Sleep quality in people with type 2 diabetes controlled at the primary level and its association with sociodemographic and clinical characteristics

Campos-Romero, Solange; Araya, Silvia Cristina Barrios; Masalan-Apip, Maria Patricia; Tobar, Viviana Guajardo; Arias-Ortiz, Nelson Enrique; Bobadilla-Beiza, Lucas

doi:10.1016/j.enfcle.2021.03.004

Cited by 5 publications

(3 citation statements)

References 19 publications

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“…Among the Chilean diabetic patients, 77.3% were classified with poor glycemic control and 46% suffered from comorbidities. The study also revealed that females in the whole study sample exhibited a higher incidence of poor sleep quality, with 80.2% compared to 64% in males, which agrees with the results of the current study [38]. The genderbased difference may be attributed to hormonal distribution [39].…”

Section: Smrsupporting

confidence: 90%

Sleep Quality Assessment in Correlation to Autonomic Nerve Function in Type 2 Diabetic Patients

Ibrahim,

Hashim,

Desher

2023

Sleep Med Res

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Background and Objective Diabetes mellitus negatively impacts the quality of life of its patients. Autonomic dysfunction may disturb sleep quality by negatively affecting multiple systems, including, but not limited to, the cardiovascular, respiratory, and genitourinary tracts. The current study aims to assess sleep quality and examine the degree of correlation with autonomic nervous function in relatively well-controlled type 2 diabetic patients.Methods This study uses a cross-sectional design to assess sleep quality in 88 type 2 diabetic patients via the Pittsburg Sleep Quality Index (PSQI), accordingly dividing them into two groups: good or poor sleepers. Subsequently, the study evaluates autonomic nerves’ conductivity by measuring electrical skin conductance using Sudoscan for the hands and feet.Results Of 88 recruited patients, 53% showed poor sleep quality, with higher incidence in females. Autonomic nerve conductivity showed moderate damage in poor sleepers with 59.53 ± 13.35 μS and 59.68 ± 16.91 μS of hand and foot electrodes, respectively. Autonomic damage induces sleep disturbance mainly through increased nighttime voiding in 91.49% of the poor sleepers group compared to 41.46% in the good sleepers group. PSQI score was found to strongly and inversely correlate with autonomic nerve conductivity via hand electrodes, with a correlation coefficient of -0.62 and a determination coefficient of 0.39.Conclusion Poor sleep quality seems to be a significant problem even in relatively well-controlled type 2 diabetic patients with no diagnosed micro- or macrovascular complications. Autonomic dysfunction negatively affects the quality of sleep and leads to sleep disturbance by increasing nighttime micturition as one of its complications.

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Section: Smrsupporting

confidence: 90%

Sleep Quality Assessment in Correlation to Autonomic Nerve Function in Type 2 Diabetic Patients

Ibrahim,

Hashim,

Desher

2023

Sleep Med Res

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“…In terms of lipotoxicity, disrupted sleep patterns are linked to alterations in lipid metabolism and elevated circulating free fatty acids, which promote lipid accumulation in non-adipose tissues. Concurrently, unhealthy dietary habits stemming from inadequate sleep further contribute to lipid accumulation and metabolic dysfunction [12,79,80].…”

Section: Sleep Patternsmentioning

confidence: 99%

Environmental and Lifestyle Determinants of Type 2 Diabetes Mellitus

Siddiqui,

Baig,

Khan

2024

Preprint

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Objective: This study aims to comprehensively investigate the role of various environmental and lifestyle factors—including obesity, diet, physical inactivity, urbanization, socioeconomic status, sleep patterns, stress, environmental pollutants, gut microbiota, smoking, and alcohol consumption—in the pathogenesis of Type 2 diabetes mellitus (T2DM). Background: Type 2 diabetes mellitus (T2DM) is a global health challenge influenced by genetics, environment, and lifestyle. Key factors affecting T2DM include obesity, unhealthy diet, physical inactivity, urbanization, socioeconomic status, sleep patterns, stress, environmental pollutants, gut microbiota, smoking, and alcohol consumption. Understanding these factors' roles in insulin resistance, beta-cell dysfunction, glucotoxicity, lipotoxicity, and inflammation is crucial for effective prevention and management. Methods: A comprehensive search of databases such as PubMed, MEDLINE, Google Scholar, and various journals was conducted without date restrictions. The studies were systematically reviewed to explore the mechanistic links between environmental factors and T2DM pathophysiology. The study adhered to PRISMA guidelines. Results: The study revealed diverse associations between environmental and lifestyle factors and T2DM pathogenesis. Obesity was identified as a central contributor, promoting insulin resistance and adipose tissue dysfunction. Unhealthy diets increased T2DM risk through glucotoxicity and lipotoxicity. Sedentary behavior and urbanization compounded these effects. Socioeconomic disparities influenced T2DM prevalence, with lower SES individuals at higher risk. Sleep patterns, stress, environmental pollutants, and gut microbiota composition significantly affected T2DM development. Smoking and alcohol consumption were linked to increased insulin resistance and beta-cell dysfunction. These findings highlight the multifactorial nature of T2DM and the importance of addressing diverse environmental and lifestyle factors for effective prevention and management strategies. Conclusion: Obesity, diet, physical inactivity, urbanization, socioeconomic status, sleep patterns, stress, environmental pollutants, gut microbiota, smoking, and alcohol consumption collectively influence insulin resistance, beta-cell dysfunction, glucotoxicity, lipotoxicity, and inflammation in T2DM. Addressing these factors is essential for prevention and management. Promoting healthy lifestyles, improving healthcare access, and mitigating environmental exposures can reduce risk and improve outcomes. Understanding the interplay of these factors provides insights into T2DM's complex nature and informs comprehensive strategies for its prevention and treatment.

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“…Several studies have been conducted on sleep disturbance among patients with T2DM; the prevalence of poor sleep quality among these patients was reported as 32% in the East Coast Region of Peninsular Malaysia, 18 75.2% in Chile 19 and 56.0% in Taiwan. 20 These studies indicate that some available factors such as sociodemographic and lifestyle factors are associated with poor sleep quality among patients with T2DM.…”

Section: Introductionmentioning

confidence: 99%

Sleep quality and its associated factors among patients with type 2 diabetes mellitus in Hunan, China: a cross-sectional study

Maimaitituerxun,

Chen,

Xiang

et al. 2024

BMJ Open

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ObjectivesType 2 diabetes mellitus (T2DM) is a serious public health issue. Compared with the general population, patients with T2DM have a higher risk of poor sleep quality, which could ultimately result in poor prognosis. Therefore, this study aimed to evaluate sleep quality and its associated factors among patients with T2DM in Hunan, China.DesignThis was a cross-sectional study.SettingA tertiary hospital in Hunan, China.ParticipantsPatients with T2DM hospitalised at the Endocrinology Department were consecutively enrolled between March 2021 and December 2022. Sociodemographic characteristics, lifestyle factors and T2DM-related information were collected retrospectively.Primary and secondary outcome measuresSleep quality was evaluated using the Pittsburgh Sleep Quality Index, with a cut-off value of >7 suggesting poor sleep quality. Multivariate logistic regression analysis was used to determine factors associated with poor sleep quality.ResultsOf the 1039 participants included, 1001 provided complete data. The mean age of the study sample was 60.24±10.09 years, and 40.5% (95% CI 37.5% to 43.5%) of patients had poor sleep quality. Multivariate logistic regression analysis showed that female sex (adjusted OR (aOR) 1.70, 95% CI 1.25 to 2.29), unmarried status (aOR 1.72, 95% CI 1.05 to 2.83), diabetic retinopathy (aOR 1.38, 95% CI 1.04 to 1.83), diabetic foot (aOR 1.80, 95% CI 1.11 to 2.93) and a per capita monthly household income of >5000 RMB (aOR 0.66, 95% CI 0.47 to 0.93) were associated with poor sleep quality.ConclusionsNearly two-fifths of patients with T2DM reported poor sleep quality in Hunan, China. Sex, marital status, diabetic retinopathy, diabetic foot and household income were independently associated with sleep quality among patients with T2DM in Hunan, China.

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Sleep quality in people with type 2 diabetes controlled at the primary level and its association with sociodemographic and clinical characteristics

Cited by 5 publications

References 19 publications

Sleep Quality Assessment in Correlation to Autonomic Nerve Function in Type 2 Diabetic Patients

Sleep Quality Assessment in Correlation to Autonomic Nerve Function in Type 2 Diabetic Patients

Environmental and Lifestyle Determinants of Type 2 Diabetes Mellitus

Sleep quality and its associated factors among patients with type 2 diabetes mellitus in Hunan, China: a cross-sectional study

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