The participants belong to the Chinese National Twin Registry (CNTR), the first and largest population-based twin registry in China described in detail elsewhere (26).
The analyses in this paper were based on a follow-up survey held from April to December 2013 among 1147 participants. The subjects were adult twins from four provinces covering 9 cities in Shandong, Zhejiang, Jiangsu and Sichuan province who completed an in-person questionnaire interview, a physical examination and a fasting blood biochemical test.
Pregnant female twins were excluded from participation. Twins were excluded from analyses if: (1) with a definitive diagnosis of medical diseases such as alimentary tract tumor, cardiovascular heart disease, stroke and kidney disease; (2) treated with weight-lowering pharmacological agents. At last, a total of 1113 individuals (541 completed twin pairs and 31 individuals) were eligible for this study.
Determination of zygosity was based on the information from questionnaires during the baseline investigation. Twins of different genders were directly classified as DZ. For twins of the same gender, a model was built according to age, gender and ‘whether they were as alike as two peas in a pod’. The model has been validated using DNA genotyping and found to be >90% accurate (27). All participants provided their written informed consent and Biomedical Ethics Committee at Peking University, Beijing, China approved the study protocol.
Clinical and Biochemical Data Collection
Data were collected with standardized computer-assisted personal interviews and medical examinations by trained staff. Information on demographic characteristics, medical history, and lifestyle factors were recorded, including questions on tobacco smoking (never, former, current), alcohol drinking (never, former, current) and exercise activities. Participants’ exercise activities on occupation, transportation, daily life and leisure time were assigned a metabolic equivalent task (MET) value, using the Compendium of Physical Activities by Ainsworth et al.(28).
In addition, each participant’s blood pressure, height, weight and percent body fat (PBF) were measured. Blood pressure was calculated as the mean of the second and third measurement out of three consecutive measurements. Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared. Height was measured to the nearest 0.1 cm on a portable stadiometer while weight was measured to the nearest 0.1 kilograms using a digital balance (Body Composition Analyzer/Scale, TANITA, Tokyo, Japan). Waist circumference was measured three times at the level of the umbilicus to the nearest centimeter and the mean value was used in the analyses. PBF was determined by bioelectrical impedance (Body Composition Analyzer/Scale, TANITA).
Venous blood samples were collected, and serum total cholesterol (TC) and triglycerides (TG) were measured by the enzymatic colorimetric method (Roche, Basel, Switzerland). Direct methods were applied to assess high density lipoprotein (HDL) cholesterol and low density lipoprotein (LDL) cholesterol (Roche, Basel, Switzerland). A modified hexokinase enzymatic method was used to detect glucose (Glu) (Roche, Basel, Switzerland), and serum insulin was measured by chemiluminescence immunoassay (CLIA) on the ADVIA Centaur immunoassay system. Insulin resistance was estimated according to homeostasis model assessment (HOMA-IR): HOMA-IR = [fasting glucose (mmol/l) × insulin (U/ml)]/22.5. Serum high-sensitivity CRP (hsCRP) was measured using a high-sensitivity immunoturbidimetric method (CRP [Latex] HS, Roche, Mannheim, Germany) on a Hitachi auto-analyzer (Roche Diagnostics, Mannheim, Germany). To minimize the effects of assay variability, samples from each twin pair were analyzed using the same assay.
Definition of the Phenotypes
We considered four components of the metabolic syndrome: 1) systolic BP ≥130 mmHg or diastolic BP ≥85 mmHg or self-reported hypertension or using antihypertensive drugs; 2) serum fasting glucose ≥5.6 mmol/L or self-reported diabetes or intake of antidiabetic medication; 3) HDL cholesterol <1.0 mmol/L for men and <1.3 mmol/L for women or using lipid-lowing drugs; and 4) triglycerides ≥1.7 mmol/L or using lipid-lowing drugs.. Individuals with waist circumference ≥90 cm (men) and 85 cm (women) were considered obese(29). According to the NCEP-ATP III criteria(30), participants with ≤1 abnormal component excluding waist circumference were defined as metabolically healthy (MH), with the remaining defined as metabolically unhealthy (MU). Status of metabolic health and obesity categories were combined to create the four phenotypes: metabolically healthy non-obesity (MHNO), metabolically healthy obesity (MHO), metabolically unhealthy non- obesity (MUNO), metabolically unhealthy obesity (MUO).
Data are presented as mean ± SD or median (first quartile (Q1) – third quartile (Q3)) for continuous variables and absolute and relative frequencies for categorical variables. We compared epidemiological, physical and biochemical characteristics between MHO and MUO twins as well as MHNO and MUNO twins. P values were corrected for the correlation between co-twins using generalized estimating equations.
Mixed-effect linear regression models with a random intercept for each twin pair to account for twin clustering were performed to examine the relationship of serum HOMA-IR and hsCRP levels with metabolic status (MH as reference group), number of MetS components, and the combined obesity-metabolic categories (MHNO as reference group),with adjustment for potential covariates. The first model was adjusted for age, sex, place, and zygosity; the second model was additionally adjusted for lifestyle factors (smoking, drinking, and MET level), obesity indicators (BMI, PBF, WHR) were further adjusted in the final model.
To investigate whether these associations were confounded by shared genetic and environmental factors, we applied co-twin regression analyses within twin pairs stratified by zygosity. The within-pair approach automatically takes into account shared familial and environmental influences. Fixed effect models were used to estimate the relation of serum HOMA-IR and hsCRP levels with metabolic status (MH as reference group), number of MetS components and the combined obesity-metabolic categories (MHNO as reference group) separately for DZ and MZ twins adjusted for lifestyle factors (smoking, drinking, and physical activity) and obesity indicators (BMI, PBF, WHR).
All the serum metabolites were handled after logarithmic transformation in the regression analyses. Robust standard error and confidence intervals for estimates have been produced. All the statistical analyses were performed with Stata statistical software (release 12.0; Stata Corporation, College Station, TX). P-values are two-sided, and statistical signiﬁcance was assumed at P<0.05.