scholarly journals Soluble ST2 levels for predicting the presence and severity of metabolic syndrome

2021 ◽  
Author(s):  
Xiao Zong ◽  
Qin Fan ◽  
Hang Zhang ◽  
Qian Yang ◽  
Hongyang Xie ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Logistic Regression ◽  
Confidence Interval ◽  
Subgroup Analysis ◽  
Odds Ratio ◽  
Regression Models ◽  
Soluble St2 ◽  
Logistic Regression Models ◽  
The Relationship ◽  
Multivariable Adjustment

To explore the relationship between soluble ST2 (sST2) and metabolic syndrome (MetS) and determine whether sST2 levels can predict the presence and severity of MetS. We evaluated 550 consecutive subjects (58.91 ± 9.69 years, 50% male) with or without MetS from the Department of Vascular and Cardiology, Shanghai Jiao Tong University-Affiliated Ruijin Hospital. Serum sST2 concentrations were measured. The participants were divided into three groups according to the sST2 tertiles. Univariate and multivariable logistic regression models were used to evaluate the association between serum sST2 concentrations and the presence of MetS. Serum sST2 concentrations were significantly higher in the MetS group than in those in the no MetS group (14.80 ± 7.01 vs. 11.58 ± 6.41 ng/ml, P < 0.01). Subjects with more MetS components showed higher levels of sST2. sST2 was associated with the occurrence of MetS after multivariable adjustment as a continuous log-transformed variable (per 1 SD, odds ratio [OR]: 1.42, 95% confidence interval [CI]: 1.13-1.80, P < 0.01). Subgroup analysis showed that individuals with MetS have significantly higher levels of sST2 than those without MetS regardless of sex and age.High serum sST2 levels were significantly and independently associated with the presence and severity of MetS. Thus, sST2 levels may be a novel biomarker and clinical predictor of MetS.

785 Reported Restful Sleep Predicting Emotional Distress: Does Exercise (and its modalities) moderate?

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A305-A306
Author(s):  
Jesse Moore ◽  
Ellita Williams ◽  
Collin Popp ◽  
Anthony Briggs ◽  
Judite Blanc ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Aerobic Exercise ◽  
Regression Models ◽  
Regression Analyses ◽  
Logistic Regression Models ◽  
The Past ◽  
Strengthening Exercise ◽  
Waking Up ◽  
The Relationship ◽  
Age And Sex

Abstract Introduction Literature shows that exercise moderates the relationship between sleep and emotional distress (ED.) However, it is unclear whether different types of exercise, such as aerobic and strengthening, affect this relationship differently. We investigated the moderating role of two types of exercise (aerobic and strengthening) regarding the relationship between ED and sleep. Methods Our analysis was based on data from 2018 National Health Interview Survey (NHIS), a nationally representative study in which 2,814 participants provided all data. Participants were asked 1) “how many days they woke up feeling rested over the past week”, 2) the Kessler 6 scale to determine ED (a score &gt;13 indicates ED), and 3) the average frequency of strengthening or aerobic exercise per week. Logistic regression analyses were performed to determine if the reported days of waking up rested predicted level of ED. We then investigated whether strengthening or aerobic exercise differentially moderated this relationship. Covariates such as age and sex were adjusted in the logistic regression models. Logistic regression analyses were performed to determine if subjective reporting of restful sleep predicted level of ED. We investigated whether strengthening exercise or aerobic exercise differentially moderated this relationship. Covariates such as age and sex were adjusted in the logistic regression models. Results On average, participants reported 4.41 restful nights of sleep (SD =2.41), 3.43 strengthening activities (SD = 3.19,) and 8.47 aerobic activities a week (SD=5.91.) We found a significant association between days over the past week reporting waking up feeling rested and ED outcome according to K6, Χ2(1) = -741, p= &lt;.001. The odds ratio signified a decrease of 52% in ED scores for each unit of restful sleep (OR = .48, (95% CI = .33, .65) p=&lt;.001.) In the logistic regression model with moderation, aerobic exercise had a significant moderation effect, Χ2(1) = .03, p=.04, but strengthening exercise did not. Conclusion We found that restful sleep predicted reduction in ED scores. Aerobic exercise moderated this relationship, while strengthening exercise did not. Further research should investigate the longitudinal effects of exercise type on the relationship between restful sleep and ED. Support (if any) NIH (K07AG052685, R01MD007716, K01HL135452, R01HL152453)

Abstract 3775: Average Blood Glucose and Mortality in Patients Hospitalized with Acute Myocardial Infarction

Circulation ◽  
2007 ◽  
Vol 116 (suppl_16) ◽  
Author(s):  
Mikhail Kosiborod ◽  
Silvio Inzucchi ◽  
Harlan M Krumholz ◽  
Lan Xiao ◽  
Phillip G Jones ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Hospital Mortality ◽  
Regression Models ◽  
Independent Predictor ◽  
Laboratory Data ◽  
Logistic Regression Models ◽  
Average Blood Glucose ◽  
The Relationship ◽  
Multivariable Adjustment ◽  
Better Than

Background: Elevated blood glucose (BG) on admission is associated with higher mortality risk in patients (pts) hospitalized with AMI. However, the prognostic value of average BG, which reflects overall glycemic exposure much better than admission BG, is unknown. Furthermore, the nature of the relationship between average BG and mortality has not been determined. Methods: We evaluated a cohort of 16,871 AMI pts hospitalized from January 2000-December 2005, using Cerner Corporation’s Health Facts® database from 40 hospitals, which contains demographics, clinical and comprehensive laboratory data. Logistic regression models evaluated the nature of the relationship between mean BG during the entire AMI hospitalization and in-hospital mortality, after adjusting for multiple patient factors and confounders. Similar analyses were performed in subgroups of pts with and without diabetes (DM). Results: A J-shaped relationship was observed between mean BG and in-hospital mortality, which persisted after multivariable adjustment (Figure ). Mortality increased with each 10 mg/dL incremental rise in mean BG over >120 mg/dL, and with incremental decline in mean BG <80 mg/dL. The slope of these relationships was much steeper in pts without DM. Conclusions: Average BG during the entire AMI hospitalization is a powerful independent predictor of in-hospital mortality. Both persistent hyper- and hypoglycemia are associated with adverse prognosis. Whether strategies directed at optimizing BG control will improve survival remains to be established. Association Between Mean BG and In-Hospital Mortality After Multivariable Adjustment (Reference: Mean BG 100 to <110)

scholarly journals Improving the odds? How to pick the winner of the English Derby

2014 ◽  
Vol 10 (1) ◽  
pp. 57-62
Author(s):  
D.J. Marlin ◽  
J.M. Williams ◽  
T. Parkin
Keyword(s):  
Logistic Regression ◽  
Confidence Interval ◽  
Regression Models ◽  
Mixed Effects ◽  
Point Estimate ◽  
Prize Money ◽  
Logistic Regression Models ◽  
Predictive Variables ◽  
Time Period ◽  
Predictive Probability

Many consider the English Derby on Epsom Downs to be ‘The Blue Riband of the Turf’. The Epsom Derby has been run annually since 1780 and the colt Diomed was the first winner. Today the Epsom Derby, run over 1.5 miles, is one of five classic races and is the second leg of the English Triple Crown, preceded by the 2,000 Guineas and followed by the St Leger. The prize money for 2010 has been in excess of £1.25 million. To the best of our knowledge, whilst epidemiological techniques have previously been applied in an attempt to identify risk factors for injury, the purpose of the present study, which we believe is unique, was to use an epidemiological approach to analyse factors that may be predictive of success (or failure) in a single race over the course of a number of consecutive years: The Epsom Derby. Information on the horses competing in the last 22 runnings of the Epsom Derby between 1988 and 2009. Univariate and multivariable single-level and mixed effects logistic regression models were developed using winning the Epsom Derby as the dependent variable. Between 1988 and 2009 in 22 runnings of the Derby, a total of 344 horses started the Epsom Derby. The number of runners in the race has varied between 12 and 25 over the same time period. On average the probability of winning the Derby between 1988 and 2009 was approximately 6% (22/344), without accounting for any potentially predictive variables. Variables that were related to an increased chance of success were being the favourite (odds ratio (OR) 4.75; 95 % confidence interval (CI) 1.58-14.3; P=0.006), the number of 2-year old wins (OR 1.45; CI 1.03-2.04; P=0.03), being foaled in Ireland (OR 2.80; CI 1.12-7.04; P=0.041) and having the same jockey in all races throughout the horses career up to and including the Derby (OR 2.53; CI 1.0-6.41; P=0.05). The highest predictive probability was for horses that started the race as a favourite, were Irish bred, had been ridden by a single jockey and had won twice as a 2-year old. Although the point estimate for this probability was 52% the degree of uncertainty around this estimate was wide, i.e. the 95% CI was 17.5 to 86.5%. Nevertheless even at the lower confidence interval this still represents a significant improvement on the approximately 6% chance of picking a winner at random. In conclusion, using mixed effects logistic regression models would allow one to improve the odds of picking the winner of the Epsom Derby over the past 22 runnings.

scholarly journals The Association between Hyperhomocysteinemia and Thoracoabdominal Aortic Aneurysms in Chinese Population

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Jianqing Deng ◽  
Jie Liu ◽  
Long Cao ◽  
Qun Wang ◽  
Hongpeng Zhang ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Confidence Interval ◽  
Regression Models ◽  
Case Control Study ◽  
Case Control ◽  
Aortic Aneurysms ◽  
Control Group ◽  
Case Group ◽  
Logistic Regression Models ◽  
Control Study

Objective. To shed light on the association between hyperhomocysteinemia (HHcy) and thoracoabdominal aortic aneurysms (TAAAs). Methods. From July 2013 to March 2017, we conducted a matched case–control study involving individuals who presented to the Chinese People’s Liberation Army General Hospital and underwent thoracoabdominal magnetic resonance angiography or computed tomography angiography. A total of 73 patients with TAAAs were enrolled in the case group, and 219 sex-matched subjects without TAAAs were included in the control group. We then examined the relationship between HHcy and TAAAs by logistic regression models and subgroup as well as interaction analyses. Results. Serum total homocysteine (tHcy) concentrations and the proportion of HHcy were significantly higher in the patients with TAAAs than in those without TAAAs (P<0.001). Furthermore, the multivariate logistic regression models indicated that participants with HHcy had a 2.14-fold higher risk of TAAAs than those with a normal serum tHcy level (adjusted odds ratio (OR), 2.14; 95% confidence interval, 1.00–4.56). Similarly, each 1 μmol/L increase in the serum tHcy concentration was associated with a 4% higher risk of TAAAs (adjusted OR, 1.04; 95% confidence interval, 1.00–1.07). Subgroup analyses indicated that HHcy tended to be associated with a greater risk of TAAAs in all stratified subgroups (adjusted ORs>1). Furthermore, the interaction analyses revealed no interactive role in the association between HHcy and TAAAs. Conclusions. The present case–control study suggests that HHcy is an independent risk factor for TAAAs. Larger prospective cohort studies are warranted to validate these findings.

scholarly journals Effects of Older Adult Driving Resumption on All-Cause Mortality

2019 ◽  
Vol 75 (10) ◽  
pp. 2263-2267
Author(s):  
Kendra L Ratnapradipa ◽  
Jing Wang ◽  
Marla Berg-Weger ◽  
and Mario Schootman
Keyword(s):  
Logistic Regression ◽  
Older Adult ◽  
Mortality Risk ◽  
Odds Ratio ◽  
Regression Models ◽  
Adjusted Odds Ratio ◽  
Community Dwelling ◽  
Driving Cessation ◽  
Logistic Regression Models ◽  
All Cause Mortality

Abstract Objectives Driving cessation is associated with adverse social and health outcomes including increased mortality risk. Some former drivers resume driving. Do resumed drivers have a different mortality risk compared to former drivers or continued drivers? Method We analyzed National Health and Aging Trends Study (2011–2015) data of community-dwelling self-responding ever drivers (n = 6,189) with weighted stratified life tables and discrete time logistic regression models to characterize mortality risk by driving status (continued, resumed, former), adjusting for relevant sociodemographic and health variables. Results Overall, 14% (n = 844) of participants died and 52% (n = 3,209) completed Round 5. Former drivers had the highest mortality (25%), followed by resumed (9%) and continued (6%) drivers. Former drivers had 2.4 times the adjusted odds of mortality compared with resumed drivers (adjusted odds ratio [aOR] = 2.41; 95% confidence interval [CI] = 1.51, 3.83), with no difference between continued and resumed drivers (aOR = 1.22; 95% CI = 0.74, 1.99). Discussion Those who resumed driving had better survival than those who did not. Practice implications include driver rehabilitation and retraining to safely promote and prolong driving.

scholarly journals Loneliness and COVID-19 preventive behaviours among Japanese adults

2020 ◽  
Author(s):  
Andrew Stickley ◽  
Tetsuya Matsubayashi ◽  
Michiko Ueda
Keyword(s):  
Mental Health ◽  
Logistic Regression ◽  
Odds Ratio ◽  
Regression Models ◽  
Online Survey ◽  
Health Behaviours ◽  
Regression Analyses ◽  
Linear Regression Models ◽  
Japanese Adults ◽  
The Relationship

Abstract Background There is some evidence that loneliness may be linked to poorer health behaviours. Despite this, there has been little research to date on the relationship between loneliness and COVID-19 preventive behaviours. We studied these associations in a sample of the Japanese population. Methods Data were analysed from an online survey of 2000 adults undertaken in April and May 2020. Loneliness was assessed with the Three-Item Loneliness Scale. Information was also collected on 13 COVID-19 preventive behaviours. Regression analyses were used to examine associations. Results In linear regression models adjusted for demographic and mental health variables, both dichotomous and continuous loneliness measures were negatively associated with engaging in COVID-19 preventive behaviours. Logistic regression analyses further showed that loneliness was also associated with reduced odds for a variety of individual preventive behaviours including wearing a mask (odds ratio [OR]: 0.77, 95% confidence interval [CI]: 0.62–0.95), disinfecting hands (OR: 0.80, 95% CI: 0.67–0.94) and social distancing when outdoors (OR: 0.75, 95% CI: 0.61–0.92). Conclusions Loneliness is associated with lower engagement in COVID-19 preventive behaviours. Interventions to prevent or ameliorate loneliness during the ongoing pandemic may be important in combating the spread of the coronavirus.

Do Demographic Factors Moderate How Well Criminal Thinking Predicts Recidivism?

2017 ◽  
Vol 62 (7) ◽  
pp. 2045-2062 ◽  
Author(s):  
Johanna B. Folk ◽  
Jeffrey B. Stuewig ◽  
Brandy L. Blasko ◽  
Michael Caudy ◽  
Andres G. Martinez ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Logistic Regression ◽  
Justice System ◽  
Regression Models ◽  
Demographic Factors ◽  
Jail Inmates ◽  
Criminal Thinking ◽  
Logistic Regression Models ◽  
Two Measures ◽  
The Relationship

Is the relationship between criminal thinking and recidivism the same for criminal justice–involved individuals from varying demographic backgrounds? Relying on two independent samples of offenders and two measures of criminal thinking, the current studies examined whether four demographic factors—gender, race, age, and education—moderated the relationship between criminal thinking and recidivism. Study 1 consisted of 226 drug-involved probationers enrolled in a randomized clinical trial. Study 2 consisted of 346 jail inmates from a longitudinal study. Logistic regression models suggested that the strength of the relationship between criminal thinking and subsequent recidivism did not vary based on participant demographics, regardless of justice system setting or measure of criminal thinking. Criminal thinking predicts recidivism similarly for people who are male, female, Black, White, older, younger, and more or less educated.

scholarly journals Examine the Association between Metabolic Syndrome and Frailty in an Older Asian Population

2021 ◽  
Author(s):  
Hiep Huu Hoang Dao ◽  
Anh Trung Nguyen ◽  
Huyen Thi Thanh Vu ◽  
Tu Ngoc Nguyen
Keyword(s):  
Metabolic Syndrome ◽  
Logistic Regression ◽  
Sex Education ◽  
Regression Models ◽  
Asian Population ◽  
Frailty Phenotype ◽  
Cross Sectional ◽  
Logistic Regression Models ◽  
Asian Populations ◽  
Definition Of

Background: There has been evidence that metabolic syndrome (MetS) may increase the risk of frailty. However, there is limited evidence on this association in Asian populations. Aims: This study aims to identify the association between MetS and frailty in older people in Vietnam. Methods: This is a cross-sectional analysis of a dataset obtained from an observational study on frailty and sarcopenia in patients aged &ge;60 at a geriatric hospital in Vietnam. Frailty was defined by the frailty phenotype. Participants were defined as having MetS if they had &ge;3 out of 5 criteria from the definition of the National Cholesterol Education Program (NCEP) Adults Treatment Panel (ATP) III. Multiple logistic regression models were performed to estimate the risk of having frailty in patients with MetS. Results: There were 669 participants (mean age 71, 60.2% female), 62.3% had MetS and 39.0% was frail. The prevalence of frailty was 42.2% in participants with MetS, 33.7% in participants without MetS (p=0.029). On logistic regression models, MetS was associated with increased likelihood of being frail (adjusted OR 1.52, 95%CI 1.01-2.28), allowing for age, sex, education, nutritional status, history of hospitalisation and chronic diseases. Conclusion: There was a significant association between MetS and frailty in this population. Further longitudinal studies are required to confirm this association.

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