Study design and participants
This cross-sectional study was conducted using data from Ravansar non-communicable diseases (RaNCD) cohort study. The RaNCD cohort study is a part of the Prospective Epidemiological Research Studies of Iranian Adult (PERSIAN) cohort. In the PERSIAN cohort, all 19 cohort sites (covering a representative sample of different Iranian ethnicities) used the same questionnaire and aimed to follow up all participants for the next 15 years. Further information is available at http://persiancohort.com. Ravansar is a district with a population of about 50,000 people, located in western Iran and in Kermanshah province. The number of participants in the baseline phase of the RaNCD was 10,000 adults, who all of whom were permanent residents of Ravansar. Details of the RaNCD methodology has been described elsewhere .
Inclusion and exclusion criteria
All subjects in the initial phase of RaNCD entered the present study. According to the objectives of the present study, subjects with cancer (n=85), renal failure (n=64), kidney stones (n= 1794), pregnant woman (n=138) and cases with missed information (n=557) were excluded from the study, finally 7362 subjects remained (Figure 1).
All interviews were conducted by trained and face-to-face individuals at the RaNCD cohort Study Center. Demographic information including age, sex, smoking and history of chronic diseases were recorded online in an electronic data collection form. Biochemical parameters, anthropometric indices and blood pressure were measured according to the PERSIAN cohort protocol.
Physical activity measured using metabolic equivalent rates (METs) of self-reported daily activities of participants of PERSIAN cohort using the questionnaire, including 22 questions about their sport, work, and leisure- related activities on an average weekday. The questionnaire information was extracted and used based on Met/ hour per week. .
Blood pressure measurements
Blood pressure was measured using a manual sphygmomanometer (Riester) from both arms, sitting position and after 10 minutes of rest, and its mean was reported. Hypertension was defined as subjects with systolic blood pressure (SBP) ≥ 140 and diastolic blood pressure (DBP)≥ 90 or current use of medication for hypertension .
Body weight was measured using Bio-Impedance Analyzer (BIA) model of (Inbody 770, Inbody Co, Seoul, Korea) with a precision of 0.5 kg. Other anthropometric measurements including body fat mass (BFM), percent body fat (PBF), skeletal muscle mass (SLM) and visceral fat area (VFA) were also measured with BIA. The height of the participants was measured with BSM 370 (Biospace Co, Seoul, Korea) with a precision of 0.1 cm. BMI was calculated weight (kg) divided by the square of height (m). WC was measured with a flexible measuring tape at a level midway between the lower rib margin and the iliac crest to the nearest 0.5 cm. VAI was measured by the following formula :
The blood samples were collected after 8- 12 hours fasting, to measure biochemical markers including lipid profile (TG, LDL-C, HDL-C, Total cholesterol) and fasting blood sugar (FBS) and Liver enzymes including Alkaline phosphatase (ALP), Aspartate transaminase (AST), Alanine aminotransferase (ALT), Gamma-glutamyl transferase (GGT). AIP was calculated by using the following formula: log10 (TG/HDL-C) ; and can be classified based on the values obtained: −0.3 to 0.1 for low risk, 0.1 to 0.24 for moderate, and 0.24 < for high risk of CVDs . Dyslipidemia was defined as LDL-C ≥ 160 mg/dL and/or total cholesterol ≥ 240 mg/dl and/ or HDL- C < 40 mg/dl and/or TG ≥ 200 mg/dl and/or having a history of medication for this condition . The MetS was defined according to International Diabetes Federation (IDF) criteria .
Definition of outcome
Participants who had at least one of the following condition were considered as patients with CVDs: a history of ischemic heart disease (IHD), heart failure and angina, stroke, Myocardial Infarction (MI) and/or current use of medication for CVDs.
Data analysis was performed using Stata version 14.1 software (Stata Corp, College Station, TX, USA). In descriptive reports, quantitative variables are presented as mean± standard deviation and qualitative variables as frequency (percentage). We compared baseline characteristics of studied participants by Chi-square and T-test between CVDs and non-CVDs groups. We used one-way ANOVA test to compare the variables in AIP and VAI tertiles. According to the binary outcome (CVDs), we used simple and multiple logistic regression models to assess the association between AIP and VAI with CVD, variables with p-value<0.2 in univariable analysis were entered into multivariable logistic model. The crude and adjusted odds ratios with 95% confidence interval were reported. The P- value < 0.05 was considered to be statistically significant in all statistical tests.