四川省城市居民冠心病主要危险因素定量评价标准的研究

目的 制定冠心病危险因素的定量评价标准,为预测个体冠心病的患病危险奠定基础。方法 通过文献检索收集冠心病危险因素的病例对照和队列研究资料及四川省的行为危险因素监测资料,运用meta分析软件对各危险因素与冠心病的比值比(OR)、相对危险度(RR)值进行合并,运用统计模型将不同暴露水平的危险因素转换成危险分数。结果 以5岁为1个年龄组,建立了15-69岁不同性别的冠心病主要危险因素：吸烟、被动吸烟、高血压、高血脂、体重指数、体育锻炼、饮酒、高脂饮食、糖尿病、冠心病家族史和高血压家族史的定量评价标准(危险分数转换表),无这些危险因素(体育锻炼除外)者其危险分数均≤1．00(进行体育锻炼者危险分数＜1．00),而伴有这些危险因素者其危险分数均＞1．00,且危险分数随危险程度的增加而增高。结论 冠心病危险分数转换表是计算冠心病存在死亡危险的基础,后者可预测个体未来10年发生冠心病死亡的危险性。该方法是健康教育的有力依据,也是当前深入开展社区卫生服务的重要方法。     

重庆社区居民糖尿病相关危险因素定量评价标准

目的 探讨重庆市16岁以上社区居民糖尿病相关危险因素,制定危险因素的定量评价模型,为预测个体糖尿病的患病危险奠定基础.方法 采用病例对照研究的方法,从重庆市沙坪坝、小龙坎、天星桥、渝碚路、磁器口5个社区中以1:2的比例抽取糖尿病患者1981例,健康人群3962例进行回顾性调查,利用logistic回归方法分析,得出各危险因素与糖尿病的OR值,运用统计模型将不同暴露水平的危险因素转化成危险分数.结果 得到不同性别、年龄、行为、疾病以及家族史的个体在不同情况下的危险分数,男性为高脂血症史(14.995)、冠心病(6.689)、高血压家族史(4.005)、吸烟(3.111)等13个危险因素进入主效应模型;女性为高脂血症史(12.426)、高血压家族史(3.986)、脑卒中史(2.714)、嗜甜食(1.244)等15个危险因素.根据个体情况得到组合危险分数,从而预测该个体的糖尿病发病危险.结论 改变不良的生活方式以及个人疾病的积极治疗和控制,能有效降低糖尿病的发病率;而根据危险因素建立的危险分数评估模型是健康教育的有力依据,也是当前开展社区卫生服务的重要方法.     

重庆市社区居民脑卒中危险因素分析及个体健康危险评价研究

目的探讨重庆市26岁以上社区居民脑卒中的危险因素,制定其定量评价模型,为预测个体发病危险奠定基础。方法采用病例-对照研究的方法,以1∶2的比例抽取脑卒中患者1034例、对照组2 068例进行回顾性调查,利用Logistic模型分析,得出各危险因素的OR值,将不同暴露水平的危险因素转化成危险分数,最后根据个体情况得到组合危险分数,从而预测该个体脑卒中的发病危险。结果Logistic逐步回归分析显示,男性脑卒中主要危险因素包括年龄、文化程度、嗜咸食、不锻炼、舒张压≥90 mmHg、高血压和脑卒中家族史、糖尿病、冠心病、高血压、高脂血症,其中危险分数较高的前3位依次为高血压（5.728）、冠心病（5.404）、脑卒中家族史（4.599）。女性主要危险因素与男性相比,不包括不锻炼和冠心病,增加了饮酒和超重,其中危险因素较高的前3位依次为高血压（5.270）、脑卒中家族史（4.866）、高脂血症（4.346）。结论高血压、高脂血症等个人病史是脑卒中发生的主要危险因素,改变不良的生活方式以及对疾病进行积极治疗和控制,能有效降低脑卒中的发病率;而根据危险因素建立的危险分数评估模型是健康教育的有力依据,也是当前开展社区卫生服务的重要方法。     

老年阿尔茨海默病发病风险预测的循证研究

目的：建立阿尔茨海默病（AD）的个体健康危险因素的评价模型，预测个体发生阿尔茨海默病的风险。方法：通过文献检索的方法，收集阿尔茨海默病的危险因素、病例对照的研究资料，并用RevMan软件对这些文献进行Meta分析，将各研究的危险因素与阿尔茨海默病的比值比（OR）进行合并，以合并的OR值为基础建立危险分数表，从而建立危险因素评价模型。结果：建立了危险分数表，将表中所列有关分数相加得出了组合危险分数，并借此预测其发病危险。结论：运用该模型可对个体未来发生阿尔茨海默病的危险进行预测。     

城市居民肺癌危险因素的定量评价标准

目的：制定肺癌危险因素的定量评价标准，以便更好地预测个体所处的危险因素对其患肺癌的危险。方法：通过文献检索收集肺癌危险因素的病例对照和队列研究资料及各种危险因素的暴露率资料，收集四川省城市疾病监测点的人口学，疾病死亡及行为危险因素监测资料，运用Meta分析软件对效应量OR值（比值比）进行合并，选择统计模型计算肺癌的危险分数，根据Reed-Merrill公式将各性别/年龄组的死亡率转换成死亡频率，用寿命表的方法将全死因及肺癌的1年死亡概率转换成10年死亡概率，再根据肺癌的危险分数及10年死亡概率计算肺癌的存在死亡危险。结果：建立了肺癌的危险分数转换表及肺癌的10年死亡概率表，根据个体所处的危险因素利用危险分数转换表及肺癌的10年死亡概率计算得到的存在死亡危险。可预测个体未来10年发生肺癌死亡的可能危险，并有力地说服个体改变不良的行为生活方式，消除或降低所处的危险因素。提高健康水平。结论：该方法是健康教育的有力依据。也是当前深入开展社区卫生服务的重要方法。     

脑血管病风险因素Meta分析及个体健康危险度评价

目的 构建脑血管病个体健康危险度评价模型,预测个体发生脑血管病的危险.方法 通过网络检索维普、万方、CNKI数据库1980到2012年公开发表的脑血管病相关危险因素病例对照研究论文,经筛选后纳入Review manager 5软件进行汇总,通过Meta分析获取脑血管病相关危险因素合并OR值,以此为依据建立评价模型生成危险分值转换表,预测发病风险.结果 本研究搜集符合要求的文献81篇,涉及生活行为方式、健康状况共计12个风险因素.针对不同年龄、性别建立脑血管病风险评价模型,并举例说明针对个体如何预测发病风险.结论 本评价模型能够依据个人存在的风险因素对脑血管病发病风险进行预测,并能评价改变风险因素后的健康效果,为脑血管病的早期预防提供了有效途径.     

冠心病个体健康危险度评估模型建立

冠状动脉粥样硬化性心脏病,简称为冠心病( coronary heart disease,CHD),目前是我国死亡率和致残率最高的疾病之一,是当今影响全球人群死亡和功能障碍的主要原因之一[1].随着疾病谱的改变及人口的老龄化,其发病率及患病率呈逐年上升的趋势.由于冠心病是一种慢性病,其预防的效果远胜于治疗,危险因素的控制是冠心病预防的重要环节.随着经济的发展和生活水平的提高,人们已经越来越关注自身的健康,并乐于改变生活中不健康的行为方式,减少人为的危险因素.本研究应用文献评阅和数据模型方法[2],建立冠心病的个体健康危险度评估模型,预测个体发生冠心病的危险,从而使临床医生能便捷和及时地识别并改进个体危险因素,达到预防和延缓冠心病发生的目的.     

四川省城市居民脑血管病主要危险因素定量评价标准的研究

目的　制定脑血管病主要危险因素的定量评价标准。方法　通过文献检索收集脑血管病的危险因素、病例对照和队列研究资料 ,收集四川省的行为危险因素监测资料 ,运用系统评价数据库软件 (ReviewManager 4 .1.1)进行Meta分析 ,将各研究的危险因素与脑血管病的比值比 (OR)、相对危险度 (RR)进行合并 ,以合并的OR(RR)值为基础 ,运用统计模型将不同暴露水平的危险因素转换为危险分数。结果　以 5岁为一个年龄组 ,建立了 35～ 6 9岁分性别的脑血管病主要危险因素 :吸烟、被动吸烟、高血压、高血脂、体重指数、体育锻炼、饮酒、高脂饮食、喝奶、口服避孕药、糖尿病史、心脏病史和脑卒中家族史的定量评价标准 (危险分数转换表 )。无这些危险因素 (体育锻炼、喝奶除外 )者其危险分数均≤ 1.0 0 ,而有这些危险因素者其危险分数均 >1.0 0 ,且危险分数随危险程度的增加而增高。结论　脑血管病危险分数转换表是计算脑血管病存在死亡危险的基础 ,后者可预测个体在未来 10年发生脑血管病死亡的概率。     

北京市东城区35～59岁社区居民心血管疾病风险评估

目的了解北京市东城区社区居民心血管病(CVD)危险因素的暴露情况及评估未来10年缺血性心血管病(ICVD)发病危险度,为不同风险类型个体或群体实施不同的健康管理策略提供科学依据。方法采用多阶段随机抽样方法,抽取35~59岁常驻居民1076人,进行心血管疾病相关危险因素流行病学调查,并对人群用国人缺血性心血管病十年发病危险度评估表评估其10年ICVD的发病危险性。结果在35~59岁人群中,高血压、糖尿病、血脂异常、体重异常、早发家族史和吸烟暴露率分别为36.8%、13.1%、69.9%、62.2%、53.3%和23.5%;超过半数的个体具有3个及以上危险因素,且男性大于3个及以上危险因素的比例明显高于女性(P<0.01),危险因素的个数随年龄的升高而升高;调查对象10年缺血性心血管疾病发病危险度处于中危及以上的检出率为3.2%;男女不同年龄组发病平均危险度除35~39岁组,其余各组均显著高于评估表提出的各年龄段绝对平均危险度参考标准。结论北京市东城区心血管疾病危险因素水平较高,35~59岁人群10年缺血性心血管疾病发病风险较大,提示应积极加强对心血管疾病危险因素的干预。     

中国结直肠癌健康风险评估模型研究

目的构建适用于中国人群的结直肠癌健康风险的评估模型,为结直肠癌高危人群筛查提供理论依据。方法通过收集结直肠癌发病相关风险因素的比值比、不同水平风险因素的人群暴露率和中国结直肠癌年龄别、性别发病率等参数,建立个体在未来5年内的结直肠癌风险分数转换表,计算组合风险分数,采用SAS 9.2软件建立个体风险评价模型,预测个体发病风险。结果本研究纳入了13个危险因素,大便潜血和黏液便史的风险分数最高,均在10分左右,其次为肠息肉史(6.86分)、慢性结直肠炎病史(4.14分)、慢性腹泻(3.82分)、一级亲属肠癌史(2.42分)、慢性阑尾炎或阑尾炎手术史(2.09分)、胆囊疾病或胆囊手术史(2.01分)、慢性便秘(2.01分)和消化道溃疡史(1.91分),而吸烟(1.09分)和饮酒(1.11分)的风险分数接近1。风险分数1的因素为吃蔬菜≥1次/d(0.78分),提示该因素为保护性因素。发病风险因素个数相同、种类不同的个体发病风险不同。相同发病风险组合分数者,年龄越高,发病风险越大;年龄相同时,男性发病风险高于女性。结论本研究建立的中国人群结直肠癌健康风险的个体化评估模型可为结直肠癌高危人群筛查提供理论依据。     

High cardiovascular mortality in Russia cannot be explained by the classical risk factors. The Arkhangelsk study 2000

Since the beginning of the 1990s the public health situation in Russia has been characterized by an extremely high mortality and a significant reduction in life expectancy. Cardiovascular diseases remained the major cause of death. Only a few large population studies were conducted in Russia during this period. A total of 1968 men and 1737 women aged 18–75 years participated in a health survey in Arkhangelsk, Russia, over the period 1999–2000. Investigation included assessment of classic cardiovascular risk factors (family history, smoking, blood pressure, and blood lipids) along with general health variables. The paper presents sex specific data on risk factors for coronary heart disease. Though the cardiovascular mortality is high in Russia, the calculated risk for coronary heart disease (the Framingham risk score and the Norwegian risk score) was lower in all age groups of men and women in Arkhangelsk compared with studies from the Western Europe and USA. Our data suggest that high cardiovascular mortality in Russia may be driven not only by the classic risk factors for coronary heart disease.     

Interactions between diabetes and family history of coronary heart disease and other risk factors for coronary heart disease among adults with diabetes in Utah

We used a unique data base containing medical family history information from representative Utah families to investigate interactions between diabetes and family history of coronary heart disease and other risk factors for coronary heart disease. We compared nonrelated individuals reported to have had diabetes mellitus diagnosed over the age of 19 (948) with 2150 nondiabetic individuals. Among both men and women, diabetes and family history of early coronary heart disease magnified the risk for coronary heart disease, so that in diabetic individuals with a positive family history of coronary heart disease, about 74% of the coronary heart disease could be attributed to interaction. Relative to nondiabetics without a family history of early coronary heart disease, nondiabetics with family history had a relative risk of 4.5 (2.3-8.7), diabetics without a family history had a relative risk of 2.8 (1.6-4.9), and diabetics with a family history had a relative risk of 21.3 (9.1-50.0). Smoking also interacted with diabetes; among smoking diabetics, 47% of early heart disease may be attributable to interaction between smoking and diabetes. Smoking entailed the highest risk for diabetic women. Hypertension and diabetes appeared to act additively, with little interaction. Among women, family history of diabetes was a risk factor for coronary heart disease with a relative risk of 2.5 (1.0-6.4), whereas for men the relative risk was estimated to be 0.4 (0.2-1.1).     

Development of health risk appraisal functions in the presence of multiple indicators: The Framingham Study nursing home institutionalization model

A health risk appraisal function is a mathematical model designed to estimate the risk or probability of a person's mortality or morbidity for various diseases based upon risk factors such as age, medical history and smoking behaviour. The Framingham Study has contributed substantially to the development and use of these for endpoints such as mortality and incidence of coronary heart disease and other cardiovascular diseases. This paper discusses a methodology for the development of health risk appraisal functions when the number of potential risk factors is large and illustrates it with sex specific functions for nursing home institutionalization. The methodology involves grouping variables substantively into sets, applying principal component factor analysis and variable clustering to obtain substantively meaningful composite scores, ranking these in order of substantive importance, and then entering these with a hierarchical ordering into a Cox proportional hazard regression.     

Potential errors resulting from sex and age difference in assessing family history of coronary heart disease

BACKGROUND: Coronary heart disease occurs nearly exponentially with age and differently between men and women. Therefore, difference in sex and age of family members yields errors in assessing the family history as a risk factor. The influence of sex and age on the positivity of family history was assessed numerically. METHODS: Through questionnaires filled in by the parents of 2316 high school students, information was obtained on the past history of coronary heart disease among students' parents, grandparents, uncles, and aunts. The sex- and age-specific proportion of a positive history was calculated from the past history among the 24,071 family members. The influence of sex and age on a positive history was estimated as odds ratios by logistic regression analysis of the past history. RESULTS: The odds ratios obtained for sex and age difference were 1.61 (95% confidence interval: 1.42-1.83) and 1.07 (95% confidence interval: 1.06-1.07), respectively. This indicated that a positive history was 1.61 times higher among male members than among female members of the same age, and that a positive history increased by (1.07)y, where y was age difference by year. CONCLUSIONS: Potential errors resulting from disregarding the sex and age of family members can be substantial, judging from the above numerical figures. Some measures to control for the sex and age of family members are required in assessing family history of coronary heart disease.     

Developing Family Healthware, a Family History Screening Tool to Prevent Common Chronic Diseases

Family health history reflects the effects of genetic, environmental, and behavioral factors and is an important risk factor for a variety of disorders including coronary heart disease, cancer, and diabetes. In 2004, the Centers for Disease Control and Prevention developed Family Healthware, a new interactive, Web-based tool that assesses familial risk for 6 diseases (coronary heart disease, stroke, diabetes, and colorectal, breast, and ovarian cancer) and provides a "prevention plan" with personalized recommendations for lifestyle changes and screening. The tool collects data on health behaviors, screening tests, and disease history of a person's first- and second-degree relatives. Algorithms in the software analyze the family history data and assess familial risk based on the number of relatives affected, their age at disease onset, their sex, how closely related the relatives are to each other and to the user, and the combinations of diseases in the family. A second set of algorithms uses the data on familial risk level, health behaviors, and screening to generate personalized prevention messages. Qualitative and quantitative formative research on lay understanding of family history and genetics helped shape the tool's content, labels, and messages. Lab-based usability testing helped refine messages and tool navigation. The tool is being evaluated by 3 academic centers by using a network of primary care practices to determine whether personalized prevention messages tailored to familial risk will motivate people at risk to change their lifestyles or screening behaviors.     

Screening results for subclinical coronary artery calcification in asymptomatic individuals in relation to a detailed parental history of premature coronary heart disease

A parental history of premature coronary heart disease (CHD) is an established risk factor for CHD events in descendants. The study aim was to investigate whether subclinical coronary artery calcification (CAC) differs between asymptomatic individuals (a) without a parental CHD history, (b) with a parental history and (c) without knowledge of parental CHD history. The inclusion of individuals without knowledge of parental CHD history is a new approach. We also differentiated between CHD of mother and father to gain insight into their individual contributions. Data was obtained for 4,301 subjects aged 45–75 years free of overt CHD from the baseline screening of the population-based Heinz Nixdorf Recall study. CAC, measured by electron-beam computed tomography, was modeled conducting logistic regressions. Model 1 included family history, Model 2 was adjusted for age (and gender) and Model 3 added common CHD risk factors. The CAC score was dichotomized using the age and sex-specific 75th percentile. The odds ratio (OR) for CAC ≥ age and sex-specific 75th percentile was 1.33 among individuals with parental premature CHD history (95 % confidence interval [95 %CI]: 1.08, 1.63), which did not change after full adjustment (OR 1.40, 95 %CI: 1.13, 1.74). Individuals with an unknown biological father or mother had a high chance of elevated CAC scores (fully adjusted; father: OR 1.38, 95 %CI: 1.01, 1.90, mother: OR 1.86, 95 %CI: 0.90, 3.84) compared to the reference group. The current study showed an association between parental CHD history and CAC independent of common CHD risk factors. This association affirms the use of parental CHD history in cardiovascular risk assessment among asymptomatic adults in routine practice. The observation that individuals who did not know their mother or father are prone to increased CAC scores needs further confirmation in large scale studies.     

奎屯市居民糖尿病危险因素调查

目的探讨奎屯市人群糖尿病发生的危险因素。方法采取整群抽样的方法进行调查,利用自行设计的调查表收集被调查人群个人基本情况,测量身高、体质量、血压,采用单因素和多因素非条件logistic回归分析方法处理资料。结果单因素分析显示,地区、年龄、职业、高血压病、冠心病、脑卒中史、高血压家族史、冠心病家族史、脑卒中家族史、糖尿病家族史、吸烟史、职业性体力活动强度、睡眠、体质量指数(BMI)、腹部肥胖(WC)可能与糖尿病有关(P均<0.05);多因素逐步回归分析显示,地区、年龄、高血压病史、高脂血症史、糖尿病家族史、BMI、WC、蔬菜与糖尿病有关(P均<0.05)。结论地区、年龄、高血压病史、糖尿病家族史、BMI、WC是奎屯市糖尿病的主要危险因素,应针对性开展体质量超标、腹型肥胖、高血压病史、糖尿病家族史等高危人群的筛查及干预工作。