The present study was a case-control study conducted in Wuhan, China, during the period of March 2013 to December 2017. The study population consisted of 2141 MetS cases and 2141 healthy controls, which were 1:1 matched by age (±2 years) and sex. All participants were aged 18 years or older, consecutively recruited from the general population undergoing a routine health checkup in the Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology. Patients with clinical significant neurological, endocrinological or other systemic diseases, as well as acute illness and chronic inflammatory or infective diseases were excluded from the study. All the participants enrolled were of Chinese Han ethnicity. All subjects gave their informed consent for inclusion before they participated in the study. The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Ethics Committee of Tongji Medical College.
Definition of MetS
The definition of MetS was based on the harmonized definition for MetS in 2009 . To be considered as a case of MetS, participants had to meet at least three of the following criteria: 1. Abdominal obesity: waist circumference ≥ 85 cm in men and ≥ 80 cm in women; 2. Hypertriglyceridemia: ≥ 150 mg/dL; 3. Low levels of HDL cholesterol: < 40 mg/dL in men and < 50 mg/dL in women; 4. High blood pressure: ≥ 130/85 mmHg and/or use of antihypertensive medication; 5. High fasting glucose: ≥ 100 mg/dL and/or current use of antidiabetic medication and/or self-reported history of diabetes. The controls had zero to two components of MetS which were mentioned above.
Demographics, health status, and lifestyle data were obtained from the questionnaires, including sex, age, education level, history of disease (diabetes, hypertension and hyperlipemia), family history of diabetes, physical activity, current smoking status, and current alcohol drinking status. Education level was classified as none or elementary school, middle school, and high school or college. Physical activity was classified as at least once/week or no. Current smoking status was classified as yes (at least one cigarette per day over the previous 6 months) or no. Current alcohol drinking status was classified as yes (drink alcohol beverage more than once a week over the previous 6 months) or no. Anthropometric data including height (m), mass (kg), waist circumference and blood pressure were measured with standardized techniques by trained and certified technicians. BMI (body mass index) was calculated as mass divided by the square of height (kg/m2). Waist circumference was obtained at the mid-point between the lowest rib and the iliac crest to the nearest 0.1 cm, after inhalation and exhalation. Hip circumference was measured at the outermost points of the greater trochanters. The ratio of waist-to-hip circumference was used as an index of fat distribution. Blood pressure was measured at rest in the seated position using a standardized automated sphygmomanometer after 5 minutes of rest, and repeated in both arms.
Blood samples were collected in all participants after an overnight fast of at least 10 hours. Details of measurement of fasting plasma glucose, fasting plasma insulin, total cholesterol, triglyceride, HDL cholesterol, low-density lipoprotein (LDL) cholesterol and calculation of homeostasis model assessment of insulin resistance (HOMA-IR) and HOMA of β-cell function (HOMA-β) have been described previously . Plasma malonaldehyde (MDA) was measured with an MDA assay kit (Jiancheng, Inc., Nanjing, China).
Measurement of plasma chromium concentrations
Plasma chromium concentrations were measured in the Ministry of Education Key Laboratory of Environment and Health and School of Public Health at Tongji Medical College of Huazhong University of Science and Technology, using inductively coupled plasma mass spectrometry (ICP-MS) (Agilent 7700 Series, Tokyo, Japan). Plasma samples were stored at -80 ℃. The case and control specimens were measured randomly in the daily measurement, with laboratory personnel blinded to the case–control status. For quality assurance, metals in standard reference materials were measured once in every 20 samples using certified reference material. The certified concentrations of human plasma controls (ClinChek no. 8883 and 8884) were 3.56 ± 0.89 μg/L and 11.1 ± 2.22 μg/L, respectively. The limit of detection (LOD) for chromium was 0.01 μg/L, and concentrations of plasma chromium levels below the LOD (0.7%) were imputed at LOD/√2. Quality control was performed (1 out of 20 samples), and the inter-assay and intra-assay coefficients of variation were <10% and <8%, respectively.
Descriptive statistics were calculated for all demographic and clinical characteristics of the study subjects, and summarized as numbers (percentages) for categorical data, mean ± standard deviations (SDs) for normally distributed data, and medians (interquartile ranges) for non-normally distributed data. Comparisons between MetS and controls were performed by t test or Mann-Whitney U test for continuous variables, and chi-square tests for categorical variables. In addition, subjects were divided into 6 groups according to their possession of 0, 1, 2, 3, 4 or 5 components of MetS. Multiple imputation based on 5 replications and a fully conditional specification method in SPSS was used to account for missing data.
For calculation of the odds ratio (OR) for MetS, plasma chromium concentration was categorized in quartiles according to the control group: category 1, <3.27 μg/L; category 2, 3.28-4.46 μg/L; category 3, 4.47-5.87 μg/L, and category 4, >5.88 μg/L. Conditional logistic regression was used to assess the association of MetS with plasma chromium concentrations. The ORs and 95% confidence intervals (CIs) of MetS were calculated between the quartiles of chromium using the lowest quartile as the reference category, and also by per 1 μg/L chromium as continuous variable. We considered three models with progressive degrees of adjustment: model 1 adjusted for age; model 2 additionally adjusted for education, current smoking status, current alcohol drinking status, physical activity and family history of diabetes; and model 3 further adjusted for BMI. Tests of linear trend across increasing chromium quartiles were conducted by assigning the median value to each quartile and treating it as a continuous variable. Furthermore, the ORs of the MetS components including high waist circumference, high triglycerides, low HDL cholesterol, high blood pressure, and high blood glucose were calculated using binary logistic regression.
To evaluate the consistency of the association between chromium and MetS by participant characteristics, additional analyses were run, stratifying age (<50, ≥50), sex, BMI (<24, ≥24), physical activity, current smoking status, and current drinking alcohol status. The interactions between these stratification variables and plasma chromium were tested by adding multiplicative terms into the multivariate logistic regression models; the likelihood ratio tests were conducted to examine the interactions.
Statistical analyses were performed with SPSS for Windows, version 24.0 (SPSS Inc., Chicago, Illinois). P values reported are two tailed, and values below 0.05 were considered statistically significant.