Study population and design. The participants of this study were from the cohort “CDC de Canarias” (CDC is the acronym for Cardiovascular, Diabetes, Cancer), which enrolled randomly selected adult individuals from the general population of the Canary Islands, in Spain, between 2000 and 2005. The cohort (n = 6,729 subjects) constituted a representative sample of the population aged eighteen to seventy-five years at the time of recruitment.
The design and methods used in the “CDC de Canarias” cohort have been described previously24 and their previous results with resistin have been published.4,5,6 The study was approved by the Ethics and Medicines Committee of the Hospital Universitario Nuestra Señora de Candelaria (HUNSC). The participation rate was 70%. All research was performed in accordance with the Declaration of Helsinki and relevant guidelines or regulations, and the informed consent was obtained from all participants or their legal guardians.
Exposure factors. Each person was interviewed about their personal and family health and lifestyle history (diet, physical activity, smoking, education, family income and living conditions). In addition, a physical examination was performed, which analyzed blood pressure and body mass index (BMI, categorized as normal [< 25 Kg/m2], overweight [25–29 Kg/m2] or obesity [≥ 30 Kg/m2]), and a venous blood sample was obtained after ten hours of fasting.
The samples were transferred daily to the HUNSC laboratory, after in situ centrifugation, for biochemical measurement within twenty-four hours; HDL-cholesterol (HDL) was measured with a Hitachi 917 auto analyzer and was categorized as low when it presented values <40 mg/dL in men or < 50 mg/dL in women. Resistin was measured in 6636 participants: Serum aliquots were frozen at -80°C until their use for the measurement of resistin by enzyme-immunoassay (ng/mL, Bio-Vendor®, Heidelberg, Germany; inter-assay variation coefficient = 7.72%; and intra- trial = 3.22%);5 quintiles (Q) were used to categorize it for the mortality analysis.
Dietary habits were obtained with a questionnaire of frequency and quantity of intake previously validated in the study population;25 the scale proposed by Trichopoulo26 was used and adherence quintiles were calculated to analyze adherence to the Mediterranean diet. The data on physical activity were obtained with the Spanish version of the Minnesota Questionnaire on Physical Activity in Leisure Time,27 and each activity described by the participants was assigned a value in metabolic equivalents (MET), according to the Compendium of Physical Activities by Ainsworth et al.28 This activity was measured using the quotient between moderate or intense physical activity (four or more MET) and total daily energy expenditure, as described by Bernstein et al.;29 the quintiles of this quotient were calculated taking quintile 1 (Q1) as sedentary.
The ICE (Income, Crowding, Education) model which had been validated in this population30 was used to measure the social class of the participants. The ICE produces a numerical scale with a range of values between four and twenty-one, where the higher the social class, the higher its value is; their quintiles were calculated for the mortality analysis.
The participant's declaration of being diabetic and receiving antidiabetic treatment was accepted as diabetes for the purposes of the study; otherwise, a fasting blood glucose level of ≥ 126 mg/dL was required, corroborated in a second analysis by his family doctor. Hypertension was recorded when the participant declared that they had the disease and was receiving antihypertensive treatment, or if the participants did not know they had hypertension but the mean of two blood pressure readings was ≥ 140 mmHg for systolic or ≥ 90 mmHg for diastolic blood pressure. Dyslipidemia was recorded when there was a previous diagnosis and the participant was receiving treatment, or when he or she had fasting serum levels ≥ 240 mg/dL of total cholesterol. Participants who declared that they smoked at least one cigarette per day were considered smokers. Alcohol consumption was classified as abstemious if the declaration was less than 1.5 g/day, moderate if the intake was between 1.5 and 30 g/day and high if the consumption was greater than 30 g/day.
Acute coronary syndrome cases were recorded when the participant declared that they had experienced an acute myocardial infarction or angina pectoris and this information was verified in the digital medical records of the patient in their public primary care center or hospital, with the permission of the participant.
Mortality registry. The identification of the participants who died during the follow-up of the cohort, as well as the cause and date of death, were obtained from the National Institute of Statistics, which in Spain collects the information obtained from all medical death certificates and uses the diagnostic codes of the 10th Revision of the International Classification of Diseases. In addition to total deaths, the following three large groups of causes were analyzed: oncological (C00-C97; D00-D09 and D37-D48), cardiovascular (I00-I09, including diabetes [E10-E14]) and a third group for all other causes.
Statistical analysis. The numerical variables were summarized with their mean (± SD) and the nominal variables with the absolute and relative frequency of their component categories. The baseline comparisons between the resistin quintiles were made with a chi-square test for trends.
The association of death with exposure to the factors studied was analyzed with Cox proportional hazards regression models, both for total mortality and for the three large groups of causes of death. The follow-up time of each participant was counted from the initial recruitment interview until December 31, 2019 or the date of death. Resistin was first included as a continuous variable, then transformed by taking its squared root to improve its approximation to the normal distribution and, finally, categorized into quintiles. The results are summarized with the hazard ratio between the categories of each factor and their 95% confidence interval (HR, 95% CI).
One model was adjusted by age and sex for resistin and another for each of the eleven exposure factors studied (hypertension, diabetes, acute coronary syndrome, BMI, smoking, alcohol, Mediterranean diet, social class, physical activity, dyslipidemia, and HDL cholesterol). The effect of resistin was then adjusted in eleven models, each of which included, in addition to age and sex, one of the exposure factors. Finally, this effect was analyzed using a maximally adjusted model that included all the factors; and one more model was adjusted including, in addition to these factors, the treatment with statins, antihypertensives, and antidiabetics.
The assumption of proportional hazards was tested by regression of the logarithm of the negative logarithm of the estimated survival function against the logarithm of time, with visual evaluation of the linearity in the graph between both variables, and checking that the product-terms between the factors were not significant when they were included in the models together with the follow-up time (log-transformed).
The variable with the highest number of missing values was social class (345 participants [5.2% of the cohort]), with missing values being less than 1% in the other factors studied. In a sensitivity analysis, social class was substituted for the individual's educational level, which is the main component of the ICE model (only fifteen participants did not have this data [0.2%]).
All hypothesis contrast tests used were two-tailed and p values less than 0.05 were considered statistically significant. The analyzes were performed with the computerized statistical data processing package SPSS®, version 24.0 in Spanish.