Abstract P469: Association Between Quality and Patterns of Sleep and Ideal Cardiovascular Health in Black Americans: Results From the Morehouse-Emory Cardiovascular (MECA) Center for Health Equity

Introduction: Sleep is hypothesized to be a contributing factor towards disparities in cardiovascular disease (CVD). It has been demonstrated that Black Americans have worse sleep quality compared to other ethnic groups, but within group differences have not been studied. Whether overall sleep quality and patterns affect cardiovascular health (CVH) among Blacks has yet to be elucidated. Hypothesis: Black individuals reporting worse sleep quality and patterns will have poor CVH as measured by the American Heart Association’s Life’s Simple 7 (LS7) scores. Methods: We recruited 499 Black adults (age 53 ± 10, 38% male) without known CVD from the Atlanta, GA metropolitan area. Sleep quality and patterns were assessed by the Pittsburgh Sleep Quality Index (PSQI) which includes sleep quality, nighttime disturbance, efficiency (amount of time slept while in bed), daytime dysfunction, duration, need of medications and latency (time required to fall asleep). CVH was determined by LS7 scores calculated from measured blood pressure, glucose, cholesterol, body mass index (BMI), and self-reported exercise, diet, and smoking, and categorized into poor (0-8), intermediate (9-10), and ideal (11-14). Multinomial logistic regression was used to examine the relationship between sleep and the odds of intermediate (vs. poor) and ideal (vs. poor) CVH categories after adjusting for age, gender, household income, education, marital status, and employment status. Results: A total of 55 (11%), 107 (21%), and 337 (67%) participants had ideal, intermediate, and poor LS7 scores, respectively. Those reporting PSQI-assessed poor sleep quality (OR 0.50, 95% CI [0.33 - 0.78]), longer latency (OR 0.50, 95% CI [0.36 - 0.70]), disturbance (OR 0.45, 95% CI [0.26 - 0.77]) and daytime dysfunction (OR 0.52, 95% CI [0.31 - 0.89]) had significantly lower adjusted odds of having ideal CVH. Daytime dysfunction was significantly associated with lower adjusted odds of having ideal blood pressure (OR 0.57, 95% CI [0.38 - 0.87]), glucose (OR 0.71, 95% CI [0.51 - 0.98]), and physical activity (OR 0.58, 95% CI [0.36 - 0.93]). Similarly, longer latency was significantly associated with lower adjusted odds of having ideal BMI (OR 0.72, 95% CI [0.54 - 0.95]), blood pressure (OR 0.71, 95% CI [0.55 - 0.92]), and cholesterol (OR 0.73, 95% CI [0.55 - 0.98]). PSQI-assessed shorter sleep duration was not associated with poor overall CVH, but was associated with significantly lower adjusted odds of having ideal blood pressure (OR 0.77, 95% CI [0.61 - 0.99]). Conclusion: Among Black Americans, poor sleep in terms of quality, nighttime disturbance, daytime dysfunction and longer latency, was associated with worse overall CVH or its components. Whether addressing sleep quality in Blacks will improve CVH and outcomes needs to be studied.

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Abstract P513: Alcohol Type and Ideal Cardiovascular Health in The Multi-Ethnic Study of Atherosclerosis

Circulation ◽

10.1161/circ.141.suppl_1.p513 ◽

2020 ◽

Vol 141 (Suppl_1) ◽

Author(s):

Oluseye Ogunmoroti ◽

Olatokunbo Osibogun ◽

Robyn L McClelland ◽

Mariana Lazo ◽

Lena Mathews ◽

...

Keyword(s):

Cardiovascular Health ◽

Multinomial Logistic Regression ◽

Heart Association ◽

Prevalence Odds Ratio ◽

Cross Sectional ◽

Lower Odds ◽

Ideal Cardiovascular Health ◽

Study Participants ◽

Sectional Analysis ◽

The Relationship

Background: Light to moderate alcohol consumption is associated with lower incidence of cardiovascular disease (CVD) and favorable cardiovascular health (CVH). However, the association between alcohol type and ideal CVH is yet to be established. This study examined the relationship between alcohol type and ideal CVH as measured by the American Heart Association Life’s Simple 7 (LS7) metrics. Methods: We analyzed data from 6,389 men and women aged 45-84 years from a multi-ethnic cohort free of CVD at baseline. Alcohol type (wine, beer and liquor), assessed from a food frequency questionnaire, was categorized as never, >0 but <1 drink/day, 1-2 drinks/day and >2 drinks/day. Each LS7 metric (smoking, physical activity, body mass index, diet, blood pressure, total cholesterol and blood glucose) was scored 0-2 points, with 2 indicating “ideal”, 1 “intermediate” and 0 “poor”. The maximum CVH score attainable ranged from 0-14 points (inadequate score, 0-8; average, 9-10; optimal, 11-14). We used multinomial logistic regression to examine the association between alcohol type and CVH adjusted for age, sex, race/ethnicity, education, income, health insurance and study site. Results: The mean (SD) age of study participants was 62 (10) years and 53% were women. Participants who consumed 1-2 drinks/day of wine had higher odds of having optimal CVH scores compared to those who never drank wine [prevalence odds ratio (POR) 1.50 (1.02-2.20), Table ]. In comparison to participants who never drank beer, those who consumed 1-2 and >2 drinks/day of beer had lower odds of having optimal scores [POR 0.49 (0.27-0.86) & 0.27 (0.12-0.58), respectively]. Additionally, those who consumed 1-2 and >2 drinks/day of liquor had lower odds of having optimal scores compared to those who never drank liquor [POR 0.52 (0.30-0.89) & 0.28 (0.14-0.55), respectively]. Conclusion: In this cross sectional analysis, moderate consumption of wine was associated with favorable CVH. However, consumption of beer or liquor was associated with poorer CVH.

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Demographic and socioeconomic inequalities in ideal cardiovascular health: A systematic review and meta-analysis

PLoS ONE ◽

10.1371/journal.pone.0255959 ◽

2021 ◽

Vol 16 (8) ◽

pp. e0255959

Author(s):

Janko Janković ◽

Stefan Mandić-Rajčević ◽

Maša Davidović ◽

Slavenka Janković

Keyword(s):

Systematic Review ◽

Blood Pressure ◽

Cardiovascular Health ◽

Meta Analysis ◽

Fasting Blood Glucose ◽

Random Effect ◽

Heart Association ◽

Ideal Cardiovascular Health ◽

Low Prevalence ◽

The Relationship

Background In 2010, the American Heart Association introduced a new concept of ideal cardiovascular health (CVH) defined as the simultaneous presence of 7 favorable CVH metrics (smoking, diet, physical activity, body mass index, blood pressure, total cholesterol, and fasting blood glucose). The objective of this study was to conduct a systematic literature review and meta-analysis of studies examining the prevalence of ideal CVH, and each of the ideal CVH metrics as well as the relationship between socio-demographic determinants and ideal CVH. Methods A comprehensive literature search was conducted in Medline and Scopus databases for studies published between 1 January 2010 and 30 June 2020. A total of 50 studies including 2,148,470 participants were analyzed. Associations were estimated using DerSimonian-Laird random-effect models. Heterogeneity was investigated through subgroup analyses, Q-test, and I2 statistics. Results This study showed a low prevalence of ideal CVH defining as 6 and 7 ideal metrics (3.3%). Among seven ideal CVH metrics, smoking was the best metric (71%), while the poorest CVH metric was a healthy diet (5.8%). Gender was a statistically significant moderator of ideal smoking (81% in females and 60% in males) and ideal blood pressure (42% in females and 30% in males). Females and young adults had better CVH status compared to males and older adults. Also, more educated and better-off individuals had a greater number of ideal CVH metrics. Conclusions To the best of our knowledge, this is the first systematic review on the relationship between participants’ socioeconomic status and ideal CVH. The results suggest that the prevalence of ideal CVH and most metrics was unsatisfactory. In order to achieve the improvement of the CVH metrics and the overall ideal CVH, nationwide prevention efforts at the population and individual levels are urgently needed.

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The Relationship Between Quality of Sleep with Blood Pressure of Hypertension Patient in Mojolangu PHC, Malang

Jurnal Berkala Epidemiologi ◽

10.20473/jbe.v6i12018.25-36 ◽

2018 ◽

Vol 6 (1) ◽

pp. 25

Author(s):

Wahid Nur Alfi ◽

Roni Yuliwar

Keyword(s):

Blood Pressure ◽

Sleep Quality ◽

Poor Sleep ◽

United States Department ◽

Quality Of Sleep ◽

Cross Sectional ◽

Department Of Health ◽

National Heart Lung ◽

The Relationship

ABSTRAKWHO memperkirakan pada tahun 2020 Penyakit Tidak Menular (PTM) akan menyebabkan 73% kematian dan 60% seluruh kesakitan di dunia (WHO, 2013). Penyakit hipertensi di Indonesia banyak diderita oleh perempuan dengan persentase sebesar 28,8% dan sering tidak menunjukkan gejala serta baru disadari setelah menyebabkan gangguan organ. National Heart, Lung, and Blood Institut dari United States Department of Health and Human Services menginformasikan bahwa kurang tidur atau kualitas tidur yang buruk meningkatkan risiko tekanan darah tinggi, penyakit jantung, dan penyakit lainnya. Penelitian ini bertujuan untuk mengetahui hubungan kualitas tidur dengan tekanan darah pasien hipertensi di Puskesmas Mojolangu Kota Malang. Jenis penelitian ini adalah observasional analitik dengan desain penelitian cross sectional. Populasi dalam penelitian ini adalah seluruh pasien hipertensi di Puskesmas Mojolangu. Penelitian ini menggunakan total populasi dan tidak ada pengambilan sampel. Besar sampel diperoleh berdasarkan periode waktu dan diperoleh besar sampel sejumlah 30 dengan menetapkan beberapa kriteria inklusi dan eksklusi. Variabel dependennya yaitu tekanan darah dan variabel independennya adalah kualitas tidur. Analisis data menggunakan uji koefisien kontingensi. Hasil penelitian menunjukkan mayoritas responden dengan tekanan darah tidak normal sebanyak 53,3% berjenis kelamin perempuan, 43,3% berada dalam kelompok umur 41-60 tahun, 66,7% dengan kualitas tidur buruk. Ada hubungan antara kualitas tidur dengan tekanan darah pada pasien hipertensi dengan kuat hubungan 0,649. Kesimpulan penelitian, sebagian besar responden yang memiliki kualitas tidur buruk akan memiliki kenaikan tekanan darah, sehingga perlu dilakukan penyuluhan dan pendampingan pada penderita hipertensi.Kata Kunci: kualitas tidur, tekanan darah, pasien hipertensi ABSTRACT WHO estimate that, in 2020 non-communicable disease causes of death 73% and 60% of all morbidity in the world (WHO, 2013). In Indonesia, hypertension is suffered by women with 28.8% and often shows no symptoms, only realized after causing organ disorders. The National Heart, Lung, and Blood Institute of the United States Department of Health and Human Services informs that less sleep or poor sleep quality increases the risk of high blood pressure, heart disease and other diseases. This study aims to determine the relationship between the quality of sleep with blood pressure in hypertensive patients in Mojolangu Public Health Center, Malang. The type of this research is observational analytic with cross sectional design. Population in this research is all patient of hypertension in Mojolangu Public Health Center. This study uses total population. The sample size is generated based on the time period and a sample size of 30 is obtained by specifying some inclusion and exclusion criteria. The dependent variable is blood pressure and the independent variable is sleep quality. Analizing data by coeficient contingency. The result of this research are respondents with abnormal blood pressure were 53.3% female, 43.3% were in the 41-60 years old, 66.7% with poor sleep quality. There is a relationship between the quality of sleep with blood pressure in hypertensive patients with a strong relationship (0.649). The conclusion is respondents who have poor quality of sleep have an increase in blood pressure, so there are needs to be counseling and menthoring for hypertensive patients.Keywords: quality of sleep, blood pressure, hypertension patient

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Hubungan Kualitas Tidur Dengan Tekanan Darah

Indonesian Journal of Nursing Research (IJNR) ◽

10.35473/ijnr.v3i2.901 ◽

2021 ◽

Vol 3 (2) ◽

pp. 57

Author(s):

Widya Kusumaningrum ◽

Rosalina Rosalina ◽

Umi Setyoningrum

Keyword(s):

Blood Pressure ◽

Sleep Quality ◽

Systolic Blood Pressure ◽

Diastolic Blood Pressure ◽

Rank Correlation ◽

P Value ◽

Poor Sleep ◽

Poor Sleep Quality ◽

Cross Sectional ◽

The Relationship

Good quality sleep gets fresh and healthy when awakened from sleep. Poor sleep quality is a risk factor for physical and psychological problems. The problem will arise activating the sympathetic nervous system which eventually causes an increase in blood pressure. So it is important to research because there are still many respondents who experience poor sleep quality with increasing blood pressure. To determine the correlation between sleep quality with blood pressure. Research design descriptive corellational with cross sectional approach. Population in this study is students of PSIK at Ngudi Waluyo University. The sample technique used purposive sampling. The number of samples is 78 respondents. Analysis of research data used the Spearman Rank Correlation test. The results showed that the students who experienced poor sleep quality were 70 respondents (89.7%). The highest blood pressure of the students was systolic blood pressure of 110 mmHg and diastolic blood pressure of 80 mmHg. On the relationship between sleep quality and systolic blood pressure with a coefficient (r) of 0.400, the strength of the relationship is interpreted at a low level. On the relationship between sleep quality and diastolic blood pressure with a coefficient (r) of 0.619, the strength of the relationship is interpreted at a high level. There was a significant correlation between sleep quality and blood pressure with p-value of 0,000 <0.05. It is expected that the respondents and the society should better regulate blood pressure in order to get good quality sleep.Key words: sleep qualityblood pressure

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THE RELATIONSHIP BETWEEN SMART PHONE USAGE AND SLEEP DISTURBANCES AND PSYCHOLOGICAL DISSTRESS AMONG STUDENTS

Journal of Medicine and Pharmacy ◽

10.34071/jmp.2017.4.19 ◽

2017 ◽

pp. 125-130

Author(s):

Minh Tam Nguyen ◽

Phuc Thanh Nhan Nguyen ◽

Thi Thuy Hang Nguyen

Keyword(s):

High School ◽

High School Students ◽

University Students ◽

Sleep Quality ◽

Sleep Disturbances ◽

Public Health Problem ◽

Smartphone Addiction ◽

Poor Sleep ◽

School Students ◽

The Relationship

The increasing use of smartphone among young people is creating negative effects and is an important public health problem in many countries. Smartphone abuse and addiction may cause physical and psychological disorders among users. However, the awarenes on this issue has been inadequate due to lacking of evidence. Objectives: To describe the current situation of smartphone using among students at highschools and universities in Hue city and to examine the relationship between smartphone using and sleep disturbances and psychological disstress among participants. Methods: A cross-sectional study with a randomly selected sample of 1,150 students at highschools and universities in Hue city. SAS-SV scale was used to evaluate phone addiction status, K10 scale was used for psychological distress assessment and PSQI scale was used to examine the sleep quality. Results: The proportion of students at highschools and universities having smartphones was 78.0%. The rate of smartphone addiction among high school students was 49.1% and that among university students was 43.7%. There was 57.3% of high school students had poor sleep quality, and that of university students was 51.6%. There was a statistically significant association between smartphone addiction and sleep disturbances and psychological disstress among participants (p <0.05). Conclusion: The prevalence of smartphone addiction among students at highschools and universities is alarming and is related to sleep disturbances and psychological disstress among participants. There is a strong call to develop intervention to help students to aware and manage the use of smartphone effectively.

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POS1465-HPR THE RELATIONSHIP BETWEEN SEDENTARY BEHAVIOR AND SLEEP IN RHEUMATOID ARTHRITIS: A CROSS-SECTIONAL STUDY

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2021-eular.641 ◽

2021 ◽

Vol 80 (Suppl 1) ◽

pp. 1017.2-1018

Author(s):

N. Kelly ◽

E. Hawkins ◽

H. O’leary ◽

K. Quinn ◽

G. Murphy ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Physical Activity ◽

Sleep Quality ◽

Sedentary Behavior ◽

Disease Duration ◽

Cross Sectional Study ◽

P Value ◽

Poor Sleep ◽

Cross Sectional ◽

The Relationship

Background:Rheumatoid arthritis (RA) is a chronic, autoimmune inflammatory condition that affects 0.5% of the adult population worldwide (1). Sedentary behavior (SB) is any waking behavior characterized by an energy expenditure of ≤1.5 METs (metabolic equivalent) and a sitting or reclining posture, e.g. computer use (2) and has a negative impact on health in the RA population (3). Sleep is an important health behavior, but sleep quality is an issue for people living with RA (4, 5). Poor sleep quality is associated with low levels of physical activity in RA (4) however the association between SB and sleep in people who have RA has not been examined previously.Objectives:The aim of this study was to investigate the relationship between SB and sleep in people who have RA.Methods:A cross-sectional study was conducted. Patients were recruited from rheumatology clinics in a large acute public hospital serving a mix of urban and rural populations. Inclusion criteria were diagnosis of RA by a rheumatologist according to the American College of Rheumatology criteria age ≥ 18 and ≤ 80 years; ability to mobilize independently or aided by a stick; and to understand written and spoken English. Demographic data on age, gender, disease duration and medication were recorded. Pain and fatigue were measured by the Visual Analogue Scale (VAS), anxiety and depression were assessed using the Hospital Anxiety and Depression Scale (HADS), and sleep quality was assessed using the Pittsburgh Sleep Quality Index. SB was measured using the ActivPAL4™ activity monitor, over a 7-day wear period. Descriptive statistics were calculated to describe participant characteristics. Relationships between clinical characteristics and SB were examined using Pearson’s correlation coefficients and regression analyses.Results:N=76 participants enrolled in the study with valid data provided by N=72 participants. Mean age of participants was 61.5years (SD10.6) and the majority 63% (n = 47) were female. Participant mean disease duration was 17.8years (SD10.9). Mean SB time was 533.7 (SD100.1) minutes (8.9 hours per day/59.9% of waking hours). Mean sleep quality score was 7.2 (SD5.0) (Table 1). Correlation analysis and regression analysis found no significant correlation between sleep quality and SB variables. Regression analysis demonstrated positive statistical associations for SB time and body mass index (p-value=0.03846, R2 = 0.05143), SB time and pain VAS (p-value=0.009261, R2 = 0.07987), SB time and HADS (p-value = 0.009721, R2 = 0.08097) and SB time and HADSD (p-value = 0.01932, R2 = 0.0643).Conclusion:We found high levels of sedentary behavior and poor sleep quality in people who have RA, however no statistically significant relationship was found in this study. Future research should further explore the complex associations between sedentary behavior and sleep quality in people who have RA.References:[1]Carmona L, et al. Rheumatoid arthritis. Best Pract Res Clin Rheumatol 2010;24:733–745.[2]Anon. Letter to the editor: standardized use of the terms “sedentary” and “sedentary behaviours”. Appl Physiol Nutr Metab = Physiol Appl Nutr Metab 2012;37:540–542.[3]Fenton, S.A.M. et al. Sedentary behaviour is associated with increased long-term cardiovascular risk in patients with rheumatoid arthritis independently of moderate-to-vigorous physical activity. BMC Musculoskelet Disord 18, 131 (2017).[4]McKenna S, et al. Sleep and physical activity: a cross-sectional objective profile of people with rheumatoid arthritis. Rheumatol Int. 2018 May;38(5):845-853.[5]Grabovac, I., et al. 2018. Sleep quality in patients with rheumatoid arthritis and associations with pain, disability, disease duration, and activity. Journal of clinical medicine, 7(10)336.Table 1.Sleep quality in people who have RASleep variableBed Time N(%) before 10pm13(18%) 10pm-12pm43 (60%) after 12pm16 (22%)Hours Sleep mean(SD)6.56 (1.54)Fall Asleep minutes mean(SD)33.3(27.7)Night Waking N(%)45(63%)Self-Rate Sleep mean(SD)2.74 (0.90)Hours Sleep mean(SD)6.56 (1.54)Disclosure of Interests:None declared

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Obstructive sleep apnea syndrome and sleep quality in hypertensive patients

Revista da Associação Médica Brasileira ◽

10.1590/1806-9282.63.12.1055 ◽

2017 ◽

Vol 63 (12) ◽

pp. 1055-1060 ◽

Cited By ~ 3

Author(s):

Marcelo Rodrigues Bacci ◽

Jonathan Naim Mora Emboz ◽

Beatriz da Costa Aguiar Alves ◽

Glaucia Luciano da Veiga ◽

Neif Murad ◽

...

Keyword(s):

Blood Pressure ◽

Obstructive Sleep Apnea ◽

Sleep Apnea ◽

Sleep Quality ◽

High Blood Pressure ◽

Antihypertensive Drugs ◽

Poor Sleep ◽

Hypertensive Patients ◽

Group I ◽

Obstructive Sleep

Summary Introduction: Obstructive sleep apnea and hypopnea syndrome (OSAHS) is one of the developmental factors of high blood pressure (HBP), a relevant global public health problem. OSAHS is characterized by the reduction or complete cessation of respiratory airflow due to intermittent airway collapse. Additionally, significant changes in sleep rhythm and pattern are observed in these patients. Objective: To evaluate the association between OSAHS and sleep quality in essential and resistant hypertensives. Method: A cross-sectional, observational study evaluated 43 hypertensive patients treated at the outpatient clinics of the Faculdade de Medicina do ABC (FMABC) who were medicated with two or more antihypertensive drugs and divided into nonresistant or resistant to treatment. Results: Group I (using up to two antihypertensive agents – 60.47% of the sample) presented mean systolic blood pressure (SBP) of 127.5±6.4 mmHg, mean diastolic blood pressure (DBP) of 79.6±5.2 mmHg, mean body mass index (BMI) of 27.2±5.3 kg/m2 and mean age of 51.2±15.1 years. Group II (using more than two antihypertensive drugs – 37.2% of the sample) presented mean SBP of 132.1±9.3 mmHg, mean DBP of 84.5±5.8 mmHg, mean BMI of 27.2±7.2 kg/m2 and mean age of 55.5±13.4 years. The patients presented low quality of sleep/sleep disorder evaluated by the Pittsburgh Sleep Quality Index (PSQI), which represents a preponderant factor for OSAHS. Conclusion: Patients at high risk for OSAHS had poor sleep quality and high levels of DBP, suggesting a causal relation between these parameters. However, they did not present a higher prevalence of resistant high blood pressure (RHBP).

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Abstract 12944: Geographical Variations in Cardiovascular Health in China: A Nationwide Population-based Survey of 74,771 Adults

Circulation ◽

10.1161/circ.142.suppl_3.12944 ◽

2020 ◽

Vol 142 (Suppl_3) ◽

Author(s):

Mei Zhang ◽

Yu Shi ◽

Oumin Shi ◽

Zhenping Zhao ◽

Xiao Zhang ◽

...

Keyword(s):

Blood Pressure ◽

Cardiovascular Disease ◽

Health Behavior ◽

Health Behaviors ◽

Cardiovascular Health ◽

Significant Heterogeneity ◽

Chinese Adults ◽

Ideal Cardiovascular Health ◽

Geographical Variations ◽

Health Factors

Background: Cardiovascular disease is the leading cause of death in China. Objectives: We aimed to evaluate the levels of cardiovascular health among Chinese adults and to understand the geographic patterns based on a nationally and provincially representative survey. Methods: In 2015, a total of 74,771 respondents aged ≥ 20 years with no history of cardiovascular disease were randomly sampled from 298 counties/districts of 31 provinces in mainland China and were interviewed. Seven metrics, including smoking, body mass index, physical activity, diet, total cholesterol, blood pressure, and fasting glucose, were determined. Ideal cardiovascular health was defined as the simultaneous presence of all metrics at the ideal level. A score ranging from 0 to 14 was calculated as the sum of all seven metrics for each province. Scores for four health behaviors and four health factors were also calculated. Results: The age-adjusted prevalence of ideal cardiovascular health was only 1.13% among Chinese adults above 20 years old in 2015 (0.50% among men and 1.77% among women; 1.63% among urban residents and 0.68% among rural residents). The age-adjusted prevalence varied greatly across provinces, ranging from 0.05% in Qinghai to 2.97% in Heilongjiang. Ideal diet (7.4%) was the least common among seven cardiovascular health metrics and ideal blood pressure (32.2%) was the second least one. We also saw significant heterogeneity among provinces in age-adjusted cardiovascular health score, health behavior score, and health factors score. In all provinces, women had higher scores than men for cardiovascular health, health behaviors and health factors. Differences in cardiovascular health and health behavior scores between urban and rural areas were associated with levels of socio-economic development. Conclusions: Strategies for addressing poor cardiovascular health require geographic targeting and localized consideration.

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0407 Sleep, Stress, Cardiovascular, and Psychological Health in College Students

SLEEP ◽

10.1093/sleep/zsaa056.404 ◽

2020 ◽

Vol 43 (Supplement_1) ◽

pp. A156-A156

Author(s):

A M Reynolds ◽

K M Mullins

Keyword(s):

College Students ◽

Blood Pressure ◽

Heart Rate ◽

Psychological Health ◽

Psychological Factors ◽

Cardiovascular Health ◽

Sleep Efficiency ◽

Poor Sleep ◽

Sleep Habits ◽

Stress Symptoms

Abstract Introduction Epidemiological studies have long established that sleep factors, stress, and cardiovascular health are related. College students often struggle with the demands of college life, which leads to increased stress, symptoms of depression and anxiety, and poor sleep. The focus of the current study was to examine habitual sleep habits in college students, in association with psychological factors and physiological factors. Methods Participants included 51 undergraduate students (18 men, average age M=20.25 years, SD=1.78) who wore wrist actigraphs to measure their typical sleep habits. After one week, participants completed questionnaires about psychological symptoms (i.e., depression, anxiety, and stress; Depression Anxiety Stress Scale, DASS-21) and subjective physiological symptoms (i.e., fatigue; Multidimensional Assessment of Fatigue Scale, MAF). Blood pressure and heart rate were measured using a wrist cuff. Results Overall total sleep time was 6.59 hours and sleep efficiency was 82.55%. Pearson correlational analyses revealed a negative moderate association between sleep efficiency and diastolic blood pressure (r(49) = -.318, p = .024). Global PSQI scores were moderately associated with stress (r(49) = .419, p = .002). MAF Global Fatigue Index scores revealed positive associations with depression (r(49) = .344, p =.014), anxiety (r(49) = .474, p<.001), and stress (r(49) = .620 p<.001). Heart rate was positively associated with depressive symptoms r(49) = .296, p= .035), stress symptoms r(49) = .447, p= .001), and fatigue r(49) = .456, p= .001). Conclusion As expected, college students’ sleep was short in duration and poor in efficiency. Sleep factors, cardiovascular factors, psychological factors, and stress were all related, demonstrating the importance of sleep on physiological and psychological health. More research should be conducted to further examine the relationships and directionality between sleep, psychological factors, and stress as there may be underlying mechanisms important for cardiovascular health. Support None.

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Prediction of Diabetic Nephropathy from the Relationship between Fatigue, Sleep and Quality of Life

Applied Sciences ◽

10.3390/app10093282 ◽

2020 ◽

Vol 10 (9) ◽

pp. 3282

Author(s):

Angela Shin-Yu Lien ◽

Yi-Der Jiang ◽

Jia-Ling Tsai ◽

Jawl-Shan Hwang ◽

Wei-Chao Lin

Keyword(s):

Quality Of Life ◽

Feature Selection ◽

Diabetic Nephropathy ◽

Sleep Quality ◽

Support Vector ◽

Svm Classifier ◽

Poor Sleep ◽

Poor Sleep Quality ◽

The Relationship

Fatigue and poor sleep quality are the most common clinical complaints of people with diabetes mellitus (DM). These complaints are early signs of DM and are closely related to diabetic control and the presence of complications, which lead to a decline in the quality of life. Therefore, an accurate measurement of the relationship between fatigue, sleep status, and the complication of DM nephropathy could lead to a specific definition of fatigue and an appropriate medical treatment. This study recruited 307 people with Type 2 diabetes from two medical centers in Northern Taiwan through a questionnaire survey and a retrospective investigation of medical records. In an attempt to identify the related factors and accurately predict diabetic nephropathy, we applied hybrid research methods, integrated biostatistics, and feature selection methods in data mining and machine learning to compare and verify the results. Consequently, the results demonstrated that patients with diabetic nephropathy have a higher fatigue level and Charlson comorbidity index (CCI) score than without neuropathy, the presence of neuropathy leads to poor sleep quality, lower quality of life, and poor metabolism. Furthermore, by considering feature selection in selecting representative features or variables, we achieved consistence results with a support vector machine (SVM) classifier and merely ten representative factors and a prediction accuracy as high as 74% in predicting the presence of diabetic nephropathy.

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