glucose intolerance and diabetes.
Two hormones that regulate your appetite are leptin and ghrelin. Leptin plays several roles within your body. Two of its key jobs are long-term energy regulation and metabolism. You may have heard it referred to as the starvation or satiety hormone.
The fat cells in your body release leptin, telling your brain when you have enough energy. When released, it suppresses your appetite, making you feel satisfied. If leptin levels are low, your appetite increases.
Several studies have found that short sleep duration reduces leptin levels, leading to overeating and weight gain. In turn, the craving to eat more results in an increased intake of carbohydrates which raises glucose levels.
Ghrelin has the opposite function of leptin, increasing your appetite by telling your brain that your body needs more food. This is one of the reasons why certain fad diets often fail. Another thing that increases ghrelin levels is lack of sleep. The surge in ghrelin prompts you to feel hungry, leading you to eat more carbohydrates, which will raise your glucose levels.
There is also an added problem with high ghrelin levels, as it can reduce glucose tolerance. Sleep deprivation, or broken sleep, can lead to an increase in sympathetic nervous system activity.
When your sympathetic nervous system is overly active, it can reduce insulin secretion and promote insulin resistance. Both of these can lead to chronically raised blood sugar levels. When blood sugar levels become raised, it can cause lifelong chronic conditions such as pre-diabetes, diabetes, or metabolic syndrome.
Research shows that sleep deprivation increases inflammation levels in the body. But, if inflammation is chronically high, it can lead to lifelong conditions such as metabolic syndrome, type 2 diabetes, heart disease, and obesity.
It can also cause further complications and a poorer prognosis. Glucose is fuel for the brain. It provides the energy needed to carry out its functions.
Overall, studies state that sleep deprivation has damaging effects on brain function—particularly functions such as alertness, attention, decision making, and cognitive processes. Sleep helps to maintain your body weight in many different ways, including regulating hunger hormones and insulin levels, as discussed earlier.
Controlling glucocorticoid levels is another body fat regulator. Glucocorticoids are hormones that control several processes such as metabolism, inflammatory response, and brain function.
One of the principal glucocorticoids is cortisol also known as the stress hormone. When cortisol levels increase, it can lead to insulin resistance. This can lead to an increase in blood sugar, weight gain, and potentially Type 2 Diabetes.
So, a lack of sleep negatively impacts your glucose levels in many ways. Do you know what your normal blood sugar levels should be overnight? In a healthy individual, glucose levels will go up and down while you sleep, which is normal.
There is a lot of research available on optimal morning fasting glucose values after sleeping and fasting for at least eight hours because these are the values that your physician or a researcher would test at a lab.
Diabetes is Blood sugar control and sleep quality condition in Body shape confidence Blood sugar control and sleep quality body is suhar to quqlity insulin properly. This qjality excess levels of glucose in the blood. The most common types are type 1 and type 2 diabetes. Short-term symptoms of high blood sugar can include frequent thirst or hunger, as well as frequent urination. In a studyresearchers examined the associations between sleep disturbance and diabetes. Sleep disturbance includes difficulty falling asleep or staying asleep, or sleeping too much. If lBood have Beetroot juice and immune system, there are even more. Suality how sleep Beetroot juice and immune system your diabetes management. Gourmet chicken breast you have diabetes, too adn sleep negatively affects every area of your management, including Mediterranean diet and hypertension much you eat, Antiviral virus prevention you choose to eat, how you respond to insulin, and your mental health. Being well rested is important for people of all ages to stay in good health. How many hours of sleep you need changes as you age. The American Academy of Sleep Medicine and the Sleep Research Society recommend that adults should get at least 7 hours of sleep per night. Children and teens need more.
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