Body Satisfaction, Performance Perception, and Weight Loss Behavior in Young Female Dancers

2018 ◽  
Vol 33 (4) ◽  
pp. 225-230 ◽  
Author(s):  
Marina G Gearhart ◽  
Dai Sugimoto ◽  
William P Meehan ◽  
Andrea Stracciolini
Keyword(s):  
Weight Loss ◽  
Logistic Regression ◽  
Body Satisfaction ◽  
Binary Logistic Regression ◽  
Young Female ◽  
Intentional Weight Loss ◽  
Weight Loss Behavior ◽  
Athletic Activities ◽  
Chi Square Analysis ◽  
The Impact

OBJECTIVE: To understand the impact of body satisfaction and performance perception on intentional weight loss behavior and body mass index (BMI) in young female dancers. METHODS: Young female dancers who visited an injury prevention center were provided a questionnaire including three questions designed to elicit their body satisfaction, perception of weight toward performance, and any intentional weight loss behavior. Binary responses (yes/no) were compared between the three questions using chi-square analysis. Also, a binary logistic regression was performed to find an indicator for intentional weight loss behaviors. Finally, BMI was compared among subgroups. RESULTS: Data from 43 young female dancers, aged 12-23 yrs, were analyzed. Dancers who were not happy with their weight were more likely to engage with intentional weight loss activity than dancers who were happy with their weight (p=0.002). Those who did not believe that their athletic activities were influenced by their weight were less likely engage with intentional weight loss and more likely to be happy with their weight than dancers who believed that athletic activities were influenced by their weight (p=0.049 and 0.015, respectively). Binary logistic regression indicated female dancers who were not happy with their body weight had nearly 9 times greater odds of intentional weight loss activity (p=0.029). There were no BMI differences among the three subgroups. CONCLUSION: Intentional weight loss behavior is heavily influenced by body satisfaction in young female dancers regardless of their current BMI.

scholarly journals EPID-34. THE DETRIMENTAL EFFECT OF BIOPSY PRECEDING RESECTION IN SURGICALLY ACCESSIBLE GLIOBLASTOMAS: RESULTS FROM THE NATIONAL CANCER DATABASE

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii85-ii86
Author(s):  
Ping Zhu ◽  
Xianglin Du ◽  
Angel Blanco ◽  
Leomar Y Ballester ◽  
Nitin Tandon ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Failure Time ◽  
Binary Logistic Regression ◽  
Rank Test ◽  
Imaging Features ◽  
National Cancer Database ◽  
Prolonged Length ◽  
Logistic Regression Models ◽  
Operative Outcomes ◽  
The Impact

Abstract OBJECTIVES To investigate the impact of biopsy preceding resection compared to upfront resection in glioblastoma overall survival (OS) and post-operative outcomes using the National Cancer Database (NCDB). METHODS A total of 17,334 GBM patients diagnosed between 2010 and 2014 were derived from the NCDB. Patients were categorized into two groups: “upfront resection” versus “biopsy followed by resection”. Primary outcome was OS. Post-operative outcomes including 30-day readmission/mortality, 90-day mortality, and prolonged length of inpatient hospital stay (LOS) were secondary endpoints. Kaplan-Meier methods and accelerated failure time (AFT) models with gamma distribution were applied for survival analysis. Multivariable binary logistic regression models were performed to compare differences in the post-operative outcomes between these groups. RESULTS Patients undergoing “upfront resection” experienced superior survival compared to those undergoing “biopsy followed by resection” (median OS: 12.4 versus 11.1 months, log-rank test: P=0.001). In multivariable AFT models, significant survival benefits were observed among patients undergoing “upfront resection” (time ratio [TR]: 0.83, 95% CI: 0.75–0.93, P=0.001). Patients undergoing upfront GTR had the longest survival compared to upfront STR, GTR following STR, or GTR and STR following an initial biopsy (14.4 vs. 10.3, 13.5, 13.3, and 9.1, months), respectively (TR: 1.00 [Ref.], 0.75, 0.82, 0.88, and 0.67). Recent years of diagnosis, higher income and treatment at academic facilities were significantly associated with the likelihood of undergoing upfront resection after adjusting the covariates. Multivariable logistic regression revealed that 30-day mortality and 90-day mortality were decreased by 73% and 44% for patients undergoing “upfront resection” over “biopsy followed by resection”, respectively (both p < 0.001). CONCLUSIONS Pre-operative biopsies for surgically accessible tumors with characteristic imaging features of Glioblastoma lead to worse survival despite subsequent resection compared to patients undergoing upfront resection.

scholarly journals AB1329-HPR THE CURRENT STATUS AND ASSOCIATED FACTORS OF FATIGUE IN CHINESE PATIENTS WITH GOUT

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1953.3-1953
Author(s):  
J. Guo ◽  
W. Zhou ◽  
M. He ◽  
Z. Gu ◽  
C. Dong
Keyword(s):  
Multiple Sclerosis ◽  
Logistic Regression ◽  
Linear Regression ◽  
Sleep Quality ◽  
Binary Logistic Regression ◽  
Psychological Status ◽  
Functional Disorder ◽  
Stepwise Linear Regression ◽  
Chi Square Analysis ◽  
Anxiety Depression

Background:Fatigue of chronic diseases has been paid more and more attention. but the status of fatigue in gout patients has not been reported all the world[1].Objectives:In the absence of previous studies, our study aims to investigate the fatigue status, explore the potential predictors of fatigue and the effects of fatigue on health-related quality of life (HRQoL) among Chinese gout patients.Methods:This cross-sectional study was conducted from the Affiliated Hospital of Nantong University. A series of questionnaires were applied: Fatigue Scale-14 (FS-14), the 10 cm visual analog scale (VAS), the Patient Health Questionnaire (PHQ-9), the Generalized Anxiety Disorder questionnaire (GAD-7), the Pittsburgh Sleep Quality Index (PSQI), Health Assessment Questionnaire(HAQ), the Short Form 36 health survey (SF-36). Laboratory examinations were taken to obtain some biochemical indicators. Independent samples t-test, Mann–Whitney U-test, Chi-square analysis, Pearson /Spearman correlation, Stepwise linear regression and binary logistic regression were used to analyze the data.Results:411 gout patients were included in this study. Among them, more than 50% patients reported physical fatigue in FS-14, severe disease, poor psychological status and reduced HRQoL were associated with fatigue. Multiple stepwise linear regression and binary logistic regression were applied and showed that pain, sleep quality, anxiety, depression and functional disorder were the potential predictors of fatigue. In addition, we found that the more severe the fatigue, the lower the patient’s HRQoL.Conclusion:Fatigue among gout patients is exceedingly common. The results of this study suggested that rheumatologists should pay closely attention to gout patients who suffer from serious fatigue, especially those with pain, poorer sleep quality, anxiety, depression and functional disorder.References:[1]Henry, A., Tourbah, A., Camus, G., Deschamps, R., Mailhan, L., Castex, C., Gout, O. & Montreuil, M. (2019) Anxiety and depression in patients with multiple sclerosis: The mediating effects of perceived social support, Multiple sclerosis and related disorders. 27, 46-51.Disclosure of Interests:None declared

scholarly journals SAT0625-HPR FATIGUE AND CONTRIBUTING FACTORS IN CHINESE PATIENTS WITH ANKYLOSING SPONDYLITIS

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1272.2-1272
Author(s):  
W. Zhou ◽  
J. Guo ◽  
R. Zhao ◽  
C. Dong ◽  
Z. Gu
Keyword(s):  
Quality Of Life ◽  
Logistic Regression ◽  
Ankylosing Spondylitis ◽  
Sleep Quality ◽  
Binary Logistic Regression ◽  
The Self ◽  
Chinese Patients ◽  
Self Rating ◽  
Chi Square Analysis

Background:Ankylosing spondylitis (AS) is a systemic chronic inflammatory disease, which most likely occurs in young men. It mainly affects sacroiliac joints, axial skeleton, thoracic cage and seriously decreasing quality of life in AS patients[1,2]. In recent years, fatigue of AS patients has been paid more and more attention[3]. Fatigue is a complex feeling, diseased individuals describe fatigue as a sense of tiredness at rest, exhaustion with activity, lack of energy which affects daily work, inertia or lack of endurance, or as loss of vitality. It has been confirmed that fatigue is not only a symptom but may also be quantified by fatigue scores and can be modified by various measures depending on the underlying cause[4]. However, there has been no study about fatigue in AS patients in China.Objectives:This study aimed to evaluate the predictors of fatigue and the effects of fatigue on HR-QoL among patients with AS.Methods:A total of 150 AS patients were involved in the study. A series of questionnaires included: Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Bath Ankylosing Spondylitis Metrology Index (BASMI), Bath Ankylosing Spondylitis Functional Index (BASFI), the 10 cm Visual Analog Scale (VAS), the Self-Rating Anxiety Scale (SAS), the Self-Rating Depression Scale (SDS), the Pittsburgh Sleep Quality Index (PSQI), the Health Assessment Questionnaire-Disability Index (HAQ-DI), the Short Form 36 Health Survey (SF-36) and the Fatigue Severity Scale(FSS). Independent samples t-test, Mann–Whitney U-test, Chi-square analysis, Pearson /Spearman correlation and binary logistic regression were used to analyze the data.Results:The results demonstrated that 48.7% individuals with AS suffered from fatigue. Compared with AS patients without fatigue, AS patients with fatigue showed higher WHR(P<0.05), increased BASDAI (P<0.01) and poorer BASFI (P<0.05). Meanwhile, AS patients with fatigue tended to have more severe pain(P<0.05), higher degree of anxiety(P=0.001), more serious functional disability(P=0.001) and worse sleep quality(P=0.001). Binary logistic regression indicated that WHR (OR=1.78,P<0.05), BASDAI (OR=1.34,P=0.01), sleep disturbance (OR=2.35,P<0.05) were independent predictors of fatigue in AS patients. Additionally, the occurrence of fatigue significantly reduced the quality of life in AS patients both physically and psychologically.Conclusion:These findings suggested that medical personnel should pay more attention to AS patients with fatigue and take effective measures to relieve fatigue.References:[1]Law L, Beckman Rehnman J, Deminger A, Klingberg E, Jacobsson LTH, Forsblad-d’Elia H (2018) Factors related to health-related quality of life in ankylosing spondylitis, overall and stratified by sex. Arthritis research & therapy 20 (1):284. doi:10.1186/s13075-018-1784-8[2]Hanson A, Brown MA (2017) Genetics and the Causes of Ankylosing Spondylitis. Rheumatic diseases clinics of North America 43 (3):401-414. doi:10.1016/j.rdc.2017.04.006[3]Ulus Y, Akyol Y, Bilgici A, Kuru O (2019) Association of work instability with fatigue and emotional status in patients with ankylosing spondylitis: comparison with healthy controls. Clinical rheumatology 38 (4):1017-1024. doi:10.1007/s10067-018-4366-x[4]Finsterer J, Mahjoub SZ (2014) Fatigue in healthy and diseased individuals. The American journal of hospice & palliative care 31 (5):562-575. doi:10.1177/1049909113494748Acknowledgments:Thanks to all the authors for their efforts and thanks to all members of the Department of Rheumatology of Affiliated Hospital of Nantong University for their helpfulness in the acquisition of data.Disclosure of Interests:None declared

scholarly journals Prevalence, Correlations, and Impact of Sleep Disturbance in Chinese Meningioma Patients

2021 ◽  
Author(s):  
Dandan Zhang ◽  
Jing Wang ◽  
Xixi Gu ◽  
Zhifeng Gu ◽  
Liren Li ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Logistic Regression ◽  
Sleep Quality ◽  
Sleep Disturbance ◽  
Short Form ◽  
Binary Logistic Regression ◽  
Anxiety And Depression ◽  
Newly Diagnosed ◽  
Chi Square Analysis

Abstract Purpose Sleep disturbance is common in meningioma patients and may lead to disease aggravation and decreases health-related quality of life (HRQoL). However, the sleep quality of meningioma patients newly diagnosed and ready for surgery has not been well clarified in China. This study aims to evaluate the prevalence, correlates, and impact of sleep disturbance among Chinese meningioma patients. Methods In this cross-sectional study, meningioma patients were recruited from the Affiliated Hospital of Nantong University from January 2020 to November 2020. A series of questionnaires were applied: the 0–10 Numerical Rating Scale (NRS), the Hospital Anxiety and Depression Scale (HADS), the Multidimensional Fatigue Inventory (MFI-20), the Epworth Sleepiness Scale (ESS), the Short-Form 36 (SF-36), the Pittsburgh Sleep Quality Index (PSQI). Independent samples t test, Mann-Whitney U test, chi-square analysis, Pearson/Spearman correlation, and binary logistic regression were used to analyze the data. Results 100 meningioma patients completed the questionnaires. Sleep disturbance affected 43% of the meningioma patients and was linked to many concomitant symptoms, such as headache, fatigue, anxiety and depression. Binary logistic regression indicated that fatigue and headache were predictors of sleep disturbance in meningioma patients. Meanwhile, severe sleep disturbance led to lower quality of life. Conclusions These findings demonstrated that a considerable number of meningioma patients newly diagnosed and ready for surgery suffered from sleep disturbance, potentially contributing to impair HRQoL. Medical personnel should pay more attention to meningioma patients with sleep disturbance and take effective measures to improve sleep quality, with the ultimate goal to improve their HRQoL.

scholarly journals Does Physical Fitness Predict Future Karate Success? A Study in Young Female Karatekas

2020 ◽  
Vol 15 (6) ◽  
pp. 868-873
Author(s):  
Óscar Martínez de Quel ◽  
Ignacio Ara ◽  
Mikel Izquierdo ◽  
Carlos Ayán
Keyword(s):  
Logistic Regression ◽  
Physical Fitness ◽  
Muscle Power ◽  
Binary Logistic Regression ◽  
Young Female ◽  
Binary Logistic Regression Analysis ◽  
Discriminative Ability ◽  
Logistic Regression Models ◽  
Elite Group ◽  
Competitive Success

Objective: To assess the discriminative ability of several fitness dimensions and anthropometric attributes for forecasting competitive success in female karate athletes. Methods: Fitness and anthropometric data from 98 female junior karatekas obtained during the training camps of the Spanish National Karate Federation between 1999 and 2012 were used. Binary logistic-regression models were built to ascertain whether the set of fitness and anthropometric variables could predict future sporting-performance levels. For this purpose, participants were classified as elite (medalist in World or European Championships in the senior category) or subelite (at least a medalist in Spanish National Championships in cadet or junior but not included in the elite group), according to the results achieved up to 2019. Results: Participants who were subsequently classified as elite karatekas showed significant differences in agility, upper- and lower-body muscle power, and general fitness in comparison with those who were classified as subelite in the senior category. A total of 57 junior female karatekas who were subsequently classified as elite (7) or subelite (50) were included in the binary logistic-regression analysis. Resultant models showed significant capacity to predict karate performance. Conclusions: Assessing physical fitness in junior categories can be a useful resource to determine future karate success. Coaches in this sport should pay special attention to the levels of muscle power and agility shown by their athletes, as both fitness dimensions could be indicators of future sportive success.

scholarly journals Application of Logistic Regression Models for the Marketability of Cucumber Cultivars

Agronomy ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 17 ◽  
Author(s):  
Manuel Díaz-Pérez ◽  
Ángel Carreño-Ortega ◽  
José-Antonio Salinas-Andújar ◽  
Ángel-Jesús Callejón-Ferre
Keyword(s):  
Weight Loss ◽  
Logistic Regression ◽  
Shelf Life ◽  
Regression Models ◽  
Chilling Injury ◽  
Binary Logistic Regression ◽  
Fruit Weight ◽  
Binary Logistic Regression Analysis ◽  
Cucumis Sativus L ◽  
Logistic Regression Models

The aim of this study is to establish a binary logistic regression method to evaluate and select cucumber cultivars (Cucumis sativus L.) with a longer postharvest shelf life. Each sample was evaluated for commercial quality (fruit aging, weight loss, wilting, yellowing, chilling injury, and rotting) every 7 days of storage. Simple and multiple binary logistic regression models were applied in which the dependent variable was the probability of marketability and the independent variables were the days of storage, cultivars, fruit weight loss, and months of evaluation. The results showed that cucumber cultivars with a longer shelf life can be selected by a simple and multiple binary logistic regression analysis. Storage time was the main determinant of fruit marketability. Fruit weight loss strongly influenced the probability of marketability. The logistic model allowed us to determine the cucumber weight loss percentage over which a fruit would be rejected in the market.

scholarly journals The impact of demographic, clinical, genetic, and imaging variables on tau PET status

2020 ◽  
Author(s):  
Rik Ossenkoppele ◽  
◽  
Antoine Leuzy ◽  
Hanna Cho ◽  
Carole H. Sudre ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Cortical Thickness ◽  
Regression Models ◽  
Neurodegenerative Disorder ◽  
Amyloid Β ◽  
Binary Logistic Regression ◽  
Clinical Genetic ◽  
Logistic Regression Models ◽  
Tau Pet ◽  
The Impact

Abstract Purpose A substantial proportion of amyloid-β (Aβ)+ patients with clinically diagnosed Alzheimer’s disease (AD) dementia and mild cognitive impairment (MCI) are tau PET–negative, while some clinically diagnosed non-AD neurodegenerative disorder (non-AD) patients or cognitively unimpaired (CU) subjects are tau PET–positive. We investigated which demographic, clinical, genetic, and imaging variables contributed to tau PET status. Methods We included 2338 participants (430 Aβ+ AD dementia, 381 Aβ+ MCI, 370 non-AD, and 1157 CU) who underwent [18F]flortaucipir (n = 1944) or [18F]RO948 (n = 719) PET. Tau PET positivity was determined in the entorhinal cortex, temporal meta-ROI, and Braak V-VI regions using previously established cutoffs. We performed bivariate binary logistic regression models with tau PET status (positive/negative) as dependent variable and age, sex, APOEε4, Aβ status (only in CU and non-AD analyses), MMSE, global white matter hyperintensities (WMH), and AD-signature cortical thickness as predictors. Additionally, we performed multivariable binary logistic regression models to account for all other predictors in the same model. Results Tau PET positivity in the temporal meta-ROI was 88.6% for AD dementia, 46.5% for MCI, 9.5% for non-AD, and 6.1% for CU. Among Aβ+ participants with AD dementia and MCI, lower age, MMSE score, and AD-signature cortical thickness showed the strongest associations with tau PET positivity. In non-AD and CU participants, presence of Aβ was the strongest predictor of a positive tau PET scan. Conclusion We identified several demographic, clinical, and neurobiological factors that are important to explain the variance in tau PET retention observed across the AD pathological continuum, non-AD neurodegenerative disorders, and cognitively unimpaired persons.

Resource-based view of innovation activity in SMEs: an empirical analysis based on the global competitiveness project

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lívia Lukovszki ◽  
András Rideg ◽  
Norbert Sipos
Keyword(s):  
Logistic Regression ◽  
Literature Review ◽  
Empirical Analysis ◽  
Binary Logistic Regression ◽  
Point Of View ◽  
Innovation Activity ◽  
Data Set ◽  
Content Type ◽  
Resources And Capabilities ◽  
The Impact

Purpose The purpose of this study is to identify the corporate functions that contribute most to the innovation success of SMEs with limited resources. After a systematic literature review, the authors used a unique primary data set of 784 SMEs from eight countries. Descriptive statistics and binary logistic regression were used to show the data set peculiarities. The logistic regression targeted the presence of innovative products and services in sales by 11 dummy variables and 4 principal factors describing SMEs’ different resources and capabilities. Design/methodology/approach The authors developed a resource-based product innovation model that is synthesising the impact of the company resources and capabilities and of the innovation activity of the company on the actual innovation performance. The authors carry out an empirical analysis of the characteristic features of innovation activity in an international sample of SMEs. Findings The results show that two corporate functions play a crucial role in the effectiveness of innovation for SMEs as follows: management and research and development (R&D). In addition, although of lesser importance, the effect of the marketing function also appears significant. The binary logistic regression had 84.2% of explanatory power. Originality/value From a scientific point of view, the SME-focussed, complex and synthesising RBV model of innovation construction and literature review can be used as a reference point for future researches. From a practical point of view, the analysis is useful for those SMEs, which want to gain a competitive advantage through innovation. Indeed, the results show that in the case of SMEs, a company wishing to innovate must invest in three corporate functions for innovation to be effective as follows: management, R&D and marketing.

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