Association of mean platelet volume with incident type 2 diabetes mellitus risk: the Dongfeng–Tongji cohort study

The study design, methods and other detailed information of the Dongfeng–Tongji (DFTJ) cohort have been described elsewhere [20]. Briefly, a total of 27,009 retired employees of the Dongfeng Motor Corporation (DMC) were recruited in the cohort and completed baseline questionnaires, medical examinations, and provided baseline blood samples between September 2008 and June 2010, and were followed until October 2013. At the first follow-up survey in 2013, participants repeated the questionnaire interview, physical examinations, and blood collection. In total, 25,978 individuals (96.2% of those at baseline) completed the first follow-up until October 2013.

Of these 27,009 individuals, we excluded participants with myocardial infarction (MI), coronary heart diseases (CHD), stroke, tumor (n = 5258), DM (n = 3080), and who was using anti-coagulation drugs, aspirin and thrombolytic drugs (n = 2182), with abnormal platelet count (PLT) data (n = 13) as well as those with missing data on baseline MPV (n = 2467) resulting in a final study sample of 14,009 participants (5980 males and 8029 females with a mean age of 62.23 years). This study was approved by the Ethics and Human Subject committee of Tongji Medical College, Dongfeng General Hospital, and DMC. All study participants provided informed consents.

Trained interviewers administrated interview questionnaire face to face to collect baseline information including socio-demographic characteristics (age, sex, and education), lifestyle habits such as smoking status (current, former, never), alcohol drinking status (current, former, never), physical activity, occupational history, environmental exposures, and family and medical histories. Participants who smoke at least one cigarette per day for more than half a year were defined as current smokers. Those who drink alcohol at least one time per week for more than half a year were defined as current alcohol drinkers. Physical activity was considered as those who regularly exercised at least 20 min per time for more than 6 months. Physical examination was performed at DMC-owned hospitals by trained physicians, nurses and technicians. Standing height, body weight and waist circumference were measured in individuals with light indoor clothing and without shoes. B-scan ultrasonography of the liver, gall bladder, spleen, kidney, prostate (for males) and uterus, ovaries and fallopian tubes (for females) were conducted. Body mass index (BMI) was calculated as weight (kilogram) divided by height (meter) squared. Hypertension was defined as individuals with self-reported physician diagnosed hypertension, or blood pressure ≥ 140/90 mmHg, or current use of antihypertensive medication. Hyperlipidemia was defined as total cholesterol > 5.72 mmol/L or triglycerides > 1.70 mmol/L at medical examination, or a previous physician diagnosis of hyperlipidemia, or taking lipid lowering medication.

Blood samples were collected after an overnight fast. Platelet counts (PLT), MPV, white blood counts (WBC), total cholesterol, triglycerides, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), fasting blood glucose (FBG), and hemoglobin A1c (HbA1c) were determined at the DMC-owned hospital’s laboratory. MPV, PLT and WBC were measured using a fully automated analyzer CELL-DYN 3700 (Abbott Laboratories. Abbott Park, Illinois, USA). The level of FBG was determined by aeroset automatic analyzer (Abbott Laboratories. Abbott Park, Illinois, USA) and the HbA1c level was measured with high-performance liquid chromatography D-10 system (Bio-Rad Laboratories. Hercules, CA, USA). The serum lipids were measured with the architect ci8200 automatic analyzer (Abbott Laboratories. Abbott Park, Illinois, USA).

The diagnosis of DM was based on the American Diabetes Association (ADA) criteria [21] when meeting any of the following criteria: (1) self-reported of physician’s diagnosis of diabetes, (2) FBG level ≥ 7.0 mmol/L, (3) HbA1c level ≥ 6.5%, (4) usage of diabetes medication (insulin or oral hypoglycemic agent). The patients were those occurred after baseline survey but before the end of October 2013. A total of 997 incident patients were diagnosed during the follow-up period.

The baseline continuous variables are expressed in means (SD) and compared by Student’s t test or analysis of variation (ANOVA) unless otherwise specified. The Categorical variables are presented as numbers and percentages and compared by Chi square analysis or Fisher’s exact test. A two-sided P value of less than 0.05 was considered to indicate statistical significance.

Eligible participants were grouped according to quartiles of MPV, and the first quartile (Q1) was regarded as the reference group. Cox proportional hazards regression model was used to evaluate the relationship between MPV and incident DM risk adjusting for covariates including age, sex, smoking status, alcohol drinking status, education, physical activity (hours per week), BMI, examination center, hypertension, hyperlipidemia, family history of DM, WBC, and PLT.

Among women, number of children, menopausal status, hormone replacement therapy, and contraception status were additionally adjusted in the Cox regression models.

Stratified analyses were further performed by baseline characteristics (including age [< 60, ≥ 60 years], sex, BMI [< 25, ≥ 25 kg/m²], current smoking [yes, no], current drinking [yes, no], hypertension [yes, no], hyperlipidemia [yes, no], WBC [< 5.7E9/L, ≥ 5.7E9/L], and baseline FBG [< 5.6, ≥ 5.6 mmol/L]). Moreover, to analyze potential interactions between MPV and main characteristics, an interaction product term was included in the model.

Finally, in order to eliminate the reverse causality between MPV and DM, we conducted sensitivity analysis by exclusion of the incident diabetes patients diagnosed during the first 2 years of follow-up. To examine whether the potential association between MPV and DM risk was due to the FBG levels at baseline, we further adjusted for baseline FBG concentrations in the full adjustment model.

Baseline characteristics of the participants according to the quartile of MPV are summarized in Table 1.

During 60,761.74 person-years of follow up, we identified a total of 997 incident diabetes cases. Among the 14,009 study participants, 42.7% were men and mean age was 62.23 years old. Overall, there were 25.07, 24.93, 24.99 and 24.99% of participant with MPV level < 7.49 fL, 7.49 ≤ MPV < 8.43 fL and 8.43 fL ≤ MPV < 9.69 fL and MPV ≥ 9.69 fL, respectively. Compared with Q1, individuals with higher levels of MPV were more likely to be younger, females, with higher levels of triglycerides, HDL-cholesterol, and WBC, and with lower levels of total cholesterol, LDL-cholesterol, and PLT. Also, study participants with higher levels of MPV were less likely to be current smokers and current drinkers. The baseline characteristics according to the quartile of MPV in women and men respectively were presented in Additional file 1: Table S1.

As shown in Table 2, compared with study participants in Q1, the HRs and 95% CI of incident DM for individuals in Q2, Q3, and Q4 were 1.39 (1.11–1.75, P = 0.005), 1.14 (0.90–1.44, P = 0.277) and 1.39 (1.07–1.81, P = 0.014) respectively after adjustment for potential confounders. To reduce the possibility of reverse causality between MPV and DM events, sensitivity analyses were conducted by exclusion of the incident DM diagnosed during the first 2 years of follow-up (2009 and 2010, n = 249). After exclusion the positive association were even stronger (Q2 vs. Q1 HR: 1.44; 95% CI 1.13–1.84 and Q4 vs. Q1, HR: 1.51; 95% CI 1.14–1.99, P for trend = 0.028). In the full adjustment model we further adjusted the baseline FBG levels and the positive association did not alter materially (Q2 vs. Q1 HR: 1.39; 95% CI 1.10–1.74 and Q4 vs. Q1, HR: 1.33; 95% CI 1.02–1.73).

Stratified analyses were further performed by stratifying the baseline characteristics (including age [< 60, ≥ 60 years], sex, BMI [< 25, ≥ 25 kg/m²], current smoking [yes, no], current drinking [yes, no], hypertension [yes, no], hyperlipidemia [yes, no], WBC [< 5.7E9/L, ≥ 5.7E9/L], and baseline FBG [< 5.6, ≥ 5.6 mmol/L]). As Fig. 1 indicated, compared with the reference group, the HRs for study participants with MPV level ≥ 9.69 fL were more pronounced in females (HR: 1.56; 95% CI 1.07–2.53), non-current smokers (HR: 1.58; 95% CI 1.17–2.13) and individuals with baseline FPG level < 5.6 mmol/L (HR: 1.95; 95% CI 1.04–3.69) than their counterparts (P for interaction was 0.017, 0.013, and 0.021, respectively). In females, further adjustment for number of children, menopausal status, hormone replacement therapy, and contraception status obtained similar results. Females with MPV ≥ 9.80 fL had 92% increased incident risk of DM (95% CI 1.30–2.84) compared with those with MPV < 7.50 fL (P for trend = 0.002; see Additional file 2: Table S2). No interaction were found for MPV and age, BMI, current drinker, hypertension, hyperlipidemia, and WBC counts (all P for interaction > 0.05; see Additional file 3: Table S3).

Some limitations also need to be noted in the present study. Firstly, in the present study MPV was measured only once and might not represent the real MPV levels over time. Secondly, Diaz et al. [39] reported that a progressive increase in MPV with storage in EDTA measured at different time intervals up to 24 h. In the present study blood samples were stored in EDTA anticoagulation tube. However, MPV levels were measured immediately once blood samples were collected. Therefore, the influence from EDTA might be reduced to a small extent. Thirdly, we did not collect information on atrial fibrillation, obstructive sleep apnea, and seasonal changes which is reported to be associated with the MPV levels [40‐42]. Missing data on these factors could inevitably lead to potential bias in the evaluation of the HRs for DM. Fourthly, all the participants included in the present study were middle-aged and older Chinese, therefore the findings might not be generalized to younger population or other ethnicities.