scholarly journals Impact of socioeconomic and demographic factors for underweight and overweight children in Bangladesh: A polytomous logistic regression model

2020 ◽  
Vol 8 (4) ◽  
pp. 1348-1355
Author(s):  
Md. Salauddin Khan ◽  
Henry Ratul Halder ◽  
Mamunor Rashid ◽  
Sohani Afroja ◽  
Masudul Islam
1997 ◽  
Vol 18 (3) ◽  
pp. S74
Author(s):  
Jong-Hyeon Jeong ◽  
Melville R. Klauber ◽  
Ronald G. Thomas ◽  
Michael Grundman ◽  
Leon J. Thal

2021 ◽  
Author(s):  
Kindu Kebede Gebre ◽  
Million Wesenu Demissie

Abstract Background: The recent outbreak of Novel Coronavirus (SARS-CoV-2) Disease (COVID-19) has put the world on alert and impacting societies around the world in an unprecedented manner. The main aims of this study was to investigate the association among the socio-demographic factors with traveling history of COVID-19 Patients in Ethiopia during stay at home state of emergency. Methods: A total of 162 respondents with COVID-19 during March 13, 2020 to May 6, 2020 in Ethiopia were used. Two sided chi-square test was used to test the association between the socio demographic factors among COVID-19 Patients. A log-complement logistic regression model was used to compute the health ratios (HR) and 95% confidence interval (CI) to measure the effect of those factors. Results: The data was analyzed using 162 patients of severe acute respiratory syndrome corona virus-2. An association was found between traveling history of COVID-19 infected patients and Gender (male vs female) [B =5.410, p<0.020] and Age group [a=13.082, p<0.004]. Log-complement logistic regression model showed that Gender and Age were significant factors associated to traveling history of COVID-19 Patients. Health ratio showed that increasing risk of traveling history for COVID-19 patients associated with higher number of males [ HR=0.5895, 95%CI: 0.4007-0.8672, P<0.0073] and Age group 18-39 years [HR=0.4139, 95%CI: 0.2385-0.7184, P<0.0017] on patients of COVID-19. Akaike information criteria with minimum value [AIC=1.2158] indicated that Log complement logistic regression model was fitted the data well for the similar dataset of patients’ with novel corona virus. Conclusions: Male Gender and Age group 18-39 years are significant socio-demographic factors associated to traveling history of patients with corona virus disease. Further socio-demographic investigations are required to better understand the extent of association with Gender and Age for effective intervention and fight this pandemic to preserve lives.


2014 ◽  
Vol 171 (2) ◽  
pp. 275-283 ◽  
Author(s):  
Cyrille B Confavreux ◽  
Pawel Szulc ◽  
Romain Casey ◽  
Annie Varennes ◽  
Joelle Goudable ◽  
...  

BackgroundBone has emerged as an endocrine organ regulating energy metabolism through secretion of osteocalcin. In epidemiological studies, presence of metabolic syndrome (MetS) was associated with lower osteocalcin level.ObjectivesWe evaluated whether osteocalcin level was associated with MetS severity in men and whether it was more strongly associated with MetS compared with N-terminal propeptide of type I procollagen (PINP), bone-specific alkaline phosphatase (BAP), and C-terminal telopeptide of type I collagen (βCTX).MethodsWe included 798 men aged 51–85 years for total osteocalcin measurement. Number of MetS criteria was used to define severity. We used polytomous logistic regression to assess the relationship between MetS severity and osteocalcin level.ResultsThirty percent of men had MetS. In patients with MetS, the higher the number of MetS traits were present, the lower was the average osteocalcin level (0–2 criteria: 551 men: 19.5±6.7 ng/ml, three criteria: 155 men: 19.3±7.4 ng/ml, four criteria: 72 men: 17.3±5.7 ng/ml, and five criteria: 20 men: 15.0±5.1 ng/ml; P for trend=0.002).In the polytomous logistic regression model, an increase in osteocalcin level of 10 ng/ml was associated with lower prevalence of severe MetS: three criteria (odds ratio (OR)=0.93 (0.70–1.24)), four criteria (OR=0.54 (0.34–0.84)), and five criteria (OR=0.28 (0.10–0.82)) in comparison with no MetS (P for trend=0.008).After adjustment, using stepwise analysis of the polytomous logistic regression model, we observed that osteocalcin, age, and apparent free testosterone entered in the model but not other bone markers (PINP, βCTX, and BAP).ConclusionIn older Caucasian men, total osteocalcin level was associated with MetS severity. Osteocalcin was more strongly associated with MetS severity than other bone turnover markers.


1989 ◽  
Vol 19 (3) ◽  
pp. 755-764 ◽  
Author(s):  
F. W. Wilmink ◽  
T. A. B. Snijders

SynopsisFirst, two examples of dichotomous logistic regression analysis are presented. The probability of being a psychiatric case according to the Present State Examination is predicted from the total score on the General Health Questionnaire and from the general practitioner's judgement on the presence of a mental health problem. Subjects were 292 primary care attenders. Results are compared with those from prior studies.Next, the extension to the polytomous case is demonstrated. The probability of being at any given level of the Index of Definition (computed from PSE data) is estimated from the General Health Questionnaire total score by an ordered polytomous logistic regression model. Several applications of the polytomous logistic regression model are discussed. These range from estimating the proportion of psychiatric cases among individuals who refuse to be interviewed to the formulation of sampling schemes which can be expected to reduce costs while at the same time yielding optimal information for testing specific hypotheses.


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