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Smoking Is a Risk Factor of Coronary Heart Disease through HDL-C in Chinese T2DM Patients: A Mediation Analysis

Smoking Is a Risk Factor of Coronary Heart Disease through HDL-C in Chinese T2DM Patients: A... Hindawi Journal of Healthcare Engineering Volume 2020, Article ID 8876812, 8 pages https://doi.org/10.1155/2020/8876812 Research Article Smoking Is a Risk Factor of Coronary Heart Disease through HDL-C in Chinese T2DM Patients: A Mediation Analysis 1 2,3 4 5 5 5 Ru Tang, Shanshan Yang , Weiguo Liu, Bo Yang , Shuang Wang, Zhengguo Yang, 3,5 and Yao He 1 nd e 2 Medical Center, Chinese PLA General Hospital, Beijing 100853, China Department of Disease Control and Prevention, e 1st Medical Center, Chinese PLA General Hospital, Beijing 100853, China Institute of Geriatrics, Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatrics Disease, nd State Key Laboratory of Kidney Disease, e 2 Medical Center, Chinese PLA General Hospital, Beijing 100853, China Emergency Department, Armed Police Corps Hospital in Henan Province, Zhengzhou 450000, China 5 th Department of Nephrology and Endocrinology, PLA 960 Hospital, Zibo 255300, China Correspondence should be addressed to Bo Yang; 1684624143@qq.com and Yao He; yhe301@x263.net Received 30 April 2020; Revised 10 June 2020; Accepted 9 July 2020; Published 28 July 2020 Academic Editor: Xiwei Huang Copyright © 2020 Ru Tang et al. .is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Objective. To investigate associations between smoking and cardiovascular and cerebrovascular complications in type 2 diabetes mellitus (T2DM) patients. Methods. .is is a cross-sectional study. Of 971 T2DM patients aged 14–93 years old in this study, 182 had ever smoked and 789 never smoked. Propensity score matching (PSM) reduced the confounding bias between groups. Logistic regression analysis was performed on matched data to evaluate coronary heart disease (CHD) and stroke risk. In addition, the mediation analysis was conducted among smoking exposure, HDL-C, and CHD. Results. A total of 139 pairs of patients who had never and ever smoked were matched. Logistic regression analysis showed that compared with patients who never smoked, those who smoked> 20 cigarettes per day (CPD) had a higher risk of CHD (odds ratio [OR]: 3.09, 95% confidence interval [CI]: 1.21–7.89). Additionally, after adjusting for age, sex, origin, oc- cupation, smoking status, body mass index, waist circumference, and diabetes duration, the OR for CHD with >20 years of cumulative smoking (pack-years) was 2.21 (95% CI: 1.05–4.65). Furthermore, we observed a significant dose-response relationship between CPD and lower high-density lipoprotein cholesterol (HDL-C) (P< 0.001). Moreover, the mediation analysis showed that the indirect effect mediated by HDL-C accounted for 86% (effect � 0.0187, 95% CI: 0.0100–0.0316). Conclusions. Smoking may be a risk factor for CHD in T2DM patients. T2DM patients should stop smoking or reduce the CPD to prevent the onset of CHD. Moreover, to prevent CHD complications, monitoring HDL-C levels in T2DM patients who smoke may be necessary. 1.54–4.00 times higher risk of CHD [5, 6] and 1.35–1.74- 1. Introduction times higher risk of stroke [7]. In China, the annual per More than 5% of adults worldwide have type 2 diabetes patient cost of healthcare associated with T2DM patients mellitus (T2DM), and the prevalence will increase to 6.3% with cardiovascular and cerebrovascular complications is by 2025 [1]. In China, an estimated 23.46 million people estimated to be 1798 USD, compared with 484 USD for currently have diabetes, and that number is predicted to those without these complications [2]. Moreover, previ- increase to 42.30 million by 2030 [2, 3]. Coronary heart ous studies also showed that the morbidity of cerebro- disease (CHD) and stroke are the most common chronic vascular disease is 2–5 times higher in patients with complications of T2DM and the main cause of T2DM- T2DM than in patients without T2DM [8]. .us, iden- related mortality [4]. Patients with T2DM have a tifying risk factors, especially preventable risk factors, for 2 Journal of Healthcare Engineering cardiovascular and cerebrovascular complications in 1,025 inpatients T2DM is important. (between January 2010 and December 2012) Cigarette smoking is an important modifiable risk factor for cardiovascular and cerebrovascular disease in a general population [9, 10]. However, this relationship is Excluded 25 type 1 DM inpatients, 11 latent less well-defined among individuals with diabetes [11], autoimmune diabetes especially in Chinese diabetic inpatients. In previous in adults inpatients studies, smoking exposure was usually categorized as Excluded 18 inpatients never, current, and past only, but objective data of with fragmentary data smoking exposure such as cigarettes per day (CPD), time of smoking, and cumulative smoking (pack-years) was not provided in these studies [12, 13]. Furthermore, the 971 included (498 men and 473 women) combined effect of smoking and the influence of blood pressure, glucose, and serum lipids on cardiovascular and Propensity score matching cerebrovascular disease is also unclear. .e mechanism by which smoking affects cardiovascular and cerebrovascular 139 with smoking 139 without smoking diseases is not clear, either. In addition, in previous exposure exposure studies, demographic characteristics of groups who ever and never smoked differed significantly. .us, we Figure 1: .e flowchart of participants. designed a study to assess the association between smoking and CHD/stroke in Chinese T2DM patients using CPD, time of smoking, and cumulative smoking kg/m ) was calculated as weight in kilograms divided by the (pack-years) to measure smoking exposure, in addition to square of height in meters. To ensure the accuracy of the propensity score matching (PSM) to control for differ- information, patient answers to the questions on tobacco use ences in characteristics between those who never and ever were confirmed by the patients and their relatives. Central smoked. Further, mediation analysis was used to explore obesity was defined by a waist circumference (WC)> 90 cm the mechanism of smoking exposure on CHD in Chinese in men and> 80 cm in women [17]. Venous blood was taken T2DM patients. after fasting of eight hours. Fasting blood-glucose (FBG), hemoglobin A1c (HbA1c), cholesterol (CHO), and high- density lipoprotein cholesterol (HDL-C) were tested in the 2. Design and Methods central laboratory of PLA 148th Hospital. Covariables ad- justed in the study included age, sex (male and female), 2.1. Study Sample. We used clinical data from the Depart- th occupation (white collar, light physical labor and hard ment of Nephrology and Endocrinology, PLA 148 Hospital th physical labor), region (Shandong province and other (renamed as PLA 960 Hospital now). Among 1,025 in- provinces), drink (yes and no), BMI, WC, and diabetes patients (between January 2010 and December 2012), we duration. excluded 25 type 1 DM inpatients, 11 latent autoimmune diabetes in adults inpatients, and 18 inpatients with frag- mentary data and recruited 971 (498 men and 473 women) 2.3. Statistical Analysis. SPSS version 19.0 was used for as our participants (Figure 1). data analysis. .e significance level for all tests was set at a We collected data regarding each participant’s sex, age, two-tailed α value of 0.05. .e differences in means and occupation, region, alcohol and smoking consumption, proportions were evaluated using Student’s t-test and the diabetes duration, and CHD and stroke status. chi-square test, respectively. Logistic regression models were used to identify the risk of tobacco use and linear 2.2. Measurements. T2DM was defined according to the regression models were used to identify the effect of to- American Diabetes Association criteria [14]. CHD and bacco use on FBG, HbA1c, CHO, HDL-C, and systolic stroke were defined using the WHO MONICA criteria [15] pressure. th by physicians of the PLA 148 Hospital. PSM [18] was used to match groups of those who did and did not consume tobacco. Sex, age, origin, occupation, A smoker was defined as a person who had smoked daily for at least 6 months during their lives [16]. CPD, time of drinking status, BMI, WC, and T2DM duration were in- cluded as covariates. We used nearest-neighbor matching to smoking, and cumulative smoking (pack-years) were used to measure cigarette consumption. An alcohol user was defined pair never smokers with current and former smokers at a 1 :1 as a regular drinker who consumed alcohol approximately ratio with a caliper width of 0.02 [19]. daily and had been regularly consuming alcohol for more Mediation analysis is a method which is used to assess than 6 months [3]. the relative magnitude of different pathways and mecha- .e information was collected by a primary nurse. nisms by which an exposure may affect an outcome [20]. Height was measured in meters (without shoes). Weight was Mediation analysis was used to analyze the indirect effect on measured in kilograms, without heavy clothing and 1 kg CPD and CHD mediated by HDL-C. Extended program of deducted for remaining garments. Body mass index (BMI, SPSS was used to do the mediation analysis (model 4 [21] Journal of Healthcare Engineering 3 was used to simulate the mediation effect, and the con- significant in this population. We used PSM to compre- ceptual diagram is shown in Figure S1). hensively control and adjust for a wide range of potential confounders and to improve the comparability between the two groups (never and ever smokers). Further, we observed a 2.4. Ethical Considerations. .e committee for medical dose-response relationship between CPD and cumulative ethics of the Chinese PLA General Hospital examined and smoking (pack-years) and the risk of CHD; this relationship approved our study. Before completing the questionnaire, was also observed between CPD and lower HDL-C in these each involved participant signed an informed consent form. T2DM patients. A study of a Middle Eastern cohort [13] showed that, 3. Results in men with diabetes, the HR (95% CI) of comparing current smokers and nonsmokers was 1.25 (0.74–2.12) for A total of 971 (498 men and 473 women) inpatients were incident CHD, while, among nondiabetic men, current involved in our study before PSM. .e average age was smokers showed significant risk for CHD (HR � 1.49, 56.8± 11.6 years (range: 14–93 years). .e average ages of 1.18–1.89); however, the study did not assess the associ- those who did and did not use tobacco were 53.5± 11.9 years ation between CPD and the risk of CHD. Another study in and 57.6± 11.4 years, respectively. .e general character- the US population (the National Health Interview Survey) istics (age, sex, origin, occupation, drinking status, BMI, and [12] also showed that the OR of current smoking for CHD central obesity) of the participants are shown in Table 1. in T2DM patients was 1.61 (95% CI: 0.98–2.65) after Compared with the group of ever smokers, the group who adjustment; however, the study only used current, former, never smoked consisted of more women, more hard physical and never smoking as the measurement of exposure and laborers, fewer drinkers, and patients who were older and did not provide information of CPD, smoking time, or had less central obesity and longer T2DM durations cumulative smoking (pack-years). While the Nurses’ (6.3± 6.1 years vs. 7.4± 6.6 years; P � 0.05). Health Study in the US female population [11] showed After PSM, a total of 139 participant pairs were matched, that, in T2DM patients, compared with never smokers, the and the two groups were balanced for age, sex, occupation, risk ratios for CHD were 1.66 (95% CI, 1.10–2.52) for drinking status, BMI, central obesity, and T2DM duration current smokers of 1 to 14 CPD and 2.68 (95% CI, (ever and never smokers: 6.8± 6.3 years vs. 6.6± 6.3 years, 2.07–3.48) for current smokers of 15 or more CPD after respectively; P � 0.849) (Table 1). adjustment, our results were similar. In logistic regression, we found that compared with A study of 1,836 Chinese [22] found that participants never smokers, ever smokers with CPD> 20/day had a with both diabetes and a smoking habit had an 8.94-times higher risk of CHD (OR: 3.09, 95% CI: 1.21–7.89) after (95% CI: 3.77–21.19) higher risk of stroke compared with adjusting for age, sex, origin, occupation, drinking, BMI, those without diabetes and a smoking habit; however, this WC, and diabetes duration. We also observed a dose-re- study did not provide a comparison between T2DM patients sponse relationship between CPD and CHD risk (after with and without smoking exposure. Another study in a adjustment, P � 0.021). Similar results were observed in Swedish population involving 13,087 patients with T2DM cumulative smoking (pack-years) (Table 2). In addition, [23] found that the adjusted HR of smoking for stroke was compared with never smokers, ever smokers with smoking 1.3 (95% CI: 1.1–1.6); however, the study did not show the years >20 years had a higher risk of CHD in a crude model relationship between CPD and stroke in T2DM patients. We (OR: 2.06, 95% CI: 1.08–3.95), and a dose-response rela- did not observe a significant association between smoking tionship between years of tobacco use and risk of CHD was exposure and stroke in our study, possibly due to the limited also observed in a crude model (P � 0.027); however, after sample size. adjustment, the effect was no longer significant (Table 2). We We also observed a dose-response relationship between also examined the effect of ever smoking on stroke risk, and CPD and lower HDL-C. In addition, the mediation analysis no significant effect was observed (Table 3). showed that the indirect effect mediated by HDL-C Further, we examined the effect of CPD, smoking years, accounted for 86% on the association between smoking and cumulative smoking (pack-years) on FBG, HbA1c, exposure and CHD in the T2DM inpatients. Previous studies CHO, HDL-C, and systolic pressure, and the results are showed that HDL-C can exhibit anti-inflammatory prop- shown in Table 4. CPD was negatively correlated with HDL- erties [24]. Moreover, HDL-C from T2DM patients with C in T2DM inpatients after adjustment (β � −0.006, standard CHD stimulated the release of tumor necrosis factor-α β� −0.312, P< 0.001). (TNF-α) in monocytes to a greater extent than that of HDL- Further, the mediation analysis showed that the indirect C from those without CHD, and HDL-C was a significant effect on CPD and CHD mediated by HDL-C accounted for predictor of the presence of CHD in patients with T2DM 86% (effect � 0.0187, 95% CI: 0.0100–0.0316), and the direct [25]. .is may indicate that smoking exposure increases the effect of CPD on CHD was 0.0030 (95% CI: −0.0183–0.0242). risk of CHD by reducing the level of HDL-C in T2DM patients. 4. Discussion .is study had several limitations. As the information on In this study, we observed a significant association between smoking exposure was based on recall, bias could not be fully ruled out; however, the information was confirmed with smoking exposure and CHD in T2DM patients; however, the association between smoking exposure and stroke was not patients and their relatives to ensure accuracy. Second, our 4 Journal of Healthcare Engineering Table 1: Demographic characteristics according to tobacco use before and after propensity score matching (PSM). Ever smoking (before PSM) Ever smoking (after PSM) Number (%) Group Total N � 971 Yes (n � 182) None (n � 789) P Yes (n � 139) None (n � 139) P Age (years) 0.001 0.728 ≤60 81 (8.3) 24 (13.2) 57 (7.2) 15 (10.8) 19 (13.7) 60–69 529 (54.5) 109 (59.9) 420 (53.2) 85 (61.2) 80 (57.6) ≥70 361 (37.2) 49 (26.9) 312 (39.5) 39 (28.1) 40 (28.8) Sex <0.001 1.000 Male 498 (51.3) 177 (97.3) 321 (40.7) 136 (97.8) 136 (97.8) Female 473 (48.7) 5 (2.7) 468 (59.3) 3 (2.2) 3 (2.2) Occupation 0.014 0.464 White collar 103 (10.6) 27 (14.8) 76 (9.6) 21 (15.1) 15 (10.8) Light physical labor 117 (12.0) 29 (15.9) 88 (11.2) 21 (15.1) 26 (18.7) Hard physical labor 751 (77.3) 126 (69.2) 625 (79.2) 97 (69.8) 98 (70.5) Region 0.397 0.562 Shandong province 940 (96.8) 178 (97.8) 862 (96.6) 138 (99.3) 137 (98.6) Other provinces 31 (3.2) 4 (2.2) 27 (3.4) 1 (0.7) 2 (1.4) Drink <0.001 1.000 Yes 182 (18.7) 90 (49.5) 48 (6.1) 47 (33.8) 47 (33.8) No 789 (81.3) 92 (50.5) 741 (93.9) 92 (66.2) 92 (66.2) BMI 0.002 0.167 <24.00 368 (37.9) 39 (21.4) 317 (40.2) 43 (30.9) 46 (33.1) 24.00–27.99 388 (40.0) 92 (50.5) 296 (37.5) 70 (50.4) 56 (40.3) ≥28.00 215 (22.1) 51 (28.0) 176 (22.3) 26 (18.7) 37 (26.6) Central obesity <0.001 0.472 Yes 625 (64.4) 90 (49.5) 535 (67.8) 71 (51.1) 65 (46.8) No 346 (35.6) 92 (50.5) 254 (32.2) 68 (48.9) 74 (53.2) Mean± SD Age 56.8± 11.6 53.5± 11.9 57.6± 11.4 <0.001 54.2± 11.7 53.4± 13.1 0.583 Duration of diabetes 7.3± 6.5 6.3± 6.1 7.4± 6.6 0.05 6.8± 6.3 6.6± 6.3 0.849 BMI 25.3± 4.1 25.6± 3.6 25.3± 4.2 0.333 25.4± 3.6 25.6± 4.0 0.552 WC 88.6± 8.8 90.7± 8.3 88.2± 8.9 0.001 90.7± 7.9 90.6± 8.6 0.904 Table 2: Odds ratio (95% confidence interval, CI) of CHD for smoking in participants. Model A Model B Model C N (%) OR (95% CI) OR (95% CI) OR (95% CI) None (reference) 29 (20.9) 1 1 1 Smoking Yes 35 (25.2) 1.28 (0.73–2.24) 1.29 (0.69–2.40) 1.36 (0.72–2.58) P 0.393 0.429 0.347 None (reference) 29 (20.9) 1 1 1 CPD ≤20 (day) 23 (21.7) 1.05 (0.57–1.95) 0.95 (0.48–1.90) 1.00 (0.49–2.04) >20 (day) 12 (36.4) 2.17 (0.96–4.92) 3.00 (1.19–7.55) 3.09 (1.21–7.89) P for trend 0.127 0.076 0.05 None (reference) 29 (20.9) 1 1 1 Time of smoking ≤20 years 11 (15.7) 0.70 (0.33–1.50) 0.95 (0.41–2.21) 0.97 (0.41–2.29) >20 years 23 (35.4) 2.06 (1.08–3.95) 1.51 (0.74–3.08) 1.59 (0.77–3.30) P for trend 0.058 0.294 0.243 None (reference) 29 (20.9) 1 1 1 Cumulative ≤20 pack-years 11 (14.7) 0.65 (0.31–1.39) 0.70 (0.30–1.61) 0.74 (0.31–1.73) smoking >20 pack-years 24 (37.5) 2.28 (1.19–4.36) 2.08 (1.01–4.28) 2.21 (1.05–4.65) P for trend 0.032 0.060 0.026 Journal of Healthcare Engineering 5 Table 2: Continued. Model A Model B Model C N (%) OR (95% CI) OR (95% CI) OR (95% CI) None (reference) 1 1 1 CPD 1.02 (1.00–1.04) 1.03 (1.00–1.05) 1.03 (1.00–1.05) P 0.055 0.024 0.021 Variables are None (reference) 1 1 1 included as continuous Smoking time (years) 1.02 (1.00–1.04) 1.00 (0.99–1.03) 1.01 (0.99–1.03) variables P 0.027 0.36 0.251 None (reference) 1 1 1 Cumulative smoking (pack-years) 1.02 (1.01–1.03) 1.02 (1.00–1.03) 1.02 (1.00–1.03) P 0.008 0.037 0.032 Model A: crude model; Model B: adjusted for age, sex, origin, and occupation; Model C: adjusted for age, sex, origin, occupation, drinking, BMI, WC, and diabetes duration; and CPD: cigarettes per day. Table 3: Odds ratio (95% confidence interval, CI) of stroke for smoking in participants. Model A Model B Model C N (%) OR (95% CI) OR (95% CI) OR (95% CI) None (reference) 18 (12.9) 1 1 1 Smoking Yes 21 (15.1) 1.20 (0.61–2.36) 1.15 (0.55–2.53) 1.25 (0.57–2.74) P 0.605 0.673 0.573 None (reference) 18 (12.9) 1 1 1 CPD ≤20 (day) 14 (13.2) 1.02 (0.48–2.16) 0.90 (0.38–2.09) 0.94 (0.40–2.25) >20 (day) 7 (21.2) 1.81 (0.69–4.78) 2.68 (0.87–8.28) 2.76 (0.89–8.53) P for trend 0.333 0.228 0.186 None (reference) 18 (12.9) 1 1 1 Time of smoking ≤20 years 10 (14.3) 1.16 (0.50–2.66) 1.88 (0.71–4.98) 1.91 (0.70–5.21) >20 years 11 (16.9) 1.42 (0.63–3.20) 0.92 (0.37–2.30) 1.01 (0.39–2.56) P for trend 0.406 0.999 0.856 None (reference) 18 (12.9) 1 1 1 Cumulative smoking ≤20 pack-years 7 (9.3) 0.69 (0.28–1.74) 0.75 (0.27–2.07) 0.77 (0.27–2.21) >20 pack-years 14 (21.9) 1.88 (0.87–4.07) 1.66 (0.69–3.98) 1.79 (0.73–4.39) P for trend 0.167 0.314 0.255 None (reference) 1 1 1 CPD 1.02 (0.99–1.04) 1.02 (1.00–1.05) 1.02 (1.00–1.05) P 0.18 0.09 0.051 Variables None (reference) 1 1 1 are included as Smoking time (years) 1.01 (0.99–1.03) 1.00 (0.97–1.02) 1.00 (0.97–1.02) continuous variables P 0.421 0.678 0.885 None (reference) 1 1 1 Cumulative smoking (pack-years) 1.01 (1.00–1.03) 1.01 (0.99–1.03) 1.01 (0.99–1.03) P 0.083 0.385 0.336 Model A: crude model; Model B: adjusted for age, gender, origin, and occupation; Model C: adjusted for age, gender, origin, occupation, drinking, BMI, WC, and diabetes duration; and CPD: cigarettes per day. sample may not be completely representative of T2DM respect to CHD because of the lack of detailed information patients in China because our hospital is one of the best regarding the onset time of CHD. hospitals in Zibo, and the inpatients here have higher In summary, our study found a dose-response rela- proportions of diabetic complications; however, the repre- tionship between smoking exposure and CHD among sentativeness of our sample should not substantially affect T2DM inpatients. We used the PSM method to increase the the internal validity of this study. Finally, we could not comparability of the never and ever smokers groups. We also examine the hazard ratio (HR) of smoking exposure with observed a dose-response relationship between CPD and 6 Journal of Healthcare Engineering Table 4: Effect of smoking exposure on fasting blood-glucose (FBG), hemoglobin A1c (HbA1c), cholesterol (CHO), high-density lipoprotein cholesterol (HDL-C), and systolic pressure. Model A Model B Model C 95% CI 95% CI 95% CI CPD β Lower Upper Standard β P β Lower Upper Standard β P β Lower Upper Standard β P FBG −0.026 −0.069 0.016 −0.074 0.220 −0.027 −0.067 0.014 −0.075 0.199 −0.026 −0.067 0.015 −0.073 0.209 HbA1c 0.000 −0.023 0.022 −0.002 0.976 0.000 −0.022 0.023 0.001 0.983 −0.001 −0.022 0.021 −0.004 0.951 CHO −0.013 −0.028 0.002 −0.109 0.093 −0.013 −0.027 0.002 −0.108 0.092 −0.013 −0.028 0.001 −0.113 0.073 HDL-C −0.006 −0.009 −0.004 −0.323 <0.001 −0.006 −0.008 −0.004 −0.316 <0.001 −0.006 −0.008 −0.004 −0.312 <0.001 Systolic pressure 0.044 −0.265 0.176 0.025 0.693 0.041 −0.255 0.174 0.023 0.711 0.031 −0.241 0.180 0.018 0.775 Time of smoking FBG −0.029 −0.069 0.011 −0.086 0.151 −0.013 −0.053 0.027 −0.039 0.516 −0.016 −0.056 0.024 −0.046 0.440 HbA1c 0.001 −0.019 0.022 0.009 0.889 0.006 −0.015 0.027 0.037 0.585 0.000 −0.021 0.020 −0.002 0.970 CHO −0.011 −0.025 0.003 −0.103 0.112 −0.006 −0.020 0.008 −0.052 0.427 −0.008 −0.022 0.006 −0.070 0.282 HDL-C −0.005 −0.007 −0.002 −0.245 <0.001 −0.004 −0.006 −0.002 −0.223 <0.001 −0.004 −0.007 −0.002 −0.231 <0.001 Systolic pressure −0.006 −0.223 0.211 −0.003 0.958 −0.077 −0.293 0.138 −0.045 0.480 −0.052 −0.264 0.160 −0.030 0.631 Cumulative smoking FBG −0.020 −0.049 0.010 −0.078 0.194 −0.011 −0.040 0.018 −0.046 0.439 −0.011 −0.040 0.018 −0.043 0.467 HbA1c −0.004 −0.019 0.012 −0.029 0.652 −0.002 −0.017 0.014 −0.013 0.843 −0.002 −0.017 0.013 −0.016 0.796 CHO −0.009 −0.019 0.002 −0.105 0.105 −0.006 −0.016 0.004 −0.072 0.265 −0.006 −0.016 0.004 −0.077 0.230 HDL-C −0.002 −0.005 0.000 −0.141 0.058 −0.002 −0.005 0.000 −0.134 0.059 −0.002 −0.005 0.000 −0.128 0.051 Systolic pressure 0.010 −0.144 0.163 0.008 0.901 0.019 −0.170 0.132 0.015 0.807 0.021 −0.169 0.126 0.018 0.776 Model A: crude model; Model B: adjusted for age, sex, occupation, and region; Model C: adjusted for age, sex, occupation, region, drinking, BMI, WC, and duration of diabetes; and CPD: cigarettes per day. 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Smoking Is a Risk Factor of Coronary Heart Disease through HDL-C in Chinese T2DM Patients: A Mediation Analysis

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Copyright © 2020 Ru Tang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Abstract

Hindawi Journal of Healthcare Engineering Volume 2020, Article ID 8876812, 8 pages https://doi.org/10.1155/2020/8876812 Research Article Smoking Is a Risk Factor of Coronary Heart Disease through HDL-C in Chinese T2DM Patients: A Mediation Analysis 1 2,3 4 5 5 5 Ru Tang, Shanshan Yang , Weiguo Liu, Bo Yang , Shuang Wang, Zhengguo Yang, 3,5 and Yao He 1 nd e 2 Medical Center, Chinese PLA General Hospital, Beijing 100853, China Department of Disease Control and Prevention, e 1st Medical Center, Chinese PLA General Hospital, Beijing 100853, China Institute of Geriatrics, Beijing Key Laboratory of Aging and Geriatrics, National Clinical Research Center for Geriatrics Disease, nd State Key Laboratory of Kidney Disease, e 2 Medical Center, Chinese PLA General Hospital, Beijing 100853, China Emergency Department, Armed Police Corps Hospital in Henan Province, Zhengzhou 450000, China 5 th Department of Nephrology and Endocrinology, PLA 960 Hospital, Zibo 255300, China Correspondence should be addressed to Bo Yang; 1684624143@qq.com and Yao He; yhe301@x263.net Received 30 April 2020; Revised 10 June 2020; Accepted 9 July 2020; Published 28 July 2020 Academic Editor: Xiwei Huang Copyright © 2020 Ru Tang et al. .is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Objective. To investigate associations between smoking and cardiovascular and cerebrovascular complications in type 2 diabetes mellitus (T2DM) patients. Methods. .is is a cross-sectional study. Of 971 T2DM patients aged 14–93 years old in this study, 182 had ever smoked and 789 never smoked. Propensity score matching (PSM) reduced the confounding bias between groups. Logistic regression analysis was performed on matched data to evaluate coronary heart disease (CHD) and stroke risk. In addition, the mediation analysis was conducted among smoking exposure, HDL-C, and CHD. Results. A total of 139 pairs of patients who had never and ever smoked were matched. Logistic regression analysis showed that compared with patients who never smoked, those who smoked> 20 cigarettes per day (CPD) had a higher risk of CHD (odds ratio [OR]: 3.09, 95% confidence interval [CI]: 1.21–7.89). Additionally, after adjusting for age, sex, origin, oc- cupation, smoking status, body mass index, waist circumference, and diabetes duration, the OR for CHD with >20 years of cumulative smoking (pack-years) was 2.21 (95% CI: 1.05–4.65). Furthermore, we observed a significant dose-response relationship between CPD and lower high-density lipoprotein cholesterol (HDL-C) (P< 0.001). Moreover, the mediation analysis showed that the indirect effect mediated by HDL-C accounted for 86% (effect � 0.0187, 95% CI: 0.0100–0.0316). Conclusions. Smoking may be a risk factor for CHD in T2DM patients. T2DM patients should stop smoking or reduce the CPD to prevent the onset of CHD. Moreover, to prevent CHD complications, monitoring HDL-C levels in T2DM patients who smoke may be necessary. 1.54–4.00 times higher risk of CHD [5, 6] and 1.35–1.74- 1. Introduction times higher risk of stroke [7]. In China, the annual per More than 5% of adults worldwide have type 2 diabetes patient cost of healthcare associated with T2DM patients mellitus (T2DM), and the prevalence will increase to 6.3% with cardiovascular and cerebrovascular complications is by 2025 [1]. In China, an estimated 23.46 million people estimated to be 1798 USD, compared with 484 USD for currently have diabetes, and that number is predicted to those without these complications [2]. Moreover, previ- increase to 42.30 million by 2030 [2, 3]. Coronary heart ous studies also showed that the morbidity of cerebro- disease (CHD) and stroke are the most common chronic vascular disease is 2–5 times higher in patients with complications of T2DM and the main cause of T2DM- T2DM than in patients without T2DM [8]. .us, iden- related mortality [4]. Patients with T2DM have a tifying risk factors, especially preventable risk factors, for 2 Journal of Healthcare Engineering cardiovascular and cerebrovascular complications in 1,025 inpatients T2DM is important. (between January 2010 and December 2012) Cigarette smoking is an important modifiable risk factor for cardiovascular and cerebrovascular disease in a general population [9, 10]. However, this relationship is Excluded 25 type 1 DM inpatients, 11 latent less well-defined among individuals with diabetes [11], autoimmune diabetes especially in Chinese diabetic inpatients. In previous in adults inpatients studies, smoking exposure was usually categorized as Excluded 18 inpatients never, current, and past only, but objective data of with fragmentary data smoking exposure such as cigarettes per day (CPD), time of smoking, and cumulative smoking (pack-years) was not provided in these studies [12, 13]. Furthermore, the 971 included (498 men and 473 women) combined effect of smoking and the influence of blood pressure, glucose, and serum lipids on cardiovascular and Propensity score matching cerebrovascular disease is also unclear. .e mechanism by which smoking affects cardiovascular and cerebrovascular 139 with smoking 139 without smoking diseases is not clear, either. In addition, in previous exposure exposure studies, demographic characteristics of groups who ever and never smoked differed significantly. .us, we Figure 1: .e flowchart of participants. designed a study to assess the association between smoking and CHD/stroke in Chinese T2DM patients using CPD, time of smoking, and cumulative smoking kg/m ) was calculated as weight in kilograms divided by the (pack-years) to measure smoking exposure, in addition to square of height in meters. To ensure the accuracy of the propensity score matching (PSM) to control for differ- information, patient answers to the questions on tobacco use ences in characteristics between those who never and ever were confirmed by the patients and their relatives. Central smoked. Further, mediation analysis was used to explore obesity was defined by a waist circumference (WC)> 90 cm the mechanism of smoking exposure on CHD in Chinese in men and> 80 cm in women [17]. Venous blood was taken T2DM patients. after fasting of eight hours. Fasting blood-glucose (FBG), hemoglobin A1c (HbA1c), cholesterol (CHO), and high- density lipoprotein cholesterol (HDL-C) were tested in the 2. Design and Methods central laboratory of PLA 148th Hospital. Covariables ad- justed in the study included age, sex (male and female), 2.1. Study Sample. We used clinical data from the Depart- th occupation (white collar, light physical labor and hard ment of Nephrology and Endocrinology, PLA 148 Hospital th physical labor), region (Shandong province and other (renamed as PLA 960 Hospital now). Among 1,025 in- provinces), drink (yes and no), BMI, WC, and diabetes patients (between January 2010 and December 2012), we duration. excluded 25 type 1 DM inpatients, 11 latent autoimmune diabetes in adults inpatients, and 18 inpatients with frag- mentary data and recruited 971 (498 men and 473 women) 2.3. Statistical Analysis. SPSS version 19.0 was used for as our participants (Figure 1). data analysis. .e significance level for all tests was set at a We collected data regarding each participant’s sex, age, two-tailed α value of 0.05. .e differences in means and occupation, region, alcohol and smoking consumption, proportions were evaluated using Student’s t-test and the diabetes duration, and CHD and stroke status. chi-square test, respectively. Logistic regression models were used to identify the risk of tobacco use and linear 2.2. Measurements. T2DM was defined according to the regression models were used to identify the effect of to- American Diabetes Association criteria [14]. CHD and bacco use on FBG, HbA1c, CHO, HDL-C, and systolic stroke were defined using the WHO MONICA criteria [15] pressure. th by physicians of the PLA 148 Hospital. PSM [18] was used to match groups of those who did and did not consume tobacco. Sex, age, origin, occupation, A smoker was defined as a person who had smoked daily for at least 6 months during their lives [16]. CPD, time of drinking status, BMI, WC, and T2DM duration were in- cluded as covariates. We used nearest-neighbor matching to smoking, and cumulative smoking (pack-years) were used to measure cigarette consumption. An alcohol user was defined pair never smokers with current and former smokers at a 1 :1 as a regular drinker who consumed alcohol approximately ratio with a caliper width of 0.02 [19]. daily and had been regularly consuming alcohol for more Mediation analysis is a method which is used to assess than 6 months [3]. the relative magnitude of different pathways and mecha- .e information was collected by a primary nurse. nisms by which an exposure may affect an outcome [20]. Height was measured in meters (without shoes). Weight was Mediation analysis was used to analyze the indirect effect on measured in kilograms, without heavy clothing and 1 kg CPD and CHD mediated by HDL-C. Extended program of deducted for remaining garments. Body mass index (BMI, SPSS was used to do the mediation analysis (model 4 [21] Journal of Healthcare Engineering 3 was used to simulate the mediation effect, and the con- significant in this population. We used PSM to compre- ceptual diagram is shown in Figure S1). hensively control and adjust for a wide range of potential confounders and to improve the comparability between the two groups (never and ever smokers). Further, we observed a 2.4. Ethical Considerations. .e committee for medical dose-response relationship between CPD and cumulative ethics of the Chinese PLA General Hospital examined and smoking (pack-years) and the risk of CHD; this relationship approved our study. Before completing the questionnaire, was also observed between CPD and lower HDL-C in these each involved participant signed an informed consent form. T2DM patients. A study of a Middle Eastern cohort [13] showed that, 3. Results in men with diabetes, the HR (95% CI) of comparing current smokers and nonsmokers was 1.25 (0.74–2.12) for A total of 971 (498 men and 473 women) inpatients were incident CHD, while, among nondiabetic men, current involved in our study before PSM. .e average age was smokers showed significant risk for CHD (HR � 1.49, 56.8± 11.6 years (range: 14–93 years). .e average ages of 1.18–1.89); however, the study did not assess the associ- those who did and did not use tobacco were 53.5± 11.9 years ation between CPD and the risk of CHD. Another study in and 57.6± 11.4 years, respectively. .e general character- the US population (the National Health Interview Survey) istics (age, sex, origin, occupation, drinking status, BMI, and [12] also showed that the OR of current smoking for CHD central obesity) of the participants are shown in Table 1. in T2DM patients was 1.61 (95% CI: 0.98–2.65) after Compared with the group of ever smokers, the group who adjustment; however, the study only used current, former, never smoked consisted of more women, more hard physical and never smoking as the measurement of exposure and laborers, fewer drinkers, and patients who were older and did not provide information of CPD, smoking time, or had less central obesity and longer T2DM durations cumulative smoking (pack-years). While the Nurses’ (6.3± 6.1 years vs. 7.4± 6.6 years; P � 0.05). Health Study in the US female population [11] showed After PSM, a total of 139 participant pairs were matched, that, in T2DM patients, compared with never smokers, the and the two groups were balanced for age, sex, occupation, risk ratios for CHD were 1.66 (95% CI, 1.10–2.52) for drinking status, BMI, central obesity, and T2DM duration current smokers of 1 to 14 CPD and 2.68 (95% CI, (ever and never smokers: 6.8± 6.3 years vs. 6.6± 6.3 years, 2.07–3.48) for current smokers of 15 or more CPD after respectively; P � 0.849) (Table 1). adjustment, our results were similar. In logistic regression, we found that compared with A study of 1,836 Chinese [22] found that participants never smokers, ever smokers with CPD> 20/day had a with both diabetes and a smoking habit had an 8.94-times higher risk of CHD (OR: 3.09, 95% CI: 1.21–7.89) after (95% CI: 3.77–21.19) higher risk of stroke compared with adjusting for age, sex, origin, occupation, drinking, BMI, those without diabetes and a smoking habit; however, this WC, and diabetes duration. We also observed a dose-re- study did not provide a comparison between T2DM patients sponse relationship between CPD and CHD risk (after with and without smoking exposure. Another study in a adjustment, P � 0.021). Similar results were observed in Swedish population involving 13,087 patients with T2DM cumulative smoking (pack-years) (Table 2). In addition, [23] found that the adjusted HR of smoking for stroke was compared with never smokers, ever smokers with smoking 1.3 (95% CI: 1.1–1.6); however, the study did not show the years >20 years had a higher risk of CHD in a crude model relationship between CPD and stroke in T2DM patients. We (OR: 2.06, 95% CI: 1.08–3.95), and a dose-response rela- did not observe a significant association between smoking tionship between years of tobacco use and risk of CHD was exposure and stroke in our study, possibly due to the limited also observed in a crude model (P � 0.027); however, after sample size. adjustment, the effect was no longer significant (Table 2). We We also observed a dose-response relationship between also examined the effect of ever smoking on stroke risk, and CPD and lower HDL-C. In addition, the mediation analysis no significant effect was observed (Table 3). showed that the indirect effect mediated by HDL-C Further, we examined the effect of CPD, smoking years, accounted for 86% on the association between smoking and cumulative smoking (pack-years) on FBG, HbA1c, exposure and CHD in the T2DM inpatients. Previous studies CHO, HDL-C, and systolic pressure, and the results are showed that HDL-C can exhibit anti-inflammatory prop- shown in Table 4. CPD was negatively correlated with HDL- erties [24]. Moreover, HDL-C from T2DM patients with C in T2DM inpatients after adjustment (β � −0.006, standard CHD stimulated the release of tumor necrosis factor-α β� −0.312, P< 0.001). (TNF-α) in monocytes to a greater extent than that of HDL- Further, the mediation analysis showed that the indirect C from those without CHD, and HDL-C was a significant effect on CPD and CHD mediated by HDL-C accounted for predictor of the presence of CHD in patients with T2DM 86% (effect � 0.0187, 95% CI: 0.0100–0.0316), and the direct [25]. .is may indicate that smoking exposure increases the effect of CPD on CHD was 0.0030 (95% CI: −0.0183–0.0242). risk of CHD by reducing the level of HDL-C in T2DM patients. 4. Discussion .is study had several limitations. As the information on In this study, we observed a significant association between smoking exposure was based on recall, bias could not be fully ruled out; however, the information was confirmed with smoking exposure and CHD in T2DM patients; however, the association between smoking exposure and stroke was not patients and their relatives to ensure accuracy. Second, our 4 Journal of Healthcare Engineering Table 1: Demographic characteristics according to tobacco use before and after propensity score matching (PSM). Ever smoking (before PSM) Ever smoking (after PSM) Number (%) Group Total N � 971 Yes (n � 182) None (n � 789) P Yes (n � 139) None (n � 139) P Age (years) 0.001 0.728 ≤60 81 (8.3) 24 (13.2) 57 (7.2) 15 (10.8) 19 (13.7) 60–69 529 (54.5) 109 (59.9) 420 (53.2) 85 (61.2) 80 (57.6) ≥70 361 (37.2) 49 (26.9) 312 (39.5) 39 (28.1) 40 (28.8) Sex <0.001 1.000 Male 498 (51.3) 177 (97.3) 321 (40.7) 136 (97.8) 136 (97.8) Female 473 (48.7) 5 (2.7) 468 (59.3) 3 (2.2) 3 (2.2) Occupation 0.014 0.464 White collar 103 (10.6) 27 (14.8) 76 (9.6) 21 (15.1) 15 (10.8) Light physical labor 117 (12.0) 29 (15.9) 88 (11.2) 21 (15.1) 26 (18.7) Hard physical labor 751 (77.3) 126 (69.2) 625 (79.2) 97 (69.8) 98 (70.5) Region 0.397 0.562 Shandong province 940 (96.8) 178 (97.8) 862 (96.6) 138 (99.3) 137 (98.6) Other provinces 31 (3.2) 4 (2.2) 27 (3.4) 1 (0.7) 2 (1.4) Drink <0.001 1.000 Yes 182 (18.7) 90 (49.5) 48 (6.1) 47 (33.8) 47 (33.8) No 789 (81.3) 92 (50.5) 741 (93.9) 92 (66.2) 92 (66.2) BMI 0.002 0.167 <24.00 368 (37.9) 39 (21.4) 317 (40.2) 43 (30.9) 46 (33.1) 24.00–27.99 388 (40.0) 92 (50.5) 296 (37.5) 70 (50.4) 56 (40.3) ≥28.00 215 (22.1) 51 (28.0) 176 (22.3) 26 (18.7) 37 (26.6) Central obesity <0.001 0.472 Yes 625 (64.4) 90 (49.5) 535 (67.8) 71 (51.1) 65 (46.8) No 346 (35.6) 92 (50.5) 254 (32.2) 68 (48.9) 74 (53.2) Mean± SD Age 56.8± 11.6 53.5± 11.9 57.6± 11.4 <0.001 54.2± 11.7 53.4± 13.1 0.583 Duration of diabetes 7.3± 6.5 6.3± 6.1 7.4± 6.6 0.05 6.8± 6.3 6.6± 6.3 0.849 BMI 25.3± 4.1 25.6± 3.6 25.3± 4.2 0.333 25.4± 3.6 25.6± 4.0 0.552 WC 88.6± 8.8 90.7± 8.3 88.2± 8.9 0.001 90.7± 7.9 90.6± 8.6 0.904 Table 2: Odds ratio (95% confidence interval, CI) of CHD for smoking in participants. Model A Model B Model C N (%) OR (95% CI) OR (95% CI) OR (95% CI) None (reference) 29 (20.9) 1 1 1 Smoking Yes 35 (25.2) 1.28 (0.73–2.24) 1.29 (0.69–2.40) 1.36 (0.72–2.58) P 0.393 0.429 0.347 None (reference) 29 (20.9) 1 1 1 CPD ≤20 (day) 23 (21.7) 1.05 (0.57–1.95) 0.95 (0.48–1.90) 1.00 (0.49–2.04) >20 (day) 12 (36.4) 2.17 (0.96–4.92) 3.00 (1.19–7.55) 3.09 (1.21–7.89) P for trend 0.127 0.076 0.05 None (reference) 29 (20.9) 1 1 1 Time of smoking ≤20 years 11 (15.7) 0.70 (0.33–1.50) 0.95 (0.41–2.21) 0.97 (0.41–2.29) >20 years 23 (35.4) 2.06 (1.08–3.95) 1.51 (0.74–3.08) 1.59 (0.77–3.30) P for trend 0.058 0.294 0.243 None (reference) 29 (20.9) 1 1 1 Cumulative ≤20 pack-years 11 (14.7) 0.65 (0.31–1.39) 0.70 (0.30–1.61) 0.74 (0.31–1.73) smoking >20 pack-years 24 (37.5) 2.28 (1.19–4.36) 2.08 (1.01–4.28) 2.21 (1.05–4.65) P for trend 0.032 0.060 0.026 Journal of Healthcare Engineering 5 Table 2: Continued. Model A Model B Model C N (%) OR (95% CI) OR (95% CI) OR (95% CI) None (reference) 1 1 1 CPD 1.02 (1.00–1.04) 1.03 (1.00–1.05) 1.03 (1.00–1.05) P 0.055 0.024 0.021 Variables are None (reference) 1 1 1 included as continuous Smoking time (years) 1.02 (1.00–1.04) 1.00 (0.99–1.03) 1.01 (0.99–1.03) variables P 0.027 0.36 0.251 None (reference) 1 1 1 Cumulative smoking (pack-years) 1.02 (1.01–1.03) 1.02 (1.00–1.03) 1.02 (1.00–1.03) P 0.008 0.037 0.032 Model A: crude model; Model B: adjusted for age, sex, origin, and occupation; Model C: adjusted for age, sex, origin, occupation, drinking, BMI, WC, and diabetes duration; and CPD: cigarettes per day. Table 3: Odds ratio (95% confidence interval, CI) of stroke for smoking in participants. Model A Model B Model C N (%) OR (95% CI) OR (95% CI) OR (95% CI) None (reference) 18 (12.9) 1 1 1 Smoking Yes 21 (15.1) 1.20 (0.61–2.36) 1.15 (0.55–2.53) 1.25 (0.57–2.74) P 0.605 0.673 0.573 None (reference) 18 (12.9) 1 1 1 CPD ≤20 (day) 14 (13.2) 1.02 (0.48–2.16) 0.90 (0.38–2.09) 0.94 (0.40–2.25) >20 (day) 7 (21.2) 1.81 (0.69–4.78) 2.68 (0.87–8.28) 2.76 (0.89–8.53) P for trend 0.333 0.228 0.186 None (reference) 18 (12.9) 1 1 1 Time of smoking ≤20 years 10 (14.3) 1.16 (0.50–2.66) 1.88 (0.71–4.98) 1.91 (0.70–5.21) >20 years 11 (16.9) 1.42 (0.63–3.20) 0.92 (0.37–2.30) 1.01 (0.39–2.56) P for trend 0.406 0.999 0.856 None (reference) 18 (12.9) 1 1 1 Cumulative smoking ≤20 pack-years 7 (9.3) 0.69 (0.28–1.74) 0.75 (0.27–2.07) 0.77 (0.27–2.21) >20 pack-years 14 (21.9) 1.88 (0.87–4.07) 1.66 (0.69–3.98) 1.79 (0.73–4.39) P for trend 0.167 0.314 0.255 None (reference) 1 1 1 CPD 1.02 (0.99–1.04) 1.02 (1.00–1.05) 1.02 (1.00–1.05) P 0.18 0.09 0.051 Variables None (reference) 1 1 1 are included as Smoking time (years) 1.01 (0.99–1.03) 1.00 (0.97–1.02) 1.00 (0.97–1.02) continuous variables P 0.421 0.678 0.885 None (reference) 1 1 1 Cumulative smoking (pack-years) 1.01 (1.00–1.03) 1.01 (0.99–1.03) 1.01 (0.99–1.03) P 0.083 0.385 0.336 Model A: crude model; Model B: adjusted for age, gender, origin, and occupation; Model C: adjusted for age, gender, origin, occupation, drinking, BMI, WC, and diabetes duration; and CPD: cigarettes per day. sample may not be completely representative of T2DM respect to CHD because of the lack of detailed information patients in China because our hospital is one of the best regarding the onset time of CHD. hospitals in Zibo, and the inpatients here have higher In summary, our study found a dose-response rela- proportions of diabetic complications; however, the repre- tionship between smoking exposure and CHD among sentativeness of our sample should not substantially affect T2DM inpatients. We used the PSM method to increase the the internal validity of this study. Finally, we could not comparability of the never and ever smokers groups. We also examine the hazard ratio (HR) of smoking exposure with observed a dose-response relationship between CPD and 6 Journal of Healthcare Engineering Table 4: Effect of smoking exposure on fasting blood-glucose (FBG), hemoglobin A1c (HbA1c), cholesterol (CHO), high-density lipoprotein cholesterol (HDL-C), and systolic pressure. Model A Model B Model C 95% CI 95% CI 95% CI CPD β Lower Upper Standard β P β Lower Upper Standard β P β Lower Upper Standard β P FBG −0.026 −0.069 0.016 −0.074 0.220 −0.027 −0.067 0.014 −0.075 0.199 −0.026 −0.067 0.015 −0.073 0.209 HbA1c 0.000 −0.023 0.022 −0.002 0.976 0.000 −0.022 0.023 0.001 0.983 −0.001 −0.022 0.021 −0.004 0.951 CHO −0.013 −0.028 0.002 −0.109 0.093 −0.013 −0.027 0.002 −0.108 0.092 −0.013 −0.028 0.001 −0.113 0.073 HDL-C −0.006 −0.009 −0.004 −0.323 <0.001 −0.006 −0.008 −0.004 −0.316 <0.001 −0.006 −0.008 −0.004 −0.312 <0.001 Systolic pressure 0.044 −0.265 0.176 0.025 0.693 0.041 −0.255 0.174 0.023 0.711 0.031 −0.241 0.180 0.018 0.775 Time of smoking FBG −0.029 −0.069 0.011 −0.086 0.151 −0.013 −0.053 0.027 −0.039 0.516 −0.016 −0.056 0.024 −0.046 0.440 HbA1c 0.001 −0.019 0.022 0.009 0.889 0.006 −0.015 0.027 0.037 0.585 0.000 −0.021 0.020 −0.002 0.970 CHO −0.011 −0.025 0.003 −0.103 0.112 −0.006 −0.020 0.008 −0.052 0.427 −0.008 −0.022 0.006 −0.070 0.282 HDL-C −0.005 −0.007 −0.002 −0.245 <0.001 −0.004 −0.006 −0.002 −0.223 <0.001 −0.004 −0.007 −0.002 −0.231 <0.001 Systolic pressure −0.006 −0.223 0.211 −0.003 0.958 −0.077 −0.293 0.138 −0.045 0.480 −0.052 −0.264 0.160 −0.030 0.631 Cumulative smoking FBG −0.020 −0.049 0.010 −0.078 0.194 −0.011 −0.040 0.018 −0.046 0.439 −0.011 −0.040 0.018 −0.043 0.467 HbA1c −0.004 −0.019 0.012 −0.029 0.652 −0.002 −0.017 0.014 −0.013 0.843 −0.002 −0.017 0.013 −0.016 0.796 CHO −0.009 −0.019 0.002 −0.105 0.105 −0.006 −0.016 0.004 −0.072 0.265 −0.006 −0.016 0.004 −0.077 0.230 HDL-C −0.002 −0.005 0.000 −0.141 0.058 −0.002 −0.005 0.000 −0.134 0.059 −0.002 −0.005 0.000 −0.128 0.051 Systolic pressure 0.010 −0.144 0.163 0.008 0.901 0.019 −0.170 0.132 0.015 0.807 0.021 −0.169 0.126 0.018 0.776 Model A: crude model; Model B: adjusted for age, sex, occupation, and region; Model C: adjusted for age, sex, occupation, region, drinking, BMI, WC, and duration of diabetes; and CPD: cigarettes per day. 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