Study design and population study
This study was performed within the framework of the TLGS, which is an ongoing community-based cohort study being conducted on a representative sample of citizens of Tehran. The TLGS aims at determining the prevalence and incidence of non-communicable diseases and their risk factors and also intended to prevent them by developing healthier life styles. Further details for the TLGS have been described before [10]. Briefly, after the first baseline examination (1999-2001), participants were followed-up until 2011. For this study, 8,400 individuals aged ≥30 years, participants of phase IV of TLGS (2008-2011), were enrolled. Firstly, we excluded 497 individuals whose glycemic status was not differentiable for us. Secondly, we excluded 177 subjects with missing data on covariates, including body mass index (BMI), total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), systolic blood pressure (SBP), diastolic blood pressure (DBP), smoking status, and family history of CVD (considering overlap features between numbers). Finally, due to the lack of information on the outcome (CHD) assessment, 8 individuals were excluded and 7,718 participants remained for the analysis of the current study.
Clinical and laboratory measurements
Using structured questionnaires, a trained nurse collected data which included demographic data, past medical history, drug history, family history of CVD, education, smoking status, and levels of physical activity. Physical activity level was evaluated by the Modifiable Activity Questionnaire (MAQ), which assessed all three types of activities, including leisure time, job, and household activities in the past year [11]. Details of anthropometric and blood pressure (BP) measurements have been published previously [11]. BMI was calculated as weight divided by the square of the height (kg/m2). After 12-14 hours overnight fasting, blood samples were collected between 07:00 AM and 09:00 AM and analyzed the same day. Except for those who had on glucose-lowering medications, a standard oral glucose tolerance test with 75 gr glucose was done for all participants. Fasting plasma glucose (FPG) and 2-hour post-challenge plasma glucose (2h-PCPG) were measured by enzymatic colorimetric glucose oxidase method; both inter-and intra-assay coefficient of variations were < 2.2%. More details of laboratory measurements have been published elsewhere [11].
Definition of terms
Participants were categorized into different groups as follows: Normal fasting glucose (NFG)/normal glucose tolerance (NGT), FPG < 5.6 and 2h-PCPG <7.7 mmol/L; isolated impaired fasting glucose (iIFG), 5.6 ≤ FPG ˂ 7 and 2h-PCPG <7.7 mmol/L; isolated impaired glucose tolerance (iIGT), 7.7 ≤ 2h-PG ˂ 11.1 and FPG <5.6 mmol/L; combined IFG and IGT (IFG/IGT), 5.6 ≤ FPG ˂ 7 and 7.7 ≤ 2h-PCPG ˂ 11.1 mmol/L [12]. Moreover, in the present study, prediabetes status was defined as the presence of IFG or IGT. Finally, newly diagnosed diabetes mellitus (NDM) was defined as FPG ≥ 7.0 or 2h-PCPG ≥ 11.1 mmol/L among those participants were not on glucose lowering medications and known diabetes mellitus (KDM) as subjects with positive history of taking any glucose lowering medications. Hypercholesterolemia was defined as having TC≥ 5.2 mmol/L or use of lipid-lowering medications. Low HDL-C was defined as HDL-C< 1.036 mmol/L for men and <1.295 mmol/L for women, or taking lipid-lowering medications. Hypertension was considered as either SBP ≥140 mmHg or DBP ≥90 mmHg or the use of anti-hypertensive medications. Smoking status was defined as current, past, and never smoker. Education levels were classified as <6 years (reference group), 6–12 years, and >12 years. Low physical activity (inactive) was defined as not achieving a minimum score of 600 MET (metabolic equivalent task)-minutes per week [13]. Positive family history of premature CVD included any history of CHD/stroke in a male first-degree relative aged <55 years or female first-degree relative aged <65 years.
Definition of CHD
Details of the collection of outcome data have been reported elsewhere [11]. To summarize, each individual was under continuous surveillance for any medical outcome leading to hospitalization. As a part of the cohort data collection, a trained nurse called all participants annually and recorded any medical events experienced during the last year. Any reported event was followed-up by a home visit and collection of medical data from hospital by a trained physician. Collected data were evaluated by a consulting committee, the outcome committee, included a principal investigator, an internist, an endocrinologist, a cardiologist, an epidemiologist, and the physician who collected the outcome data and specific outcomes. Every confirmed event was considered as a non-communicable disease outcome based on ICD-10 criteria [11, 14]. In this study, CHD was selected from ICD-10 rubric I20-I25. CHD cases included [14-17]:
(1) Myocardial infarction (MI), included a) definite MI diagnosed by diagnostic electrocardiogram (ECG) and biomarkers (including CK, CK-MB, CK-MBm, troponin (cTn), and myoglobin), b) probable MI distinguished by positive ECG findings plus cardiac symptoms or signs and biomarkers showing negative or equivocal results.
(2) Cardiac procedure, defined as a) angiography proven CHD with a result of ≥ 50% stenosis in at least one major coronary vessel, b) history of angioplasty or bypass surgery.
(3) Unstable angina pectoris, who developed new cardiac symptoms or showed changing symptom patterns and positive ECG findings with normal biomarkers and admitted to coronary care unit (CCU).
Statistics
Baseline characteristics are presented as means ± standard deviations (SD), median (interquartile range) and number (frequency) as appropriate. ANOVA and Kruskal-Wallis tests were used for comparison of means and medians, respectively. Chi squared tests were applied for comparison of frequencies.
The crude and age-standardized prevalence (95% confidence interval: CI) were calculated for all glycemic status including NFG/NGT, iIFG, iIGT, IFG/IGT, NDM, and KDM. Regarding differences in the age distributions between the TLGS population from 2008 to 2011 and the Iranian census 2010 (supplementary Table 1), especially in the 30-39-year age-group and those aged ≥70 years, the age-standardized prevalence was reported, using the Iranian (Tehran province) census 2010.
We also examined the association of different glycemic status with prevalence of CHD, compared with NFG/NGT group (as reference). Using logistic regression analyses, odds ratios (ORs) for this association were calculated in 3 levels of adjustment: 1) without adjustment (crude OR); 2) age and sex adjustment; 3) full adjustment (adjusted for age, sex, BMI, hypercholesterolemia, low HDL-C, hypertension, family history of premature CVD, and smoking status).
Statistical analyses were done using STATA version 14. P-values < 0.05 were considered to be statistically significant.