农村居民高血压病影响因素的多项式Logistic回归分析

目的：了解青岛市农村居民轻度、中度、重度高血压患病的影响因素。方法：采用整群抽样法，对7个自然村的3700名18岁以上的居民进行血压测量及相关因素调查，并进行多项式Logistic回归分析。结果：高血压家族史、体质指数增加、口味重、重度体力 劳动是3种不同程度高血压患病共同的影响因素；其他的影响因素有，轻度：年龄、男性，中度：年龄、男性、经济收入，重度：经济收入、饮酒、吸烟，与正常组相比，其差别在统计学上有显著性。结论：农村居民不同程度高血压患病的影响因素不完全相同，应采取不同措施，预防轻度高血压，控制中度和重度高血压。     

肥城市烟酒与食管病变关联的多项式logistic回归分析

1970～1974年调查发现肥城市为食管癌高发区，1970～1974、1985～1989、1990～1992、1997～1999年4个时期食管癌死亡率分别为63．19／10万（以下略去／10万）、71．68、66．87和82．33；标化死亡率（1964年中国人口标化）分别为45．37、46．67、51．21、46．32。该地区没有医学等外来因素的“干扰”，     

农村居民高血压患病影响因素的多项式Logistic回归分析

目的　了解青岛市农村居民轻度、中度、重度高血压患病的影响因素。方法　采用整群抽样法 ,对 7个自然村的 370 0名 18岁以上的居民进行血压测量及相关因素调查 ,并进行多项式Logistic回归分析。结果　高血压家族史、体质指数增加、口味重、重度体力劳动是 3种不同程度高血压患病共同的影响因素 ;其他的影响因素有 ,轻度 :年龄、男性 ,中度 :年龄、男性、经济收入 ,重度 :经济收入、饮酒、吸烟 ,与正常组相比 ,其差别在统计学上有显著性。结论　农村居民不同程度高血压患病的影响因素不完全相同 ,应采取不同措施 ,预防轻度高血压 ,控制中度和重度高血压     

2型糖尿病视网膜病变相关因素Logistic回归分析

目的研究影响2型糖尿病视网膜病变（DR）的相关因素。方法对720例2型糖尿病患者的糖尿病病程、糖尿病家族史、心脑血管病史、吸烟史、居住地域等进行调查,测量血压、血脂、体质指数（BMI）、糖化血红蛋白（HbA1c）、空腹血糖（FPG）、24h尿微量白蛋白等,检查糖尿病周围神经病变,并对上述DR相关因素进行Logistic回归分析。结果单因素Logistic回归分析结果显示,居住地域、糖尿病病程、血压、糖尿病周围神经病变、HbA1c、24h尿微量白蛋白与DR发生之间的联系有统计学意义（P〈0．05）;多因素Logistic回归分析结果显示,糖尿病病程、HbA1c、24h尿微量白蛋白与DR发生之间的联系有统计学意义（均P〈0．05）。结论糖尿病病程、HbA1c、24h尿微量白蛋白与DR发生相关。     

三明市高血压危险因素的Logistic回归分析

[目的]找出三明市高血压的危险因素。[方法]采用分层抽样随机抽取30岁以上常住人口,用EpiInfo软件进行单因素分析。SPSS10.00软件包进行多因素非条件Logistic回归分析。[结果]三明市高血压的危险因素为超重（BMI为25-29.9)、身材肥胖（BMI≥30）、饮酒、糖尿病,高血压家族史、吸烟;保护性因素有体育活动和喜食豆及其制品。[结论]三明市高血压的干预措施是控制体重、戒烟酒,提倡食用豆及其制品和开展全民健身运动。     

多项式logistic回归分析在患者就诊行为影响因素研究中的应用

应用多项式ｌｏｇｉｓｔｉｃ回归分析患者选择就诊单位的影响因素,一是探讨该方法在卫生服务研究中的适宜性;二是研究影响中国城乡虱选择就诊单位的因素。方法影响城市虱选择就诊单位的最主要因素是医疗保障制度和居民健康状况,农村则主要为经济收入和疾病严重程度。     

剖宫产影响因素的条件Logistic回归分析

剖宫产的影响因素很多,为了探讨其主要因素,本文运用了流行病学病例对照的研究方法,按1:1配成97对,并进行条件 logisitic 回归分析。结果表明:分娩时的临床印象(X12),新生儿体重(X10),孕妇贫血(X17),及职业(X15),为剖宫产的主要因素。而孕妇的年龄(X1),增加的体重(X3),文化程度(X4),丈夫的年龄在单因素 Logistic 回归分析中与剖宫产也有明显的联系。产前检查次数,流产史,活动程度与剖宫产的联系还有待进一步研究。     

农村地区高血压危险因素的条件Logistic回归分析

本文采用1:1配对病例对照研究方法,在山东省莱芜市农村开展高血压危险因素调查。结果体重指数和家族史与高血压病有统计学联系,体重指数的相对危险性为4.39,父母单方患高血压的相对危险性为2.42,父母双方均患高血压的相对危险性为5.85,其余因素未见与高血压病有统计学联系。     

妊娠晚期贫血影响因素的Logistic回归分析

目的 探讨妊娠晚期贫血的影响因素.方法 数据来自104例孕妇的资料,以她们妊娠中期的血清铁蛋白(SF)、游离红细胞原卟啉(FEP)、红细胞容积分布宽度(RDW)和平均红细胞容积(MCV)四项指标作为自变量,以妊娠晚期游离红细胞原卟啉(FEP)作为因变量,作Logistic回归分析.结果 只有妊娠中期游离红细胞原卟啉(FEP)对妊娠晚期贫血的影响有显着意义(P<0.001),其偏回归系数为12.048,妊娠晚期贫血Logistic回归分析的理论分类与实际分类的总符合率为894%,结果较好,而妊娠中期血清铁蛋白(SF)、红细胞容积分布宽度(RDW)和平均红细胞容积(MCV)对妊娠晚期贫血的影响均无显着性意义(P>0.05).结论 妊娠中期游离红细胞原卟啉对妊娠晚期贫血有重要作用.     

2型糖尿病视网膜病变危险因素的非条件Logistic回归分析

随着糖尿病发病率的逐年上升，糖尿病视网膜病变已成为导致成人失明的主要原因之一。糖尿病视网膜病变的发生发展与环境因素和遗传因素密切相关。本研究旨在探讨2型糖尿病视网膜病变的相关危险因素。     

Multinomial goodness-of-fit tests for logistic regression models.

We examine the properties of several tests for goodness-of-fit for multinomial logistic regression. One test is based on a strategy of sorting the observations according to the complement of the estimated probability for the reference outcome category and then grouping the subjects into g equal-sized groups. A g x c contingency table, where c is the number of values of the outcome variable, is constructed. The test statistic, denoted as Cg, is obtained by calculating the Pearson chi2 statistic where the estimated expected frequencies are the sum of the model-based estimated logistic probabilities. Simulations compare the properties of Cg with those of the ungrouped Pearson chi2 test (X2) and its normalized test (z). The null distribution of Cg is well approximated by the chi2 distribution with (g-2) x (c-1) degrees of freedom. The sampling distribution of X2 is compared with a chi2 distribution with n x (c-1) degrees of freedom but shows erratic behavior. With a few exceptions, the sampling distribution of z adheres reasonably well to the standard normal distribution. Power simulations show that Cg has low power for a sample of 100 observations, but satisfactory power for a sample of 400. The tests are illustrated using data from a study of cytological criteria for the diagnosis of breast tumors.     

肥城市居民饮食与食管疾病关系

目的探讨各种主食、副食、蔬菜及其营养成分与食管炎症、增生、早期癌间的关联。方法在食管癌高发区肥城市1个乡镇3304名40～69岁人群中，将内镜检查正常者作为对照组，将用碘染色内镜和活检病理诊断方法确诊的炎症、增生、早期癌患者分为3组，采用多项式Logistic回归分析饮食与食管疾病的关联，将OR作为关联强度的指标。结果肉类是早期癌的危险因素，大豆、鱼类、油类、芹菜、茄子、芸豆、青椒、脂肪、粗纤维素、灰分、钙能降低其危险性；小麦、油类、热量是食管增生的危险因素，韭菜、莴苣具有预防作用；油类、热量是食管炎症的危险因素。结论在食管癌高发区，饮食及其含有的营养成分与食管疾病具有重要关系。     

食物中总亚硝基化合物及其相关危险因素研究

目的　探索南方食管癌现场中亚硝基化合物综合危险因素。方法　在南方食管癌高发区南澳县和低发区陆丰县各随机选择12 0名35～6 4岁健康男性居民,收集2 4小时膳食和3天12小时夜尿。分别为空白尿样、5 0 0mg脯氨酸+2 0 0mg维生素C(VC)负荷尿样和5 0 0mg脯氨酸负荷尿样。测定总亚硝基化合物(TNOC)、挥发性亚硝胺、亚硝基氨基酸(NAAs)和还原型VC。用非条件logistic模型分析各类亚硝胺摄入水平和排泄水平、NAAs内源性合成能力、VC的营养状况及其对内源性合成的阻断能力等综合因素与食管癌死亡率的关系。结果　非条件logistic回归分析筛选出两个食管癌亚硝胺危险因素—膳食TNOC含量(OR为9 6. 13,95 %CI 1 92 .1～4 8 .115 )和服VC后尿NAAs浓度(OR为1 137,95 %CI为1 0. 0 1～1 2 .98)。结论　膳食TNOC高含量和VC对NOC内源性合成的低阻断能力是南方食管癌高死亡率的两个重要危险因素。     

新生儿出生结局危险因素Logistic回归分析

目的 探讨新生儿出生结局的影响因素。方法 采用整群抽样的方法抽取2个医院2003～2004年产科1011例育龄产妇进行孕期状况问卷调查。对24个相关因素分别进行单因素及多因素Logistic逐步回归分析。结果 糖尿病（β=1．698，OR=5．461）、阴道出血（β=2．856，OR=17．394）、羊水异常（β=1．660，OR=1．190）、妊高症（β=1．510，OR=1．221）为新生儿出生结局的危险因素。结论 应加强孕妇围产期医疗保健，定期体检，以减少分娩时的危险因素。     

Tree-based model checking for logistic regression

A tree procedure is proposed to check the adequacy of a fitted logistic regression model. The proposed method not only makes natural assessment for the logistic model, but also provides clues to amend its lack-of-fit. The resulting tree-augmented logistic model facilitates a refined model with meaningful interpretation. We demonstrate its use via simulation studies and an application to the Pima Indians diabetes data.     

Semi‐varying coefficient multinomial logistic regression for disease progression risk prediction

This paper proposes a risk prediction model using semi‐varying coefficient multinomial logistic regression. We use a penalized local likelihood method to do the model selection and estimate both functional and constant coefficients in the selected model. The model can be used to improve predictive modelling when non‐linear interactions between predictors are present. We conduct a simulation study to assess our method's performance, and the results show that the model selection procedure works well with small average numbers of wrong‐selection or missing‐selection. We illustrate the use of our method by applying it to classify the patients with early rheumatoid arthritis at baseline into different risk groups in future disease progression. We use a leave‐one‐out cross‐validation method to assess its correct prediction rate and propose a recalibration framework to evaluate how reliable are the predicted risks. Copyright © 2016 John Wiley & Sons, Ltd.     

Adjusting risk factors in spontaneous abortion by multiple logistic regression

A cross-sectional case-control study was performed to identify some obstetric and gynaecologic factors that can influence spontaneous abortion. Statistical and epidemiologic analyses were done by multiple logistic regression to adjust OR through the coefficient. A dicotomized outcome variable, representing spontaneous abortion, and different independent variables, representing distinct medical factors, were designed. The analysis was carried out with a personal computer and an appropriate statistic package.The variables representing age over 35 and previous spontaneous abortions were shown to be risk factors, adjusted for the rest of variables. The variables representing parity and late menarcheal age lost significance when they were adjusted with multiple logistic regression.Corresponding author.     

2型糖尿病危险因素的1ogistic回归分析

目的 探讨多种因素与2型糖尿病的关系。方法 对有糖尿病家族史的家系成员进行流行病学调查。采用多因素非条件logistic回归模型分析2型糖尿病的危险因素。结果 调查武汉市有糖尿病家族史的家系42个。logistic回归分析发现高血压病史、年龄的增长、腰围、体重指数(按贡献大小)是2型糖尿病的危险因素；较高的教育水平为其保护因素。结论 对有糖尿病家族史的人群，随着年龄的增长应特别注意其体重、腰围、血糖、血压水平变化。对其进行防治，以减少危险因素的聚集。     

Extension of the Peters–Belson method to estimate health disparities among multiple groups using logistic regression with survey data

Determining the extent of a disparity, if any, between groups of people, for example, race or gender, is of interest in many fields, including public health for medical treatment and prevention of disease. An observed difference in the mean outcome between an advantaged group (AG) and disadvantaged group (DG) can be due to differences in the distribution of relevant covariates. The Peters–Belson (PB) method fits a regression model with covariates to the AG to predict, for each DG member, their outcome measure as if they had been from the AG. The difference between the mean predicted and the mean observed outcomes of DG members is the (unexplained) disparity of interest. We focus on applying the PB method to estimate the disparity based on binary/multinomial/proportional odds logistic regression models using data collected from complex surveys with more than one DG. Estimators of the unexplained disparity, an analytic variance–covariance estimator that is based on the Taylor linearization variance–covariance estimation method, as well as a Wald test for testing a joint null hypothesis of zero for unexplained disparities between two or more minority groups and a majority group, are provided. Simulation studies with data selected from simple random sampling and cluster sampling, as well as the analyses of disparity in body mass index in the National Health and Nutrition Examination Survey 1999–2004, are conducted. Empirical results indicate that the Taylor linearization variance–covariance estimation is accurate and that the proposed Wald test maintains the nominal level. Copyright © 2014 John Wiley & Sons, Ltd.     

油炸食品与食管癌及癌前病变关系的多元有序logistic回归分析

目的 探讨油炸食品摄入对食管癌及癌前病变发病的影响。方法 以2005-2013年在河南省农村地区开展上消化道癌症筛查项目的11个行政县（市）的40~69岁居民为研究对象,收集人口学、生活方式等信息,采用碘染色内镜进行筛查并取活检组织进行病理诊断,依据病理诊断标准分为不同病变等级,并采用多元有序logistic回归分析油炸食品摄入频率与食管癌及癌前病变发病的关系。结果 共纳入食管正常8 792例、轻度增生3 680例、中度增生972例、重度增生/原位癌413例、食管癌336例。多因素有序logistic回归分析结果显示,调整年龄、性别、婚姻状况、文化程度、BMI、吸烟和饮酒状况后,油炸食品是食管癌及癌前病变发病的危险因素。与不食油炸食品者相比,当油炸食品摄入频率<2次/周时,其OR值为1.60（95% CI：1.40~1.83）;当油炸食品摄入频率≥ 2次/周时,其OR值为2.58（95% CI：1.98~3.37）。结论 油炸食品摄入是食管癌及癌前病变发病的危险因素。