Literature DB >> 35669384

The importance of sleep studies in improving the health indices of a nation.

Jitendra Kumar Sinha1,2, Kshitij Vashisth2, Shampa Ghosh1,3.   

Abstract

Entities:  

Year:  2022        PMID: 35669384      PMCID: PMC9163577          DOI: 10.1016/j.sleepx.2022.100049

Source DB:  PubMed          Journal:  Sleep Med X        ISSN: 2590-1427


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Sleep quality has been considered as one of the most important parameters of good sleep health. A recent study [1] conducted on Singapore residents identified the different correlated (sociodemographic) factors of poor sleep outcome using the Pittsburg Sleep Quality Index (PSQI), which is a well accepted technique to study sleep in a large population [2]. The study links poor sleep with a marked decrease in health outcomes; importantly, metabolic syndrome, multimorbidity and mental health issues. It is also linked to unhealthy lifestyle practices such as smoking and excessive alcohol consumption. The strength of the study lies in the inclusion of various ethnicities and groups across the country. Similar studies with regional modifications need to be performed in other countries to find out the modifiable factors that can help in improving quality of sleep as well as overall health of the population. Inclusion of sleep medicine specialists at district/county-level hospitals would further enhance the health indices significantly in the coming years. The recent advancements in artificial intelligence based trackers and diagnostics bring a lot of hope for affordable sleep health improvement applications [3]. Ethical data collected through actigraphy and other affordable techniques could bring a massive change in understanding sleep health at global level. As a caution, we also need to be careful about the application of technology to certain groups vulnerable to sleep disorders like older population, people with mental disorders or other medical conditions. The psychological stress due to misdiagnosing someone with a sleep disorder should also be considered while informing the analytical results.
  3 in total

1.  Association between number of comorbid conditions, depression, and sleep quality using the Pittsburgh Sleep Quality Index: results from a population-based survey.

Authors:  Yasuaki Hayashino; Shin Yamazaki; Misa Takegami; Takeo Nakayama; Shigeru Sokejima; Shunichi Fukuhara
Journal:  Sleep Med       Date:  2010-03-09       Impact factor: 3.492

2.  Mood Prediction of Patients With Mood Disorders by Machine Learning Using Passive Digital Phenotypes Based on the Circadian Rhythm: Prospective Observational Cohort Study.

Authors:  Chul-Hyun Cho; Taek Lee; Min-Gwan Kim; Hoh Peter In; Leen Kim; Heon-Jeong Lee
Journal:  J Med Internet Res       Date:  2019-04-17       Impact factor: 5.428

3.  Sleep quality of Singapore residents: findings from the 2016 Singapore mental health study.

Authors:  Ying Ying Lee; Jue Hua Lau; Janhavi Ajit Vaingankar; Rajeswari Sambasivam; Saleha Shafie; Boon Yiang Chua; Wai Leng Chow; Edimansyah Abdin; Mythily Subramaniam
Journal:  Sleep Med X       Date:  2022-01-28
  3 in total

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