scholarly journals Poor Sleep Quality is Independently Associated with Cardiometabolic Risk Factors

2018 ◽  
Vol 32 (S1) ◽  
Author(s):  
Kevin L. Smith ◽  
Angelica R. Boeve ◽  
Virend K. Somers ◽  
Jan Bukartyk ◽  
Erik K. St Louis ◽  
...  
Keyword(s):  
Risk Factors ◽  
Sleep Quality ◽  
Cardiometabolic Risk ◽  
Cardiometabolic Risk Factors ◽  
Poor Sleep ◽  
Poor Sleep Quality

scholarly journals Determinants of poor sleep quality in elderly patients with diabetes mellitus, hyperlipidemia and hypertension in Singapore

2018 ◽  
Vol 19 (6) ◽  
pp. 610-615 ◽  
Author(s):  
Grace S. H. Chiang ◽  
Brenda L. H. Sim ◽  
Jeannette J. M. Lee ◽  
Joanne H. M. Quah
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Elderly Patients ◽  
Sleep Quality ◽  
Elderly Population ◽  
Cardiometabolic Risk ◽  
Poor Sleep ◽  
Poor Sleep Quality ◽  
Quality Sleep ◽  
Patients With Diabetes

AbstractAimThe objective of this study was to assess determinants of poor sleep quality which is an under-diagnosed and under-treated problem in elderly patients with diabetes mellitus, hyperlipidemia and hypertension.BackgroundPoor sleep quality is linked to decreased quality of life, increased morbidity and mortality. Poor sleep quality is common in the elderly population with associated cardiometabolic risk factors such as diabetes, hyperlipidemia and hypertension.MethodsThis is a cross-sectional study undertaken in the primary healthcare setting (Singhealth Polyclinics-Outram) in Singapore. Singaporeans aged 65 years and above who had at least one of the three cardiometabolic risk factors (diabetes, hypertension and hyperlipidemia) were identified. Responders’ sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) questionnaire and were divided into those with good quality sleep and those with poor quality sleep, based on the PSQI score. Information on demographics, co-morbidities and lifestyle practices were collected. Descriptive and multivariate analyses of determinants of poor sleep were determined.FindingsThere were 199 responders (response rate 88.1%). Nocturia (adjusted prevalence rate ratio 1.54, 95% confidence interval 1.06–2.26) was found to be associated with an increased risk of poor sleep quality in elderly patients with diabetes mellitus, hypertension and hyperlipidaemia. Nocturia, a prevalent problem in the Asian elderly population, has been found to be associated with poor sleep quality in our study. Hence, it is imperative to identify and treat patients with nocturia to improve sleep quality among them.

scholarly journals The prevalence and risk factors for depressive symptoms in frontline nurses under COVID-19 pandemic based on a large cross-sectional study using the propensity score-matched method

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hongyan Wang ◽  
Xiaoling Dai ◽  
Zichuan Yao ◽  
Xianqing Zhu ◽  
Yunzhong Jiang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Depressive Symptoms ◽  
Sleep Quality ◽  
Psychological Capital ◽  
Cross Sectional Study ◽  
Poor Sleep ◽  
Sectional Study ◽  
Poor Sleep Quality ◽  
Related Factors ◽  
Cross Sectional

Abstract Introduction To explore the prevalence of depressive symptoms and the associated risk factors in frontline nurses under COVID-19 pandemic. Methods This cross-sectional study was conducted from February 20, 2020 to March 20, 2020 and involved 562 frontline nurses. The effective response rate was 87.68%. After propensity score matched, there were 498 participants left. Extensive characteristics, including demographics, dietary habits, life-related factors, work-related factors, and psychological factors were collected based on a self-reported questionnaire. Specific scales measured the levels of sleep quality, physical activity, depressive symptoms, perceived organization support and psychological capital. Adjusted odds ratios and 95% confidence intervals were determined by binary paired logistic regression. Results Of the nurses enrolled in the study, 50.90% had depressive symptoms. Three independent risk factors were identified: poor sleep quality (OR = 1.608, 95% CI: 1.384–1.896), lower optimism of psychological capital (OR = 0.879, 95% CI: 0.805–0.960) and no visiting friend constantly (OR = 0.513, 95% CI: 0.286–0.920). Conclusions This study revealed a considerable high prevalence of depressive symptoms in frontline nurses during the COVID-19 outbreak, and identified three risk factors, which were poor sleep quality, lower optimism of psychological capital, and no visiting friend constantly. Protecting mental health of nurses is important for COVID-19 pandemic control and their wellbeing. These findings enrich the existing theoretical model of depression and demonstrated a critical need for additional strategies that could address the mental health in frontline nurses for policymakers.

scholarly journals Association between Cluster of Lifestyle Behaviors and HOMA-IR among Adolescents: ABCD Growth Study

Medicina ◽  
2018 ◽  
Vol 54 (6) ◽  
pp. 96 ◽  
Author(s):  
André Werneck ◽  
Ricardo Agostinete ◽  
Suziane Cayres ◽  
Jacqueline Urban ◽  
Andréa Wigna ◽  
...  
Keyword(s):  
Risk Factors ◽  
Insulin Resistance ◽  
Sleep Quality ◽  
Poor Sleep ◽  
Lifestyle Behaviors ◽  
Poor Sleep Quality ◽  
Growth Study ◽  
Tv Viewing ◽  
Body Fatness ◽  
Skipping Breakfast

Objective: To analyze the association of potential risk factors to health with body fatness and insulin resistance. Baseline measures of the ongoing longitudinal Analysis of Behaviors of Children During (ABCD) Growth Study. Materials and Methods: The sample was composed of 280 adolescents of both sexes (198 boys and 82 girls) aged from 10 to 18 years. Four risk factors were considered, as follows: no sports practice, skipping breakfast, poor sleep quality, and TV viewing. The outcomes considered were insulin resistance (HOMA-IR) and body fatness (densitometer scanner). Age, sex, maturity offset, and ethnicity were treated as covariates. Results: No sports practice and skipping breakfast were associated with higher body fatness (Sports practice: Wald: 8.786; p = 0.003. Breakfast: Wald: 9.364; p = 0.002). Poor sleep quality was related to a greater HOMA-IR index (Wald: 6.013; p = 0.014). Adolescents with ≥3 risk factors presented a higher risk of high HOMA-IR (OR = 4.89 (95%CI: 1.61 to 14.84)) than their counterparts with no risk factors. Conclusion: Lifestyle risk factors seem relevant to affect obesity and insulin resistance, while the aggregation of these risk factors affects insulin resistance, independent of adiposity.

Prevalence and risk factors of poor sleep quality and fatigue during exam periods in university students

2017 ◽  
Author(s):  
Izolde Bouloukaki ◽  
George Stathakis ◽  
Athina Koloi ◽  
Ekaterini Bakiri ◽  
Maria Moudatsaki ◽  
...  
Keyword(s):  
Risk Factors ◽  
University Students ◽  
Sleep Quality ◽  
Poor Sleep ◽  
Poor Sleep Quality

scholarly journals Sleep and Association With Cardiovascular Risk Among Midwestern US Firefighters

2021 ◽  
Vol 12 ◽  
Author(s):  
Juan Luis Romero Cabrera ◽  
Mercedes Sotos-Prieto ◽  
Antonio García Ríos ◽  
Steven Moffatt ◽  
Costas A. Christophi ◽  
...  
Keyword(s):  
Risk Factors ◽  
Sleep Quality ◽  
Sleep Duration ◽  
Body Fat ◽  
Cardiometabolic Risk ◽  
Cross Sectional Study ◽  
Cardiometabolic Risk Factors ◽  
Short Sleep Duration ◽  
Cross Sectional ◽  
Short Sleep

IntroductionCardiovascular disease is the leading cause of on-duty fatalities among U.S. firefighters. Research has demonstrated that many modifiable risk factors are contributors to the high prevalence of cardiometabolic risk factors. The current study aimed to assess whether sleep is associated with cardiometabolic risk factors among Indianapolis firefighters. The findings could support improving sleep hygiene in this population.Material and MethodsThis cross-sectional study was conducted from the baseline data of eligible firefighters enrolled in “Feeding America’s Bravest”, a Mediterranean diet lifestyle intervention within the Indiana Fire Departments. Participants’ sleep quality was categorized as “good” (≤ 8 points) or “bad” (>8 points) by a sleep quality questionnaire based on some questions from Pittsburgh Sleep Quality Index. In addition, firefighters’ sleep duration was stratified based on the number of hours slept per night (≤6 as “short sleep” or >6 hours as normal). Linear and logistic regression models were used to examine the association of sleep with cardiometabolic risk factors.ResultsA total of 258 firefighters were included. Bad sleepers had higher weight, greater waist circumference, higher body mass index (BMI), and increased body fat (all p<0.01) compared to good sleepers. Similarly, participants with short sleep duration were heavier (p<0.02), had greater BMI (p<0.02) and increased body fat (p<0.04) compared with participants with normal sleep duration. Both bad and short sleepers had a higher prevalence of hypertension and obesity (p <0.05).ConclusionsOur study supports that both sleep quality and quantity are associated with cardiometabolic risk among firefighters.

scholarly journals Poor sleep quality, long working hours and fatigue in coastal areas: a dangerous combination of silent risk factors for deck officers on oil tankers

2020 ◽  
Vol 71 (4) ◽  
pp. 237-248
Author(s):  
Farhad Azimi Yancheshmeh ◽  
S. Hossain Mousavizadegan ◽  
Amin Amini ◽  
Andrew P. Smith ◽  
Reza Kazemi
Keyword(s):  
Risk Factors ◽  
Sleep Quality ◽  
Working Hours ◽  
Coastal Areas ◽  
Poor Sleep ◽  
Poor Sleep Quality ◽  
Long Working Hours ◽  
Oil Tankers

scholarly journals The prevalence of poor sleep quality and associated risk factors among Chinese elderly adults in nursing homes: a cross-sectional study

2019 ◽  
Author(s):  
Zhao Hu ◽  
Xidi Zhu ◽  
Yunhan Yu ◽  
Huilan Xu
Keyword(s):  
Risk Factors ◽  
Social Support ◽  
Chronic Disease ◽  
Nursing Homes ◽  
Sleep Quality ◽  
Cross Sectional Study ◽  
Poor Sleep ◽  
Elderly Adults ◽  
Poor Sleep Quality ◽  
Cross Sectional

Abstract Background: Sleep problems have become the most common complaints among elderly adults. There are a few studies indentified prevalence of poor sleep quality and its associated factors in nursing home setting.Therefore, our study aim to examine the prevalence of poor sleep quality, its risk factors, and their interactions among Chinese elderly adults in nursing homes. Methods: A total of 817 elderly residents from 24 nursing homes were included in this cross-sectional study. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), and poor sleep quality was defined as PSQI >5. Multiple binary logistic regression was used to estimate adjusted odds ratios (AORs) and 95% confidence intervals (CIs) between risk factors and poor sleep quality. An additional interaction model was used to analyse the interaction between risk factors. Results: The prevalence of poor sleep quality was 67.3% (95% CI: 64.0, 70.5%) among elderly adults in nursing homes. Multiple binary logistic regression results showed that participants with the following characteristics had an increased risk of poor sleep quality after adjustments for other confounders: being 70-79 years old (AOR: 1.81, 95% CI: 1.10, 2.97) or 80 years old and above (AOR: 2.64, 95% CI: 1.67, 4.17); having less than 7 years of education (AOR: 1.59, 95% CI: 1.08, 2.33); having one to two kinds of chronic diseases (AOR: 2.26, 95% CI: 1.53, 3.32) or three or more kinds of chronic disease (AOR: 2.81, 95% CI: 1.65, 4.76); having depression (AOR: 3.13, 95% CI: 2.04, 4.81), anxiety (AOR: 3.42, 95% CI: 1.68, 6.97), and lower social support (AOR: 1.57, 95% CI: 1.11, 2.21). Additive interactions were detected between age and anxiety (AOR: 8.34, 95% CI: 4.43, 15.69), between chronic disease and anxiety (AOR: 8.61, 95% CI; 4.28, 17.31) and between social support and anxiety (AOR: 6.43, 95% CI: 3.22, 12.86). Conclusions: The prevalence of poor sleep quality in nursing homes is relatively high. Anxiety has additive interactions with age, chronic disease and social support for poor sleep quality. These findings have significant implications for interventions that aim to improve sleep quality among elderly residents in nursing homes.

scholarly journals The prevalence and risk factors for anxiety in frontline nurses under COVID-19 pandemic based on a large cross-sectional study using the propensity score-matched method

2021 ◽  
Author(s):  
Qingyun Zhao ◽  
Zichuan Yao ◽  
Xianqing Zhu ◽  
Yunzhong Jiang ◽  
Chunyu Pan
Keyword(s):  
Mental Health ◽  
Risk Factors ◽  
Sleep Quality ◽  
Psychological Capital ◽  
Cross Sectional Study ◽  
Poor Sleep ◽  
Sectional Study ◽  
Poor Sleep Quality ◽  
Related Factors ◽  
Cross Sectional

Abstract Introduction: We determined the prevalence of anxiety and the associated risk factors in in frontline nurses under COVID-19 pandemic. Methods: This cross-sectional study was conducted from February 20, 2020 to March 20, 2020 and involved 562 frontline nurses. The effective response rate was 87.68%. After propensity score matched, there were 532 participants left. Extensive characteristics, including demographics, dietary habits, life-related factors, work-related factors, and psychological factors were collected based on a self-reported questionnaire. Specific scales measured the levels of sleep quality, physical activity, anxiety, perceived organization support and psychological capital. Adjusted odds ratios and 95% confidence intervals were determined by binary paired logistic regression.Results: Of the nurses enrolled in the study, 33.60% had anxiety. Five independent risk factors were identified for anxiety: poor sleep quality (OR=1.235), experienced major events (OR=1.653), lower resilience and optimism of psychological capital (OR=0.906, and OR=0.909) and no visiting friend constantly (OR=0.629). Conclusions: This study revealed a considerable high prevalence of anxiety in frontline nurses during the COVID-19 outbreak, and identified five risk factors, which were poor sleep quality, experienced major events, lower resilience and optimism of psychological capital, and no visiting friend rarely. Protecting mental health of nurses is important for COVID-19 pandemic control and their wellbeing. These findings enrich the existing theoretical model of anxiety and demonstrated a critical need for additional strategies that could address the mental health in frontline nurses for policymakers.

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