Physical activity accrued as part of public transport use in England

2018 ◽  
Vol 41 (2) ◽  
pp. 222-230 ◽  
Author(s):  
R Patterson ◽  
E Webb ◽  
C Millett ◽  
A A Laverty
Keyword(s):  
Physical Activity ◽  
Logistic Regression ◽  
Confidence Interval ◽  
Public Transport ◽  
Regression Models ◽  
Daily Life ◽  
Active Travel ◽  
Linear Regression Models ◽  
Physical Activity Guidelines ◽  
Logistic Regression Models

Abstract Background Walking and cycling for transport (active travel) is an important source of physical activity with established health benefits. However, levels of physical activity accrued during public transport journeys in England are unknown. Methods Using the English National Travel Survey 2010–14 we quantified active travel as part of public transport journeys. Linear regression models compared levels of physical activity across public transport modes, and logistic regression models compared the odds of undertaking 30 min a day of physical activity. Results Public transport users accumulated 20.5 min (95% confidence interval=19.8, 21.2) a day of physical activity as part of public transport journeys. Train users accumulated 28.1 min (26.3, 30.0) with bus users 16.0 min (15.3, 16.8). Overall, 34% (32%, 36%) of public transport users achieved 30 min a day of physical activity in the course of their journeys; 21% (19%, 24%) of bus users and 52% (47%, 56%) of train users. Conclusion Public transport use is an effective way to incorporate physical activity into daily life. One in three public transport users meet physical activity guidelines suggesting that shifts from sedentary travel modes to public transport could dramatically raise the proportion of populations achieving recommended levels of physical activity.

scholarly journals Muscle Strength Explains the Protective Effect of Physical Activity against COVID-19 Hospitalization among Adults aged 50 Years and Older

2021 ◽  
Author(s):  
Silvio Maltagliati ◽  
Stephen Sieber ◽  
Philippe Sarrazin ◽  
Stéphane Cullati ◽  
Aïna Chalabaev ◽  
...  
Keyword(s):  
Physical Activity ◽  
Risk Factors ◽  
Logistic Regression ◽  
Muscle Strength ◽  
Confidence Interval ◽  
Protective Effect ◽  
Regression Models ◽  
Protective Factor ◽  
Lower Odds ◽  
Logistic Regression Models

AbstractObjectivesPhysical activity has been proposed as a protective factor for COVID-19 hospitalization. However, the mechanisms underlying this association are unclear. Here, we examined the association between physical activity and COVID-19 hospitalization and whether this relationship was explained by other risk factors for severe COVID-19.MethodWe used data from adults aged 50 years and older from the Survey of Health, Ageing and Retirement in Europe. The outcome was self-reported hospitalization due to COVID-19 measured before August 2020. The main exposure was usual physical activity, self-reported between 2004 and 2017. Data were analyzed using logistic regression models.ResultsAmong the 3139 participants included in the study (69.3 ± 8.5 years, 1763 women), 266 were tested positive for COVID-19 and 66 were hospitalized. Results showed that individuals who engaged in physical activity more than once a week had lower odds of COVID-19 hospitalization than individuals who hardly ever or never engaged in physical activity (odds ratios = 0.41, 95% confidence interval = 0.22–0.74, p = .004). This association between physical activity and COVID-19 hospitalization was explained by muscle strength, but not by other risk factors.ConclusionThese findings suggest that, after 50 years of age, engaging in physical activity more than once a week is associated with lower odds of COVID-19 hospitalization. The protective effect of physical activity on COVID-19 hospitalization is explained by muscle strength.

scholarly journals Aplicación de modelos de regresión logística en metodología observacional: modalidades de competición en la iniciación al fútbol.

2015 ◽  
Vol 32 (1) ◽  
pp. 288 ◽  
Author(s):  
Daniel Lapresa ◽  
Javier Arana ◽  
M.Teresa Anguera ◽  
J.Ignacio Pérez-Castellanos ◽  
Mario Amatria
Keyword(s):  
Physical Activity ◽  
Logistic Regression ◽  
Regression Model ◽  
Regression Models ◽  
Logistic Regression Model ◽  
Multiple Logistic Regression ◽  
Observational Methodology ◽  
Logistic Regression Models ◽  
Game Format ◽  
Simple Logistic

This study shows how simple and multiple logistic regression can be used in observational methodology and more specifically, in the fields of physical activity and sport. We demonstrate this in a study designed to determine whether three-a-side futsal or five-a-side futsal is more suited to the needs and potential of children aged 6-to-8 years. We constructed a multiple logistic regression model to analyze use of space (depth of play) and three simple logistic regression models to determine which game format is more likely to potentiate effective technical and tactical performance.

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 Does healthcare inequity reflect variations in peoples’ abilities to access healthcare? Results from a multi-jurisdictional interventional study in two high-income countries

2020 ◽  
Vol 19 (1) ◽  
Author(s):  
Jeannie Haggerty ◽  
Jean-Frederic Levesque ◽  
Mark Harris ◽  
Catherine Scott ◽  
Simone Dahrouge ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Primary Healthcare ◽  
Social Vulnerability ◽  
Regression Models ◽  
Social Systems ◽  
Social Characteristics ◽  
Linear Regression Models ◽  
Logistic Regression Models ◽  
Wide Range ◽  
Social Vulnerabilities

Abstract Background Primary healthcare services must respond to the healthcare-seeking needs of persons with a wide range of personal and social characteristics. In this study, examined whether socially vulnerable persons exhibit lower abilities to access healthcare. First, we examined how personal and social characteristics are associated with the abilities to access healthcare described in the patient-centered accessibility framework and with the likelihood of reporting problematic access. We then examined whether higher abilities to access healthcare are protective against problematic access. Finally, we explored whether social vulnerabilities predict problematic access after accounting for abilities to access healthcare. Methods This is an exploratory analysis of pooled data collected in the Innovative Models Promoting Access-To-Care Transformation (IMPACT) study, a Canadian-Australian research program that aimed to improve access to primary healthcare for vulnerable populations. This specific analysis is based on 284 participants in four study regions who completed a baseline access survey. Hierarchical linear regression models were used to explore the effects of personal or social characteristics on the abilities to access care; logistic regression models, to determine the increased or decreased likelihood of problematic access. Results The likelihood of problematic access varies by personal and social characteristics. Those reporting at least two social vulnerabilities are more likely to experience all indicators of problematic access except hospitalizations. Perceived financial status and accumulated vulnerabilities were also associated with lower abilities to access care. Higher scores on abilities to access healthcare are protective against most indicators of problematic access except hospitalizations. Logistic regression models showed that ability to access is more predictive of problematic access than social vulnerability. Conclusions We showed that those at higher risk of social vulnerability are more likely to report problematic access and also have low scores on ability to seek, reach, pay, and engage with healthcare. Equity-oriented healthcare interventions should pay particular attention to enhancing people’s abilities to access care in addition to modifying organizational processes and structures that reinforce social systems of discrimination or exclusion.

Exposure to Organophosphate Pesticides and Menstrual Cycle Characteristics in Chinese Preconceptional Women

2019 ◽  
Vol 189 (5) ◽  
pp. 375-383 ◽  
Author(s):  
Yan Zhang ◽  
Lin Ji ◽  
Yi Hu ◽  
Lap Ah Tse ◽  
Yiwen Wang ◽  
...  
Keyword(s):  
Menstrual Cycle ◽  
Confidence Interval ◽  
Regression Models ◽  
Linear Regression Models ◽  
Cross Sectional ◽  
Logistic Regression Models ◽  
Maternity Hospitals ◽  
Diethyl Phosphate ◽  
Sectional Analysis ◽  
The Relationship

Abstract Organophosphates (OPs) are the most heavily used pesticides in China. The Chinese population, including preconceptional women, is highly exposed, yet little is known regarding the associations between OP exposure and menstruation in humans. We conducted a cross-sectional analysis in women preparing for pregnancy to investigate the relationship between biomarkers of OP exposure and menstrual cycle characteristics. From 2013 to 2015, 627 women visiting free preconception-care clinics at 2 maternity hospitals in Shanghai, China, were included. Information on menstrual cycle characteristics was obtained through questionnaires. OP exposure was assessed by measuring urine concentrations of 6 dialkylphosphate metabolites (dimethylphosphate, dimethylthiophosphate, dimethyldithiophosphate, diethylphosphate, diethylthiophosphate, and diethyldithiophosphate). The relationship between concentrations of dialkylphosphate metabolites and menstrual cycle characteristics was analyzed using multiple linear regression models and logistic regression models. Log-transformed levels of diethyl phosphate metabolites (the sum of diethylphosphate and diethylthiophosphate levels) were related to a higher risk of irregularity of menstrual cycles (adjusted odds ratio = 2.36, 95% confidence interval: 1.28, 4.34). Subjects with a higher concentration of diethyl phosphate metabolites (log-transformed) had a shorter duration of menstrual bleeding (adjusted β = −0.33, 95% confidence interval: −0.64, −0.02). The findings suggest that OP exposure may be associated with alterations in menstrual function in preconceptional women.

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.

scholarly journals Influence of year-on-year performance on final degree classification in a chiropractic master's degree program

2016 ◽  
Vol 30 (1) ◽  
pp. 14-19 ◽  
Author(s):  
Philip Dewhurst ◽  
Jacqueline Rix ◽  
David Newell
Keyword(s):  
Logistic Regression ◽  
Problem Solving ◽  
Linear Regression ◽  
Regression Models ◽  
Linear Regression Models ◽  
Logistic Regression Models ◽  
The Difference ◽  
Degree Classification ◽  
Grade Performance ◽  
Final Degree

Objective: We explored if any predictors of success could be identified from end-of-year grades in a chiropractic master's program and whether these grades could predict final-year grade performance and year-on-year performance. Methods: End-of-year average grades and module grades for a single cohort of students covering all academic results for years 1–4 of the 2013 graduating class were used for this analysis. Analysis consisted of within-year correlations of module grades with end-of-year average grades, linear regression models for continuous data, and logistic regression models for predicting final degree classifications. Results: In year 1, 140 students were enrolled; 85.7% of students completed the program 4 years later. End-of-year average grades for years 1–3 were correlated (Pearson r values ranging from .75 to .87), but the end-of-year grades for years 1–3 were poorly correlated with clinic internship performance. In linear regression, several modules were predictive of end-of-year average grades for each year. For year 1, logistic regression showed that the modules Physiology and Pharmacology and Investigative Imaging were predictive of year 1 performance (odds ratio [OR] = 1.15 and 0.9, respectively). In year 3, the modules Anatomy and Histopathology 3 and Problem Solving were predictors of the difference between a pass/merit or distinction final degree classification (OR = 1.06 and 1.12, respectively). Conclusion: Early academic performance is weakly correlated with final-year clinic internship performance. The modules of Anatomy and Histopathology year 3 and Problem Solving year 3 emerged more consistently than other modules as being associated with final-year classifications.

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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