A cross-sectional study of the relationship between quality of life and sleep quality in Japanese patients with type 1 diabetes mellitus

Ichikawa, Masahiro; Yamakawa, Tadashi; Sakamoto, Rika; Takahashi, Kenichiro; Suzuki, Jun; Matsuura-Shinoda, Minori; Shigematsu, Erina; Tanaka, Shun‐ichi; Kaneshiro, Mizuki; Asakura, Taro; Kawata, Takehiro; Yamada, Yoshihiko; Osada, Uru Nezu; Isozaki, Tetsuo; Takahashi, Atsushi; Kadonosono, Kazuaki; Terauchi, Yasuo

doi:10.1507/endocrj.ej21-0408

Cited by 5 publications

(3 citation statements)

References 28 publications

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“…The PSQI scores showed direct relationships with anxiety and depression, consistent with the reports from other studies (Qiu et al, 2016;Zhong et al, 2015). Furthermore, the PSQI scores had inverse relationships with quality of life, in agreement with previous studies (Nunes et al, 2009;Ichikawa et al, 2022).…”

Section: Discussionsupporting

confidence: 92%

Psychometric properties of the Mongolian version of the Pittsburgh Sleep Quality Index

Tumurbaatar,

Hiramoto,

Tumur-Ochir

et al. 2023

Neurosci Res Notes

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Poor sleep quality is associated with decreased brain health, such as fatigue, low quality of life, and risk of neurological and psychiatric comorbidities. Until now, no testing instruments for an accurate assessment of sleep quality for use in the general population have been rigorously translated and validated in Mongolia. We aimed to determine the psychometric properties of the globally recognized screening tool and sleep quality in the general population of Mongolia. In this cross-sectional study, participants were randomly selected between August and October 2020, from 64 sites in 8 urban, and 9 rural areas in Mongolia. Of the total 1152 participants (mean age, SD=42.66±12.6, range: 18 and 65) 76% were women. An overall Cronbach’s α was 0.69. Both EFA and CFA indicated a two-factor solution. The PSQI total score was positively correlated with anxiety and depression. The PSQI total score (p values < 0.01) was negatively correlated with the mean scores of all domains of WHOQOL-BREF. The mean PSQI total score was 5.67±3.4 and 43% of the participants were classified as poor sleepers by a global cut-off point of 5. The Mongolian version of the PSQI demonstrated a reliable and valid tool for screening sleep quality among the Mongolian general population. The results suggest that the prevalence rate of poor sleep quality was 43% using PSQI global cut-off point.

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Section: Discussionsupporting

confidence: 92%

Psychometric properties of the Mongolian version of the Pittsburgh Sleep Quality Index

Tumurbaatar,

Hiramoto,

Tumur-Ochir

et al. 2023

Neurosci Res Notes

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“…The most common MD, which has been reported globally is diabetes mellitus (DM) [ 53 ] and mapping of global trends has indicated an increase in research related to this non-communicable disease (NCD) [ 54 ]. It is projected that the current reported caseload of 463 million people living with diabetes will increase steadily over the next three decades [ 55 ], prompting the need for interventions at multiple levels including recommending changes in lifestyle [ 56 ], management of gut microflora [ 57 , 58 ], the implantation of stem cells [ 59 ] and genome editing using CRISPR-based platforms [ 60 ]. The current COVID-19 pandemic has highlighted the fact that patients with comorbidities such as diabetes have an increased SARS-CoV-2 susceptibility [ 61 ] and further complications, which include insulin resistance and lipid metabolic dysregulation [ 62 ].…”

Section: Diabetes Mellitus (Dm)mentioning

confidence: 99%

Current Understanding on the Genetic Basis of Key Metabolic Disorders: A Review

Rodrigues

Yong

Bhuiyan

et al. 2022

Biology

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Advances in data acquisition via high resolution genomic, transcriptomic, proteomic and metabolomic platforms have driven the discovery of the underlying factors associated with metabolic disorders (MD) and led to interventions that target the underlying genetic causes as well as lifestyle changes and dietary regulation. The review focuses on fourteen of the most widely studied inherited MD, which are familial hypercholesterolemia, Gaucher disease, Hunter syndrome, Krabbe disease, Maple syrup urine disease, Metachromatic leukodystrophy, Mitochondrial encephalopathy lactic acidosis stroke-like episodes (MELAS), Niemann-Pick disease, Phenylketonuria (PKU), Porphyria, Tay-Sachs disease, Wilson’s disease, Familial hypertriglyceridemia (F-HTG) and Galactosemia based on genome wide association studies, epigenetic factors, transcript regulation, post-translational genetic modifications and biomarker discovery through metabolomic studies. We will delve into the current approaches being undertaken to analyze metadata using bioinformatic approaches and the emerging interventions using genome editing platforms as applied to animal models.

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“…Diabetes is an essential health issue in the modern world, and its consequences affect millions of people. Therefore, factors related to its occurrence and treatment are the subject of numerous scientific studies [ 1 , 5 , 10 , 11 , 12 , 13 ]. The relationship between the health status of patients with diabetes and their place of residence is one of the studied areas [ 14 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

What Differentiates Rural and Urban Patients with Type 1 Diabetes—A Pilot Study

Sińska,

Kucharska,

Rzońca

et al. 2023

Nutrients

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The effective management of diabetes is a complex issue and may be determined according to numerous patient-dependent and patient-independent factors. This study aimed to analyze the relationship between the place of residence and selected sociodemographic, psychological and diabetes-related parameters in people with type 1 diabetes (T1D). This study was conducted on 419 adults with T1D using nonprobability sampling. The following questionnaires were used: the Diabetes Dietary Guidelines Adherence Index, the Acceptance of Illness Scale, the Sense of Responsibility for Health Scale, the Diabetes Eating Problem Survey-Revised scale, the Eating Attitudes Test and questions on sociodemographic and diabetes-related parameters. People living in rural areas were characterized by a significantly lower age and level of education, a higher incidence of being overweight, a higher glycated hemoglobin concentration, a lower number of glucose measurements during the day and a higher level of acceptance of the disease compared to urban residents. The degree of adherence to dietary recommendations and the sense of responsibility for one’s own health were significantly higher among urban residents. It is necessary to assess barriers to a proper diet and to increase the effectiveness in managing the disease in rural communities. Targeted actions promoting the health of type 1 diabetics need to be developed with particular emphasis on patients from rural areas.

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A cross-sectional study of the relationship between quality of life and sleep quality in Japanese patients with type 1 diabetes mellitus

Cited by 5 publications

References 28 publications

Psychometric properties of the Mongolian version of the Pittsburgh Sleep Quality Index

Psychometric properties of the Mongolian version of the Pittsburgh Sleep Quality Index

Current Understanding on the Genetic Basis of Key Metabolic Disorders: A Review

What Differentiates Rural and Urban Patients with Type 1 Diabetes—A Pilot Study

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