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

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.

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Physical activity accrued as part of public transport use in England

Journal of Public Health ◽

10.1093/pubmed/fdy099 ◽

2018 ◽

Vol 41 (2) ◽

pp. 222-230 ◽

Cited By ~ 10

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.

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Factors associated with the serological prevalence of Salmonella enterica in Greek finishing swineherds

Epidemiology and Infection ◽

10.1017/s0950268803008732 ◽

2003 ◽

Vol 131 (1) ◽

pp. 599-606 ◽

Cited By ~ 24

Author(s):

L. S. LEONTIDES ◽

E. GRAFANAKIS ◽

C. GENIGEORGIS

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Salmonella Enterica ◽

Regression Models ◽

Finishing Pigs ◽

Blood Samples ◽

Lower Odds ◽

Logistic Regression Models ◽

Factors Associated ◽

Procaine Penicillin

Blood samples were taken from 50 finishing pigs at 90–105 kg in each of 59 randomly selected farrow-to-finish herds. The sera were tested for antibodies to Salmonella enterica by the Danish mix-ELISA. Samples with an optical density of >10% were considered to be positive. Associations between the odds of seropositivity of pigs and possible risk factors were evaluated in multivariable logistic regression models. The results of the analysis indicated that pigs fed non-pelleted dry or wet ration had 11 (P=0·0004) or 9 (P=0·02) times, respectively, lower odds of seropositivity than those fed pelleted ration. The risk of seropositivity was 4 (P=0·0006) times higher in pigs fed a combination of chlortetracycline, procaine penicillin and sulphamethazine during fattening than in those fed an approved growth promotor or a probiotic.

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Abstract 17220: Risk Factors for Recurrent Peripartum Cardiomyopathy in 783 Women in California

Circulation ◽

10.1161/circ.138.suppl_1.17220 ◽

2018 ◽

Vol 138 (Suppl_1) ◽

Author(s):

Punag Divanji ◽

Gregory Nah ◽

Ian Harris ◽

Anu Agarwal ◽

Nisha I Parikh

Keyword(s):

Risk Factors ◽

Cardiovascular Disease ◽

Logistic Regression ◽

Regression Models ◽

Subsequent Pregnancy ◽

Peripartum Cardiomyopathy ◽

Lv Function ◽

Logistic Regression Models ◽

Grand Multiparity ◽

Adjusted Logistic Regression

Introduction: Characterized by significant left ventricular (LV) dysfunction and clinical heart failure (HF), peripartum cardiomyopathy (PPCM) has an incidence of approximately 1/2200 live births (0.04%). Prior studies estimate that approximately 25% of those with recovered LV function will have recurrent clinical PPCM during subsequent pregnancies, compared to 50% of those without recovered LV function. Specific predictors of recurrent PPCM have not been studied in cohorts with large numbers. Methods: From 2005-2011, we identified 1,872,227 pregnancies by International Classification of Diseases, 9th Revision (ICD-9) codes in the California Healthcare Cost and Utilization Project (HCUP) database, which captures over 95% of the California hospitalized population. Excluding 15,765 women with prior cardiovascular disease (myocardial infarction, coronary artery disease, stroke, HF, valve disease, or congenital heart disease), yielded n=1,856,462 women. Among women without prior cardiovascular disease, we identified index and subsequent pregnancies with PPCM to determine episodes of recurrent PPCM. We considered the following potential predictors of PPCM recurrence in both univariate and age-adjusted logistic regression models: age, race, hypertension, diabetes, smoking, obesity, chronic kidney disease, family history, pre-eclampsia, ectopic pregnancy, income, and insurance status. Results: In HCUP, n=783 women had pregnancies complicated by PPCM (mean age=30.8 years). Among these women, n=133 had a subsequent pregnancy (17%; mean age=28.1 years), with a mean follow-up of 4.34 years (±1.71 years). In this group of 133 subsequent pregnancies, n=14 (10.5%) were complicated by recurrent PPCM, with a mean time-to-event of 2.2 years (±1.89 years). Among the risk factors studied, the only univariate predictor of recurrent PPCM was grand multiparity, defined as ≥ 5 previous deliveries (odds ratio: 22; 95% confidence interval 4.43-118.22). The other predictors we studied were not significantly associated with recurrent PPCM in either univariate or multivariable models. Conclusion: In a large population database in California with 783 cases of PPCM over a 6-year period, 17% of women had a subsequent pregnancy, of which 10.5% had recurrent PPCM. In age-adjusted logistic regression models, grand multiparity was the only statistically significant predictor of recurrent PPCM.

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A model-based concordance-type index for evaluating the added predictive ability of novel risk factors and markers in the logistic regression models

Journal of Applied Statistics ◽

10.1080/02664763.2019.1580253 ◽

2019 ◽

Vol 46 (12) ◽

pp. 2145-2163 ◽

Cited By ~ 1

Author(s):

M. Shafiqur Rahman ◽

Afrin Sadia Rumana

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Regression Models ◽

Predictive Ability ◽

Logistic Regression Models ◽

Model Based ◽

Novel Risk Factors

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

Anales de Psicología ◽

10.6018/analesps.32.1.186951 ◽

2015 ◽

Vol 32 (1) ◽

pp. 288 ◽

Cited By ~ 2

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.

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

Comparative Exercise Physiology ◽

10.3920/cep10017 ◽

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.

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The Association between Hyperhomocysteinemia and Thoracoabdominal Aortic Aneurysms in Chinese Population

BioMed Research International ◽

10.1155/2020/4691026 ◽

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.

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Forced Sexual Victimization Among Youth in Custody: Do Risk Factors Vary by Gender and Perpetrator?

The Prison Journal ◽

10.1177/0032885519894561 ◽

2019 ◽

Vol 100 (2) ◽

pp. 151-172

Author(s):

Eileen M. Ahlin

Keyword(s):

Risk Factors ◽

Gender Differences ◽

Logistic Regression ◽

National Survey ◽

Regression Models ◽

Sexual Victimization ◽

Multivariate Logistic Regression ◽

Logistic Regression Models ◽

Factors Associated ◽

Using Data

There is relatively little literature examining risk factors associated with sexual victimization among youth in custody. The current study explored whether risk of forced sexual victimization among youth in custody differs by gender or perpetrator. Using data from a sample of 8,659 youth who participated in the National Survey of Youth in Custody, multivariate logistic regression models were employed to investigate gender differences in risk factors associated with overall forced sexual victimization and staff-on-inmate and inmate-on-inmate forced sexual victimization. Findings suggest that gender differences are more pronounced when perpetrator type is considered.

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