青少年代谢综合征因子分析

【目的】 通过青少年代谢综合征(metabolic syndrome, MS)相关组分的因子分析,探索青少年MS病理生理机制。 【方法】 以哈尔滨市某校130名高一学生为研究对象。测量身高、体重、腰围、臀围、收缩压、舒张压,计算体质指数、腰臀比和腰围身高比;测定空腹血糖、血清总胆固醇、甘油三酯、高密度脂蛋白胆固醇、低密度脂蛋白胆固醇及血清超敏C反应蛋白(high sensitivity C reactive protein, hs-CRP)含量。 【结果】 未引入hs-CRP变量时,提取三个公因子:肥胖因子、脂代谢因子和血压血糖因子,分别解释10个原始变量的31.730%、22.287%和16.767%,累计方差贡献率为70.784%。引入hs-CRP变量后,青少年MS相关组分共提取3个因子,分别为肥胖因子、脂代谢因子和血压血糖因子,分别解释10个原始变量的32.697%、20.275%、15.454%,累计方差贡献率为68.427%。 【结论】 肥胖因子在青少年MS发病机制中起主要作用;腰围身高比较腰围更适于评价青春期MS的中心性肥胖;hs-CRP可能参与青春期MS的发病。     

超重肥胖儿童代谢综合征组分的因子分析

目的 分析超重肥胖儿童代谢综合征(MS)各组分的聚集特征,探索儿童代谢综合征的病理生理机制.方法 研究对象来自前期工作收集的2批样本,为北京市835名14,15岁超重肥胖儿童,其中样本1有93人(超重62人,肥胖31人)、样本2有742人(超重371人,肥胖371人).先对样本1中超重和肥胖儿童代谢综合征的组分(包括体质指数、腰围、血糖、血脂、血压)进行因子分析,后对样本2进行因子分析用以验证和确认分析结果.结果 超重儿童MS组分共提取4个因子,脂代谢因子(LDL-C,TC,TG,HDL-C)、血压因子(SBP,DBP)、肥胖因子(WC,BMI)和糖代谢因子(FPG,HDL-C),累积方差贡献率达到77.44%;肥胖儿章MS组分共提取3个因子,肥胖-血压因子(WC.BMI,SBP,DBP)、脂代谢因子(LDL-C,TC,TG,HDL-C)和糖代谢因子(FPG),累积方差贡献率达到69.84%.结论 儿童MS的病理生理机制复杂,任何一个因子都不能单独解释MS的全部变量.     

瘦素与代谢综合征组成成分的聚集特性分析

目的　探讨瘦素水平与代谢综合征 (MS)组成成分的关系 ,分析MS危险因素聚集的特征和规律。方法　观测 795名非糖尿病成人的空腹血清真胰岛素 (FTI)、瘦素、血脂、血糖水平以及血压、体重指数、腰臀围比值和定量胰岛素敏感检测指数 (QUICKI)等指标 ,采用因子分析等方法探讨瘦素水平与上述变量的关系。结果　血清瘦素浓度随代谢异常组合个数的增多而上升。瘦素水平处于上三分位人群检出肥胖、高血压、血脂紊乱以及MS的比例比处在下三分位的人群明显升高。因子分析结果显示 ,男性与女性组包括瘦素等 11个变量的变化各受 3个因子支配 ,累计方差贡献率分别为6 2 0 %和 6 6 7% ,分别由瘦素与体重指数、腰臀围比值、FTI、QUICKI和高甘油三酯和低的高密度脂蛋白胆固醇等变量构成的核心因子 ,由血糖、FTI、QUICKI和高甘油三酯 (女 )构成的糖耐量因子以及由血压和体重指数 (男 )构成的高血压因子 ,其中高胰岛素和胰岛素抵抗 (IR)同时连接前两个因子。结论　该人群的瘦素水平与MS的多个关键组成成分密切相关 ,高瘦素血症可能是MS的 1个新成分。MS危险因素的聚集受多个因子支配 ,IR虽起重要作用 ,但不能单独解释其成因。     

因子分析在中西医协同信息化指标构建中的应用

目的将因子分析方法应用于中西医协同基层医疗卫生机构信息化建设指标构建过程。方法通过文献复习和专家访谈,对初步建立的指标集运用因子分析方法验证。结果通过对原始变量进行重新组合,建立了由3个一级指标、6个二级指标和29个三级指标构成的指标体系。结论运用因子分析方法构建的中西医协同发展的基层医疗卫生机构信息化建设指标体系,能够找出影响信息化建设的公共因子,简化计算,可操作性较强。     

应征男青年体格状况与血压心率的关系研究

[目的]探讨北京应征男青年体格指标与血压、心率之间的关系。[方法]采用因子分析将2 198名男青年的13项体格指标综合为彼此独立数目较少的因子,将因子的因子得分作为自变量,收缩压、舒张压、心率分别作为因变量进行Logistic回归,估计其OR值。[结果]13项指标被综合为围度、高度和宽度3个因子,围度因子是收缩压(OR=2.32,P﹤0.05)与舒张压(OR=2.14,P﹤0.05)升高的危险因素,与心率加快没有联系(P﹥0.05),高度因子、宽度因子与血压升高、心率加快没有联系(P﹥0.05)。[结论]北京应征男青年血压值的增高与反映身体肥胖程度的指标有关,与反映身体高度、宽度的指标无关;心率的加快与反映身体肥胖程度、高度、宽度的指标都无关。     

影响海南省疟疾流行的气候因素及植被指数的因子分析

目的应用因子分析方法研究海南省疟疾流行与气候因素和植被指数(NDVI)之间的关系。方法收集1995年海南省各市(县)疟疾月发病率与月平均温度、月最高温度、月最低温度、月降雨量和月相对湿度等资料;从同年3~12月份AVHRR卫星图像中提取月平均NDVI、月最大NDVI、月最小NDVI。利用SPSS 11.0软件对以上各变量进行因子分析,并用公因子得分建立疟疾流行的多元回归模型。结果提取了海南省各市(县)月NDVI与月气候变量的各12个月数据(NDVI为10个月)的主成分,并用方差最大正交旋转后的公因子得分建立了如下回归方程:I′=-0.022 0.463 X1 0.519X2(R2=0.799,P=0.000),其中I′为经标准变量变换的月发病率,X1为月平均NDVI的第2个公因子,X2为月降雨量的第2个公因子。结论平均NDVI和降雨量可能是描述疟疾流行的重要环境因素。     

藏族儿童少年生长发育因子分析

儿童少年的生长发育和身体素质是反映不同人群生活条件和健康水平最重要的标志[1]。体质发育指标是反映人体生长发育的基本数据[2]。通过对尽可能多的生长发育指标进行因子分析,可以了解各指标在模型中的贡献率,对建立完善的儿童少年生长发育筛查指标和评价因子,评价个体的生长发育状况具有重要意义。本文采用因子分析(factor analysis)的方法从多个实测的原变量中提取出少数的、互不相关的、抽象的综合指标,对藏族儿童少年体质发育项目指标进行因子提取,并进行分析。报道如下。     

浙江省成人膳食营养素与代谢综合征危险性研究

目的探索浙江省居民的膳食营养素摄入结构并分析不同的膳食营养素主因子与代谢综合征及其组分之间的关系,为进一步开展营养干预,预防代谢综合征的发生提供理论依据。方法选取2010~2012年"中国居民营养状况监测项目"中浙江省地区成人的膳食调查资料,因子分析获得膳食营养素的主因子及因子得分,利用Logistic回归模型分析膳食营养素主因子与代谢综合征及其组分的关系。结果因子分析获得四个膳食营养素主因子,其总的方差贡献率为77.56%,其中"矿物质+膳食纤维"组可使高血糖危险性降低(OR=0.74,95%CI:0.59,0.93),"胆固醇+硒"组的因子得分与代谢综合征及其组分之间无关联,"供能营养素+维生素"组的Q3可使腹型肥胖危险性增加为(OR=1.45,95%CI:1.02,2.08),"钠灰"组的Q5可分别使MS(OR=1.43,95%CI:1.01,2.03)、高血压(OR=1.58,95%CI:1.15,2.17)及高脂血症(OR=1.57,95%CI:1.15,2.14)的危险性分别增加。结论 "矿物质+膳食纤维"组可降低血糖异常风险性,"供能营养素+维生素"和"钠灰"组可增加MS及其组分异常危险性,结合中国居民膳食指南,建议居民控制脂肪及总能量摄入,保证维生素、矿物质的摄入量,同时增加膳食纤维的摄入量,并降低钠盐食用量,从而降低MS及其组分异常的风险。     

湖北省居民健康素养与健康状况典型相关性研究

目的通过分析探讨健康素养与健康状况之间的关系,为提升人群健康状况提供科学依据。方法以湖北省2012年居民健康素养调查为例,于2012年9~12月,在湖北省采用多阶段分层随机抽样的方法,确定4 501名15~69岁常住居民作为调查对象,使用《全国居民健康素养监测调查问卷》进行问卷调查。对6个方面健康素养指标和2个方面健康状况指标进行典型相关分析。结果健康素养6个方面的得分中,安全和急救素养和科学健康观素养得分最高,分别为(68.86±20.34)分、(68.38±18.92)分;信息获取素养和慢性病素养得分最低,分别为(52.37±17.78)分、(49.54±25.36)分;健康素养与健康状况之间存在1对有意义的典型相关变量(即第一典型相关变量,典型相关系数为0.19,P0.01),其中信息素养和自觉健康状况分别起主要作用。结论应将信息素养作为健康素养促进的关键点,从多个维度提高居民信息素养水平。     

广州市小学男生行为问题与家庭环境的典型相关分析

目的了解广州市城区6～11岁男童问题发生情况,探讨儿童行为问题与家庭环境因素关系.方法采用分层整群抽样的方法,用Achenbach儿童行为量表、家庭环境量表(中文版,以下简称FES-CV),对广州市950名小学男生进行统一问卷调查.对儿童行为问题指标与家庭环境因素指标进行典型相关分析.结果家庭环境因子与行为问题因子两组变量存在相关关系,y6(知识性)的得分越高、y3(矛盾性)的得分越低,则x7(多动)、x8(攻击性)、x2(抑郁)、x3(交往不良)的得分越低.y5(成功性)、y2(情感表达)的得分越高、y9(组织性)的得分越低,则x6(社交退缩)、x3(交往不良)的得分越低,x1(分裂样)的得分越高.结论改善家庭环境功能,可预防和减少学龄期男童的行为问题的发生.     

Clustering of procoagulation, inflammation, and fibrinolysis variables with metabolic factors in insulin resistance syndrome

The known metabolic cardiovascular disease risk factors associated with insulin resistance syndrome (IRS) do not adequately explain the excess cardiovascular disease risk attributed to this syndrome, and abnormalities in hemostatic variables may contribute to this excess risk. Using data from 322 nondiabetic elderly men and women (aged 65-100 years) participating in the Cardiovascular Health Study during 1989-1990, the authors performed factor analysis on 10 metabolic risk factors associated with IRS and 11 procoagulation, inflammation, and fibrinolysis variables to examine the clustering of the metabolic and hemostatic risk markers. Factor analysis of the metabolic variables confirmed four uncorrelated factors: body mass, insulin/glucose, lipids, and blood pressure. Adding the hemostatic variables yielded three new factors interpreted as inflammation, vitamin K-dependent proteins, and procoagulant activity. Plasminogen activator inhibitor-1 clustered with the body mass factor, supporting the hypothesis that obesity is related to impaired fibrinolysis. Fibrinogen clustered with the inflammation summary factor rather than procoagulant activity, supporting the position that fibrinogen principally reflects underlying inflammation rather than procoagulant potential. The authors conclude that should hemostatic variables be shown to contribute to IRS-related cardiovascular disease, apart from plasminogen activator inhibitor-1, they may do so independently of the established metabolic abnormalities.     

Metabolic syndrome and ischemic heart disease in elderly men and women

Associations between metabolic syndrome components and prevalent ischemic heart disease (IHD) were investigated in a cross-sectional, community-based study of elderly men (n = 1,015) and women (n = 1,259) in Rancho Bernardo, California, in 1984-1987. In both sexes, there were significant positive associations between IHD defined by resting electrocardiogram criteria and age, systolic blood pressure, fasting and postchallenge hyperglycemia, total cholesterol/high density lipoprotein cholesterol (HDL cholesterol) ratio, and triglycerides and an inverse significant association with HDL cholesterol. High collinearity and interactions between serum insulin and metabolic syndrome variables were accounted for by uncorrelated principal components identified by factor analysis. In both men and women, three uncorrelated principal components were identified, representing a central metabolic factor (body mass index, fasting and 2-hour serum insulin, high serum triglycerides, and low HDL cholesterol), a glucose factor, and a blood pressure factor. In a multivariate model with age and sex, all three factors were significantly associated with IHD by electrocardiogram criteria; central metabolic factor (odds ratio (OR) = 1.6, p = 0.001), glucose factor (OR = 1.4, p < 0.001), blood pressure factor (OR = 1.2, p = 0.005), age (10 years) (OR = 1.8, p < 0.001), and female sex (OR = 0.5, p < 0.02). Similar results were obtained in analyses using clinically manifest IHD as the outcome. These results support the thesis that the metabolic syndrome exerts effects through different risk factors by different mechanisms.     

Utility of the PRECEDE Model in Differentiating Users and Nonusers of Smokeless Tobacco

The utility of the PRECEDE model in identifying factors associated with smokeless tobacco use among male adolescents was investigated. Users and triers were more likely than nonusers to be white, older than average age for their grade, receive below average grades in school, and have had no classroom instruction on adverse effects of smokeless tobacco use. The standard score means of users, triers, and nonusers differed significantly on six of seven PRECEDE model components: attitudes, beliefs, values, perceptions, reinforcing factors, and enabling factors. The standard score means of triers and nonusers, only, differed significantly for the knowledge component. A stepwise multiple regression analysis using all seven model components as predictor variables of smokeless tobacco use accounted for 47.9% of explained variance among users, triers, and nonusers. The values component was the most powerful predictor of smokeless tobacco use (35% of the explained variance). Discriminant function analysis demonstrated the seven components of the PRECEDE mode instrument accurately classified 93.1% of users and nonusers.     

某市农村生活饮用水水质主因子分析

目的通过主因子分析对某市农村生活饮用水的污染特征进行研究。方法从原始数据的相关矩阵出发,提取占总方差85%以上的主因子,对主因子及其空间变化规律做出合理的解释。结果利用SPSS13.0软件分析可知前6个主因子累计方差贡献率为89.703%,分别对应的污染指标为铅、砷和有机物污染、锰和营养盐污染、铁污染、无机盐污染、砷污染、铜污染。结论富营养盐和有机物污染因子、重金属污染因子、砷污染因子和无机盐污染因子是该市农村生活饮用水水质污染的几个主要因子;工业排放和生活污水是其主要污染源。     

Cardiovascular risk factors clustering features of insulin resistance syndrome (Syndrome X) in a biracial (Black-White) population of children, adolescents, and young adults: the Bogalusa Heart Study.

Recently, independent factors representing different features of insulin resistance syndrome (Syndrome X) have been identified by factor analysis in middle-aged and elderly adult populations. In this study, factor analysis was applied to the clustering characteristics of Syndrome X in a biracial (Black-White) community-based population of 4,522 children (ages 5-11 years), adolescents (ages 12-17 years), and young adults (ages 18-38 years) from the Bogalusa Heart Study who were screened during 1988-1996. Ponderal index (weight (kg)/height (m)3), levels of insulin, glucose, triglycerides, and high density lipoprotein cholesterol, and systolic and diastolic blood pressure were used as measures of components of Syndrome X. No evidence was found to support a one-factor hypothesis for this syndrome, but factor analysis yielded two uncorrelated factors (factor 1: insulin/lipids/glucose/ponderal index; factor 2: insulin/blood pressure). These two factors explained 54.6% of the total variance in the entire sample. The factor loading patterns were very similar in all race and age groups, based on high values of coefficients of congruence (0.89-1.0). These results suggest that Syndrome X is characterized by the linking of a metabolic entity (hyperinsulinemia/insulin resistance, dyslipidemia, and obesity) to a hemodynamic factor (hypertension) through shared correlation with hyperinsulinemia/insulin resistance, and that the clustering features are independent of sex and age in both Black and White populations.     

Metabolic Syndrome in the Rural Population of Wardha,Central India: An Exploratory Factor Analysis

Background and Objectives:

Metabolic syndrome – a plausible precondition for type II diabetes and cardiovascular diseases is also on rise. To understand the mechanistic complexity of metabolic syndrome it is imperative to study the specific contribution of the determinants of metabolic syndrome. Such study can help to identify the most significant factor which may be of use in early detection as well as prevention efforts. Such information is scarcely available from India and especially from rural India. Hence, the present study was undertaken to explore for such factor which might be considered crucial for development of such pathogenesis particularly in rural population of Wardha.

Methods:

A cross-sectional study comprising of 300 subjects was carried out in rural area of Primary Health Center, attached to medical college with approximate 31,000 populations. The anthropometric parameters such as height, weight, waist circumference were measured. Overnight fasting samples were collected for lipid profile (total cholesterol, triglyceride, high density lipoproteins, low density lipoproteins, very low density lipoproteins) and fasting blood glucose levels. The National Cholesterol Education Programme Adult Treatment Panel, ATP-III guidelines were used to categorize the study subjects. As many of the variables are highly intercorrelated, exploratory factor analysis was carried out to reduce the data to a smaller number of independent factors that accounts for the most of the variances in the data. Principal component analysis was used as a method of extraction.

Results:

For both sexes, three factors were extracted accounting for about 71% variance in the measured variables. An adiposity factor which accounted for highest explained variance (28%), was the initial factor extracted. It was loaded positively by waist circumference, triglyceride, and very low density lipoprotein and negatively loaded by high density lipoprotein. Second factor extracted was a cholesterol factor which explained about 20% variance. It was positively loaded by total cholesterol and low density lipoprotein. Blood pressure factor was third to be extracted which again explained about 20% variance. It was positively loaded by systolic and diastolic blood pressure.

Interpretation and Conclusion:

The results clearly indicate the significance of visceral adiposity over the obesity in general or simple abdominal obesity measured anthropometrically as a pathogenic determinant of the metabolic syndrome. The most consistent factor has been found to be dyslipidemia which explained major share of the observed variance and the most significant load of this factor being rested on triglyceride and the VLDL level. Hence, we conclude measurement of triglyceride might be a rewarding screening parameter for assessment of cardio-metabolic risk in general populace and warrants a large scale study focusing into this issue.     

Determinants of plasma lipoproteins and coagulation factors in men from Caerphilly, South Wales.

Dietary, social, and constitutional determinants of plasma concentrations of some major risk factors for ischaemic heart disease were investigated in a cross sectional study among 711 men from the general population aged 30-69. For high density lipoprotein cholesterol (HDL-C) six variables were significantly associated with plasma concentrations, and these variables explained 12.6% of the variance. For low density lipoprotein cholesterol (LDL-C), total cholesterol (T-C), and triglyceride 8.4%, 7.5%, and 18.5% of the variance was explained by significantly associated variables. Fibrinogen concentrations determined chemically were significantly associated with age, smoking habit, body mass index, alcohol consumption, and intake of cereal fibre (24.2% variance). These data provide some encouragement for the possibility of dietary intervention to influence plasma concentrations of major risk factors for ischaemic heart disease in men.     

A factor analysis of dyspnea indexes and lung function parameters in patients with chronic obstructive pulmonary disease

The purpose of the present study was to investigate the correlation between dyspnea ratings and a large group of lung function parameters, and extract those factors that best reflect the functional profile of patients with COPD using factor analysis. Ninety nine patients with COPD in stable clinical condition (age 60 +/- 8 years, ATS score = 2.5 +/- 0.9, FEV1% pred. = 33 +/- 13%) were included in the study. The factor analysis of the results yielded 5 factors which accounted for 80.1% of the total variance of the changes. The highest coefficients found between the factors and the original group of variables after Varimax rotation are given in the following table: Factor 1: Oxygen-cost diagram: 0.92; ATS dyspnea score: -0.80; TL,CO/VA: 0.78; Factor 2: FEV1% pred.: 0.87; FEV1/VC%: 0.86; FEV1L: 0.79; Factor 3: MIF50% pred.: 0.85; FIV1% pred.: 0.76; PImax: 0.67; Factor 4: PaCO2: -0.81; SaO2: 0.77; Mean pulmonary arterial pressure: -0.67 Factor 5: Age: 0.88; Six minutes walk distance: -0.72 The factor analysis showed that the functional profile of COPD patients has several dimensions. Therefore, in order to have COPD comprehensively evaluated, assessment of dyspnea and the respective set of lung function parameters (exercise capacity, forced inspiration and pulmonary hemodynamics), should be included in the battery of tests, besides the conventional tests.     

Use of factor analysis to consolidate multiple outcome measures in chronic obstructive pulmonary disease

Multiple outcome measures are often used in clinical research and practice. However, the use of multiple measures inflates the probability of a type I error. In this paper, we used factor analysis techniques to reduce multiple outcome measures to a lesser number of orthogonal dimensions. The data were obtained from 119 patients with chronic obstructive pulmonary disease. Each patient had measurements made of 28 variables, including multiple parameters of pulmonary function, exercise tolerance and gas exchange. Factor analysis using a maximum likelihood iterative solution was performed. The factors were then rotated to a varimax solution. The analysis yielded four meaningful factors: exercise tolerance, disease severity, lung volumes and flow rates. Exercise tolerance and disease severity were the most important factors accounting, respectively, for 44 and 13% of the common variance. For further analyses, these composite factors could be used or a representative clinical measure from each factor might be chosen. We conclude that many physiologic measures provide highly correlated information about chronic obstructive pulmonary disease patients. Factor analysis may help reduce these measures into a smaller number of reliable composites.