Study design and population
The China Cardiometabolic Disease and Cancer Cohort (4C) Study is a population-based, multicenter, prospective cohort study. The study design of the 4C Study has been described in detail previously [5-6]. During 2011 to 2012, 193846 adults aged ≥ 40 years were recruited from 20 different communities from various geographic regions in China to represent the general population. During 2014 to 2016, all participants were invited to attend an in-person visit, and 170240 participants (87.8%) were successfully followed up. According to standardized protocols, a comprehensive set of questionnaires, clinical measurements, oral glucose tolerance tests (OGTTs), and laboratory examinations were carried out at baseline and follow-up visits. In this study, 133572 participants who had complete baseline information on diabetes, hypertension, and dyslipidemia, were free from CVD at baseline, and had complete ascertainment of CVD events during follow-up were included in the main analyses of the associations between these morbidities and incident CVD. To analyze the associations between cardiometabolic disorders and CVD events, we further excluded participants without complete information on glucose tolerance status, glycated hemoglobin A1c (HbA1c), blood pressures, and lipid profiles at baseline, and 129072 participants were included in the analyses. This study was approved by the Medical Ethics Committee of Ruijin Hospital, Shanghai Jiao Tong University. All study participants provided written informed consent.
According to a standard protocol, data collection was performed in local community clinics by trained study personnel at baseline and the follow-up visit. A questionnaire comprising information on demographic characteristics, lifestyle factors (including alcohol drinking and cigarette smoking) was administered by trained interviewers. Current alcohol drinker was defined as a person who drank alcohol regularly in the past 6 months. Smoking status were categorized as current, former, and never smoking. Education attainment was categorized as less than high school and high school or more. Physical activity was assessed by the International Physical Activity Questionnaire . The metabolic equivalent (MET) was calculated to estimate average weekly energy expenditure. Physical activity was categorized as active (≥600 MET-min per week), insufficiently active (>0 to <600 MET-min per week), and inactive (0 MET-min per week) .
Height and body weight were measured according to the standard protocol, and body mass index (BMI) was calculated as the weight in kilograms divided by height in meters squared. After at least a 5-minute quiet rest, every participant needed to measure blood pressure in a seated position for three times, and an automated electronic device (OMRON Model HEM-752 FUZZY) was used to measure blood pressure. Before the blood pressure measurement, alcohol, coffee, tea, smoking, and exercise should be avoided at least 30 minutes. At last, the 3 readings were averaged for the analysis.
After an overnight fast of at least 10 hours, all participants underwent an OGTT, and blood samples were collected at 0 and 2 hours. Fasting and 2-hour plasma glucose concentrations was measured locally within 2 hours after blood sample collection using the glucose oxidase or hexokinase method under a stringent quality control program. Finger capillary whole-blood samples were collected by the Hemoglobin Capillary Collection System (Bio-Rad Laboratories) and were stored at 2℃ to 8℃ and shipped to the central laboratory in the Shanghai Institute of Endocrine and Metabolic Diseases, which was certificated by the National Glycohemoglobin Standardization Program and the College of American Pathologists Laboratory Accreditation Program. HbA1c was measured by high-performance liquid chromatography using the VARIANT II Hemoglobin Testing System (Bio-Rad Laboratories) within 4 weeks after collection. The capillary HbA1c values and the venous values from whole-blood samples, which collected using ethylene diamine tetraacetic acid dipotassium tubes, were highly correlated (r = 0.99) in a validation subsample . Total cholesterol (TC), low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, and triglycerides (TG) were measured using an autoanalyzer (ARCHITECT ci16200 analyzer; Abbott Laboratories) at the central laboratory.
Diagnosis of Diabetes, hypertension and dyslipidemia
According to the American Diabetes Association 2010 criteria, diabetes was defined as fasting plasma glucose level of 126 mg/dL (7.0 mmol/L) or more, or OGTT-2 h plasma glucose level of 11.1 mmol/L or more, or HbA1c level of 6.5% or more, or by a self-reported previous diagnosis by health care professionals . Dyslipidemia was defined as LDL cholesterol ≥160 mg/dL (4.14 mmol/L), or HDL cholesterol <40 mg/dL (1.04 mmol/L), or triglycerides ≥200 mg/dL (2.26 mmol/L), or total cholesterol ≥240 mg/dL (6.22 mmol/L), or taking lipid-lowering medications . Hypertension was defined as systolic blood pressure (SBP) ≥140 mmHg, or diastolic blood pressure (DBP) ≥90 mmHg, or by a self-reported previous diagnosis by health care professionals .
Ascertainment of Cardiovascular Events
The outcome of this study was the composite of incident fatal or nonfatal CVD events, which included myocardial infarction, stroke, cardiovascular death, and hospitalized or treated heart failure. The ascertainment of cardiovascular events has been described in detail previously .
Continuous variables were presented as means with standard deviations (SDs) and categorical variables were presented as numbers with percentages. Person-time for every participant was calculated from the date of enrollment to the date of CVD diagnosis, death, or the end of follow-up. We first calculated the hazard ratios (HRs) and 95% confidence intervals (CIs) for CVD events using the Cox proportional hazards models in all participants, with multivariable adjustment for age, sex, education attainment (below high school, high school or above), BMI, physical activity (inactive, insufficiently active, active), smoking status (never, former, current), and drinking status (never, former, current). Next, we calculated all these above hazard ratios (HRs) and 95% confidence intervals (CIs) for CVD events among men and women, respectively. We then calculated the multivariable-adjusted HRs and 95% CIs for incident of CVD events for participants with cardiometabolic disorders, which were defined by measures of glucose, blood pressures, and lipids, in comparison with participants without the relative disorders. We also assessed the associations between cardiometabolic disorders and CVD events by sex stratifications. All statistical analyses were performed by using SAS software, version 9.4 (SAS Institute Inc). A two-sided P value <0.05 was considered statistically significant.