scholarly journals Seasonal Changes in Sleep Patterns in Two Saskatchewan First Nation Communities

2021 ◽  
Vol 3 (3) ◽  
pp. 415-428
Author(s):  
Chandima P. Karunanayake ◽  
Vivian R. Ramsden ◽  
Clifford Bird ◽  
Jeremy Seeseequasis ◽  
Kathleen McMullin ◽  
...  
Keyword(s):  
Seasonal Changes ◽  
Sleep Problems ◽  
Marked Change ◽  
Binary Logistic Regression ◽  
The Body ◽  
First Nation ◽  
Seasonal Effects ◽  
Sleep Patterns ◽  
Binary Logistic Regression Model ◽  
Canada Data

Sleep is crucial for maintaining the recovery and restoration of the body and brain. Less sleep is associated with poor mental and physical performance. Seasonal changes in sleep patterns can be observed. This paper examines seasonal effects on sleep timing, duration, and problems in two Cree First Nation communities in Saskatchewan, Canada. Data were available from a community survey of 588 adults aged 18 years and older (range: 18–78 years) with 44.2% males and 55.8% females. Results are presented using descriptive statistics and a binary logistic-regression model to identify the association between seasonal changes in sleep patterns, and demographic, social, and environmental factors. The participants reported sleeping the least during the spring and summer months and sleeping the most during the fall and winter months. This was further confirmed by sleep hours and the lower proportion of recommended hours of sleep during the spring and summer, and a higher proportion of longer sleep duration during the fall and winter months. There was no significant variation in sleeping onset and wake-up times by season. Overall, there were no significant differences in the prevalence of sleep deprivation, insomnia, and excessive daytime sleepiness by season. When stratified by age group and sex, some differences existed in the prevalence of sleep problems by season. More than two-thirds (68.6%) of the participants reported that there was a change in sleep patterns across seasons, and about 26.0% reported a very or extremely marked change in sleep patterns across seasons. Changes in sleep patterns by season were related to money left at the end of the month and damage caused by dampness in the house.

Determinants of pain occurrence in dance teachers

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Jasmin Haenel ◽  
Thomas Schoettker-Koeniger ◽  
David A. Groneberg ◽  
Eileen M. Wanke
Keyword(s):  
Logistic Regression ◽  
Professional Practice ◽  
Online Survey ◽  
Health Hazard ◽  
Binary Logistic Regression ◽  
Warning Signal ◽  
The Body ◽  
Binary Logistic Regression Model ◽  
Dance Teachers ◽  
Pain Prevalence

Abstract Objectives Dance teachers are strongly dependent on their functional body in their professional practice. As yet, it has largely been unclear whether the musculoskeletal system is endangered by a dance teaching activity. Pain can be a warning signal for a health hazard. The aims of the study were (a) to determine the pain prevalence, location and assessment of dance teachers and (b) to identify determinants of pain occurrence over a 3-month period prior to the survey. Methods The quantitative, retrospective cohort study was conducted with n=166 dance teachers by an anonymous online survey. The data on the study sample, professional practice and pain prevalence, location and assessment were presented descriptively. A binary logistic regression was used to identify determinants of pain occurrence in the last 3 months from the sample parameters and the data of professional practice. Results In the 3-month period n=143 (86.1%) of dance teachers had been in pain, often localized in the lower back and lower extremities. In the binary logistic regression model, the Body mass index (BMI) (odds ratio (OR)=1.15, 95% CI: 0.93–1.42, p=0.18), age (OR=1.03, 95% CI: 0.99–1.08, p=0.11) and the presence of disease (OR=2.81, 95% CI: 0.78–10.15, p=0.12) were identified as determinants of pain occurrence (LR-Chi2=7.8, p<0.05, pseudo R2=0.06, n=160). Conclusions Pain occurs in dance teachers under multifactorial conditions. Pain occurrence seems to be favored by context factors, such as the BMI, age and the presence of diseases. However, none of these factors could be identified as a significant, clear risk factor for the occurrence of pain in this sample. Education and preventive measures, that consider pain as a warning signal, should take effect early in the dance career.

Credit constraints and Rural Migration: Evidence from Six Villages in Uttar Pradesh

2018 ◽  
Vol 15 (3) ◽  
pp. 389-398
Author(s):  
Ruchi Singh
Keyword(s):  
Credit Constraints ◽  
Uttar Pradesh ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Male Migration ◽  
Rural Economies ◽  
And Migration ◽  
The Relationship ◽  
The Empirical Analysis

Rural economies in developing countries are often characterized by credit constraints. Although few attempts have been made to understand the trends and patterns of male out-migration from Uttar Pradesh (UP), there is dearth of literature on the linkage between credit accessibility and male migration in rural Uttar Pradesh. The present study tries to fill this gap. The objective of this study is to assess the role of credit accessibility in determining rural male migration. A primary survey of 370 households was conducted in six villages of Jaunpur district in Uttar Pradesh. Simple statistical tools and a binary logistic regression model were used for analyzing the data. The result of the empirical analysis shows that various sources of credit and accessibility to them play a very important role in male migration in rural Uttar Pradesh. The study also found that the relationship between credit constraints and migration varies across various social groups in UP.

Prevalence of facemask use among general public when visiting wet market during Covid-19 pandemic: An observational study. (Preprint)

2020 ◽  
Author(s):  
Gobi Hariyanayagam ◽  
Sera Selvanthan Sundram Gunasekaran ◽  
Shargunan Selvanthan Gunasekaran ◽  
Nur Syafina Insyirah Zaimi ◽  
Nor Amirah Abdul Halim
Keyword(s):  
High Risk ◽  
General Population ◽  
Binary Logistic Regression ◽  
Final Analysis ◽  
High Risk Population ◽  
Binary Logistic Regression Model ◽  
Chi Square ◽  
Hygiene Measures ◽  
Wet Market ◽  
Medical Grade

BACKGROUND In late December 2019, an outbreak of a novel coronavirus disease (COVID-19; previously known as 2019-nCoV) was epidemiologically linked to seafood and wet animal market in Wuhan, Hubei, China. This event has instigated negative stigma among the general population to view the wet market as a high-risk location for potential transmission of coronavirus. OBJECTIVE This study investigated the prevalence of facemask use among general population visiting the wet market as well as factors contributing to unacceptable facemask practice. Setting The visitors to a district wet market selling range of live or freshly slaughtered animals during COVID-19 pandemic outbreak was observed for facemask practice. METHODS All Individuals visiting the market were observed for the type, category and practice of wearing facemas. Subjects were categorized into two groups of acceptable and unacceptable facemask practice. The Pearson chi-square was used to test for differences in investigated variables in the univariate setting and Binary Logistic regression model was used in the multivariate setting. Main outcome measure Prevalence, acceptance practice and odds ratio of unacceptance of facemask use. RESULTS Among 1697 individuals included in the final analysis, 1687 (99.7%) was observed wearing facemask with 1338 (78.8%) using medical-grade facemask. Among them, 1615 (95.7%) individuals facemask practice was acceptable while the reaming 72 (4.3%) individuals were observed with unacceptable facemask practice. Individuals using medical-grade facemask and high-risk age group are 6.4 times (OR=6.40; 95% CI, 2.00-20.43; p=.002) and 2.06 times practice (OR=2.06; 95% CI, 1.08-3.94; p=.028) more likely to have unacceptable facemask practice respectively. CONCLUSIONS High saturation of facemask among the general population is an adequate indicator of public hygiene measures strategy which can help to mitigate the COVID-19 epidemic impact. Alarmingly, the unacceptable facemask practice among high-risk population raises the need for a targeted approach by healthcare authorities to ensure satisfactory facemask use.

scholarly journals Least Likely Observations in Regression Models for Categorical Outcomes

2002 ◽  
Vol 2 (3) ◽  
pp. 296-300 ◽  
Author(s):  
Jeremy Freese
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Binary Logistic Regression ◽  
Positive Outcome ◽  
Ordinary Least Squares ◽  
Parameter Estimates ◽  
Least Squares Regression ◽  
Binary Logistic Regression Model ◽  
Ordered Logistic Regression ◽  
Negative Outcome

This article presents a method and program for identifying poorly fitting observations for maximum-likelihood regression models for categorical dependent variables. After estimating a model, the program leastlikely will list the observations that have the lowest predicted probabilities of observing the value of the outcome category that was actually observed. For example, when run after estimating a binary logistic regression model, leastlikely will list the observations with a positive outcome that had the lowest predicted probabilities of a positive outcome and the observations with a negative outcome that had the lowest predicted probabilities of a negative outcome. These can be considered the observations in which the outcome is most surprising given the values of the independent variables and the parameter estimates and, like observations with large residuals in ordinary least squares regression, may warrant individual inspection. Use of the program is illustrated with examples using binary and ordered logistic regression.

scholarly journals The effects of seasons and weather on sleep patterns measured through longitudinal multimodal sensing

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Stephen M. Mattingly ◽  
Ted Grover ◽  
Gonzalo J. Martinez ◽  
Talayeh Aledavood ◽  
Pablo Robles-Granda ◽  
...  
Keyword(s):  
Sleep Duration ◽  
Seasonal Effects ◽  
Sleep Patterns ◽  
Sleep Habits ◽  
Sleep Behavior ◽  
Weather Effects ◽  
Wake Time ◽  
Multimodal Sensing ◽  
Four Seasons ◽  
Local Weather

AbstractPrevious studies of seasonal effects on sleep have yielded unclear results, likely due to methodological differences and limitations in data size and/or quality. We measured the sleep habits of 216 individuals across the U.S. over four seasons for slightly over a year using objective, continuous, and unobtrusive measures of sleep and local weather. In addition, we controlled for demographics and trait-like constructs previously identified to correlate with sleep behavior. We investigated seasonal and weather effects of sleep duration, bedtime, and wake time. We found several small but statistically significant effects of seasonal and weather effects on sleep patterns. We observe the strongest seasonal effects for wake time and sleep duration, especially during the spring season: wake times are earlier, and sleep duration decreases (compared to the reference season winter). Sleep duration also modestly decreases when day lengths get longer (between the winter and summer solstice). Bedtimes and wake times tend to be slightly later as outdoor temperature increases.

Predictive Factors for Patients’ Failure to Show for Initial Outpatient Physical Therapist Evaluation

2021 ◽  
Author(s):  
Matthew Briggs ◽  
Christine Ulses ◽  
Lucas VanEtten ◽  
Cody Mansfield ◽  
Anthony Ganim ◽  
...  
Keyword(s):  
Predictive Factors ◽  
Employment Status ◽  
Physical Therapist ◽  
Demographic Data ◽  
Binary Logistic Regression ◽  
Final Analysis ◽  
Outpatient Setting ◽  
Binary Logistic Regression Model ◽  
Number Of Patients ◽  
Payer Source

Abstract Objective The objective of this study was to xamine primary factors which may predict patients’ failure to show at initial physical therapist evaluation in an orthopedic and sports outpatient setting. Methods A retrospective analysis of patients’ demographic data for physical therapist evaluations between January 2013 and April 2015 was performed. A binary logistic regression model was used to evaluate the odds of a no-show at evaluation. Demographic variables of age, employment status, days waited for the appointment, payer source, and distance traveled to clinic were analyzed. Independent variables were considered significant if the 95% Cis of the odds ratios did not include 1.0. Results A total of 6971 patients were included in the final analysis with 10% (n = 698) of the scheduled patients having a no-show event for their initial evaluation. The following factors increased the odds of patients having a no-show event: days to appointment (OR = 1.058; 95% CI = 1.042 to 1.074), unemployment status (OR = 1.96; 95% CI = 1.41 to 2.73), unknown employment status (OR = 3.22; 95% CI = 1.12 to 8.69), Medicaid insurance (OR = 4.87; 95% CI = 3.43 to 6.93), Medicare insurance (OR = 2.22; 95% CI = 1.10 to 4.49), unknown payer source (OR = 262.84; 95% CI = 188.72 to 366.08), and distance traveled ≥5 miles (OR = 1.31; 95% CI = 1.01 to 1.70). Female sex [OR = 0.73; 95% CI = 0.57 to 0.95) and age ≥ 40 years (OR = 0.44; 95% CI = 0.33 to 0.60) decreased the odds of a no-show event. Conclusion Results from this study indicate there may be some demographic factors that are predictive of patients failing to attend their first physical therapist visit. Impact Understanding the predictive factors and identifying potential opportunities for improvements in scheduling processes might help decrease the number of patients failing to show for their initial physical therapy appointment, with the ultimate goal of positively influencing patient outcomes.

scholarly journals SAT0084 SERUM ADIPOKINES PROFILE IN PATIENTS WITH RHEUMATOID ARTHRITIS TREATED WITH TNF-INHIBITORS

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 976.2-976
Author(s):  
M. Novella-Navarro ◽  
B. Hernández-Breijo ◽  
F. Genre ◽  
L. Lera-Gómez ◽  
V. Pulito-Cueto ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Remission Rate ◽  
Binary Logistic Regression ◽  
Negative Influence ◽  
Normal Weight ◽  
The Body ◽  
Response To Treatment ◽  
Bivariate Analysis ◽  
Tnf Inhibitor ◽  
Serum Leptin

Background:In recent years, the relationship between obesity and autoimmune diseases has taken interest, since adipose tissue has been identified as an endocrine organ that secretes cytokines (adipokines), among which leptin stands out as a soluble pro-inflammatory mediator associated with the body mass index (BMI).Objectives:The main objectives of this study are: i) to analyse the influence of BMI on clinical response in Rheumatoid Arthritis (RA) patients who initiate TNF-inhibitor (TNFi) therapy; ii) to analyse the differences in the serum profile of adipokines (leptin and adiponectin) according to BMI and their association with response to treatment.Methods:Observational study of a prospective cohort of 73 RA patients who initiated biological treatment with TNFi from the Complex Therapy Unit (CTU) of our Hospital. Patients were classified according to their BMI in normal-weight (BMI<25) and overweight/obesity (O/O) (IMC≥25). Demographic, clinical and laboratory variables were collected at baseline and at 6 months. Our outcome measures were DAS28-VSG remission (DAS28<2.6) at 6 months after TNFi initiation. Serum leptin and adiponectin levels were measured by Enzyme-Linked Immuno Sorbent Assay (ELISA) at baseline and 6 months. A descriptive sample analysis comparing the characteristics of both patient subgroups was performed using Chi-square, T-test for independent samples and U-Mann Whitney. Likewise, a bivariate analysis was carried out by means of binary logistic regression to assess the probable association of the parameters studied with remission.Results:Of the 73 patients studied, 51% were classified in O/O group. The O/O patients presented higher levels of baseline CRP (16.69±6.16 vs 8.74±3.81, p=0.01). No statistically significant differences were observed in the remaining variables (sex, age at the beginning of the TNFi, disease duration, baseline DAS-28), as well as therapeutic variables (use of previous DMARDs and doses of methotrexate and/or steroids). Patients with overweight/obesity presented higher DAS28-ESR values at 6 months of treatment (3.59±1.14 vs 2.93±1.27, p=0.02) and achieved remission less frequently (18.9% vs 48.6%, p=0.007). Serum leptin levels were significantly higher in O/O patients, both baseline (29.39±21.50 vs 13.49±8.78, p<0.001) and 6 months (33.06±22.03 vs 14.77±9.50, p<0.001) after TNFi initiation. In addition, O/O patients were less likely to reach remission at 6 months than normal-weight patients. [OR= 4.04 IC95% (1.40-11.64); p=0.009]. Lower frequency of remission was associated to greater leptin levels at 6 months [OR=0.94 CI95% (0.90-098); p=0.012]. No differences in serum adiponectin were found between both subgroups of patients.Conclusion:In this RA patient cohort, overweight/obesity is associated with i) a reduced response to TNFi therapy and ii) a lower short-term remission rate. Within the adipokine profile, leptin seems to play a relevant role in the maintenance of pro-inflammatory activity with a negative influence on the response to TNFi therapy in O/O patients.References:[1] Versini M. et al. Autoimmun Rev. 2014; 13, 981-1000[2] Toussirot E et al. Life Sci. 2015;140: 29-36.Disclosure of Interests:Marta Novella-Navarro: None declared, Borja Hernández-Breijo: None declared, Fernanda Genre: None declared, Leticia Lera-Gómez: None declared, Verónica Pulito-Cueto: None declared, Laura Nuño: None declared, Alejandro Villalba: None declared, Alejandro Balsa Grant/research support from: BMS, Roche, Consultant of: AbbVie, Gilead, Lilly, Pfizer, UCB, Sanofi, Sandoz, Speakers bureau: AbbVie, Lilly, Sanofi, Novartis, Pfizer, UCB, Roche, Nordic, Sandoz, Chamaida Plasencia: None declared

scholarly journals Correlation of age, sex and season with the state of human decomposition as quantified by postmortem computed tomography

2021 ◽  
Author(s):  
Dominic L. C. Guebelin ◽  
Akos Dobay ◽  
Lars Ebert ◽  
Eva Betschart ◽  
Michael J. Thali ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Demographic Data ◽  
Sociodemographic Factors ◽  
The State ◽  
The Body ◽  
Seasonal Effects ◽  
Whole Body ◽  
Postmortem Computed Tomography ◽  
Whole Body Computed Tomography ◽  
Urban Study

AbstractDead bodies exhibit a variable range of changes with advancing decomposition. To quantify intracorporeal gas, the radiological alteration index (RAI) has been implemented in the assessment of postmortem whole-body computed tomography. We used this RAI as a proxy for the state of decomposition. This study aimed to (I) investigate the correlation between the state of decomposition and the season in which the body was discovered; and (II) evaluate the correlations between sociodemographic factors (age, sex) and the state of decomposition, by using the RAI as a proxy for the extent of decomposition. In a retrospective study, we analyzed demographic data from all autopsy reports from the Institute of Forensic Medicine of Zurich between January 2017 to July 2019 and evaluated the radiological alteration index from postmortem whole-body computed tomography for each case. The bodies of older males showed the highest RAI. Seasonal effects had no significant influence on the RAI in our urban study population with bodies mostly being discovered indoors. Autopsy reports contain valuable data that allow interpretation for reasons beyond forensic purposes, such as sociopolitical observations.

scholarly journals Hair Cortisol Concentrations Are Associated with Dental Anxiety during Pregnancy

2021 ◽  
Vol 9 (4) ◽  
pp. 42
Author(s):  
Hilja Viitaniemi ◽  
Auli Suominen ◽  
Linnea Karlsson ◽  
Paula Mustonen ◽  
Susanna Kortesluoma ◽  
...  
Keyword(s):  
Hair Sample ◽  
Psychological Symptoms ◽  
Smoking Status ◽  
Dental Anxiety ◽  
Binary Logistic Regression ◽  
Birth Cohort Study ◽  
Hair Cortisol ◽  
Binary Logistic Regression Model ◽  
Gestational Week ◽  
Independent Association

Dental anxiety (DA) and hair cortisol concentrations (HCC) are associated with psychological symptoms and vary during pregnancy. We aimed to examine the association between HCC and DA at two points of pregnancy. Participants were pregnant mothers (n = 533) drawn from the FinnBrain Birth Cohort Study donating a hair sample at gestational week (gwk) 24 (n = 442) and/or at delivery (n = 176) and completed questionnaires on DA. Two groups, HCC1 and HCC2, treated as separate in the analyses, were formed according to the hair sample donation time i.e., gwk24 and delivery. 85 subjects were included in both groups. MDAS, EPDS, and SCL-90 were used to measure DA, depressive and anxiety symptoms, respectively, at gwk14 for the HCC1 group and gwk34 for the HCC2 group. The association between DA and HCC was studied with a binary logistic regression model, adjusted for anxiety and depressive symptoms, age, BMI, and smoking status. Individuals with high DA had lower HCC levels at gwk24 (OR = 0.548; 95% CI = 0.35–0.86; p = 0.009), but the association was not statistically significant at the delivery (OR = 0.611; 95% CI = 0.28–1.33; p = 0.216). The independent association between HCC and DA in pregnant women suggests that long-term cortisol levels could play a role in the endogenous etiology of DA. Further studies are however, needed.

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