• Title/Summary/Keyword: odds ratio

Search Result 2,179, Processing Time 0.026 seconds

A Case-Control Study for Risk Factor Related to Hypertension (고혈압의 위험요인에 대한 환자-대조군 연구)

  • Kam, Sin;Yeh, Min-Hae;Lee, Sung-Kook;Chun, Byung-Yeol
    • Journal of Preventive Medicine and Public Health
    • /
    • v.24 no.2 s.34
    • /
    • pp.221-231
    • /
    • 1991
  • A case-control study was conducted to investigate the risk factors (Part of job, Obesity, Alcohol, Smoking, Milk, Salt. and Family history) for hypertension. We selected 330 hypertension cases (male;247, female;83) and 1,336 controls (male;887, female;449) from employees in Taegu city from 1 May to 30 November, 1908. Data was analysed using a logistic regression model. Statistically significant elevated odds ratio were noted for alcohol (odds ratio=3.23), obesity (odds ratio=2.31), salt(odds ratio=1.75) in male (p<0.05) and those in female were noted for alcohol (odds ratio=16.49), family history(odds ratio=3.70), obesity (odds ratio=1.74) and salt (odds ratio=1.73) (p<0.05). Statistically significant reduced odds ratio was noted for milk in both sexes (odds ratio=0.69 for male and 0.65 for female)(p<0.05) and the dose-response relationship between milk intake and hypertension was confirmed (p<0.05). Therefore, milk seems to be preventive factor for hypertension. Smoking was not significantly associated with hypertension in both sexes. The part of job was significantly associated with hypertension in female by simple analysis (P<0.05) but the relationship was disappeared when multivariate analysis (logistic regression analysis) was done.

  • PDF

Predicting Factors on Youth Runaway Impulse (청소년의 가출충동에 영향을 미치는 예측요인)

  • Chung Hae-Kyung;Ann Ok-Hee
    • Child Health Nursing Research
    • /
    • v.7 no.4
    • /
    • pp.483-493
    • /
    • 2001
  • This study is attempted to define risk factor of youth runaway impulse and to structure forecast model through an extensive analysis of the factors influencing the runaway impulse of youth. The subjects were 610 high school students in Seoul and Kyunggido. The collected data was analysed by SAS. The differences between the runaway impulse group and the non-runaway impulse group were subject to chi-square and t-test. Also logistic regression analysis was conducted on the basis of purposeful selection method for constructing the forecast model. The findings are as follows : the major predicting factors of youth runaway impulse are sex(odds ratio=1.886, p=.009), existence of friends of the opposit sex(odds ratio=2.011, p=.007), anti-social personality(odds ratio= 4.953, p=.000), depressive trend(odds ratio= 2.695, p=.000), family structure(odds ratio= 5.381, p=.000), marital relationship(odds ratio =1.893, p=.009) and also between parents and youth(odds ratio=3.877, p=.000), emotional abuse(odds ratio=1.963, p=.003), authoritative controlled rearing(odds ratio=2.135, p=.005) and stress from school(odds ratio=1.924, p=.008). Therefore, the forecast model will be contribute to the nursing intervention for prevention of runaway youth.

  • PDF

The Lifestyle Factors in Stroke Etiology: Smoking, Alcohol Consumption, Obesity, Perception of Saltness (뇌졸중에 영향을 미치는 생활습관 요인 -흡연, 음주, 비만, 식습관을 중심으로-)

  • Won, Jong-Im;Ohrr, Hee-Choul
    • Physical Therapy Korea
    • /
    • v.6 no.3
    • /
    • pp.82-93
    • /
    • 1999
  • Stroke is a serious disease despite recent improvement in medical and surgical treatment. Hence, identification of modifiable risk factors for stroke is important. This case-control study was done to demonstrate that relationship between smoking, alcohol consumption, obesity, perception of saltness and the incidence of stroke and to identify that smoking, alcohol consumption, obesity and perception of saltness, after adjusting for age, hypertension. A structured interview was carried out from April 15, 1996 to May 3, 1996 in Yonsei Medical Center. The study group consisted of 59 neurologically confirmed stroke patients as the study group and 59 non-stroke patients as controls. Analysis of the data was done by means of ${\chi}^2$-test and logistic regression analysis. The results were as follows. In the study group: 1) Hypertension in males had a 10.2 odds ratio (p<0.05), cardiovascular disease in females had a 11.3 odds ratio (p<0.05) and a farnily history of stroke in males had a 3.1 odds ratio (p<0.05). 2) Females smoking one or more cigarettes had a 8.3 odds ratio (p<0.1), but males had no direct relationship with odds ratio of 1.5 (non-significant). 3) Alcohol consumption in males had a 0.4 odds ratio, and in females had a 0.8 odds ratio. The odds ratio was decreased in alcohol consumption group (non-significant). 4) Males with more than 20 cigarettes pack-years history had a 2.5 odds ratio (p<0.05), more than 25 Body Mass Index had a 3.1 odds ratio (p<0.05) and more than 220 ml ethanol weekly consumption had a 1.5 odds ratio (non-significant). 5) Female smokers had a 8.3 odds ratio (p<0.1), drinkers a 0.8 odds ratio and more than 25 Body Mass Iidex, a 43.1 odds ratio (p<0.05). 6) Females without saltness perception from a 0.5% salt solution had a 6.8 odds ratio (non-significant). 7) By logistic regression analysis independent risk factors for stroke in males were found to be hypertention, age, and obesity. The study was limited because number of subjects was too small for practical implications. However, like as other results, this study suggest that people should be advised to control hypertension, and obesity since these carry a risk of stroke.

  • PDF

Empirical Bayes Posterior Odds Ratio for Heteroscedastic Classification

  • Kim, Hea-Jung
    • Journal of the Korean Statistical Society
    • /
    • v.16 no.2
    • /
    • pp.92-101
    • /
    • 1987
  • Our interest is to access in some way teh relative odds or probability that a multivariate observation Z belongs to one of k multivariate normal populations with unequal covariance matrices. We derived the empirical Bayes posterior odds ratio for the classification rule when population parameters are unknown. It is a generalization of the posterior odds ratio suggested by Gelsser (1964). The classification rule does not have complicated distribution theory which a large variety of techniques from the sampling viewpoint have. The proposed posterior odds ratio is compared to the Gelsser's posterior odds ratio through a Monte Carlo study. The results show that the empiricla Bayes posterior odds ratio, in general, performs better than the Gelsser's. Especially, for large dimension of Z and small training sample, the performance is prominent.

  • PDF

Inference for Order Restrictions on Odds in 2 * k Contingency Tables

  • Oh, Myong-Sik
    • Journal of the Korean Statistical Society
    • /
    • v.25 no.3
    • /
    • pp.381-391
    • /
    • 1996
  • In the analysis of contingency table with ordered categories, the relationship between odds for adjacent categories has received con-siderable interest. We consider likelihood ratio tests of independence against an order restriction on odds in 2 $\times$ k contingency tables.

  • PDF

Effective Computation for Odds Ratio Estimation in Nonparametric Logistic Regression

  • Kim, Young-Ju
    • Communications for Statistical Applications and Methods
    • /
    • v.16 no.4
    • /
    • pp.713-722
    • /
    • 2009
  • The estimation of odds ratio and corresponding confidence intervals for case-control data have been done by traditional generalized linear models which assumed that the logarithm of odds ratio is linearly related to risk factors. We adapt a lower-dimensional approximation of Gu and Kim (2002) to provide a faster computation in nonparametric method for the estimation of odds ratio by allowing flexibility of the estimating function and its Bayesian confidence interval under the Bayes model for the lower-dimensional approximations. Simulation studies showed that taking larger samples with the lower-dimensional approximations help to improve the smoothing spline estimates of odds ratio in this settings. The proposed method can be used to analyze case-control data in medical studies.

Estimation of continuous odds ratio function with censored data (중도절단된 자료를 포함한 승산비 연속함수의 추정)

  • Kim, Jung-Suk;Kwon, Chang-Hee
    • 한국디지털정책학회:학술대회논문집
    • /
    • 2006.12a
    • /
    • pp.327-336
    • /
    • 2006
  • The odds ratio is used for assessing the disease-exposure association, because epidemiological data for case-control of cohort studies are often summarized into 2 ${\times}$ 2 tables. In this paper we define the odds ratio function(ORF) that extends odds ratio used on discrete survival event data to continuous survival time data and propose estimation procedures with censored data. The first one is a nonparametric estimator based on the Nelson-Aalen estimator of comulative hazard function, and the others are obtained using the concept of empirical odds ratio. Asymptotic properties such as consistency and weak convergence results are also provided. The ORF provides a simple interpretation and is comparable to survival function or comulative hazard function in comparing two groups. The mean square errors are investigated via Monte Carlo simulation. The result are finally illustrated using the Melanoma data.

  • PDF

Association between systemic disease activity restriction and oral health

  • Jung, Yu Yeon
    • Journal of the Korea Society of Computer and Information
    • /
    • v.26 no.12
    • /
    • pp.187-193
    • /
    • 2021
  • The purpose of this study was to analyze the responses of 5,824 adults(2,574 males and 3,250 females over the age of 19 years) using raw data from the 7th period of the National Health and Nutrition Examination Survey to investigate the relationship between systemic disease activity restriction and oral health. There were many systemic disease activity restrictions in adults with oral chewing and speaking problems, and it was statistically significant(p<.001). Factors influencing activity restriction due to systemic disease include age(odds ratio 1.03), Male(odds ratio 0.84), education level(odds ratio 0.57, 0.45, 0.31), drinking(odds ratio 1.38), chewing(odds ratio 1.86) and speaking(odds ratio 1.84) problems. There was a higher probability of activity restriction due to systemic disease when they received treatment for periodontal disease(odds ratio 1.27) and broken teeth(odds ratio 2.1). Also, it was statistically significant that the quality of life decreased when there was chewing and speaking problems.

Notes on Upper and Lower Bounds of Odds Ratio

  • Woo, Jung-Soo
    • Journal of the Korean Data and Information Science Society
    • /
    • v.11 no.1
    • /
    • pp.31-35
    • /
    • 2000
  • We shall give upper and lower bounds of the odds ratio of an event by a slight condition of the conditional probability of events.

  • PDF

Comparision of Family Environment, Health Behavior and Health State of Elementary Students in Urban and Rural Areas (도시.농촌 지역 초등학생의 가족환경, 건강행위 및 건강상태에 관한 비교)

  • Bae, Yeon-Suk;Park, Kyung-Min
    • Research in Community and Public Health Nursing
    • /
    • v.9 no.2
    • /
    • pp.502-517
    • /
    • 1998
  • This research intends to survey family environment, health behavior and health status of the students in urban-rural elementary schools and analyze those factors comparatively, and use the result as basic material for school health teacher to teach health education in connection with family and regional areas. It also intends to improve a pupil's self-abilitiy in health care. The subjects involve 2,774 students of urban elementary schools and 583 student in rural ones, who were selected by means of a multi -stage probability sampling. Using the questionnaire and school documents, we collected data on family environment, health behavior and health status for 19 days. Feb. 2nd 1998 through Feb. 20th 1998. The R -form of Family Environment Scale (Moos, 1974) was used in the analysis of family environment(Cronbach's Alpha =0.80). Questionnaires of Health Behavior in School-aged children used by the WHO in Europe(Aaro et al., 1986) and the ones developed by the Health Promotion Committee of the Western Pacific(WHO, 1995)(adapted by long Young-suk and Moon Young-hee(1996)) were used in the analysis of health behavior, as well documents on absences due to sickness, school health room-visits, levels of physical strength, height, weight and degree of obesity were used to determine health status. In next step, We used them with an $X^2$-test, t-test, Odds Ratio, and a 95% Confidence Interval. 1. In two dimensions of three, family-relationship (t=3.41, p=0.001) and system -maintenances(t= 2.41, p=0.0l6) the mean score of urban children were significantly higher than those of rural ones. In the personal development dimension however, there was little significant difference. Assorting family environment into 10 sub-fields and analyzing them, we recognized that urban children were superior to rural children in the sub-fields of expressiveness (t =3.47, p=0.001), conflict (t=0.48, p=0.001), active-recreational orientation (t = 1.97, p=0.049) and organization (t=4.33, p=0.000). 2. Referring to the Odds Ratios of urban-rural children's health behaviors, urban children set up more desirable behavior than rural children wear ing safety belts (Odds Ratio =0.32, p=0.000), washing hands after meals(Odds Ratio = 0.43, p= 0.000), washing hands after excreting (Odds Ratio = 0.39, p=O.OOO), washing hands after coming - home ( Odds Ratio = 0.75, p = 0.003), brushing teeth before sleeping(Odds Ratio =0.45, p=0.000), brushing teeth more than once a day (Odds Ratio =0.73, p=0.0l2), drinking boiled water (Odds Ratio = 0.49, p=0.000), collecting garbage at home(Odds Ratio=0.31, p=0.000) and in the school(Odds Ratio =0. 67, p=0.000). All these led to significant differences. As to taking milk(Odds Ratio = 1.50, p=0.000), taking care of eyesight(Odds Ratio=1.41, p=0.001) and getting physical exercise in(Odds Ratio = 1.33, p=0.0l9) and outside the school(Odds Ratio = 1.32, p=0.005), rural children had more desirable behavior which also revealed a significant difference. There was little significant difference in smoking, but the smoking rate of rural children(5.5%) was larger than that of urban children(3.9%). 3. Health status was analyzed in terms of absences, school health room-visits, levels of physical strength, and the degree of obesity, height and weight. Considering Odds Ratios of the health status of urban-rural children, the health status of rural children was significantly better than that of the urban ones in the level of physical strength(t=1.51, p=0.000) and the degree of obesity(t=1.84, p=0.000). The mean height of urban children ($150.4{\pm}7.5cm$) is taller than that of their counterparts($149.5{\pm}7.9$), which revealed a significant difference (t =2.47, p=0.0l4). The mean weight of urban children($42.9{\pm}8.6kg$) is larger than that of their counterparts($41.8{\pm}9.0kg$), which was also a significant difference(t=2.81, p=0.005). Considering the results above, we can recognize that there are significant differences in family environment, health behavior, and health status in urban-rural children. These results also suggestion ideas for health education. What we would suggest for the health program of elementary schools is that school health teachers should play an active role in promoting the need and importance of health education, develop the appropriate programs which correspond to the regional characteristics, and incorporate them into schools to improve children's ability to manage their own health management.

  • PDF