http://informahealthcare.com/tam ISSN: 1368-5538 (print), 1473-0790 (electronic) Aging Male, 2015; 18(1): 27–33 ! 2015 Informa UK Ltd. DOI: 10.3109/13685538.2014.1002082
ORIGINAL ARTICLE
Metabolic diseases and sex hormone levels affect differently in the development of cardiovascular and cerebrovascular diseases in elderly males
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Yanping Gong*, Xiaoling Cheng*, Chunlin Li, Jian Li, Mengmeng Jin, Banruo Sun, and Hui Tian Department of Geriatric Endocrinology, The Chinese People’s Liberation Army General Hospital, Beijing, China
Abstract
Keywords
Objective: This single-centre cross-sectional study aimed to investigate the metabolic and gonadal risk factors of vascular diseases in elderly males. Methods: After screening, 337 subjects aged 60–90 were found to be qualified. Odds ratios (ORs) in cross-table analyses and exp(B) in logistic regression analyses were used to evaluate the vascular risk of dependent factors. R2 of logistic regression equation was used to estimate the goodness-of-fit of vascular diseases logistic regression models. Results: Hypertension increased the risk of cardiovascular disease (CAVD) in elderly men approximately 3-fold. The number of metabolic diseases also correlated with incremental risks of CAVD; presence of one abnormality approximately increases the risk approximately 62%. Cerebrovascular disease (CEVD) development was closely associated with both metabolic syndrome and sex hormone levels; their explanation effects of single action and combined action were 13.2%, 12.55% and 28.5%. C-peptide might be the underlying mechanism of the metabolic syndrome’s effect on CEVD. C-peptide ¼ 2.43 U/L and FE2 ¼ 0.66 were the tangent points in receiver operating characteristic (ROC) analyses. Conclusions: Metabolic diseases and sex hormones play different roles in the development of CAVD and CEVD, the methods for vascular protection in elderly men should be promoted differently according to the their risks of CAVD and CEVD.
Elderly, male, metabolic syndrome, sex hormone, vascular disease
Introduction Cardiovascular disease (CAVD) and cerebrovascular disease (CEVD) are major cause of morbidity and mortality in the elderly [1]. More than 1.5 million people die from vascular diseases every year. Metabolic diseases and sex hormone levels are believed to be the risk factors of both of these vascular diseases. But, these two factors have been largely observed separately. Metabolic syndrome (MS) [2] is the cluster of abnormal metabolism that includes hypertension, hyperglycemia, excess abdominal fat, high triglycerides and low high-density lipoprotein (HDL). It is quite plausible that the current MS epidemic will induce a new worldwide CAVD epidemic. But the relationship of MS and CAVD is subject to debate. In the Framingham Offspring Study, MS and homeostasis model assessment - insulin resistance (HOMA-IR) did not
*These authors contributed equally to this work. Address for correspondence: Chunlin Li, Department of Geriatric Endocrinology, the Chinese People’s Liberation Army General Hospital, Beijing 100853, China. Tel: +86 13810921655. Fax: +86 10 66937711. E-mail: [email protected]
History Received 20 September 2014 Revised 11 December 2014 Accepted 21 December 2014 Published online 6 February 2015
independently predict the incidence of CAVD [3,4]. It is also known that although black men have a higher prevalence of MS, their risk of MI is not proportionally increased [5]. Some researchers believe that some specific metabolic disease (like hypertension, obesity, dyslipidemia, diabetes, hyperuricemia) might play an independent role in the development of CAVD, other than MS as a whole [3,6–8]. The relationships between the total testosterone (TT) levels, estradiol (E2) levels and vascular diseases have also been the subjects of much research [9]. Some researchers report that low TT levels are associated with increased CAVD [2,10], while others claim that high TT levels have been associated with sudden cardiac death [11]. However, estrogen is significantly associated with the risk of vascular disease. In healthy young men, aromatase inhibition reduces plasma E2 levels, and this reduction is associated with reduced flowmediated dilatation of the brachial artery [12]. Our previous study [13] showed that T/E2 balance plays a key role in the relationship between sex hormones and the risk of CEVD. Extremely low T/E2 and inappropriately high T/E2 ratio can both harm the brain blood vessels. There also exist a relationship between metabolic diseases and sex hormone levels [13]. We reported previously that
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metabolic factors could regulate hormone levels in elderly males through their effects on sex hormone-binding globulin (SHBG) levels [14]. The extents of the specific roles of metabolic diseases and sex hormones on CAVD and CEVD, however, are not clear. Given the correlation of increased age and incidence of metabolic diseases and variations of sex hormones, this issue becomes more relevant. Better control of either the metabolic diseases or sex hormone variations can lead to decrease in healthcare spending. Thus, we designed this study as an investigation of the association between metabolic diseases, sex hormone levels and the developments of CAVD and CEVD in elderly males to provide a clinical basis for the prevention in elder men.
Methods
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Study population This single-centre cross-sectional study enrolled 1920 men above 60 years of age who underwent routine physical examinations at the Chinese People’s Liberation Army General Hospital. Overall, 337 subjects were included in the analyses. The screening details were provided in previous studies [3,14]. The study was carried out in accordance with the Declaration of Helsinki and ARRIVE guidelines, and was approved by the Ethics Committee of the Chinese People’s Liberation Army General Hospital (reference number 12BJZ41) and written informed consent was obtained from the patient or assent from their relatives. Clinical parameters and laboratory measurements After the patients were fasted for at least 8 h overnight, physical examination, fasting venous blood samples, medical history were obtained by trained physicians during the next morning between 6:00 and 8:00. A postprandial venous blood sample was extracted 2 h after the consumption of 100 g glucose. The blood samples were immediately centrifuged for 15 min at 4 C and stored at 20 C. All of the samples were tested within 1 week. An automated enzymatic procedure (Cobas E601; Roche, Basel, Switzerland) was used to determine all the biochemistry indices. Diagnoses of metabolic diseases (including metabolic syndrome, abnormal metabolic syndrome components and hyperuricemia), CAVD or CEVD are provided in previous studies [3,14]. New diagnoses were made if abnormal results were obtained [14]. Total TT, E2, SHBG, follicle-stimulating hormone (FSH) and luteinising hormone [15] levels were measured automatically with an electrochemiluminescence system (Roche Cobas C6000, Roche Diagnostics GmbH, Mannheim, Germany). Free testosterone (FT) and bioactive testosterone [16] levels were calculated with Vermeulen’s formula, free estradiol (FE2) levels were calculated according to the formula reported by Rinald et al. [17], and the T/E2 and E2/SHBG ratios were also calculated. The FT index (FTI) was calculated as FTI ¼ T/SHBG, and the testosterone secretion index (TSI) was calculated as TSI ¼ T/LH. Statistical analyses SPSS 17.0 (SPSS Inc., Chicago, IL) was used for both data management and analyses. Continuous variables were
Aging Male, 2015; 18(1): 27–33
presented as the mean ± SD. We categorised the patients according to vascular disease diagnoses as follows: CAVD only (CAVD), CEVD only (CEVD), both types of vascular disease (BVD) and controls. The data distribution was evaluated before analysis. Multiple-factor linear regression was used to compare the normally distributed data, and nonparametric K-sample tests were used to compare the nonnormally distributed data (Table 1). Classifying variables were reported as percentages. 2 tests were performed for 2group comparisons. Cross-table analyses were used for intergroup comparisons. The influences of metabolic and gonadal factors on vascular disease development and interactions were further studied with logistic regression analyses. Four models were used in logistic regression analyses (Table 2). Odds ratios [16] in cross-table analyses and exp(B) in logistic regression analyses were used to evaluated the vascular risk of dependent factors. R2 in logistic regression equation was used to estimate the goodness-of-fit of vascular diseases logistic regression models. The 95% confidence intervals (95% CI) were calculated to describe the magnitudes of the associations. ROC curves were used to analyse the tangent points of vascular disease-related continuous variables, the tangent point was the point with the best sensitivity, specificity and the Youden index (sensitivity + specifity 1). p50.05 was considered statistically significant.
Results Vascular diseases in this population The cohort included 101 (29.97%) and 31 (9.20%) subjects with only CAVD and CEVD, respectively. Fifty-four (16.02%) subjects had both type of the vascular diseases (BVD). The morbidity rates in the CAVD, CEVD and BVD groups all increased with age (p50.01). Metabolic diseases in patients with vascular diseases Subjects without any metabolic disease only accounted for 2.67%; those with 1–5 metabolic diseases accounted for 4.74%, 18.99%, 28.78%, 36.49% and 8.30%, respectively. Subjects with vascular diseases had a higher percentage of metabolic diseases than those without vascular diseases, and the hypertension incidence in CAVD, BVD and the dyslipidemia incidence in BVD differed significantly from those without vascular diseases (p50.01, p50.05, Figure 1A and B). Cross-table analyses showed that the risks of CAVD and BVD (odds ratio, OR) in hypertension patients were 3.24and 3.28-fold of that in normal blood pressure subjects; while the risk of CAVD in dyslipidemia was 2.14-fold (Figure 1C) of that in normal plasma lipid subjects. The risk of CAVD development significantly increased in patients with 3, 4 or 5 metabolic diseases compared with non-metabolic diseases subjects, with the OR values were 1.68, 1.80 and 2.11, respectively (Figure 1D). Sex hormone levels in patients with vascular diseases Plasma TT, BT, FTI, TSI, E2, E2/SHBG and PCG levels were lower in patients with vascular diseases than in the control group, while the LH, FSH and SHBG levels were higher in the vascular disease groups. However, after adjusting for age
Metabolic and gonadal risk factors of vascular diseases in elderly males
DOI: 10.3109/13685538.2014.1002082
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Table 1. Differences in sex hormone levels after grouping the subjects according to vascular disease.
TT (nmol/L) FT (nmol/L) BT (nmol/L) T/E2 E2 (pmol/L) E2/SHBG FE2 PROG (nmol/L) LH (IU/L) FSH (IU/L) FTI TSI (nmol/IU) SHBG (nmol/L)
Control
CEVD
CAVD
BVD
5.16 ± 0.16 0.22 ± 0.01 5.13 ± 0.16 0.19 ± 0.01 29.14 ± 0.71 0.65 ± 0.03 0.60 ± 0.28 275.05 ± 11.24 9.39 ± 0.49 16.32 ± 1.29 0.11 ± 0.09 0.72 ± 0.03 51.63 ± 1.67
5.06 ± 0.35 0.25 ± 0.02 4.99 ± 0.35 0.19 ± 0.01 27.34 ± 1.54 0.61 ± 0.06 0.50 ± 0.02 217.54 ± 24.73 10.55 ± 1.07 19.57 ± 2.84 0.18 ± 0.01 0.68 ± 0.07 53.24 ± 3.67
4.94 ± 0.19 0.21 ± 0.01 4.94 ± 0.19 0.18 ± 0.01 28.44 ± 0.84 0.65 ± 0.03 0.51 ± 0.02 242.96 ± 13.44 9.17 ± 0.58 17.01 ± 1.54 0.11 ± 0.00 0.68 ± 0.04 49.03 ± 2.01
5.01 ± 0.27 0.21 ± 0.01 4.94 ± 0.27 0.18 ± 0.01 28.60 ± 1.17 0.62 ± 0.04 0.51 ± 0.02 227.18 ± 18.93 9.52 ± 0.82 17.08 ± 2.17 0.10 ± 0.00 0.61 ± 0.05 54.56 ± 2.81
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All data from the different vascular disease groups were adjusted by age and smoking history.
and smoking history, the differences between the control and vascular disease groups decreased, and all of the significant differences disappeared (Table 1). Effects of metabolic diseases and sex hormone levels on vascular diseases Four models were used in logistic regression analyses. Models 1 and 2 evaluated the effect of metabolic diseases and sex hormone levels separately; model 3 estimated the combined effect of metabolic diseases and sex hormone levels; model 4 replaces the diagnoses of metabolic diseases in model 3 with corresponding continuous metabolic indexes. We summarized the results of four models of each vascular disease as below (Table 2). (1) Age was an independent risk factor for all vascular diseases (exp(B): 1.05–1.87). (2) CAVD was closely associated with metabolic diseases. The goodness-of-fit of metabolic diseases diagnoses in CAVD regression was 17.60%, while continuous metabolic indexes accounted for 31.10% (R2). The CAVD risk increased in patients with hypertension (exp(B)¼3.10; p50.01) and increased with the increment of metabolic diseases (Ab-Met) (exp(B)¼1.62; p50.01). Sex hormones did not influence the goodness-of-fit and risks of metabolic factors, and none of the sex hormone levels was included in the CAVD logistic regression equation. (3) CEVD development is closely associated with both metabolic diseases and sex hormone levels (R2 were 13.2% and 12.55%, respectively, and combined R2 was 28.5%). MS associated significantly with the CEVD development (exp(B)¼4.24; p50.05), and the role of MS could not be replaced by the increment of metabolic diseases and groups with more than or less than three abnormal metabolism. But, in model 4 where continuous metabolic indexes were introduced, MS was replaced by C-peptide (with similar R2 and exp(B)). If C-peptide was excluded, FBG, PBG, INS and HOMA could not substitute for the role of C-peptide. (4) The risk of BVD increased in patients with hypertension (exp(B)¼2.87; p50.05) and with the increment of metabolic diseases (exp(B)¼1.87; p50.01). BVD reversely correlated with FE2 levels significantly (exp(B)¼0.03; p50.01).
Analyses of the tangent points of the metabolic indicators and sex hormones ROC curves (Figure 2A) showed that FE2 was the only factor that had a CEVD protective effect. No ideal Youden index was obtained from all the sex hormones, so they were analyzed by quarter (Figure 2D). The tangent points of age and C-peptide in CEVD ROC curves were obtained at 74.5 and 2.43 (Figure 2B). Patients were then divided into two groups according to the tangent point of C-peptide ¼ 2.43; the results showed that the CEVD incidence rates in these two groups were significantly different (p ¼ 0.01; Figure 2C). BVD ROC curve showed that age and FE2 were closely associated with BVD development (Figure 3A and B). The tangent point for age also occurred at 74.5 years. Patients were divided into two groups according to the tangent point of FE2 ¼ 0.39, and the results showed that the incidence rates of BVD in these two groups were significantly different (p50.01) (Figure 3C). A quartile-based analysis also showed that in Q3 and Q4, FE2 was associated with a lower risk of a BVD event (OR ¼ 0.38 and 0.27; p ¼ 0.02 and 0.01, respectively), compared to the values in Q1 (Figure 3D).
Discussion The result of our study showed that sex hormone levels and metabolic diseases had different effects on CAVD and CEVD: CAVD related only with metabolic diseases, while CEVD had close relationship with both sex hormone levels and metabolic diseases; furthermore, metabolic diseases affected CAVD and CEVD differently. It was really interesting that hypertension was the most important metabolic risk factor that correlated with CAVD, other than MS, diabetes, BMI, etc. Hypertension might increase CAVD risk in an independent way different with other metabolic factors, because multifactor logistic regression analyses did not change much of its risk compared with simple cross-table analysis. Our findings are further corroborated by other studies. Besides Framingham Offspring Study [3], Bello-Rodriguez et al. [6] also found that hypertension is for itself an individual risk to developing cardiovascular disease with high frequency un-related with MS and diabetes. Research of Thanassoulis et al. [18] suggest that impaired vascular function may contribute to exaggerated BP responses
7.60
Model 2
1.13** 3.10 (1.62–5.93)
17.60
Model 3
0.48** 1.62 (1.18–2.22)
31.10
Model 4
1.01* 2.73 (1.05–7.11)
13.20
Model 1
4.33* 75.71 (1.10–4100)
12.50
Model 2
9.11* 4100 (4.17–4100)
5.79* 0.01 (50.01–0.69)
1.45* 4.24 (1.23–14.67)
28.50
Model 3
29.42* 4100 (0.95–4100)
1.41* 4.09 (1.14–14.68)
27.20
Model 4
1.01* 2.74 (1.17–6.41)
23.50
Model 1
Model 1: All metabolic categorical variables, age, smoking history and hepatic/renal function were included in the regression equation. 2: All sex hormones, age, smoking history and hepatic/renal function were included in the regression equation. 3: All sex hormones, all metabolic categorical variables, age, smoking history and hepatic/renal function were included in the regression equation. 4: All sex hormones, all metabolic continuous variables, age, smoking history and hepatic/renal function were included in the regression equation.
1.13** 3.10 (1.62–5.93)
17.60
Model 1
CEVD
2.42** 0.09 (0.02–0.46)
28.80
Model 2
30.20
Model 3
2.97** 0.05 (0.01–0.33)
1.06* 2.87 (1.16–7.14)
BVD
4.00** 0.02 (50.01–0.21)
0.63** 1.87 (1.17–2.99)
38.30
Model 4
Y. Gong et al.
Notes: Model Model Model
R HP B exp(B) 95%CI MS B exp(B) 95%CI Num of Ab-Met B exp(B) 95%CI C-peptide B exp(B) 95%CI T/E2 B exp(B) 95%CI FE2 B exp(B) 95%CI FT B exp(B) 95%CI
2
CAVD
Table 2. Logistic regression analyses of different vascular disease group.
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30 Aging Male, 2015; 18(1): 27–33
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DOI: 10.3109/13685538.2014.1002082
Metabolic and gonadal risk factors of vascular diseases in elderly males
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Figure 1. The relationships between metabolic diseases and the incidence rates of different vascular diseases. (A) The incidence rates of each metabolic diseases in populations with different vascular diseases. The rankings are arranged from low to high according to the incidence rates in the control group. *p50.05, **p50.01 versus the group without vascular diseases. (B) Comparisons of the numbers of metabolic diseases in populations with different vascular diseases. (C) The incidence rates of different vascular diseases in populations with different metabolic diseases. Hypertension increased the risk of CAVD and BVD, while dyslipidemia increased the risk of CAVD (shown by OR value and 95% CI). (D) The incidence rates of different vascular diseases in groups of different numbers of metabolic diseases. Patients with 3, 4 or 5 abnormal metabolisms had significant high risk of CAVD (shown by OR value and 95% CI). VD: vascular diseases; CEVD: cerebrovascular disease; CAVD: cardiovascular disease; BVD: both CEVD and CAVD.
during daily living, resulting in repetitive increments in load on the heart and vessels and increased cardiovascular disease risk. RAS system activation in hypertension patients may also play some role in the development of CAVD [19]. Except for hypertension, increase of one metabolic disease could increase 62% risk of CAVD; replacement of metabolic disease diagnoses with continuous metabolic indexes improved the goodness-of-fit (extra 13.5%) in logistic regression. These results were coordinate with some other researches, they also thought more metabolic indices [20] and more measurements [21] of their values could improve the prediction a little more. So, in order to get the most protection effect on CAVD, we recommend overall control of metabolic indexes in elderly males, besides the greatest content rational control of blood pressure. Unlike CAVD, MS was an independent risk factor of CEVD. Neither the increment of metabolic diseases, grouping by three abnormal metabolisms nor MS components could replace the effect of MS, which indicated that MS affects CEVD independent of the accumulating its components’ effects. Insulin resistance (IR) is generally accepted as the primary underlying abnormality that precedes and contributes
to MS [22], and the currently used indicators are HOMA-IR, INS and C-peptide. In our analysis, it was surprising that C-peptide could replace the effect of MS on CEVD. Though there were many researches focused on MS and CEVD [23,24], its mechanism was seldom explored. Similarly, none of the studies on C-peptide and CEVD discovered its role in the relation of MS and CEVD [15,25]. To our knowledge, it was reported the first time that C-peptide level was the underlying mechanism of the CAVD risk effect of MS. More CEVD-protective effect could be observed when C-peptide 52.43 U/L. Therefore, it is important to increase insulin sensitivity in elderly patients; for patients with MS, if necessary, the administration of insulin sensitivity drugs, such as metformin, might offer better vascular protection effects. Sex hormone levels were found to be closely related with the risk of CEVD development as reported before [13]: 12.55% risk of CEVD related with the change of sex hormones and independent of metabolic risk factors; T/E2 ratio plays a key role in the development of CEVD (better balanced between 0.13–0.15). But the level of FE2, above which the vascular protective effect would be
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Figure 2. CEVD ROC curves and tangent points of metabolic and gonadal risk factors. (A) CEVD positive ROC curve. (B) ROC curve of FE2. (C) Patients were divided into two groups with C-peptide ¼ 2.43 as the tangent point. The CEVD incidence rates in these groups were significantly different (p ¼ 0.01). (D) Quartile-based analyses. ‘‘Q4:Q1–3’’ means the CEVD risk in Q4, compared to the pooled results from Q1–3.
Figure 3. BVD ROC curves and tangent points of metabolic and gonadal risk factors. (A) BVD positive ROC curve. (B) ROC curve of FE2. (C) Patients were divided into two groups with FE2 ¼ 0.66 as the tangent point. The BVD incidence rates in these groups were significantly different (p ¼ 0.01). (D) Using men in quartile 1 (Q1) as a reference, the BVD risks in Q2, Q3, Q4 and ‘‘Q4:Q1– 3’’ are shown.
observed, was not clear in the former study. In this study we confirmed by ROC curve that FE2 was the only sex hormone that had protective effect on vascular; and that FE2 ¼ 0.66 pmol/L was a tangent point to reduce vascular disease development. Population with the FE2 lower than
0.66 pmol/L will have 50% less CEVD incidence than that of higher than 0.66 pmol/L. Therefore, to provide the vascular protective effects in elderly males with high CEVD risk, appropriate doses of supplemental estrogen should be considered.
DOI: 10.3109/13685538.2014.1002082
Metabolic and gonadal risk factors of vascular diseases in elderly males
Aging Male Downloaded from informahealthcare.com by Kainan University on 04/15/15 For personal use only.
Conclusion Metabolic diseases and sex hormone levels play different roles in the development of CAVD and CEVD. CAVD relates only with metabolic risk factors; and the overall controlling of metabolic indexes, especially hypertension, will be more important. CEVD development associates with MS; higher C-peptide is the underlying mechanism. FE2 level plays an important protective role in CEVD development independent of metabolism. So we believed that in order to get more optimized vascular protective effects in elderly males, the clinic methods for vascular protection should be promoted differently according to the evaluation of their risks of CAVD and CEVD. To elderly men with high risk of cardiovascular disease, improved control and management of the metabolic diseases would be critical. While to elder males who had high risk of CEVD or had high risk of both CAVD and CEVD, attention should be paid to low FE2 level, in addition to metabolic risk factors and insulin resistance.
Acknowledgements Thanks for the kindness help of Dr. Wang (Pulmonary division, Boston Children’s Hospital, MA, USA), who helps a lot in language revise.
Declaration of interest The authors have declared that no conflict of interest exists. This work was supported by the grants from the National Natural Science Foundation of China (NFSC, No. 81173625 and No. 81373458).
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7. Grassi D, Ferri L, Desideri G, et al. Chronic hyperuricemia, uric acid deposit and cardiovascular risk. Curr Pharm Des 2013;19: 2432–8. 8. Poss J, Custodis F, Werner C, et al. Cardiovascular disease and dyslipidemia: beyond LDL. Curr Pharm Des 2011;17:861–70. 9. Sher L. High and low testosterone levels may be associated with suicidal behavior in young and older men, respectively. Aust N Z J Psychiatry 2012. 10. Francomano D, Bruzziches R, Natali M, et al. Cardiovascular effect of testosterone replacement therapy in aging male. Acta Biomed 2010;81:101–6. 11. Dos Santos RL, da Silva FB, Ribeiro RF, Stefanon I. Sex hormones in the cardiovascular system. Horm Mol Biol Clin Investig 2014;18: 89–103. 12. Naessen T, Bergquist J, Lind L, Kushnir MM. Higher endogenous estrogen levels in 70-year-old women and men: an endogenous response to counteract developing atherosclerosis? Menopause 2012. 13. Gong Y, Xiao H, Li C, et al. Elevated t/e2 ratio is associated with an increased risk of cerebrovascular disease in elderly men. PLoS One 2013;8:e61598. 14. Gong Y, Xiao H, Bai J, et al. Association between sex hormone levels and abnormal metabolism in a population of elderly Chinese men. Aging Male 2013;16:8–16. 15. Kotb NA, Gaber R, Salama M, et al. Clinical and biochemical predictors of increased carotid intima–media thickness in overweight and obese adolescents with type 2 diabetes. Diab Vasc Dis Res 2012;9:35–41. 16. Shabtai R, Shapiro MS, Orenstein D, et al. The antithyroid arthritis syndrome reviewed. Arthritis Rheum 1984;27:227–9. 17. Rinaldi S, Geay A, Dechaud H, et al. Validity of free testosterone and free estradiol determinations in serum samples from postmenopausal women by theoretical calculations. Cancer Epidemiol Biomarkers Prev 2002;11:1065–71. 18. Thanassoulis G, Lyass A, Benjamin EJ, et al. Relations of exercise blood pressure response to cardiovascular risk factors and vascular function in the Framingham Heart Study. Circulation 2012;125: 2836–43. 19. Ruiz-Ortega M, Lorenzo O, Ruperez M, et al. Role of the renin– angiotensin system in vascular diseases: expanding the field. Hypertension 2001;38:1382–7. 20. Miyagawa N, Murakami Y, Okayama A, et al. Prevalence, treatment, and control of cardiovascular disease risk factors among adults in Shiga Prefecture: analysis using the receipt and health checkup information database in Japan. Nihon Koshu Eisei Zasshi 2014;61:333–41. 21. Bell K, Hayen A, McGeechan K, et al. Effects of additional blood pressure and lipid measurements on the prediction of cardiovascular risk. Eur J Prev Cardiol 2012;19:1474–85. 22. Resnick HE, Jones K, Ruotolo G, et al. Insulin resistance, the metabolic syndrome, and risk of incident cardiovascular disease in nondiabetic american indians: the Strong Heart Study. Diabetes Care 2003;26:861–7. 23. Jadidi E, Mohammadi M, Moradi T. High risk of cardiovascular diseases after diagnosis of multiple sclerosis. Mult Scler 2013;19: 1336–40. 24. Maksimovic M, Vlajinac H, Radak D. Metabolic syndrome and restenosis of carotid artery. Vojnosanit Pregl 2014;71: 298–300. 25. Walcher D, Marx N. Advanced glycation end products and C-peptide-modulators in diabetic vasculopathy and atherogenesis. Semin Immunopathol 2009;31:103–11.
ORIGINAL ARTICLE
Metabolic diseases and sex hormone levels affect differently in the development of cardiovascular and cerebrovascular diseases in elderly males
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Yanping Gong*, Xiaoling Cheng*, Chunlin Li, Jian Li, Mengmeng Jin, Banruo Sun, and Hui Tian Department of Geriatric Endocrinology, The Chinese People’s Liberation Army General Hospital, Beijing, China
Abstract
Keywords
Objective: This single-centre cross-sectional study aimed to investigate the metabolic and gonadal risk factors of vascular diseases in elderly males. Methods: After screening, 337 subjects aged 60–90 were found to be qualified. Odds ratios (ORs) in cross-table analyses and exp(B) in logistic regression analyses were used to evaluate the vascular risk of dependent factors. R2 of logistic regression equation was used to estimate the goodness-of-fit of vascular diseases logistic regression models. Results: Hypertension increased the risk of cardiovascular disease (CAVD) in elderly men approximately 3-fold. The number of metabolic diseases also correlated with incremental risks of CAVD; presence of one abnormality approximately increases the risk approximately 62%. Cerebrovascular disease (CEVD) development was closely associated with both metabolic syndrome and sex hormone levels; their explanation effects of single action and combined action were 13.2%, 12.55% and 28.5%. C-peptide might be the underlying mechanism of the metabolic syndrome’s effect on CEVD. C-peptide ¼ 2.43 U/L and FE2 ¼ 0.66 were the tangent points in receiver operating characteristic (ROC) analyses. Conclusions: Metabolic diseases and sex hormones play different roles in the development of CAVD and CEVD, the methods for vascular protection in elderly men should be promoted differently according to the their risks of CAVD and CEVD.
Elderly, male, metabolic syndrome, sex hormone, vascular disease
Introduction Cardiovascular disease (CAVD) and cerebrovascular disease (CEVD) are major cause of morbidity and mortality in the elderly [1]. More than 1.5 million people die from vascular diseases every year. Metabolic diseases and sex hormone levels are believed to be the risk factors of both of these vascular diseases. But, these two factors have been largely observed separately. Metabolic syndrome (MS) [2] is the cluster of abnormal metabolism that includes hypertension, hyperglycemia, excess abdominal fat, high triglycerides and low high-density lipoprotein (HDL). It is quite plausible that the current MS epidemic will induce a new worldwide CAVD epidemic. But the relationship of MS and CAVD is subject to debate. In the Framingham Offspring Study, MS and homeostasis model assessment - insulin resistance (HOMA-IR) did not
*These authors contributed equally to this work. Address for correspondence: Chunlin Li, Department of Geriatric Endocrinology, the Chinese People’s Liberation Army General Hospital, Beijing 100853, China. Tel: +86 13810921655. Fax: +86 10 66937711. E-mail: [email protected]
History Received 20 September 2014 Revised 11 December 2014 Accepted 21 December 2014 Published online 6 February 2015
independently predict the incidence of CAVD [3,4]. It is also known that although black men have a higher prevalence of MS, their risk of MI is not proportionally increased [5]. Some researchers believe that some specific metabolic disease (like hypertension, obesity, dyslipidemia, diabetes, hyperuricemia) might play an independent role in the development of CAVD, other than MS as a whole [3,6–8]. The relationships between the total testosterone (TT) levels, estradiol (E2) levels and vascular diseases have also been the subjects of much research [9]. Some researchers report that low TT levels are associated with increased CAVD [2,10], while others claim that high TT levels have been associated with sudden cardiac death [11]. However, estrogen is significantly associated with the risk of vascular disease. In healthy young men, aromatase inhibition reduces plasma E2 levels, and this reduction is associated with reduced flowmediated dilatation of the brachial artery [12]. Our previous study [13] showed that T/E2 balance plays a key role in the relationship between sex hormones and the risk of CEVD. Extremely low T/E2 and inappropriately high T/E2 ratio can both harm the brain blood vessels. There also exist a relationship between metabolic diseases and sex hormone levels [13]. We reported previously that
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metabolic factors could regulate hormone levels in elderly males through their effects on sex hormone-binding globulin (SHBG) levels [14]. The extents of the specific roles of metabolic diseases and sex hormones on CAVD and CEVD, however, are not clear. Given the correlation of increased age and incidence of metabolic diseases and variations of sex hormones, this issue becomes more relevant. Better control of either the metabolic diseases or sex hormone variations can lead to decrease in healthcare spending. Thus, we designed this study as an investigation of the association between metabolic diseases, sex hormone levels and the developments of CAVD and CEVD in elderly males to provide a clinical basis for the prevention in elder men.
Methods
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Study population This single-centre cross-sectional study enrolled 1920 men above 60 years of age who underwent routine physical examinations at the Chinese People’s Liberation Army General Hospital. Overall, 337 subjects were included in the analyses. The screening details were provided in previous studies [3,14]. The study was carried out in accordance with the Declaration of Helsinki and ARRIVE guidelines, and was approved by the Ethics Committee of the Chinese People’s Liberation Army General Hospital (reference number 12BJZ41) and written informed consent was obtained from the patient or assent from their relatives. Clinical parameters and laboratory measurements After the patients were fasted for at least 8 h overnight, physical examination, fasting venous blood samples, medical history were obtained by trained physicians during the next morning between 6:00 and 8:00. A postprandial venous blood sample was extracted 2 h after the consumption of 100 g glucose. The blood samples were immediately centrifuged for 15 min at 4 C and stored at 20 C. All of the samples were tested within 1 week. An automated enzymatic procedure (Cobas E601; Roche, Basel, Switzerland) was used to determine all the biochemistry indices. Diagnoses of metabolic diseases (including metabolic syndrome, abnormal metabolic syndrome components and hyperuricemia), CAVD or CEVD are provided in previous studies [3,14]. New diagnoses were made if abnormal results were obtained [14]. Total TT, E2, SHBG, follicle-stimulating hormone (FSH) and luteinising hormone [15] levels were measured automatically with an electrochemiluminescence system (Roche Cobas C6000, Roche Diagnostics GmbH, Mannheim, Germany). Free testosterone (FT) and bioactive testosterone [16] levels were calculated with Vermeulen’s formula, free estradiol (FE2) levels were calculated according to the formula reported by Rinald et al. [17], and the T/E2 and E2/SHBG ratios were also calculated. The FT index (FTI) was calculated as FTI ¼ T/SHBG, and the testosterone secretion index (TSI) was calculated as TSI ¼ T/LH. Statistical analyses SPSS 17.0 (SPSS Inc., Chicago, IL) was used for both data management and analyses. Continuous variables were
Aging Male, 2015; 18(1): 27–33
presented as the mean ± SD. We categorised the patients according to vascular disease diagnoses as follows: CAVD only (CAVD), CEVD only (CEVD), both types of vascular disease (BVD) and controls. The data distribution was evaluated before analysis. Multiple-factor linear regression was used to compare the normally distributed data, and nonparametric K-sample tests were used to compare the nonnormally distributed data (Table 1). Classifying variables were reported as percentages. 2 tests were performed for 2group comparisons. Cross-table analyses were used for intergroup comparisons. The influences of metabolic and gonadal factors on vascular disease development and interactions were further studied with logistic regression analyses. Four models were used in logistic regression analyses (Table 2). Odds ratios [16] in cross-table analyses and exp(B) in logistic regression analyses were used to evaluated the vascular risk of dependent factors. R2 in logistic regression equation was used to estimate the goodness-of-fit of vascular diseases logistic regression models. The 95% confidence intervals (95% CI) were calculated to describe the magnitudes of the associations. ROC curves were used to analyse the tangent points of vascular disease-related continuous variables, the tangent point was the point with the best sensitivity, specificity and the Youden index (sensitivity + specifity 1). p50.05 was considered statistically significant.
Results Vascular diseases in this population The cohort included 101 (29.97%) and 31 (9.20%) subjects with only CAVD and CEVD, respectively. Fifty-four (16.02%) subjects had both type of the vascular diseases (BVD). The morbidity rates in the CAVD, CEVD and BVD groups all increased with age (p50.01). Metabolic diseases in patients with vascular diseases Subjects without any metabolic disease only accounted for 2.67%; those with 1–5 metabolic diseases accounted for 4.74%, 18.99%, 28.78%, 36.49% and 8.30%, respectively. Subjects with vascular diseases had a higher percentage of metabolic diseases than those without vascular diseases, and the hypertension incidence in CAVD, BVD and the dyslipidemia incidence in BVD differed significantly from those without vascular diseases (p50.01, p50.05, Figure 1A and B). Cross-table analyses showed that the risks of CAVD and BVD (odds ratio, OR) in hypertension patients were 3.24and 3.28-fold of that in normal blood pressure subjects; while the risk of CAVD in dyslipidemia was 2.14-fold (Figure 1C) of that in normal plasma lipid subjects. The risk of CAVD development significantly increased in patients with 3, 4 or 5 metabolic diseases compared with non-metabolic diseases subjects, with the OR values were 1.68, 1.80 and 2.11, respectively (Figure 1D). Sex hormone levels in patients with vascular diseases Plasma TT, BT, FTI, TSI, E2, E2/SHBG and PCG levels were lower in patients with vascular diseases than in the control group, while the LH, FSH and SHBG levels were higher in the vascular disease groups. However, after adjusting for age
Metabolic and gonadal risk factors of vascular diseases in elderly males
DOI: 10.3109/13685538.2014.1002082
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Table 1. Differences in sex hormone levels after grouping the subjects according to vascular disease.
TT (nmol/L) FT (nmol/L) BT (nmol/L) T/E2 E2 (pmol/L) E2/SHBG FE2 PROG (nmol/L) LH (IU/L) FSH (IU/L) FTI TSI (nmol/IU) SHBG (nmol/L)
Control
CEVD
CAVD
BVD
5.16 ± 0.16 0.22 ± 0.01 5.13 ± 0.16 0.19 ± 0.01 29.14 ± 0.71 0.65 ± 0.03 0.60 ± 0.28 275.05 ± 11.24 9.39 ± 0.49 16.32 ± 1.29 0.11 ± 0.09 0.72 ± 0.03 51.63 ± 1.67
5.06 ± 0.35 0.25 ± 0.02 4.99 ± 0.35 0.19 ± 0.01 27.34 ± 1.54 0.61 ± 0.06 0.50 ± 0.02 217.54 ± 24.73 10.55 ± 1.07 19.57 ± 2.84 0.18 ± 0.01 0.68 ± 0.07 53.24 ± 3.67
4.94 ± 0.19 0.21 ± 0.01 4.94 ± 0.19 0.18 ± 0.01 28.44 ± 0.84 0.65 ± 0.03 0.51 ± 0.02 242.96 ± 13.44 9.17 ± 0.58 17.01 ± 1.54 0.11 ± 0.00 0.68 ± 0.04 49.03 ± 2.01
5.01 ± 0.27 0.21 ± 0.01 4.94 ± 0.27 0.18 ± 0.01 28.60 ± 1.17 0.62 ± 0.04 0.51 ± 0.02 227.18 ± 18.93 9.52 ± 0.82 17.08 ± 2.17 0.10 ± 0.00 0.61 ± 0.05 54.56 ± 2.81
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All data from the different vascular disease groups were adjusted by age and smoking history.
and smoking history, the differences between the control and vascular disease groups decreased, and all of the significant differences disappeared (Table 1). Effects of metabolic diseases and sex hormone levels on vascular diseases Four models were used in logistic regression analyses. Models 1 and 2 evaluated the effect of metabolic diseases and sex hormone levels separately; model 3 estimated the combined effect of metabolic diseases and sex hormone levels; model 4 replaces the diagnoses of metabolic diseases in model 3 with corresponding continuous metabolic indexes. We summarized the results of four models of each vascular disease as below (Table 2). (1) Age was an independent risk factor for all vascular diseases (exp(B): 1.05–1.87). (2) CAVD was closely associated with metabolic diseases. The goodness-of-fit of metabolic diseases diagnoses in CAVD regression was 17.60%, while continuous metabolic indexes accounted for 31.10% (R2). The CAVD risk increased in patients with hypertension (exp(B)¼3.10; p50.01) and increased with the increment of metabolic diseases (Ab-Met) (exp(B)¼1.62; p50.01). Sex hormones did not influence the goodness-of-fit and risks of metabolic factors, and none of the sex hormone levels was included in the CAVD logistic regression equation. (3) CEVD development is closely associated with both metabolic diseases and sex hormone levels (R2 were 13.2% and 12.55%, respectively, and combined R2 was 28.5%). MS associated significantly with the CEVD development (exp(B)¼4.24; p50.05), and the role of MS could not be replaced by the increment of metabolic diseases and groups with more than or less than three abnormal metabolism. But, in model 4 where continuous metabolic indexes were introduced, MS was replaced by C-peptide (with similar R2 and exp(B)). If C-peptide was excluded, FBG, PBG, INS and HOMA could not substitute for the role of C-peptide. (4) The risk of BVD increased in patients with hypertension (exp(B)¼2.87; p50.05) and with the increment of metabolic diseases (exp(B)¼1.87; p50.01). BVD reversely correlated with FE2 levels significantly (exp(B)¼0.03; p50.01).
Analyses of the tangent points of the metabolic indicators and sex hormones ROC curves (Figure 2A) showed that FE2 was the only factor that had a CEVD protective effect. No ideal Youden index was obtained from all the sex hormones, so they were analyzed by quarter (Figure 2D). The tangent points of age and C-peptide in CEVD ROC curves were obtained at 74.5 and 2.43 (Figure 2B). Patients were then divided into two groups according to the tangent point of C-peptide ¼ 2.43; the results showed that the CEVD incidence rates in these two groups were significantly different (p ¼ 0.01; Figure 2C). BVD ROC curve showed that age and FE2 were closely associated with BVD development (Figure 3A and B). The tangent point for age also occurred at 74.5 years. Patients were divided into two groups according to the tangent point of FE2 ¼ 0.39, and the results showed that the incidence rates of BVD in these two groups were significantly different (p50.01) (Figure 3C). A quartile-based analysis also showed that in Q3 and Q4, FE2 was associated with a lower risk of a BVD event (OR ¼ 0.38 and 0.27; p ¼ 0.02 and 0.01, respectively), compared to the values in Q1 (Figure 3D).
Discussion The result of our study showed that sex hormone levels and metabolic diseases had different effects on CAVD and CEVD: CAVD related only with metabolic diseases, while CEVD had close relationship with both sex hormone levels and metabolic diseases; furthermore, metabolic diseases affected CAVD and CEVD differently. It was really interesting that hypertension was the most important metabolic risk factor that correlated with CAVD, other than MS, diabetes, BMI, etc. Hypertension might increase CAVD risk in an independent way different with other metabolic factors, because multifactor logistic regression analyses did not change much of its risk compared with simple cross-table analysis. Our findings are further corroborated by other studies. Besides Framingham Offspring Study [3], Bello-Rodriguez et al. [6] also found that hypertension is for itself an individual risk to developing cardiovascular disease with high frequency un-related with MS and diabetes. Research of Thanassoulis et al. [18] suggest that impaired vascular function may contribute to exaggerated BP responses
7.60
Model 2
1.13** 3.10 (1.62–5.93)
17.60
Model 3
0.48** 1.62 (1.18–2.22)
31.10
Model 4
1.01* 2.73 (1.05–7.11)
13.20
Model 1
4.33* 75.71 (1.10–4100)
12.50
Model 2
9.11* 4100 (4.17–4100)
5.79* 0.01 (50.01–0.69)
1.45* 4.24 (1.23–14.67)
28.50
Model 3
29.42* 4100 (0.95–4100)
1.41* 4.09 (1.14–14.68)
27.20
Model 4
1.01* 2.74 (1.17–6.41)
23.50
Model 1
Model 1: All metabolic categorical variables, age, smoking history and hepatic/renal function were included in the regression equation. 2: All sex hormones, age, smoking history and hepatic/renal function were included in the regression equation. 3: All sex hormones, all metabolic categorical variables, age, smoking history and hepatic/renal function were included in the regression equation. 4: All sex hormones, all metabolic continuous variables, age, smoking history and hepatic/renal function were included in the regression equation.
1.13** 3.10 (1.62–5.93)
17.60
Model 1
CEVD
2.42** 0.09 (0.02–0.46)
28.80
Model 2
30.20
Model 3
2.97** 0.05 (0.01–0.33)
1.06* 2.87 (1.16–7.14)
BVD
4.00** 0.02 (50.01–0.21)
0.63** 1.87 (1.17–2.99)
38.30
Model 4
Y. Gong et al.
Notes: Model Model Model
R HP B exp(B) 95%CI MS B exp(B) 95%CI Num of Ab-Met B exp(B) 95%CI C-peptide B exp(B) 95%CI T/E2 B exp(B) 95%CI FE2 B exp(B) 95%CI FT B exp(B) 95%CI
2
CAVD
Table 2. Logistic regression analyses of different vascular disease group.
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30 Aging Male, 2015; 18(1): 27–33
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DOI: 10.3109/13685538.2014.1002082
Metabolic and gonadal risk factors of vascular diseases in elderly males
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Figure 1. The relationships between metabolic diseases and the incidence rates of different vascular diseases. (A) The incidence rates of each metabolic diseases in populations with different vascular diseases. The rankings are arranged from low to high according to the incidence rates in the control group. *p50.05, **p50.01 versus the group without vascular diseases. (B) Comparisons of the numbers of metabolic diseases in populations with different vascular diseases. (C) The incidence rates of different vascular diseases in populations with different metabolic diseases. Hypertension increased the risk of CAVD and BVD, while dyslipidemia increased the risk of CAVD (shown by OR value and 95% CI). (D) The incidence rates of different vascular diseases in groups of different numbers of metabolic diseases. Patients with 3, 4 or 5 abnormal metabolisms had significant high risk of CAVD (shown by OR value and 95% CI). VD: vascular diseases; CEVD: cerebrovascular disease; CAVD: cardiovascular disease; BVD: both CEVD and CAVD.
during daily living, resulting in repetitive increments in load on the heart and vessels and increased cardiovascular disease risk. RAS system activation in hypertension patients may also play some role in the development of CAVD [19]. Except for hypertension, increase of one metabolic disease could increase 62% risk of CAVD; replacement of metabolic disease diagnoses with continuous metabolic indexes improved the goodness-of-fit (extra 13.5%) in logistic regression. These results were coordinate with some other researches, they also thought more metabolic indices [20] and more measurements [21] of their values could improve the prediction a little more. So, in order to get the most protection effect on CAVD, we recommend overall control of metabolic indexes in elderly males, besides the greatest content rational control of blood pressure. Unlike CAVD, MS was an independent risk factor of CEVD. Neither the increment of metabolic diseases, grouping by three abnormal metabolisms nor MS components could replace the effect of MS, which indicated that MS affects CEVD independent of the accumulating its components’ effects. Insulin resistance (IR) is generally accepted as the primary underlying abnormality that precedes and contributes
to MS [22], and the currently used indicators are HOMA-IR, INS and C-peptide. In our analysis, it was surprising that C-peptide could replace the effect of MS on CEVD. Though there were many researches focused on MS and CEVD [23,24], its mechanism was seldom explored. Similarly, none of the studies on C-peptide and CEVD discovered its role in the relation of MS and CEVD [15,25]. To our knowledge, it was reported the first time that C-peptide level was the underlying mechanism of the CAVD risk effect of MS. More CEVD-protective effect could be observed when C-peptide 52.43 U/L. Therefore, it is important to increase insulin sensitivity in elderly patients; for patients with MS, if necessary, the administration of insulin sensitivity drugs, such as metformin, might offer better vascular protection effects. Sex hormone levels were found to be closely related with the risk of CEVD development as reported before [13]: 12.55% risk of CEVD related with the change of sex hormones and independent of metabolic risk factors; T/E2 ratio plays a key role in the development of CEVD (better balanced between 0.13–0.15). But the level of FE2, above which the vascular protective effect would be
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Figure 2. CEVD ROC curves and tangent points of metabolic and gonadal risk factors. (A) CEVD positive ROC curve. (B) ROC curve of FE2. (C) Patients were divided into two groups with C-peptide ¼ 2.43 as the tangent point. The CEVD incidence rates in these groups were significantly different (p ¼ 0.01). (D) Quartile-based analyses. ‘‘Q4:Q1–3’’ means the CEVD risk in Q4, compared to the pooled results from Q1–3.
Figure 3. BVD ROC curves and tangent points of metabolic and gonadal risk factors. (A) BVD positive ROC curve. (B) ROC curve of FE2. (C) Patients were divided into two groups with FE2 ¼ 0.66 as the tangent point. The BVD incidence rates in these groups were significantly different (p ¼ 0.01). (D) Using men in quartile 1 (Q1) as a reference, the BVD risks in Q2, Q3, Q4 and ‘‘Q4:Q1– 3’’ are shown.
observed, was not clear in the former study. In this study we confirmed by ROC curve that FE2 was the only sex hormone that had protective effect on vascular; and that FE2 ¼ 0.66 pmol/L was a tangent point to reduce vascular disease development. Population with the FE2 lower than
0.66 pmol/L will have 50% less CEVD incidence than that of higher than 0.66 pmol/L. Therefore, to provide the vascular protective effects in elderly males with high CEVD risk, appropriate doses of supplemental estrogen should be considered.
DOI: 10.3109/13685538.2014.1002082
Metabolic and gonadal risk factors of vascular diseases in elderly males
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Conclusion Metabolic diseases and sex hormone levels play different roles in the development of CAVD and CEVD. CAVD relates only with metabolic risk factors; and the overall controlling of metabolic indexes, especially hypertension, will be more important. CEVD development associates with MS; higher C-peptide is the underlying mechanism. FE2 level plays an important protective role in CEVD development independent of metabolism. So we believed that in order to get more optimized vascular protective effects in elderly males, the clinic methods for vascular protection should be promoted differently according to the evaluation of their risks of CAVD and CEVD. To elderly men with high risk of cardiovascular disease, improved control and management of the metabolic diseases would be critical. While to elder males who had high risk of CEVD or had high risk of both CAVD and CEVD, attention should be paid to low FE2 level, in addition to metabolic risk factors and insulin resistance.
Acknowledgements Thanks for the kindness help of Dr. Wang (Pulmonary division, Boston Children’s Hospital, MA, USA), who helps a lot in language revise.
Declaration of interest The authors have declared that no conflict of interest exists. This work was supported by the grants from the National Natural Science Foundation of China (NFSC, No. 81173625 and No. 81373458).
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