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RELATIONSHIP OF DISTURBED SLEEP CYCLE AND DIFFERENT METABOLIC DISEASE IN PAKISTAN

Authors: Dr Sidra Saleem, Dr Anum Awan, Dr Shandana Nadeem;

RELATIONSHIP OF DISTURBED SLEEP CYCLE AND DIFFERENT METABOLIC DISEASE IN PAKISTAN

Abstract

Introduction: Metabolic syndrome (MetS) is an aggregation of cardiometabolic problems, characterized by a rise in arterial pressure (AP), fasting venous blood glucose (FVBG), plasma triglycerides (PT), abdominal circumference (AC) and reduction in the levels of high density lipoprotein-cholesterol (cholesterol) (HDL-C). Aims and objectives: The basic aim of the study is to find the relationship of sleep cycle and different common metabolic diseases among local population of Pakistan. Methodology of the study: This cross sectional study was conducted at RMC during Dec 2018 to May 2019. The data was collected from both genders, age range from 18 years to 50 years. The evaluation of the socio-demographic data and data on sleep quality, undertaken through a structured questionnaire, took place at times distinct from those of collection of clinical data. Results: Our results shows that the mean age of the sample was 21.5 years (SD±4.5 years). The value of AC was elevated in 5.4% of the students, while only 3.0% of the participants were classified as hypertensive. The prevalence of MetS in the study population was below 2%. We did not identify statistically significant proportional differences between the groups in relation to the prevalence of MetS (p=1.000). However, all the participants with MetS were classified as poor sleepers. Conclusion: It is concluded that sleep quality has direct relationship with metabolic syndromes. Several common sleep problems including insufficient sleep schedules, insomnia, sleep apnea, narcolepsy, and shift work disorder are known to cause sleep deficiencies that likely contribute to metabolic diseases.

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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