Relationship Between Thyroid Function and the Prevalence of Type 2 Diabetes Mellitus in Euthyroid Subjects

The Journal of Clinical Endocrinology & Metabolism, Feb 2017

Gu, Yeqing, Li, Huihui, Bao, Xue, Zhang, Qing, Liu, Li, Meng, Ge, Wu, Hongmei, Du, Huanmin, Shi, Hongbin, Xia, Yang, et al.

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Relationship Between Thyroid Function and the Prevalence of Type 2 Diabetes Mellitus in Euthyroid Subjects

J Clin Endocrinol Metab, February The Relationship Between Thyroid Function and the Prevalence of Type 2 Diabetes Mellitus in Euthyroid Subjects Yeqing Gu 2 Huihui Li 2 Xue Bao 2 Qing Zhang 0 Li Liu 0 Ge Meng 2 Hongmei Wu 2 Huanmin Du 2 Hongbin Shi 0 Yang Xia 2 Qian Su 2 Liyun Fang 2 Fei Yu 2 Huijun Yang 2 Bin Yu 2 Shaomei Sun 0 Xing Wang 0 Ming Zhou 0 Qiyu Jia 0 Qi Guo 1 Hong Chang 2 Guolin Wang 0 Guowei Huang 2 Kun Song 0 Kaijun Niu 0 2 0 Health Management Centre, Tianjin Medical University General Hospital , 300070 Tianjin , China 1 Department of Rehabilitation and Sports Medicine Tianjin Medical University , 300070 Tianjin , China 2 Nutritional Epidemiology Institute and School of Public Health Purpose: Thyroid hormones (THs) are primarily responsible for the regulation of energy balance and metabolism, suggesting that TH levels may contribute to the development of type 2 diabetes mellitus (T2DM). However, few studies have investigated the relationship between TH and T2DM in a general population. The aim of this study was to evaluate whether serum TH levels within the reference range are related to T2DM. Methods: A cross-sectional study (n = 15,296) was performed in Tianjin, China. Serum free triiodothyronine (FT3), free thyroxine (FT4), and thyroid-stimulating hormone (TSH) levels were measured by chemiluminescence immunoassay, and T2DM was defined according to the American Diabetes Association criteria. Multiple logistic regression models were used to assess the sexspecific relationships between FT3, FT4, FT3/FT4 ratios, and TSH quintiles and T2DM. Results: The prevalence of T2DM was 16.2% in males and 7.7% in females. In males, the multivariable-adjusted odds ratios (95% confidence interval) of T2DM for increasing quintiles of FT3, FT4, and FT3/FT4 ratios were 1.00, 0.75(0.63 to 0.89), 0.70(0.58 to 0.84), 0.63(0.52 to 0.76), 0.56 (0.46 to 0.68; P for trend , 0.0001); 1.00, 1.05(0.87 to 1.27), 1.16(0.96 to 1.40), 1.09(0.90 to 1.31), 1.29 (1.07 to 1.56; P for trend = 0.01); and 1.00, 0.69(0.58 to 0.83), 0.72(0.60 to 0.86), 0.59(0.48 to 0.71), and 0.55(0.46 to 0.66; P for trend , 0.0001), respectively. Similar results also were observed in females. In contrast, a strong negative correlation between TSH and T2DM was observed in males, but not in females. Conclusions: This study demonstrated that decreased FT3, FT3/FT4 ratios, and increased FT4 levels are independently related to a higher prevalence of T2DM in both males and females, and TSH is inversely related to T2DM in males only. (J Clin Endocrinol Metab 102: 434-442, 2017) - Tchronic endocrine disease, characterized by hyperype 2 diabetes mellitus (T2DM) is the most common glycemia resulting from impaired insulin secretion and/or insulin resistance ( 1 ). The long-term complications of T2DM can significantly increase the risks of cardiovascular disease (CVD) and cancer, among many other diseases, as well as significantly increase risk of mortality ( 2, 3 ). The global prevalence of diabetes mellitus is rapidly increasing due to an ageing population, urbanization and associated lifestyle changes. In 2013, an estimated 382 million people worldwide had diabetes mellitus, about 90 to 95% of whom had T2DM, and the Abbreviations: BMI, body mass index; BP, blood pressure; CI, confidence interval; CVD, cardiovascular disease; FT3, free triiodothyronine; FT4, free thyroxine; LDL, low-density lipoprotein; OR, odds ratio; SD, standard deviation; T2DM, type 2 diabetes mellitus; T3, triiodothyronine; T4, thyroxine;TC, total cholesterol; TG, triglyceride; TH, thyroid hormone; TSH, thyroid-stimulating hormone. number will increase to 592 million (8.8% of adults aged 20 to 79 years) by 2035 (1). In particular, the latest national survey suggests that China has become the global epicenter of the T2DM epidemic with more than 11.6% of the adult population (aged 18 years and over) suffering from diabetes mellitus ( 4 ). Clarifying the common pathophysiologic mechanisms of T2DM is a crucial step toward providing early prevention and treatment. Recently, increased interest has focused on the relationship between thyroid function and metabolic diseases, including T2DM ( 5 ). The thyroid function is primarily responsible for the regulation of energy balance and metabolism ( 6 ). Thyroid dysfunction increases muscle and adipose tissue insulin resistance ( 7 ) and decreases glucose transport in myocytes ( 8 ). Meanwhile, thyroid hormone (TH) stimulates the basal expressions of glucose transporters, which regulate the intracellular glucose uptake on the surface of myocytes ( 5 ). Moreover, recently studies have demonstrated that free triiodothyronine (FT3) regulates insulin secretion ( 9, 10 ). Because glucose metabolism and insulin secretion are most closely related to the pathogenesis of T2DM, it is hypothesized that TH is a useful predictive factor for developing T2DM. On the other hand, thyroidstimulating hormone (TSH) binds to receptors on epithelial cells in the thyroid gland, stimulating synthesis and secretion of TH by negative feedback inhibition (11). However, to date, few studies have evaluated the relationship between TH, TSH, and T2DM in the general population with euthyroid status. The aim of this study was to investigate whether serum TH concentrations within the reference range as well as TSH levels are related to the prevalence of T2DM among a large-scale adult population. Materials and Methods Participants A large prospective dynamic cohort study, called The Tianjin Chronic Low-Grade Systemic Inflammation and Health Cohort Study, was carried out in a general adult population living in Tianjin, China. The study was based on annual health examinations conducted in Tianjin Medical University General Hospital Health Management Center and focused on the relationship between chronic low-grade systemic inflammation and the health status. Participants who had received health examinations (including medical examinations such as blood tests, abdominal ultrasonography, etc.) and had completed questionnaires regarding their smoking and drinking habits and disease history over the course of January 2007 to December 2015 were recruited. Moreover, a detailed lifestyle questionnaire covering family income, marital status, employment status, educational level, physical activity, sleep habits, dietary habits, overall computer/mobile device usage time, television time, history of prior infections, and use of medicines, as well as physical performance tests were administered to randomly selected subjects from this population since May 2013. This cross-sectional study used data from the Tianjin Chronic Low-Grade Systemic Inflammation and Health Cohort Study ranging from 2013 to 2015. The participant selection process was described in Fig. 1. During the research period, there were 18,682 participants who had received at least 1 health examination including blood glucose, TH, and TSH tests agreed to participate and provided written informed consent for their data to be analyzed. We excluded those with a history of CVD (n = 1461) or cancer (n = 286). Moreover, participants who having a level exceeding the standard reference range of TH and/or TSH [FT3 ,3.5 pmol/L (n = 43) or .6.5 pmol/L (n = 237), free thyroxine (FT4) ,11.5 pmol/L (n = 113) or .22.7 pmol/L (n = 84), TSH ,0.55 mIU/L (n = 251) or .4.78 mIU/L (n = 938)] were excluded. Moreover, participants who had a history of thyroid disease, type 1 diabetes mellitus, or who had used antithyroid drugs were not included in the current study. Owing to these exclusions, the final crosssectional study population comprised 15,269 participants including 8970 males [mean age 6 standard deviation (SD): 48.1 6 10.6 years] and 6299 females (mean age 6 SD: 47.6 6 11.2 years). Assessment of T2DM Levels of fasting blood sugar were measured by glucose oxidase method. Blood samples for analysis of HbA1c were mixed with ethylenediaminetetraacetic acid (as an anticoagulant) before testing. HbA1c separation and quantification were performed using a high-performance liquid chromatography analyzer (HLC-723 G8; Tosoh, Tokyo, Japan) with intra- and interassay coefficients of variation of ,3%. To measure 2-hour serum glucose, subjects were given a standard 75-g glucose solution, and serum glucose was measured at 2 hours after administration during the oral glucose tolerance test. In undiagnosed participants, T2DM was defined as a fasting blood sugar level $126 mg/dl (7.0 mmol/L), oral glucose tolerance test $200 mg/dl (11.1 mmol/L), HbA1c $48 mmol/mol (6.5%), or a history of T2DM based on the American Diabetes Association 2013 criteria ( 12 ). FT3, FT4, and TSH measurements Serum FT3 and FT4 were measured by chemiluminescence immunoassay using ADVIA Centaur FT3 analyzer and ADVIA Centaur FT4 analyzer (Siemens Healthcare Diagnostics, New York, NY) and expressed as pmol/L. The measuring range of FT3 and FT4 were 0.3 to 30.8 pmol/L and 1.3 to 155 pmol/L, respectively. Serum TSH was measured by chemiluminescence immunoassay using ADVIA Centaur TSH3-Ultra analyzer (Siemens Healthcare Diagnostics) and expressed as mIU/L. The measuring range was 0.001 to 150 mIU/L. The reference ranges of FT3, FT4, and TSH were 3.70;6.93 pmol/L, 11.61;21.41 pmol/L, and 0.55;4.87 mIU/L, respectively. We divided participants into 5 categories (quintiles) according to the actual concentrations of FT3, FT4, and TSH. Assessment of other variables Blood pressure (BP) was measured twice in the right arm using an automatic device (Andon, Tianjin, China) after 5 minutes of rest in a seated position. The mean of these 2 measurements was taken as the BP value. Hypertension is defined as having a BP higher than 140/90 mm Hg (systolic BP/ covariance for continuous variables and multiple logistic regression analysis for proportional variables after adjustment for age. The prevalence of T2DM was used as dependent variables, and quintiles of FT3, FT4, and TSH concentrations were used as independent variables. The multiple logistic regression models were used to examine the relationships between quintiles of FT3, FT4, and TSH and the prevalence of T2DM with adjustment for the covariates: age, BMI, waist circumference, smoking status, drinking status, hypertension, hyperlipidemia, and family history of CVD, hypertension, hyperlipidemia, and diabetes. Because the previous studies suggested an important role of thyroxine (T4) to triiodothyronine (T3) conversion ( 15–17 ), we additionally assessed the relationship between the quintiles of FT3/FT4 ratios and the prevalence of T2DM. Odds ratios (ORs) with their corresponding 95% CIs were calculated. Furthermore, because certain medicines (such as nonsteroidal anti-inflammatory drug, estrogen, antiepileptic drugs, etc.) may affect thyroid function ( 18, 19 ), a sensitivity analysis was performed after excluding the subjects who reported taking these drugs. All P values for linear trends were calculated using the median value of quintiles of FT3, FT4, FT3/FT4 ratios, and TSH. All tests were 2-tailed and P , 0.05 was defined as statistically significant. Results The prevalence of T2DM is 16.2% (1449/8970) and 7.7% (488/6,99) in males and females, respectively. Among participants with T2DM, 482 participants [368 (25.4%) males and 114 (23.4%) females] reported that they take medications for diabetes. FT3 and FT4 levels were both significantly higher in males than in females [means (SD), in males: 5.5 (0.5) pmol/L, 16.8 (2.0) pmol/ L; in females: 5.0 (0.5) pmol/L, 15.7 (1.8) pmol/L, both P , 0.0001], whereas the TSH level was significantly lower in males than in females [means (SD), in males: 1.9 (0.8) mIU/L; in females: 2.3 (1.0) mIU/L, P , 0.0001]. Age-adjusted participant characteristics in relation to T2DM were presented in Table 1. Compared with participants without T2DM, those with T2DM tended to be older and to have higher BMI, waist circumference, TC, TG, systolic BP, diastolic BP, the proportion of family history of hyperlipidemia and diabetes, and lower highdensity lipoprotein (all P values , 0.01) in both males and females. However, there are also some differences between males and females. Compared with participants without T2DM, males with T2DM tended to have lower FT3 and FT3/FT4 ratios and higher FT4 levels (all P values , 0.05); and females with T2DM tended to have diastolic BP) or having a history of hypertension. As for lipids, triglycerides (TGs) and total cholesterol (TC) were measured by enzymatic methods. Low-density lipoprotein (LDL) was measured by the polyvinyl sulfuric acid precipitation method, and high-density lipoprotein was measured by the chemical precipitation method using appropriate kits on a Cobas 8000 analyzer (Roche, Mannheim, Germany). Hyperlipidemia was defined as TC $5.17 mmol/L, TG $1.7 mmol/L, LDL $3.37 mmol/L, or history of hyperlipidemia. Height and body weight were measured using a standard protocol, and body mass index (BMI) was calculated as weight/height2 (kg/m2). Waist circumference was measured at the umbilical level with subjects standing and breathing normally. Information on age, sex, and smoking and drinking status was obtained from a questionnaire survey. A detailed personal and family history of physical illness and current medications was noted from “yes” or “no” responses to relevant questions. Statistical analysis All statistical analyses were performed using the Statistical Analysis System 9.3 edition for Windows (SAS Institute Inc., Cary, NC). Because previous studies have reported that sexspecific difference was observed on the levels of TH, TSH, and the incident of T2DM ( 13, 14 ), we analyzed the relationships between TH, TSH, and T2DM by sex. Distributions of continuous variables were assessed for normality using the Kolmogorov-Smirnov (n . 2,000) or Shapiro-Wilk (n # 2,000) test. Because the distributions of all the continuous variables were not normal in the current study, the natural logarithm was applied to normalize the data before statistical analysis. The continuous covariates after the log transformation approached normal distribution. Descriptive data are presented as the geometric mean [95% confidence interval (CI)] for adjusted continuous variables and as percentages for categorical variables. For baseline characteristics analysis, the differences among T2DM categories were examined using analysis of No. of subjects Age (y) BMI (kg/m2) WC (cm) TC (mmol/L) LDL (mmol/L) HDL (mmol/L) TG (mmol/L) SBP (mmHg) DBP (mmHg) FT3 (pmol/L) FT4 (pmol/L) TSH (mIU/L) FT3/FT4 ratios Smoking status (%) Smoker Ex-smoker Nonsmoker Drinker (%) Everyday Sometime Ex-drinker Nondrinker Family history of diseases (%) CVD Hypertension Hyperlipidemia Diabetes aAnalysis of covariance or multiple logistic regression analysis. bGeometric mean (95% CI; all such values). higher LDL and FT4 levels and lower FT3/FT4 ratios (all P values , 0.01). No significant differences were observed among the TSH levels, proportion of current smokers, alcohol consumers and the proportion of those with a family history of CVD and hypertension (all P values . 0.05) in both males and females. The crude and adjusted relationship between FT3, FT4, TSH, and the prevalence of T2DM was indicated in Table 2. In males, the adjusted ORs (95% CI) of T2DM were related to the gradual increase of the FT3, FT4, FT3/FT4 ratios, and TSH concentrations as compared with participants who had the lowest concentrations and were as follows: FT3: 0.75 (0.63 to 0.89), 0.70 (0.58 to 0.84), 0.63 (0.52 to 0.76), and 0.56 (0.46 to 0.68; P for trend , 0.0001); FT4: 1.05 (0.87 to 1.27), 1.16 (0.96 to 1.40), 1.09 (0.90 to 1.31), and 1.29 (1.07 to 1.56; P for trend = 0.01); FT3/FT4 ratios: 0.69 (0.58 to 0.83), 0.72 (0.60 to 0.86), 0.59 (0.48 to 0.71), and 0.55 (0.46 to 0.66; P for trend , 0.0001); and TSH: 0.89 (0.74 to 1.08), 0.94 (0.78 to 1.13), 0.76 (0.63 to 0.92), and 0.80 (0.67 to 0.97; P for trend = 0.01). In females, the adjusted ORs between FT3, FT4, FT3/FT4 ratios, TSH, and the prevalence of T2DM were as follows: FT3: 1.00, 0.97 (0.72 to 1.30), 0.91 (0.67 to 1.22), 0.71 (0.52 to 0.96), 0.63 (0.46 to 0.86; P for trend , 0.01); FT4: 1.00, 0.81 (0.58 to 1.13), 1.15 (0.84 to 1.58), 1.12 (0.81 to 1.54), and 1.54 (1.14 to 2.08; P for trend , 0.0001); FT3/FT4 ratios: 1.00, 0.79 (0.59 to 1.05), 0.56 (0.41 to 0.76), 0.64 (0.47 to 0.85), and 0.57 (0.42 to 0.78; P for trend , 0.0001); and TSH: 1.00, 1.22 (0.91 to 1.66), 0.83 (0.60 to 1.15), 0.89 (0.65 to 1.22), and 0.82 (0.60 to 1.12; P for trend = 0.04). We further performed a sensitivity analysis after excluding the subjects who reported taking certain medicines (such as nonsteroidal anti-inflammatory drug, estrogen, antiepileptic drugs, etc.; n = 220). However, the relationship between TH, TSH and T2DM did not change. The adjusted OR (95% CI) of T2DM for increasing quintiles of TH and TSH for males were as follows: FT3: 1.00 (reference), 0.75 (0.63 to 0.89), 0.70 (0.58 to 0.84), 0.63 (0.53 to 0.76), and 0.56 (0.46 to 0.69; P for trend , 0.0001); FT4: 1.00 (reference), 1.05 (0.87 to 1.27), 1.14 (0.94 to 1.38), 1.09 (0.90 to 1.32), and 1.29 (1.07 to 1.57; P for trend = 0.01); FT3/FT4 ratios: 1.00 (reference), 0.70 (0.58 to 0.84), 0.73 (0.61 to 0.87), 0.59 (0.49 to 0.71), and 0.55 (0.46 to 0.67; P for trend aMultiple logistic regression analysis. bAdjusted ORs (95% CI; all such values). cAdjusted for age, BMI, waist circumference, smoking status, drinking status, hypertension, hyperlipidemia, and family history of cardiovascular diseases, hypertension, hyperlipidemia, and diabetes. Males FT3 concentration (pmol/L, range) Number of subjects Number of diabetes Crude Age- and BMI-adjusted Multiple adjustedc FT4 concentration (pmol/L, range) Number of subjects Number of diabetes Crude Age- and BMI-adjusted Multiple adjustedc FT3/FT4 ratios Number of subjects Number of diabetes Crude Age- and BMI-adjusted Multiple adjustedc TSH concentration (mIU/L, range) Number of subjects Number of diabetes Crude Age- and BMI-adjusted Multiple adjustedc Females FT3 concentration (pmol/L, range) Number of subjects Number of diabetes Crude Age- and BMI-adjusted Multiple adjustedc FT4 concentration (pmol/L, range) Number of subjects Number of diabetes Crude Age- and BMI-adjusted Multiple adjustedc FT3/FT4 ratios Number of subjects Number of diabetes Crude Age- and BMI-adjusted Multiple adjustedc TSH concentration (mIU/L, range) Number of subjects Number of diabetes Crude Age- and BMI-adjusted Multiple adjustedc Level 1 3.50 to 5.07 1822 430 Reference Reference Reference 11.50 to 15.08 1802 309 Reference Reference Reference 0.18 to 0.29 1795 385 Reference Reference Reference 0.55 to 1.22 1795 313 Reference Reference Reference 3.50 to 4.59 1298 112 Reference Reference Reference 11.50 to 14.08 1264 85 Reference Reference Reference 0.16 to 0.29 1261 136 Reference Reference Reference 0.55 to 1.42 1260 89 Reference Reference , 0.0001); and TSH: 1.00 (reference), 0.89 (0.74 to 1.08), 0.93 (0.77 to 1.12), 0.75 (0.62 to 0.91), and 0.80 (0.66 to 0.97; P for trend , 0.01). In females, the adjusted OR (95% CI) of T2DM for increasing quintiles of TH and TSH were as follows: FT3: 1.00 (reference), 0.95 (0.71 to 1.29), 0.87 (0.64 to 1.18), 0.70 (0.51 to 0.95), and 0.62 (0.45 to 0.86; P for trend , 0.001); FT4: 1.00 (reference), 0.88 (0.62 to 1.24), 1.21 (0.88 to 1.68), 1.20 (0.86 to 1.66), and 1.67 (1.23 to 2.28; P for trend , 0.0001); FT3/ FT4 ratios: 1.00 (reference), 0.77 (0.57 to 1.02), 0.52 (0.38 to 0.71), 0.61 (0.45 to 0.82), and 0.53 (0.39 to 0.72; P for trend , 0.0001); and TSH: 1.00 (reference), 1.17 (0.86 to 1.59), 0.83 (0.60 to 1.15), 0.83 (0.60 to 1.14), and 0.77 (0.56 to 1.06; P for trend = 0.02). Discussion The current study has assessed the relationships between TH, TSH, and T2DM in an adult population. The results suggest that, after adjustment for confounding factors in both males and females, a higher prevalence of T2DM has a negative correlation to FT3 and a positive correlation to FT4. Furthermore, a negative correlation was observed between TSH and T2DM in males, but not in females. To our knowledge, this study firstly demonstrated that TH levels within reference range are significantly related to the prevalence of T2DM. We adjusted for multiple potentially confounding factors in our analysis. This study suggests that numerous factors (age, sex, BMI, drinking, smoking status, family history of some diseases) are correlated with the prevalence of T2DM. Because studies have shown that serum TH and TSH levels are related to age ( 20 ) and BMI ( 21 ), we first adjusted for these 2 variables. Adjustment for age and BMI significantly affected the relationship between serum FT4 levels and T2DM in males, leading us to conclude that age and BMI are major confounding factors. We subsequently adjusted for waist circumference, smoking status, drinking status, hypertension, hyperlipidemia, TC, TG [influential factors on TH and TSH levels ( 22–24 )], and genetic factors, such as family history of CVD, hypertension, hyperlipidemia, and diabetes [influential factors on T2DM ( 25 )]. However, after these adjustments, serum FT3 levels had a more obvious correlation with T2DM in both males and females. Several studies have explored the relationship between TH, TSH, and insulin resistance or glucose levels. Four cross-sectional studies reported that serum FT4 was negatively related to insulin resistance, fasting insulin or the homoeostasis model assessment index for insulin resistance, whereas a positive relationship was found between TSH and insulin resistance ( 26–29 ). Two other cross-sectional and a small-scale case-control studies found a positive correlation among higher T3 (30), T3 to T4 ratio ( 31 ), FT3 and FT4 ( 32 ) levels, and high fasting glucose levels and insulin resistance. In contrast, a crosssectional study showed that FT3, FT3 to FT4 ratio, and TSH are significantly and negatively associated with HbA1c levels in patients with T2DM ( 33 ). Although the reasons for these discrepancies remain unclear, the differences in confounding factors, study setting, small sample sizes for some studies, use of T3 instead of FT3, and the difference of outcome indicators might partly explain the cause for conflicting results. On the other hand, to date, few studies have illustrated the relationship between TH, TSH, and T2DM in the general population. This study demonstrates that T2DM is negatively related to FT3 and positively related to FT4 in both males and females. Further studies are necessary to explore whether these results can also be observed in other adult populations. Our results showed a similar relationship between TH and T2DM in both males and females, but sex difference was observed in the relationship between TSH and T2DM. Still, detailed molecular mechanisms remain unclear, because sex hormones (such as estrogen, and testosterone, etc.) can regulate the thyroid function ( 34 ), and estrogen levels affect the development of T2DM ( 35 ). The difference in sex hormones may partly explain the sex-difference in the relationship between TSH and T2DM. However, because levels of sex hormones such as testosterone and estrogen were not measured in this study, further research is needed to explore this issue. In addition, because the sample size was smaller for females and the prevalence of T2DM was markedly lower in females (7.7%) than in males (16.2%), the precision and statistical power of the analysis may be lower for females. Further large-scale population studies are required to confirm the above findings. On the other hand, in males, the significance of the relationship between FT3 and T2DM started from the second quintile, but from the fourth quintile in females. Because FT3 concentrations on the fourth quintile in females are equivalent to the second quintile in males, it is speculated that the increased prevalence of T2DM depends on the concentrations of FT3 regardless of sex. Further studies are needed to clarify this hypothesis. Multiple putative mechanisms could explain the relationship between thyroid function and T2DM. On the 1 hand, T3 regulates hepatic gluconeogenesis and antagonize insulin action ( 36 ), even in the euthyroid state ( 28 ). T3 modulates mRNA and protein expression of the glucose transporter 4, adenosine monophosphate–activated protein kinase, and acetyl coenzyme A carboxylase in skeletal muscle ( 37 ). Furthermore, increases in plasma T3 levels impair the ability of insulin to suppress hepatic glucose production and to increase glucose uptake in muscle ( 38 ). Interestingly, even subtle increases in the levels of T3 or T4 within the physiological range have been shown to induce insulin resistance ( 39 ). On the other hand, inadequate insulin secretion is an early event in the natural history of T2DM ( 40 ). There is convincing evidence from independent research that T3 directly increases islet b-cell mass via thyroid hormone receptor a-dependent pathways ( 41 ). Moreover, insulin secretion from b-cells is potentially controlled by the truncated mitochondrial T3 receptor p43 ( 42 ). These changes have been associated with a decrease in specific glucose transporters, namely GLUT2 and Kir6.2, and may thus be more broadly mediated by the control of intracellular glucose availability, which may have implications for other actions of T3 ( 5 ). FT3 is also a powerful inducer of pancreatic acinar cell proliferation in rodents ( 43 ). FT3 promotes expression of important proteins involved in both glucose and lipid metabolism that may influence insulin secretion ( 44 ). Finally, an interaction between TSH and insulin sensitivity has been proposed by several studies ( 45 ). Nonetheless, no direct effect of insulin or insulin resistance on thyroid function in humans has yet been demonstrated. Interestingly, the current study has also found a strong and inverse link between the FT3/FT4 ratios and T2DM. It is known that TSH upregulates deiodinase expression and activity ( 46, 47 ). Higher peripheral deiodinase activity increases conversion of FT4 to FT3 ( 15, 16, 48 ). Thus, FT3/FT4 ratios can be considered an indicator of peripheral deiodinase activity. Because the inhibition of peripheral deiodinase activity lowers basal metabolic rate ( 48, 49 ), and basal metabolic rate is closely related to the pathogenesis of T2DM, it is possible that the FT3/FT4 ratios were inversely related to T2DM because of the regulation of basal metabolic rate by deiodinasemediated TH signaling ( 49 ). In contrast, 3 small-scale cross-sectional studies reported that the FT3/FT4 ratio positively correlates with the homeostasis model assessment for insulin resistance in obese adolescents with nonalcoholic fatty liver disease (n = 200) ( 15 ), with both waist circumference and BMI in obese women aged 18 to 68 years (n = 201) ( 17 ), and with nonalcoholic fatty liver disease in patients with euthyroidism or hypothyroidism (n = 115) ( 16 ). The differences in population and sample size may be the cause for the observational discrepancies between the aforementioned studies and the current study. Furthermore, a recent study suggested that as TSH levels increase, FT3/FT4 ratios increase until age 40, but this differential increase does not occur in older age groups ( 50 ). Based on this finding, we performed a stratified analysis to ascertain whether age (,40 years or $40 years) confounds the relationship between FT3/ FT4 ratios and T2DM. However, in the final multiple logistic regression model, similar results were observed in subjects from different age groups (P for interaction = 0.54 in males and 0.58 in females). Therefore, we speculated that although age mediates the TSH regulation of FT3/FT4 ratios, FT3/FT4 ratios are significantly related to T2DM independent of age. Further studies are needed to explore the potential mechanisms underlying this association. The current study has several limitations. Firstly, this is a cross-sectional study, which is impossible to infer causality. Further cohort studies and intervention trials should be undertaken to establish a causal relationship between TH and T2DM. However, the present large-scale crosssectional study supports the important hypothesis that TH levels even within the euthyroid range, may contribute to the development of T2DM in the general population. Secondly, because this population-based study was carried out among apparently healthy adult population, and only euthyroid subjects were included in the final analysis, only 1 serum TH test and 1 TSH test were measured in this study. Therefore, further high-quality research is necessary to confirm these results. Thirdly, although we adjusted for a considerable number of potentially confounding factors, we cannot exclude the possibility that T2DM is affected by other lifestyle variables including supplementation of iodine, which is intrinsically related to TH levels. Thus, a well-designed randomized controlled trial is required to verify these results. Finally, although the participants with thyroid disease were excluded, serum thyroperoxidase antibodies levels were not routinely checked in the general population. Therefore, we cannot fully exclude the possibility that the relationship between the categories of TH, TSH, and T2DM is affected by these patients with positive thyroperoxidase antibodies. Conclusion Decreased FT3 and FT3/FT4 ratios and increased FT4 levels were independently related to the prevalence of T2DM among the adult population. A significantly negative relationship between TSH and T2DM was observed in males but not in females. Future studies should be aimed at clarifying the cause-and-effect relationship between TH and T2DM. Acknowledgments The authors gratefully acknowledge all the people that have made this study. Address all correspondence and requests for reprints to: Kaijun Niu, Nutritional Epidemiology Institute and School of Public Health, Tianjin Medical University, 22 Qixiangtai Road, Heping District, Tianjin 300070, China. E-mail: nkj0809@ gmail.com or . This study was supported by grants from the National Natural Science Foundation of China (No. 81302422, 81673166, 81372118 and 81372467), the key technologies R&D program of Tianjin (Key Project: No. 11ZCGYSY05700, 12ZCZDSY20400, 13ZCZDSY20200, and 15YFYZSY00020), the National Science and Technology Support Program (No. 2012BAI02B02), 2012 and 2016 Chinese Nutrition Society (CNS) Nutrition Research Foundation—DSM Research Fund (No. 2014-071 and 2016-046), the Technologies development program of Beichen District of Tianjin (No. bcws2013-21 and bcws2014-05), the technologies project of Tianjin Binhai New Area (No. 2013-02-04 and 2013-02-06), the Science Foundation of Tianjin Medical University (No. 2010KY28 and 2013KYQ24), the Key Laboratory of Public Health Safety (Fudan University), Ministry of Education (No. GW2014-5), and the National Training Programs of Innovation and Entrepreneurship for Undergraduates (No. 201510062013), China. 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Gu, Yeqing, Li, Huihui, Bao, Xue, Zhang, Qing, Liu, Li, Meng, Ge, Wu, Hongmei, Du, Huanmin, Shi, Hongbin, Xia, Yang, Su, Qian, Fang, Liyun, Yu, Fei, Yang, Huijun, Yu, Bin, Sun, Shaomei, Wang, Xing, Zhou, Ming, Jia, Qiyu, Guo, Qi, Chang, Hong, Wang, Guolin, Huang, Guowei, Song, Kun, Niu, Kaijun. Relationship Between Thyroid Function and the Prevalence of Type 2 Diabetes Mellitus in Euthyroid Subjects, The Journal of Clinical Endocrinology & Metabolism, 2017, 434-442, DOI: 10.1210/jc.2016-2965