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 >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= <.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=<.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)

The Past Is Prologue: Criminal Specialization Continuity in the Delinquent Career

2018 ◽  
Vol 17 (4) ◽  
pp. 335-353 ◽  
Author(s):  
Matt DeLisi ◽  
Ramate Bunga ◽  
Mark H. Heirigs ◽  
Jacob H. Erickson ◽  
Andy Hochstetler
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Specific Form ◽  
Theoretical Research ◽  
Logistic Regression Models ◽  
Aggravated Assault ◽  
The Past ◽  
California Youth Authority ◽  
Important Evidence ◽  
Robust Evidence

The versatility/specialization debate in criminology has important theoretical, research, and juvenile/criminal justice ramifications. Although offenders are mostly versatile, there is important evidence of specialization, but much of this evidence is derived from highly technical statistical approaches. Drawing on data from a cohort of serious delinquents committed to the California Youth Authority, logistic regression models revealed robust evidence for criminal specialization net the effects of behavioral and demographic controls. Prior homicide was associated with a 1,467% increased likelihood of being currently adjudicated for a homicide offense. Similar prior–current involvement in robbery (294% increased likelihood), aggravated assault (200%), burglary (148%), and drug sales (736%) was found. Logistic regression with odds ratios provides intuitive, valuable estimates of specialization in offending whereby prior involvement in a specific form of delinquency dramatically increases the likelihood of current involvement in the same form of crime.

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 Inflammation and mortality in COVID-19 hospitalized patients with and without type 2 diabetes

2022 ◽  
Author(s):  
Jia Guo ◽  
Wen-Hsuan W Lin ◽  
Jason E Zucker ◽  
Renu Nandakumar ◽  
Anne-Catrin Uhlemann ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Logistic Regression ◽  
Inflammatory Markers ◽  
Regression Models ◽  
Serum Levels ◽  
Hospitalized Patients ◽  
Logistic Regression Models ◽  
Diabetes Status ◽  
The Relationship

Abstract Background The aim of this study was to determine the relationship of inflammation with mortality in COVID-19 hospitalized patients and to assess if the relationship differed by strata of type 2 diabetes status. We hypothesized that the association of inflammation with mortality was different by type 2 diabetes status. Methods A case-control (died-survived) study of 538 COVID-19 hospitalized patients, stratified by diabetes status, was conducted at Columbia University Irving Medical Center. We quantified the levels of eight cytokines and chemokines in serum, including interferon(IFN)-α2, IFN-γ, Interleukin(IL)-1α, IL-1β, IL-6, IL-8/CXCL8, IFNγ-induced protein 10 (IP10)/CXCL10 and tumor necrosis factor α (TNF-α) using immunoassays. Logistic regression models were used to model the relationships of log-transformed inflammatory markers (or their principal components) and mortality. Results In multiple logistic regression models, higher serum levels of IL-6 (adjusted odds ratio (aOR):1.74, 95% confidence intervals (CI): (1.48, 2.06)), IL-8 (aOR: 1.75 (1.41, 2.19)) and IP10 (aOR: 1.36 (1.24, 1.51)), were significantly associated with mortality. This association was also seen in second principal component (PC) with loadings reflecting similarities among these three markers (aOR: 1.88 (1.54-2.31)). Significant positive association of these same inflammatory markers with mortality was also observed within each strata of diabetes. Conclusions We show that mortality in COVID19 patients is associated with elevated serum levels of innate inflammatory cytokine IL-6 and inflammatory chemokines IL-8 and IP10. This relationship is consistent across strata of diabetes, suggesting interventions targeting these innate immune pathways could potentially also benefit patients with diabetes.

scholarly journals 1400Central but not general obesity is positively associated with risk of hyperhomocysteinemia in middle-aged women

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Yingying Wang
Keyword(s):  
Cardiovascular Disease ◽  
Logistic Regression ◽  
Regression Models ◽  
Central Obesity ◽  
Multiple Logistic Regression ◽  
Obese Women ◽  
General Obesity ◽  
Middle Aged ◽  
Logistic Regression Models ◽  
The Relationship

Abstract Background Obesity and homocysteine (Hcy) are two important risk factors for cardiovascular disease (CVD); however, there were conflicting results for the relationship between them. Our study is to explore the associations of general and central obesity with hyperhomocysteinemia (HHcy) in middle-aged women. Methods The current analysis was based on data from 11007 women aged 40-60 years. Height, weight, and waist circumference (WC) were measured and serum homocysteine was determined. Multiple logistic regression models were used to assess the associations of the risk of hyperhomocysteinemia (HHcy, Hcy>15μmol/L) with BMI and WC. Results 13.71% women had HHcy. The prevalences of BMI-based general obesity and WC-based central obesity were 11.17% and 22.88%, respectively. Compared with non-obese women, the mean serum Hcy concentration was significantly higher in WC-based central obese women (P = 0.002), but not in BMI-based general obese women (P > 0.05). In the multiple logistic regression models, central obesity was positively related to the risk of HHcy (OR = 1.30, 95%CI=1.10 to 1.52), while general obesity was inversely related to the risk of HHcy (OR = 0.82, 95%CI=0.72 to 0.93 and OR = 0.71,95% CI = 0.57 to 0.89). Conclusions Central obesity was positively, while general obesity was negatively related to the risk of HHcy. Menopause showed no effect modification on these associations. Key messages Homocysteine; Central obesity; Menopause; Cardiovascular Disease

scholarly journals THE MODE CHOICES AND COMMUTING STRESS: EMPIRICAL EVIDENCE FROM JAKARTA AND DENPASAR

2019 ◽  
Vol 7 (1) ◽  
pp. 68
Author(s):  
Ismatulloh Rosida ◽  
Dyah Wulan Sari ◽  
Amelia Dertta Irjayanti
Keyword(s):  
Logistic Regression ◽  
Public Transport ◽  
Regression Models ◽  
Toll Roads ◽  
Multiple Logistic Regression ◽  
Logistic Regression Models ◽  
High Impedance ◽  
Logistic Regressions ◽  
Using Data ◽  
The Relationship

Jabodetabek and Sarbagita have the highest worker commuter population in Indonesia. However, Jabodetabek has various and larger coverage of public transport than Sarbagita. This study also analyzes the relationship between the usage of specific transport modes and commuting stress. Multiple logistic regression models have been estimated using data of both Jabodetabek Commuter Survey and Sarbagita Commuter Survey. Using logistic regressions, the results show that mode choices, gender, and travel time have a significant effect on commuting stress. The analysis also indicates that both in high impedance and low impedance metropolitans, car commuting is perceived to be more stressful than non-car commuting. In a condition of restricted mode choices, commuters who use cars have a greater probability of commuting stress. Furthermore, the findings of this study imply limitation of car usage and as an evaluation of the policy of opening toll roads as a solution to urban congestion.

The Timing of Prison Sanctions and the Odds of Returning to Prison After Release

2021 ◽  
pp. 001112872110547
Author(s):  
Christopher D’Amato ◽  
Ian A. Silver ◽  
John Wooldredge ◽  
Jamie Newsome
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Moderating Effect ◽  
Moderation Effect ◽  
Logistic Regression Models ◽  
The Relationship ◽  
Release From Prison

A sample of 48,930 inmates was examined to estimate the direct and moderating effect of the timing of prison sanctions on recidivism. Logistic regression models demonstrated that number of sanctions was positively associated with recidivism but timing of an inmate’s last sanction before release did not significantly influence recidivism. However, timing of an inmate’s last sanction moderated the association between number of sanctions and recidivism. This moderation effect suggested that as time between an inmate’s last sanction and release from prison increased, the effect of the total number of sanctions on recidivism decreased in magnitude. The results of this assessment suggest that the number and timing of sanctions matter in explaining the relationship between prison sanctions and recidivism.

Gardens of Stone: Searching for Evidence of Secularization and Acceptance of Death in Grave Inscriptions from 1900–2009

2011 ◽  
Vol 63 (4) ◽  
pp. 359-371 ◽  
Author(s):  
Keith A. Anderson ◽  
Christine L. Sielski ◽  
Elizabeth A. Miles ◽  
Alexis V. Dunfee
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Binary Logistic Regression ◽  
Logistic Regression Models ◽  
The Past ◽  
The Sublime ◽  
Attitude Toward Death ◽  
The Dead ◽  
Death Acceptance

From the magnificent to the mundane to the sublime, grave inscriptions serve as remembrances of the dead and provide concrete evidence of the thoughts and values of the day. In this study, 1,214 grave inscriptions ( N = 1,214) dated 1900 to 2009 were examined for evidence of secularization and changes in attitude toward death. Using set criteria, the researchers categorized grave inscriptions in terms of language used (sacred/secular) and acceptance of death (acceptance/other). Binary logistic regression models revealed significantly more use of sacred language and significantly less acceptance of death over the past 110 years. Findings from these analyses suggest that: (a) secularization may not be as pervasive as thought, particularly with respect to death; and (b) as death has become increasingly medicalized and marginalized, society has grown less accepting of the finitude of life. These findings are further discussed in light of the continued evolution of death memorials.

On Consistency of Bayesian Inference with Mixtures of Logistic Regression

2006 ◽  
Vol 18 (1) ◽  
pp. 224-243 ◽  
Author(s):  
Yang Ge ◽  
Wenxin Jiang
Keyword(s):  
Logistic Regression ◽  
Bayesian Inference ◽  
Regression Models ◽  
Classification Rule ◽  
Logistic Regression Models ◽  
Mixtures Of Experts ◽  
The Relationship ◽  
Consistency Properties ◽  
Flexible Model ◽  
True Relationship

This is a theoretical study of the consistency properties of Bayesian inference using mixtures of logistic regression models. When standard logistic regression models are combined in a mixtures-of-experts setup, a flexible model is formed to model the relationship between a binary (yes-no) response y and a vector of predictors x. Bayesian inference conditional on the observed data can then be used for regression and classification. This letter gives conditions on choosing the number of experts (i.e., number of mixing components) k or choosing a prior distribution for k, so that Bayesian inference is consistent, in the sense of often approximating the underlying true relationship between y and x. The resulting classification rule is also consistent, in the sense of having near-optimal performance in classification. We show these desirable consistency properties with a nonstochastic k growing slowly with the sample size n of the observed data, or with a random k that takes large values with nonzero but small probabilities.

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.

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