Associations between cardiovascular risk, physical activity, and sleep quality in type 2 diabetes

Abstract

AimThe aim of this study was to evaluate cardiovascular risk, physical activity, and sleep quality in patients with type 2 diabetes.MethodsA total of 240 patients with type 2 diabetes (94 males, 146 females) were included. An information form questionnaire, the International Physical Activity Questionnaire, and the Pittsburgh Sleep Quality Index were applied to the participants through a face-to-face interview. Body composition was assessed using Bioelectrical Impedance Analysis. Routine biochemical test results were recorded. Cardiovascular risk status was determined using the Framingham Risk Score.ResultsFemale patients were more likely to be physically inactive, had lower cardiovascular risk scores, and were approximately 2.5 times more likely to have poor sleep quality than male patients. Mean skeletal muscle mass was significantly higher in participants with good sleep quality and in those who were more physically active (p<0.05). Those who were physically active had significantly better sleep quality (p<0.05). Those with low cardiovascular risk had lower physical activity (p<0.05).ConclusionIn individuals with diabetes, lifestyle factors such as physical activity and sleep quality interact with each other. However, these factors and influencing parameters should not be ignored in the diagnosis, treatment, and follow-up of diabetes, which is known to pose a risk for cardiovascular diseases.

Keywords

Introduction

Diabetes is a chronic disease that requires the management of multifactorial risk conditions as well as glucose management.¹ Today, diabetes continues to be a serious health problem all over the world due to the increasing frequency and decreasing age of onset. The number of individuals diagnosed with diabetes worldwide is expected to reach 643 million by 2030 and 783 million by 2045. In Türkiye, it has been found that the prevalence of adult diabetes, standardized according to age distribution, has reached 14.5%, and the number of people has reached 9 million, making it the country with the highest prevalence of diabetes in the European region. According to the estimates of 2045, Türkiye is among the top 10 countries worldwide, with the number of 13.4 million diabetic patients expected to be reached.²
Diabetes, despite advances in its management and treatment, is a major health problem that leads to cardiovascular disease. Hyperglycemia and insulin resistance affect many molecular pathways, causing deterioration of systolic and diastolic functions, endothelial dysfunction, and arterial stiffness. Given that patients with diabetes may develop early atherosclerosis, the risk of cardiovascular disease is higher than in the general population.³
Exercise in diabetes has significant benefits for improving blood sugar levels, reducing cardiovascular risk factors, contributing to weight loss, and improving overall health.⁴
Recent studies suggest that melatonin plays a role in circadian regulation of insulin sensitivity and that melatonin is the responsible mechanism linking poor sleep to the incidence of type 2 diabetes.⁵ In addition, the daily release of cortisol is also under the influence of the circadian rhythm. Sudden changes in sleep period cause a profound disturbance in the daily cortisol rhythm and result in reduced sleep quality.⁶ Poor sleep quality increases the risk of metabolic and cardiovascular diseases.⁵
In order to maintain physiological and mental health, lifestyle interventions occupy an important place in diabetes control. Physical activity, which is part of the treatment of patients with diabetes, and sleep profile, which affects a large part of life, are factors to be considered in routine check-ups.
Although there are separate studies in the literature examining the cardiovascular risk, physical activity status, or sleep status of patients with diabetes, there are no studies examining these concepts together. In this study, the aim was to determine the cardiovascular risk, sleep quality, and physical activity levels of patients with diabetes and to evaluate the relationships among them and with influencing factors.

Materials and Methods

Study Population and Study Design
The study was conducted between July 18, 2022, and January 31, 2023, and included 240 patients with type 2 diabetes mellitus who volunteered at the Selçuk University Faculty of Medicine Family Medicine Diabetes Education Polyclinic. The study was conducted under the principles of the Declaration of Helsinki. Written informed consent was obtained from all participants.
Patients who declined to participate in the study, patients with known heart disease (ischemic heart disease, a history of stents or bypass surgery), and patients who had experienced a cardiovascular event within the previous 6 months (myocardial infarction, cerebrovascular disease, peripheral artery disease) were excluded from the study.Patient Information FormThe questionnaire included questions on participants’ sociodemographic and diabetes-related clinical characteristics.Calculation of 10-Year Cardiovascular Risk ScoresThe Framingham Risk Score (FRS) was used to assess the 10-year cardiovascular disease (CVD) risk. Patients’ age, systolic blood pressure, smoking status, whether they received antihypertensive therapy, total cholesterol, and high-density lipoprotein (HDL) levels were used. Risk is considered low if the FRS is less than 10%, moderate if it is 10% to 19%, and high if it is 20% or higher.^7-8International Physical Activity Questionnaire (IPAQ)In this survey, the duration of vigorous physical activity, moderate physical activity, walking, and one-day sitting periods are questioned, evaluating the last 7 days. In the evaluation of the questionnaire, the MET-min (Metabolic Equivalent) score is used. It is categorized as inactive if the total MET-min/week value is below 600, minimally active if 600-3000 MET-min/week is detected, and active if it is above 3000.⁹Pittsburgh Sleep Quality Index (PSQI)Each question of the scale, which is formed from a total of 24 questions, is evaluated between 0 and 3 points. PSQI has 7 components. A total PSQI score ≥ 5 indicates poor sleep quality.^10-11Measurements of Body CompositionThe height of the study participants was measured on a Seca 264 digital height meter device. Weight, skeletal muscle mass (SMM), fat-free mass (FFM), body mass index (BMI), percent body fat (PBF), and visceral fat area (VFA) were measured. Anthropometric measurements were done with In-Body 770 body composition analysis (Biospace Co., South Korea).Biochemical TestsRoutine biochemical parameters, including glycosylated hemoglobin A1c (HbA1c) and lipid indices such as total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), and high-density lipoprotein cholesterol (HDL-C), were obtained within the last 15 days for the patient and used.Ethical ApprovalThe study was approved by the Ethics Committee of Selçuk University Faculty of Medicine (Date: 05.07.2022, Decision No: 2022/343).Statistical AnalysisAll statistical analyses were performed using R statistical language software (version 4.1.2; The R Foundation for Statistical Computing, Vienna, Austria; https://www.r-project.org). To check the normality of the data, the Shapiro-Wilk test and Q-Q plots were used, and Levene’s test was used to assess the homogeneity of variance. Numerical variables were presented as mean ± standard deviation, median with ranges (minimum–maximum), or median with interquartile range (IQR, 1st quartile–3rd quartile), as appropriate. Categorical variables were also described as counts (n) and percentages (%). Independent samples t-test, Pearson chi-square test, Chi-square test with Yates continuity correction, Mann-Whitney U test, and Welch’s t-test were used to compare sleep quality, physical activity, and cardiovascular risk across sociodemographic, clinical, and body-composition variables, as appropriate. Bivariate correlation using Spearman’s rho correlation coefficients was used to assess the relationship between PSQI score, IPAQ score, and FRS. Multiple logistic regression analysis was conducted to identify the independent risk factors of poor sleep quality, high + medium CVD risk, and low physical activity. Odds ratios (ORs) were calculated with 95% confidence intervals. Significance level was set at 5%, and all tests were two-sided.Reporting GuidelinesThis study is reported in accordance with the STROBE guidelines.

Results

240 patients with type 2 diabetes (94 males, 146 females) were included in this study. The mean age of patients with type 2 DM was 56.11 ± 9.39 years, and 60.8% were female. The majority of the patients were married (n = 205, 85.4%) and had an education level of primary school or below (n = 138, 57.5%). This study found that 19.6% of the patients were current smokers and 56.3% had obesity. The median duration of diabetes was 8 years (range, 0.25–40 years) (Supplementary Table 1).Factors Associated with Poor Sleep QualityMultiple logistic regression analysis with stepwise variable selection was performed to identify factors independently associated with poor sleep quality. Initially, gender, education level, smoking status, TG level, body composition assessments, and IPAQ score were included in the logistic regression analysis since these variables were significantly associated in the univariate analysis. After stepwise variable selection, smoking status, TG level, FFM, and SMM remained significantly associated with poor sleep quality. Females were about 2.5 times (OR: 2.68, 95% CI: 1.33–5.39, p=0.005) more likely to have poor sleep quality than males. While current smokers were significantly more likely to have poor sleep quality compared to non-smokers (OR: 2.82, 95% CI: 1.12–7.06, p=0.027), ex-smokers had a significantly higher likelihood of having good sleep quality than non-smoker patients (OR: 0.39, 95% CI: 0.18 – 0.82, p=0.014). Higher TG levels were associated with higher odds of poor sleep quality (OR: 2.54, 95% CI: 1.35–4.77, p=0.004). FFM (OR: 2.20, 95% CI: 1.13–4.28, p=0.019) and SMM (OR: 0.25, 95% CI: 0.08–0.75, p=0.014) were significantly associated with poor sleep quality.Factors Associated with Medium and High CVD RiskThe multiple logistic regression analysis with the stepwise variable selection method was performed to identify factors independently associated with medium-to-high CVD risk. Initially, education level, LDL levels, body composition assessments, IPAQ score, and PSQI score were included in the logistic regression analysis. After stepwise variable selection, the final model showed that higher education levels (university education or higher versus primary school education or lower, OR: 3.18, 95% CI: 1.35–7.49, p=0.008), high levels of LDL (OR: 4.38, 95% CI: 2.09–9.17, p<0.001), increased FFM (OR: 2.37, 95% CI: 1.15–4.89, p=0.020), lower SMM (OR: 0.26, 95% CI: 0.08–0.88, p=0.031) and PBF (OR: 0.94, 95% CI: 0.90–0.99, p=0.009) were associated with high CVD risk.Factors Associated with Low Physical ActivityThe multiple logistic regression analysis with the stepwise variable selection method was performed to identify factors independently associated with low physical activity. Initially, gender, education level, employment, BMI, body composition assessments, FRS, and PSQI scores were included in the logistic regression analysis. After stepwise variable selection, the final model showed that female gender (OR: 2.55, 95% CI: 1.43–4.53, p=0.001) and individuals with primary school education or lower (OR: 0.43, 95% CI: 0.20–0.91, p=0.028) were associated with low physical activity.Relationship Between PSQI Score, IPAQ Score, and FRSThere was a statistically significant and positive relationship between IPAQ score and FRS (Spearman’s rho = 0.127, p=0.049). Also, IPAQ score was significantly and negatively correlated with PSQI score (Spearman’s rho = –0.172, p=0.008). However, no significant relationship was observed between FRS and PSQI score (Spearman’s rho = –0.107, p=0.098).

Discussion

When we look at both the modifiable factors that pose a risk to diabetes and the risks posed by diabetes, it is seen that lifestyle interventions have a very important place in the management, treatment, and control of the disease and its complications. In addition to the medical treatment organized in the routine controls of the patients, questioning the quality of physical activity and sleep, and the counseling that can be provided when necessary, have an important role in preventing complications, especially cardiovascular diseases.
In this study, most of the participants (70.4%) were found to have poor sleep quality. Poor sleep frequency was higher in obese participants. The mean SMM and FFM of the participants with poor sleep quality were found to be significantly lower, and the mean PBF was higher. Several studies have also revealed the relationship between anthropometric measurements and sleep quality.^12-13 In this study, similar results were found in the literature, and it was supported that obesity is an important factor in sleep quality that should not be ignored.
According to the results, which are similar to most studies in the literature, sleep quality deteriorates as the level of education decreases.^14-16 It is thought that this situation is caused by the combination of social and economic inadequacy brought about by a lack of education.
According to our results, which are thought to be due to social pressure, stress factors, difficulty of the education system, and exams for educated individuals in Türkiye, the cardiovascular risk level of those in primary school and below education level was found to be lower, and the risk was higher in university and above education level. Similarly, Su et al. found that as the level of education increased in Malaysia, the level of risk in Framingham increased.¹⁷
Christie et al. found that having more physical activity was associated with better sleep quality.¹⁸ The results of this study also support that sleep quality increases with an increase in physical activity. It is thought that physical activity creates positive interactions in sleep quality by improving physical, social, and mental states.
Around 57% of the individuals participating in the study were found to be inactive. A significant relationship was found between BMI and physical activity status. Although BMI is widely used as a general indicator of obesity, it cannot provide separate evaluations for fat and muscle mass. Several studies in the literature, similarly to this study, found a significant inverse relationship between PBF, VFA, and physical activity, which also supports the results obtained about BMI.^19-20
Oliveira et al. observed that physically active participants had a lower FRS score, as expected.¹⁹ On the contrary, in this study, those with a low cardiovascular risk had a lower average score of physical activity. This result may be due to the fact that physical activity has not been objectively measured by dynamic methods. In the literature, studies assessing cardiovascular risk in patients with diabetes are very rare. It is thought that more studies are needed in this regard.
The literature concludes that poor sleep quality increases the risk of cardiovascular disease.^21-23 In this study, patients in the medium-high CVD risk groups had low PSQI scores. The fact that the study populations and sample sizes are different may cause similar results not to be obtained with the studies in the literature. It is thought that more studies examining sleep quality and cardiovascular risk in patients with diabetes are needed.

Limitations

The study's limitations included being a single-center study and patient refusal to participate.

Conclusion

We concluded that there is a significant relationship between physical activity, sleep quality, and cardiovascular risk in individuals with diabetes. We also found parameters of anthropometric measurements showing a significant relationship with sleep, physical activity, and cardiovascular risk. Sleep quality and physical activity were associated with several participant characteristics, and further studies are needed to clarify their relationships with cardiovascular risk.

Declarations

Abbreviations

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