Study on the relationship between insulin resistance and cardiovascular disease risk based on a coal mining population in Northern Shaanxi
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摘要:
目的 探索煤矿人群胰岛素抵抗(insulin resistance，IR)与心血管疾病风险之间的关系。 方法 数据来自2020―2023年建立的陕北煤矿工人队列的横断面研究，根据三酰甘油(triglyceride，TG)和空腹血糖(fasting plasma glucose，FPG)构建反映机体IR的三酰甘油-葡萄糖(triglycerides-glucose，TyG)指数和三酰甘油-葡萄糖-BMI (triglycerides glucose-BMI，TyG-BMI)，以性别、年龄、腰围、血压、胆固醇、是否吸烟、疾病史以及地域特征计算心血管疾病风险预测(prediction for ASCVD risk, PAR)。BMI分组：BMI＜18.5 kg/m2为体重过低组，18.5≤BMI≤24.0 kg/m2为正常组，24.0＜BMI＜28.0 kg/m2为超重组，BMI≥28.0 kg/m2为肥胖组。TyG和TyG-BMI均按其三分位分为T1、T2、T3组，以T1组作为参照组。采用logistic回归分析模型探索IR与心血管疾病风险之间的关系。 结果 共有4 359名研究对象纳入分析，调整混杂因素后，TyG每增加1个单位，高PAR增加27.6%(OR=1.276, 95% CI: 1.193~1.365)，TyG处于T3组人群高PAR是T1组的3.013倍(OR=3.013, 95% CI: 2.341~3.879)。敏感性分析和亚组分析进一步验证了TyG与PAR关联稳定。在正常组人群中，TyG每增加1个单位，高PAR增加29.1%(OR=1.291, 95% CI: 1.171~1.422)，TyG处于T3组人群高PAR的风险是T1组的3.658倍(OR=3.658, 95% CI: 2.550~5.247)；在超重组人群中，TyG每增加1个单位，高PAR增加56.9%(OR=1.569, 95% CI: 1.402~1.756)，TyG处于T3组人群的高PAR是T1组的5.610倍(OR=5.610, 95% CI: 3.753~8.386)；在肥胖组人群中，TyG每增加1个单位，高PAR增加47.5%(OR=1.475, 95% CI: 1.211~1.796)，TyG处于T3组人群高PAR是T1组的4.147倍(OR=4.147, 95% CI: 2.254~7.628)；在体重过低组人群中，TyG与PAR差异无统计学意义(P＞0.05)。 结论 在煤矿人群中，机体IR水平升高与心血管疾病风险的发展密切相关，BMI可能调节了两者之间的关系。在超重或肥胖早期，预防机体IR水平升高对于动脉粥样硬化性心血管病风险的防控可能具有积极作用。 -
关键词:
- 煤矿人群 /
- 三酰甘油-葡萄糖指数 /
- 胰岛素抵抗 /
- 肥胖
Abstract:Objective To investigate the relationship between insulin resistance (IR) and cardiovascular disease (CVD) risk in a population of miners. Methods The data were collected from a cross-sectional study of a group of coal miners in Northern Shaanxi Province between 2020 and 2023. TyG/TyG-BMI was developed to indicate insulin resistance in the body based on TG and FPG levels, while the Prediction for ASCVD Risk (PAR) was created to assess the risk of cardiovascular disease using factors including sex, age, waist circumference, blood pressure, cholesterol levels, smoking habits, medical history, and geographic location. BMI group: underweight group with BMI < 18.5 kg/m2, normal group with BMI ≤ 24.0 kg/m2, overweight group with BMI < 28.0 kg/m2 and obesity group with BMI≥28.0 kg/m2. The TyG and TyG-BMI variables were divided into three groups (T1, T2, and T3) according to their tertiles, with the T1 group serving as the reference group. To explore the association between insulin resistance and the risk of cardiovascular disease, a logistic regression model was employed. Results Totally 4 359 subjects were included. After adjusting for covariates, each unit increases in the TyG increased high PAR by 27.6%(OR=1.276, 95% CI: 1.193-1.365).The high PAR in the group with the TyG in T3 was 3.013 times of that in the group T1 (OR=3.013, 95% CI: 2.341-3.879). Sensitivity analysis and the subgroup analysis confirmed the stability of the association between the TyG and the PAR. In the general population, for every unit increase in the TyG as a continuous variable, the high PAR increased by 29.1%(OR=1.291, 95% CI: 1.171-1.422). As a categorical variable, the risk for high PAR in the T3 group was 3.658 times of that in the T1 group (OR=3.658, 95% CI: 2.550-5.247). In the hyperreconstituted population, for every unit increase in the TyG as a continuous variable, the risk for high PAR increase by 56.9% (OR=1.569, 95% CI: 1.402-1.756). As a categorical variable, the risk for high PAR in the T3 group was 5.610 times of that in the T1 group (OR=5.610, 95% CI: 3.753-8.386). In the obese population, for every unit increased in the TyG as a continuous variable, the high PAR increased by 47.5% (OR=1.475, 95% CI: 1.211-1.796). As a categorical variable, the risk for high PAR in the T3 group was 4.147 times of that in the T1 group (OR=4.147, 95% CI: 2.254-7.628). No statistically significant association existed between TyG and PAR in individuals with the obese population. Conclusions In coal mining populations, elevated levels of body insulin resistance strongly associates with an increased risk of developing cardiovascular disease. BMI may modulate this relationship. Early suppression of elevated levels of body insulin resistance, before the onset of overweight or obesity, may positively influence the prevention and control of atherosclerotic cardiovascular disease. -
Key words:
- Coal miners /
- Triglyceride-glucose index /
- Insulin resistance /
- Obesity
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图 1 TyG(A)/TyG-BMI(B)与PAR的剂量-反应关系
TyG：三酰甘油-葡萄糖；TyG-BMI：三酰甘油-葡萄糖-BMI；PAR：心血管疾病风险预测; TyG、TyG-BMI和PAR均作为连续变量，调整了性别、年龄、吸烟、饮酒、BMI(TyG-BMI中不调整BMI)、工龄、噪声。
Figure 1. Dose-response relationship between TyG(A)/TyG-BMI(B)and PARb
TyG: triglycerides-glucose; TyG-BMI: triglycerides-glucose-BMI; PAR: prediction for ASCVD risk; TyG, TyG-BMI, and PAR were used as continuous variables, adjusted for gender, age, smoking, drinking, BMI (not adjusted for BMI in TyG-BMI), seniority, and noise.
表 1 根据中国心血管疾病风险预测模型评估的不同风险状态的研究对象基本特征
Table 1. Basic characteristics of study subjects with different risk status as assessed by prediction for ASCVD risk in China project
变量Variable 合计 ①
Total ① (n=4 359)低PAR组 ①
Low-PAR group ① (n=3 423)高PAR组 ①
High-PAR group ① (n=936)Z/χ2值
valueP值
value性别Gender 17.48 ＜0.01 男Male 4 296(98.6) 3 360(98.2) 936(100.0) 女Female 63(1.4) 63(1.8) 0(0.0) 年龄组/岁Age group/years 761.86 ＜0.01 18~＜30 477(11.0) 461(13.5) 16(1.7) 30~＜40 2 476(56.8) 2 169(63.4) 307(32.8) 40~＜50 991(22.7) 642(18.7) 349(37.3) ≥50 415(9.5) 151(4.4) 264(28.2) 工龄/年Seniority/years 329.81 ＜0.01 ＜5 589(13.5) 566(16.5) 23(2.5) 5~＜10 452(10.4) 401(11.7) 51(5.4) 10~＜15 1 458(33.4) 1 225(35.8) 233(24.9) ≥15 1 860(42.7) 1 231(36.0) 629(67.2) 吸烟Smoking 139.35 ＜0.01 否No 2 024(46.4) 1 749(51.1) 275(29.4) 是Yes 2 335(53.6) 1 674(48.9) 661(70.6) 饮酒Drinking 9.98 ＜0.01 否No 2 585(59.3) 2 072(60.5) 513(54.8) 是Yes 1 774(40.7) 1 351(39.5) 423(45.2) 收缩压Systolic pressure/mmHg 124.0(114.0, 134.0) 124.0(115.0, 134.0) 122.0(113.0, 131.0) -4.25 ＜0.01 舒张压Diastolic pressure/mmHg 78.0(72.0, 86.0) 78.0(72.0, 86.0) 78.0(71.0, 85.0) -2.21 ＜0.05 腰围Waist circumference/cm 88.0(81.0, 94.0) 88.0(81.0, 94.0) 87.0(80.0, 94.0) -1.28 0.20 臀围Hip circumference/cm 98.0(94.0, 102.5) 98.0(94.0, 103.0) 98.0(94.0, 102.5) -0.16 0.87 BMI/(kg·m-2) 24.7(22.5, 27.1) 24.7(22.5, 27.1) 24.5(22.2, 26.8) -1.29 0.20 TC/(mmol·L-1) 4.4(3.9, 5.0) 4.4(3.9, 5.0) 4.4(3.9, 5.0) -0.47 0.64 TG/(mmol·L-1) 1.4(0.9, 2.2) 1.4(0.9, 2.2) 1.4(0.9, 2.1) -1.62 0.10 LDL-C/(mmol·L-1) 2.7(2.3, 3.2) 2.7(2.3, 3.2) 2.7(2.3, 3.2) -1.18 0.24 HDL-C/(mmol·L-1) 1.3(1.1, 1.5) 1.3(1.1, 1.5) 1.3(1.1, 1.5) -2.60 ＜0.01 FPG/(mmol·L-1) 4.5(4.1, 4.9) 4.5(4.1, 4.9) 4.5(4.1, 5.0) -1.70 0.09 TyG 8.8(8.7, 9.0) 8.8(8.7, 8.9) 8.9(8.8, 9.1) 11.57 ＜0.01 TyG-BMI 218.8(197.1, 240.5) 214.3(194.2, 236.2) 215.6(233.3, 256.3) 16.10 ＜0.01 粉尘浓度/(mg·m-3) Dust content/(mg·m-3) 4.78 0.09 ＜15 1 774(40.7) 1 422(41.5) 352(37.6) 15~＜30 1 911(43.8) 1 477(43.2) 434(46.4) ≥30 674(15.5) 524(15.3) 150(16.0) CO浓度/(mg·m-3) CO content/(mg·m-3) 1.31 0.52 ＜14.0 792(18.2) 632(18.5) 160(17.1) 14.0~＜27.5 1 404(32.2) 1 106(32.3) 298(31.8) ≥27.5 2 163(49.6) 1 685(49.2) 478(51.1) CO2浓度/(mg·m-3) CO2 content/(mg·m-3) 0.26 0.88 ＜9 750 948(21.8) 750(21.9) 198(21.2) 9 750~＜15 700 637(14.6) 500(14.6) 137(14.6) ≥15 700 2 774(63.6) 2 173(63.5) 601(64.2) NO浓度/(mg·m-3) NO content/(mg·m-3) 5.04 0.08 ＜0.10 319(7.3) 266(7.8) 53(5.7) 0.10~＜0.20 2 032(46.6) 1 594(46.6) 438(46.8) ≥0.20 2 008(46.1) 1 563(45.6) 445(47.5) NO2浓度/(mg·m-3) NO2 content/(mg·m-3) 5.97 0.05 ＜0.18 317(7.2) 241(7.1) 76(8.1) 0.18~＜0.33 513(11.8) 385(11.2) 128(13.7) ≥0.33 3 529(81.0) 2 797(81.7) 732(78.2) 噪声/[dB(A)] Noise/[dB(A)] 50.85 ＜0.01 ＜85 207(4.7) 169(4.9) 38(4.1) 85~＜90 443(10.2) 396(11.6) 47(5.0) 90~＜95 2 066(47.4) 1 583(46.2) 483(51.6) 95~＜100 1 377(31.6) 1 091(31.9) 286(30.5) ≥100 266(6.1) 184(5.4) 82(8.8) 注：TC，总胆固醇；TG，三酰甘油；LDL-C，低密度脂蛋白胆固醇；HDL-C，高密度脂蛋白胆固醇；FPG，空腹血糖；TyG，三酰甘油-葡萄糖。
①以人数(占比/%)或M(P25, P75)表示。
Note：TC, total cholesterol; TG, triglyceride; LDL-C, low density lipoprotein-cholesterol; HDL-C, high density lipid-cholesterol; FPG, fasting plasma glucose; TyG, triglyceride-glucose.
① Number of people (proportion/%) or M(P25, P75).
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表 2 三酰甘油-葡萄糖/三酰甘油-葡萄糖-BMI与高心血管疾病预测风险的关联
Table 2. Association of triglycerides-glucose/triglycerides-glucose-BMI with high prediction for ASCVD risk
变量Variable 模型1 Model 1 模型2 Model 2 模型3 Model 3 OR值value
(95% CI)P值
valueOR值value
(95% CI)P值
valueOR值value
(95% CI)P值
avalue三酰甘油-葡萄糖Triglycerides-glucose 连续变量Continuous variable 1.412(1.327~1.502) ＜0.01 1.268(1.193~1.347) ＜0.01 1.276(1.193~1.365) ＜0.01 T1 1.000 1.000 1.000 T2 1.717(1.350~2.183) ＜0.01 1.434(1.121~1.835) ＜0.01 1.369(1.057~1.773) ＜0.05 T3 4.665(3.717~5.854) ＜0.01 3.158(2.488~4.009) ＜0.01 3.013(2.341~3.879) ＜0.01 三酰甘油-葡萄糖-BMI Triglycerides-glucose-BMI 连续变量Continuous variable 1.011(1.010~1.012) ＜0.01 1.011(1.009~1.012) ＜0.01 1.011(1.010~1.012) ＜0.01 T1 1.000 1.000 1.000 T2 1.598(1.258~2.030) ＜0.01 1.572(1.236~1.998) ＜0.01 1.478(1.149~1.902) ＜0.05 T3 4.754(3.790~5.962) ＜0.01 4.626(3.684~5.809) ＜0.01 4.357(3.428~5.537) ＜0.01 注: 采用logistic回归分析，模型1调整了性别、年龄；模型2在模型1的基础上进一步调整吸烟、饮酒、BMI(三酰甘油-葡萄糖-BMI的模型2中不调整BMI)；模型3在模型2的基础上进一步调整工龄和噪声。
Note: analyses using logistic regression, Model 1 adjusted for gender, age; Model 2 further adjusts for smoking, drinking consumption, and BMI (BMI is not adjusted in model 2 for triglycerides-glucose-BMI) on top of Model 1; Model 3 further adjusts for seniority and noise on top of Model 2.
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表 3 TyG/TyG-BMI与心血管疾病预测风险的关联分析
Table 3. Association analysis between TyG/TyG-BMI and prediction for ASCVD risk
变量Variable 模型1 Model 1 模型2 Model 2 模型3 Model 3 β值value (95% CI) P值value β值value (95% CI) P值value β值value (95% CI) P值value TyG 0.343(0.250~0.436) ＜0.01 0.245(0.149~0.342) ＜0.01 0.247(0.134~0.361) ＜0.01 TyG-BMI 0.013(0.011~0.016) ＜0.01 0.013(0.010~0.015) ＜0.01 0.013(0.011~0.016) ＜0.01 注: 1. TyG：三酰甘油-葡萄糖；TyG-BMI：三酰甘油-葡萄糖-BMI。
2. 采用线性回归分析，PAR和TyG/TyG-BMI都作为连续变量。模型1调整了性别、年龄；模型2在模型1的基础上进一步调整吸烟、饮酒、BMI(TyG-BMI的模型2中不调整BMI)；模型3在模型2的基础上进一步调整工龄和噪声。
Note: 1. TyG：triglycerides-glucose；TyG-BMI: triglycerides-glucose-BMI.
2. Analyses using linear regression, PAR and TyG/TyG-BMI were continuous variables. Model 1 adjusted for gender, age; Model 2 further adjusts for smoking, drinking consumption, and BMI (BMI is not adjusted in model 2 for TyG-BMI) on top of model 1; Model 3 further adjusts for seniority and noise on top of Model 2.
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表 4 不同BMI状态下三酰甘油-葡萄糖和高心血管疾病风险预测的关联
Table 4. Association between triglycerides-glucose and high prediction for ASCVD risk in different BMI states
BMI/(kg·m-2) 模型1 Model 1 模型2 Model 2 模型3 Model 3 OR值value
(95% CI)P值
valueOR值value
(95% CI)P值
valueOR值value
(95% CI)P值
value体重过低组Underweight group 1.980(0.841~4.661) 0.12 2.232(0.832~5.988) 0.11 2.162(0.789~5.926) 0.13 T1 1.000 1.000 1.000 T2 0.594(0.086~4.124) 0.60 0.781(0.096~6.379) 0.82 0.702(0.081~6.071) 0.75 T3 2.721(0.484~15.296) 0.26 3.103(0.466~20.665) 0.24 2.821(0.405~19.665) 0.30 正常组Normal group 1.290(1.183~1.406) ＜0.01 1.282(1.175~1.399) ＜0.01 1.291(1.171~1.422) ＜0.01 T1 1.000 1.000 1.000 T2 1.451(1.012~2.080) 0.04 1.415(0.985~2.034) 0.06 1.377(0.946~2.005) 0.10 T3 3.849(2.741~5.403) ＜0.01 3.756(2.669~5.287) ＜0.01 3.658(2.550~5.247) ＜0.01 超重组Overweight group 1.512(1.363~1.677) ＜0.01 1.499(1.351~1.663) ＜0.01 1.569(1.402~1.756) ＜0.01 T1 1.000 1.000 1.000 T2 2.058(1.391~3.044) ＜0.01 2.011(1.358~2.978) ＜0.01 2.022(1.329~3.077) ＜0.01 T3 5.755(3.969~8.343) ＜0.01 5.579(3.842~8.101) ＜0.01 5.610(3.753~8.386) ＜0.01 肥胖组Obesity group 1.552(1.291~1.865) ＜0.01 1.521(1.265~1.830) ＜0.01 1.475(1.211~1.796) ＜0.01 T1 1.000 1.000 1.000 T2 1.986(1.077~3.664) ＜0.05 1.927(1.038~3.577) ＜0.05 1.633(0.864~3.086) 0.13 T3 5.083(2.841~9.095) ＜0.01 4.899(2.710~8.855) ＜0.01 4.147(2.254~7.628) ＜0.01 注: 采用logistic回归分析，模型1调整了性别、年龄；模型2在模型1的基础上进一步调整吸烟、饮酒、BMI(TyG-BMI的模型2中不调整BMI)；模型3在模型2的基础上进一步调整工龄和噪声。
Note: analyses using logistic regression, Model 1 adjusted for gender, age; Model 2 further adjusts for smoking, drinking consumption, and BMI (BMI is not adjusted in model 2 for TyG-BMI) on top of model 1; Model 3 further adjusted for seniority and noise on top of model 2.
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表 5 三酰甘油-葡萄糖/三酰甘油-葡萄糖-BMI与高心血管疾病风险预测的关联
Table 5. Association of triglycerides-glucose/triglycerides-glucose-BMI with high prediction for ASCVD risk
变量Variable 多重插补Multiple interpolation PAR以中位数分界PAR split by median OR值value
(95% CI)P值
valueOR值value
(95% CI)P值
value三酰甘油-葡萄糖Triglycerides-glucose 连续变量Continuous variable 1.283(1.207~1.364) ＜0.01 0.888(0.855~0.921) ＜0.01 T1 1.000 1.000 T2 1.468(1.146~1.880) ＜0.01 0.662(0.552~0.793) ＜0.01 T3 3.267(2.573~4.149) ＜0.01 1.310(1.086~1.580) ＜0.01 三酰甘油-葡萄糖-BMI Triglycerides-glucose-BMI 连续变量Continuous variable 1.011(1.010~1.012) ＜0.01 1.004(1.003~1.005) ＜0.01 T1 1.000 1.000 T2 1.591(1.251~2.023) ＜0.01 0.855(0.718~1.019) 0.08 T3 4.790(3.814~6.014) ＜0.01 2.276(1.913~2.709) ＜0.01 注: 采用多重插补法填补缺失协变量，补全协变量后进行分析，并调整性别、年龄、吸烟、饮酒、BMI(三酰甘油-葡萄糖-BMI中不调整BMI)、工龄、噪声。
Note: multiple interpolation was used to impute missing covariates, and analyses were performed after covariates were imputed. Adjusted for gender, age, smoking, drinking, BMI (no adjustment for BMI in triglycerides-glucose-BMI), seniority, and noise.
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表 6 BMI、噪声和三酰甘油-葡萄糖对心血管疾病风险预测的相乘交互作用
Table 6. Multiplied interaction of BMI、noise and triglycerides-glucose on prediction for ASCVD risk
变量Variable OR值value(95% CI) P值value 变量Variable OR值value (95% CI) P值value BMI 1.040(0.843~1.283) ＞0.05 噪声Noise 1.045(0.926~1.179) ＞0.05 TyG 0.966(0.654~1.428) ＞0.05 TyG 0.957(0.420~2.181) ＞0.05 BMI×TyG 0.989(0.974~1.004) ＞0.05 噪声×TyG Noise×TyG 0.996(0.987~1.005) ＞0.05
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表 7 三酰甘油-葡萄糖与心血管疾病风险预测关系的亚组分析
Table 7. Subgroup analysis of the relationship between triglycerides-glucose and prediction for ASCVD risk
亚组
Subgroup人数
Number of peopleOR值value
(95% CI)P值
value亚组
Subgroup人数
Number of peopleOR值value
(95% CI)P值
value年龄组/岁Age group/years BMI /(kg·m-2) 18~＜30 477 2.262(1.382~3.703) ＜0.01 体重过低组Underweight group 84 2.162(0.789~5.926) 0.13 30~＜40 2 476 1.329(1.190~1.483) ＜0.01 正常组Normal group 1 780 1.291(1.171~1.422) ＜0.01 40~＜50 991 1.116(1.001~1.245) 0.05 超重组Overweight group 1 708 1.569(1.402~1.756) ＜0.01 ≥50 415 1.153(0.984~1.352) 0.08 肥胖组Obesity group 787 1.475(1.211~1.796) ＜0.01 吸烟Smoking 饮酒Drinking 否No 2 024 0.936(0.888~0.988) ＜0.05 否No 2 585 0.947(0.905~0.990) ＜0.05 是Yes 2 335 0.949(0.903~0.996) ＜0.05 是Yes 1 774 0.932(0.867~1.001) 0.54 噪声/[dB(A)] Noise/[dB(A)] 工龄/年Seniority/years ＜85 207 1.075(0.790~1.463) 0.64 ＜5 589 1.511(1.209~1.888) ＜0.01 85~＜90 443 1.145(0.953~1.375) 0.15 5~＜10 452 1.170(0.998~1.371) 0.05 90~＜95 2 066 1.423(1.262~1.604) ＜0.01 10~＜15 1 458 0.996(0.864~1.147) 0.95 95~＜100 1 377 1.268(1.122~1.434) ＜0.01 ≥15 1 860 2.352(1.988~2.782) ＜0.01 ≥100 266 1.533(1.130~2.079) ＜0.01 注: 调整性别、年龄、吸烟、饮酒、BMI、工龄、噪声；在各亚组中，调整了除亚组变量以外的其他变量；三酰甘油-葡萄糖作为连续变量纳入亚组分析。
Note: adjusted for gender, age, smoking, drinking, BMI, seniority, noise; In each subgroup, adjusted for variables other than subgroup variables; Triglycerides-glucose was included as a continuous variable in the subgroup analyses.
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[1] 中国心血管健康与疾病报告编写组. 中国心血管健康与疾病报告2021概要[J]. 中国循环杂志, 2022, 37(6): 553-578. DOI: 10.3969/j.issn.1000-3614.2022.06.001.Chinese Cardiovascular Health and Disease Report Writing Group. Report on cardiovascular health and diseases in China 2021: an updated summary[J]. Chin Circ J, 2022, 37(6): 553-578. DOI: 10.3969/j.issn.1000-3614.2022.06.001. [2] 马丽媛, 王增武, 樊静, 等. 《中国心血管健康与疾病报告2022》要点解读[J]. 中国全科医学, 2023, 26(32): 3975-3994. DOI: 10.12114/j.issn.1007-9572.2023.0408.Ma LY, Wang ZW, Fan J, et al. Interpretation of report on cardiovascular health and diseases in China 2022[J]. Chin Gen Pract, 2023, 26(32): 3975-3994. DOI: 10.12114/j.issn.1007-9572.2023.0408. [3] 张丽梅. 山东省煤矿工人心血管疾病流行病学调查研究[D]. 济南: 山东大学, 2015.Zhang LM. Epidemiology study for angiocardiopathy among coal miners in Shandong Province[D]. Jinan: Shandong University, 2015. [4] 王博, 刘珺, 张晓燕, 等. 男性2型糖尿病患者胰岛素抵抗相关因素分析[J]. 同济大学学报(医学版), 2021, 42(4): 534-539. DOI: 10.12289/j.issn.1008-0392.20520.Wang B, Liu J, Zhang XY, et al. Factors related to insulin resistance in male patients with type 2 diabetes mellitus[J]. J Tongji Univ Med Sci, 2021, 42(4): 534-539. DOI: 10.12289/j.issn.1008-0392.20520. [5] Wang SJ, Shi J, Peng Y, et al. Stronger association of triglyceride glucose index than the HOMA-IR with arterial stiffness in patients with type 2 diabetes: a real-world single-centre study[J]. Cardiovasc Diabetol, 2021, 20(1): 82. DOI: 10.1186/s12933-021-01274-x. [6] 史丽萍, 王雯霞, 郑亮, 等. TyG指数对社区老年人群心血管疾病合并代谢综合征的预测价值[J]. 同济大学学报(医学版), 2023, 44(6): 841-847. DOI: 10.12289/j.issn.1008-0392.23075.Shi LP, Wang WX, Zheng L, et al. Predictive value of TyG index for cardiovascular disease combined with metabolic syndrome in community-dwelling elderly[J]. J Tongji Univ Med Sci, 2023, 44(6): 841-847. DOI: 10.12289/j.issn.1008-0392.23075. [7] Han C, Liu FC, Yang XL, et al. Ideal cardiovascular health and incidence of atherosclerotic cardiovascular disease among Chinese adults: the China-PAR project[J]. Sci China Life Sci, 2018, 61(5): 504-514. DOI: 10.1007/s11427-018-9281-6. [8] Sánchez-García A, Rodríguez-Gutiérrez R, Mancillas-Adame L, et al. Diagnostic accuracy of the triglyceride and glucose index for insulin resistance: a systematic review[J]. Int J Endocrinol, 2020, 2020: 4678526. DOI: 10.1155/2020/4678526. [9] Song K, Park G, Lee HS, et al. Prediction of insulin resistance by modified triglyceride glucose indices in youth[J]. Life, 2021, 11(4): 286. DOI: 10.3390/life11040286. [10] Yang XL, Li JX, Hu DS, et al. Predicting the 10-year risks of atherosclerotic cardiovascular disease in Chinese population: the china-PAR project (prediction for ASCVD risk in China)[J]. Circulation, 2016, 134(19): 1430-1440. DOI: 10.1161/CIRCULATIONAHA.116.022367. [11] 赵丽敏, 辛权达, 赵兴胜. 三酰甘油葡萄糖指数与心血管疾病相关性研究现状[J]. 国际心血管病杂志, 2023, 50(6): 358-361. DOI: 10.3969/j.issn.1673-6583.2023.06.006.Zhao LM, Xin QD, Zhao XS. Research status of correlation between triacylglycerol glucose index and cardiovascular diseases[J]. Int J Cardiovasc Dis, 2023, 50(6): 358-361. DOI: 10.3969/j.issn.1673-6583.2023.06.006. [12] Li C, Liu YZ, Shi GS, et al. Cohort profile: regional ethnic cohort study in Northwest China[J]. Int J Epidemiol, 2022, 51(2): e18-e26. DOI: 10.1093/ije/dyab212. [13] 黄妍, 汪子平, 景慧, 等. 基于西安城市自然人群的甘油三酯葡萄糖乘积指数与系统免疫炎症指数的关联研究[J]. 中华流行病学杂志, 2023, 44(11): 1762-1768. DOI: 10.3760/cma.j.cn112338-20230328-00187.Huang Y, Wang ZP, Jing H, et al. Study on the relationship between triglyceride glucose index and systemic immune- inflammation index based on natural population in Xi'an[J]. Chin J Epidemiol, 2023, 44(11): 1762-1768. DOI: 10.3760/cma.j.cn112338-20230328-00187. [14] 赖智维, 王枭冶, 谭红专, 等. 煤矿井下作业对工人心血管系统的影响[J]. 中南大学学报(医学版), 2015, 40(10): 1103-1108. DOI: 10.11817/j.issn.1672-7347.2015.10.008.Lai ZW, Wang XY, Tan HZ, et al. Effect of underground work on cardiovascular system in coal miners[J]. J Cent South Univ (Med Sci), 2015, 40(10): 1103-1108. DOI: 10.11817/j.issn.1672-7347.2015.10.008. [15] 徐明成, 赵玉娟. 甘油三酯葡萄糖指数对动脉粥样硬化性心血管疾病的预测价值[J]. 心血管病学进展, 2023, 44(9): 810-813, 822. DOI: 10.16806/j.cnki.issn.1004-3934.2023.09.010.Xu MC, Zhao YJ. Predictive value of triglyceride glucose index in atherosclerotic cardiovascular disease[J]. Adv Cardiovasc Dis, 2023, 44(9): 810-813, 822. DOI: 10.16806/j.cnki.issn.1004-3934.2023.09.010. [16] Tian X, Zuo YT, Chen SH, et al. Triglyceride-glucose index is associated with the risk of myocardial infarction: an 11-year prospective study in the Kailuan cohort[J]. Cardiovasc Diabetol, 2021, 20(1): 19. DOI: 10.1186/s12933-020-01210-5. -
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