Fornari et al. BMC Public Health 2010, 10:574 http://www.biomedcentral.com/1471-2458/10/574 at baseline). Diabetes mellitus was defined using self- reported diagnosis, information on insulin and oral hypoglycaemic treatments and fasting blood glucose (FBG) exceeding 126 mg/dl. Individual 10-year global cardiovascular risk was identified using Progetto CUORE predictive equation of coronary events [27]. This equation for prediction of cardiovascular events was calibrated on the 35-69 year-old Italian population and included the following risk factors: age, total and HDL cholesterol, systolic blood pressure, cigarette smoking, diabetes mellitus and drug treatment for hypertension. Educational level and marital status were collected by a standard questionnaire at baseline and they were used as the indicators of social status. The choice of educa- tion was due to its simplicity as an index, importance in determining socioeconomic conditions, and, finally, sta- bility over time. Educational level was categorized into three groups, taking into account the effect of changes in the education system over time. A study on the defi- nition of the school system for the Brianza MONICA cohorts remarked that the schooling cut-off points stabi- lized to 8.5 and 12.5 years only for men born after 1952 and women born after 1960 [32]. Otherwise cut-off points were 5 and 8 years. As men born after 1952 or women born after 1960 were only the 3% of the studied population, educational levels were defined as follows: “High” included high school, college or university (>8 years), “Medium” secondary school (5-8 years) and “Low” primary school (<5 years). Marital Status was categorised into four classes: sub- jects married or cohabitating, single, separated or divorced and widowed. Due to the low number of sin- gle, separated, divorced and widowed subjects in the studied population (<5%) and according to previous reported association between marital status and CVD risk [33] we grouped marital status into two classes: subjects “married or cohabitating” and subjects with “other living arrangements” as single, separated or divorced and widowed. We ascertained that these people lived alone. Ascertainment of cardiovascular events Fatal and non-fatal major cardiovascular events were collected until December 2002, except for the ATENA cohort which concluded the follow-up in December 2001. Deaths were identified through an active collec- tion of information on subject vital status from munici- palities and death certificates from Local Health Districts. Causes of death with International Classifica- tion of Disease (ICD-IX) codes 410-414, identified a suspected coronary event and ICD-IX codes 430-432, 434-436, 437 a suspected stroke event. Non-fatal coron- ary and stroke events were identified in the regional Page 3 of 9 hospital discharge datasets, through deterministic or, when necessary (incomplete data), probabilistic record linkage between the name of the enrolled subjects and the diagnosis coded ICD-IX 410-411, 430-432, 434-436 as discharge diagnosis or ICD-IX 36.0-9, 38.12 as proce- dure codes. Re-screening of cohorts, phone and postal interviews or MONICA registers were also used to iden- tify suspected events in the cohort enrolled before the 1990s, when hospital discharge registration was inade- quate. Suspected events were validated according to the MONICA diagnostic criteria [28]. Case-fatality for inci- dent events was defined by death within 28 days from the onset of acute symptoms. Events validated as definite and possible myocardial infarctions (MIs), coronary revascularization, silent MIs and sudden cardiac deaths were included in the analysis as coronary end-points; definite stroke and carotid arter- ectomy as stroke end-points. Statistical analysis The relationship between cardiovascular risk factors, education and marital status was studied at baseline stratifying by gender. Mean values and proportions were age-adjusted using direct standardization method with the 1995 European population, age group 35-69 years. ANOVA for continuous variables and Chi-square test were used to assess statistical significance. Bonferroni correction for multiple comparisons was used. Hazard ratios (HR) and 95% confidence intervals for cardiovascular events or case-fatality in social categories were computed using Cox proportional hazard models adjusted for age, cohort and cardiovascular risk factors (systolic blood pressure, total cholesterol, HDL choles- terol, diabetes, smoking habits, antihypertensive medica- tion). Cox models for marital status were adjusted also for educational level. Reference groups for HR calcula- tion were “High education” for education classes and “Married or cohabitating” for marital status. The analy- sis was performed also stratifying by geographical area: North and Centre-South of Italy. No differences were found where not specified. Statistical analysis was car- ried out using the SAS software and 0.05 as significance level. Results About 70% of the population studied had a low or med- ium level of education and more than 80% was married or cohabitating, both for men and women (Table 1). In Tables 2 and 3 main cardiovascular risk factors are described by educational level and marital status, respectively in men and women. There was a signifi- cant relationship between educational level and several major cardiovascular risk factors. Men in the low edu- cation category had significantly lower levels of total