Association of Sleep Patterns with Type 2 Diabetes Mellitus: A Cross-Sectional Study Based on Latent Class Analysis

Liu, Mengdie; Ahmed, Wali Lukman; Zhuo, Lang; Yuan, Hui; Wang, Shuo; Zhou, Fang

doi:10.3390/ijerph20010393

Cited by 7 publications

(5 citation statements)

References 53 publications

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“…This approach should involve interventions such as meditation, improving sleep patterns, cultivating social support networks, and providing psychological support. [21][22][23][24] Recognizing the need for these interventions is crucial in effectively managing diabetes.…”

Section: Tablementioning

confidence: 99%

The effect of close and intensive therapeutic monitoring of patients with poorly controlled type 2 diabetes with different glycemic background

Erbakan,

Arslan Bahadir,

Kaya

et al. 2023

Medicine

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Patients with type 2 diabetes who have HbA1c values ≥ 10% have different previous glycemic trends, including new diagnosis of diabetes. We aimed to assess the efficacy of 3 months of intensive and facilitated antihyperglycemic treatment in patients with different glycemic backgrounds. In this observational study, patients with type 2 diabetes and poor glycemic control (indicated by an HbA1c level of > = 10%) were divided into groups based on their previous HbA1c levels (group 1; newly diagnosed type 2 diabetics, group 2; patients with previously controlled but now deteriorated HbA1c levels, group 3; patients whose HbA1c was not previously in the target range but was now above 10%, and group 4; patients whose HbA1c was above 10% from the start). Patients received intensive diabetes management with close monitoring and facilitated hospital visits. For further analysis, patients who were known to have previously had good metabolic control (either did not have diabetes or had previously had an HbA1c value < =7) and patients who had prior poor metabolic control were analyzed separately. Of the 195 participants [female, n = 84 (43.1%)], the median age was 54 years (inter-quantile range [IQR] = 15, min = 29, max = 80) and the median baseline HbA1c was 11.8% (IQR = 2.6%, min = 10%, max = 18.3%). The median duration of diabetes was 10 years (IQR = 9, min = 1, max = 35) when newly diagnosed patients were excluded. The ≥ 20% reduction in HbA1c at month 3 was observed in groups 1 to 4 in 97%, 88.1%, 69.1%, and 55.4%, respectively. The percentage of patients who achieved an HbA1c level of 7% or less was 60.6%, 38.1%, 16.4%, and 6.2% in the groups, respectively. The rate of those who achieved an HbA1c of 7% or less was nearly 50% of patients with type 2 diabetes mellitus who had previously had good metabolic control, whereas successful control was achieved in only 1 in 10 patients with persistently high HbA1c levels. Patients’ glycemic history played an important role in determining their HbA1c levels at 3 months, suggesting that previous glycemic management patterns may indicate future success in diabetes control.

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Section: Tablementioning

confidence: 99%

The effect of close and intensive therapeutic monitoring of patients with poorly controlled type 2 diabetes with different glycemic background

Erbakan,

Arslan Bahadir,

Kaya

et al. 2023

Medicine

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“…Diperkirakan sekitar 462 juta orang atau setara dengan 6,28 % populasi dunia terkena diabetes mellitus tipe 2 sejak tahun 2017 dan diproyeksikan terus meningkat menjadi 7.079 orang per 100.000 penduduk pada tahun 2030 (Khan et al, 2020;Setyawati et al, 2020). Tingginya kasus diabetes mellitus merupakan faktor risiko independen terhadap gangguan tidur, gejala cemas, dan berdampak pada kualitas hidup yang buruk (Dong et al, 2020;Liu et al, 2023).…”

Section: Pendahuluanunclassified

Intervensi Non Farmakologis pada Pasien Diabetes Mellitus dengan Gangguan Tidur

Irbar,

Dahlia,

Aryani

et al. 2023

JKS

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This study aims to investigate the effects of non-pharmacological interventions in diabetes mellitus patients with sleep disturbances. The research method used was a systematic review with a randomized controlled trial (RCT) and quasi-experimental design. Article searches used five databases, Scopus, Proquest, ScienceDirect, Pubmed, and EbscoHost, published from January 2018 to December 2022. The results showed that eight articles met the criteria. Non-pharmacological interventions given to diabetes mellitus patients with sleep disorders include Cognitive Behavioral Therapy (CBT), Acceptance and Commitment Therapy (ACT), aromatherapy, personalized intervention, and nutritional therapy. Most studies report that non-pharmacological interventions can improve sleep quality in diabetes mellitus patients with sleep disorders. CBT therapy is the recommended therapy that is more effective. In conclusion, non-pharmacological interventions can be used as a companion or substitute therapy to improve sleep quality in patients with diabetes mellitus who experience sleep disturbances. Keywords: Diabetes Mellitus, Non-Pharmacological Intervention, Sleep Quality

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“…Healthy behaviors have beneficial impacts in reducing cardiovascular disease and mortality [6,7]. Several studies have suggested an association between cardiovascular disease and unhealthy lifestyles, such as sedentary behavior [8], unhealthy dietary behavior [9], and unhealthy sleep patterns [10].…”

Section: Introductionmentioning

confidence: 99%

The U-Shaped Association between Sleep Duration, All-Cause Mortality and Cardiovascular Risk in a Hispanic/Latino Clinically Based Cohort

Henríquez-Beltrán,

Dreyse,

Jorquera

et al. 2023

JCM

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Sleep is essential for life, and inappropriate sleep duration patterns may lead to chronic consequences regarding human health. Several studies have confirmed the presence of a U-shaped association between sleep duration and mortality. Moreover, many consequences related to cardiometabolic aspects have been suggested in patients with abnormal sleep durations. In this study, we analyzed the associations between sleep duration, total sleep time (TST), the risk of all-cause mortality, and 10-year cardiovascular risk in a cohort of patients at a sleep medicine center in Santiago, Chile. We conducted a prospective cohort study of patients (SantOSA). A short TST was defined as ≤6 h, a normal TST as 6 to 9 h, and a long TST as ≥9 h. Adjusted hazard ratios (aHRs) for all-cause mortality were calculated. A cross-sectional analysis between TST and 10-year cardiovascular risk (calculated using the Framingham 2008 formula) was determined using logistic regression models. A total of 1385 subjects were included in the results (78% male; median age: 53, interquartile range (IQR): 42–64 years; median BMI: 29.5, IQR: 16.7–33.1). A total of 333 subjects (24%) reported short TSTs, 938 (67.7%) reported normal TSTs, and 114 (8.3%) reported long TSTs. In the fully adjusted model, the association remained significant for short (aHR: 2.51 (1.48–4.25); p-value = 0.01) and long TSTs (aHR: 3.97 (1.53–10.29); p-value = 0.04). Finally, a U-shaped association was found between short and long TSTs, with an increase in cardiovascular risk at 10 years. Compared with normal TSTs, short (≤6 h) and long (≥9 h) TSTs were significantly associated with all-cause mortality and increased 10-year cardiovascular risk.

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Association of Sleep Patterns with Type 2 Diabetes Mellitus: A Cross-Sectional Study Based on Latent Class Analysis

Cited by 7 publications

References 53 publications

The effect of close and intensive therapeutic monitoring of patients with poorly controlled type 2 diabetes with different glycemic background

The effect of close and intensive therapeutic monitoring of patients with poorly controlled type 2 diabetes with different glycemic background

Intervensi Non Farmakologis pada Pasien Diabetes Mellitus dengan Gangguan Tidur

The U-Shaped Association between Sleep Duration, All-Cause Mortality and Cardiovascular Risk in a Hispanic/Latino Clinically Based Cohort

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