The association and predictive value analysis of metabolic syndrome combined with resting heart rate on cardiovascular autonomic neuropathy in the general Chinese population

Yu Lu, Zi-Hui Tang, Fangfang Zeng, Yiming Li, Linuo Zhou, Yu Lu, Zi-Hui Tang, Fangfang Zeng, Yiming Li, Linuo Zhou

Abstract

Background: The purpose of this study was to explore the extent of associations of cardiovascular autonomic neuropathy (CAN) with metabolic syndrome (MetS) and resting heart reate (HR), and to evaluate the predictive value of MetS combined with HR on CAN in a large sample derived from a Chinese population.

Materials and methods: We conducted a large-scale, population-based, cross-sectional study to explore the relationships of CAN with MetS and resting HR. This study included 2092 participants aged 30-80 years, and a total of 387 subjects were diagnosed with CAN in our dataset. The associations of CAN with MetS and resting HR were assessed by a multivariate logistic regression (MLR) analysis (using subjects without CAN as a reference group) after controlling for potential confounding factors. The predictive performance of resting HR and MetS was evaluated using the area under the receiver-operating characteristic curve (AUC).

Results: A tendency toward increased CAN prevalence with increasing resting HR was reported (p for trend < 0.001). MLR analysis showed that MetS and resting HR were very significantly and independently associated with CAN (β = 0.495 for MetS and β = 0.952 for HR, P < 0.001 for both). Resting HR alone and combined with MetS (MetS-HR) strongly predicted CAN (AUC = 0.719, P < 0.001 for resting HR and AUC = 0.735, P < 0.001 for MetS-HR).

Conclusion: Our findings signify that MetS and resting HR were very significantly and independently associated with CAN in the general Chinese population. Resting HR and MetS-HR both have a high value in predicting CAN in the general population.

Figures

Figure 1
Figure 1
Cardiovascular autonomic neuropathy (CAN) prevalence according to metabolic syndrome (MetS). The CAN prevalence was 14.54% and 24.49% in respective groups according to MetS. P value for trend was less then 0.001.
Figure 2
Figure 2
Cardiovascular autonomic neuropathy (CAN) prevalence according to resting heart rate (HR). The CAN prevalence was 5.92%, 12.93%, 23.94% and 53.67% in respective groups according to HR. P value for trend was less then 0.001.
Figure 3
Figure 3
Cardiovascular autonomic neuropathy (CAN) prevalence according to the variable of metabolic syndrome (MetS) combined with resting heart rate (MetS-HR). The CAN prevalence was 5.32%, 7.23%, 9.8%, 17.81%, 21.15%, 27.38%, 45.87% and 61.46% in respective groups according to MetS-HR. P value for trend was less then 0.001.
Figure 4
Figure 4
Receiver operating characteristic curves showed the performance of resting heart rate (HR), metabolic syndrome (MetS) and categorical variable of MetS + HR in predicting cardiovascular autonomic neuropathy (CAN) prevalence in this dataset. The 95% confidence interval (CI) is given in parentheses. AUC represents area under the curve. HR: AUC = 0.719 (95% CI : 0.690-0.748), P < 0.001; MetS: AUC = 0.579 (95% CI: 0.547-0.611), P < 0.001; MetS-HR: AUC = 0.735 (95% CI: 0.707-0.763), P < 0.001.

References

    1. Hazari MA, Khan RT, Reddy BR. et al.Cardiovascular autonomic dysfunction in type 2 diabetes mellitus and essential hypertension in a South Indian population. Neurosciences (Riyadh) 2012;17:173–175.
    1. Kuehl M, Stevens MJ. Cardiovascular autonomic neuropathies as complications of diabetes mellitus. Nat Rev Endocrinol. 2012;8:405–416. doi: 10.1038/nrendo.2012.21.
    1. Spallone V, Ziegler D, Freeman R, Cardiovascular autonomic neuropathy in diabetes: clinical impact, assessment, diagnosis, and management. Diabetes Metab Res Rev. 2011. [Epub ahead of print]
    1. Garruti G, Giampetruzzi F, Vita MG. et al.Links between metabolic syndrome and cardiovascular autonomic dysfunction. Exp Diabetes Res. 2012;2012:615835.
    1. Laitinen T, Lindstrom J, Eriksson J. et al.Cardiovascular autonomic dysfunction is associated with central obesity in persons with impaired glucose tolerance. Diabet Med. 2011;28:699–704. doi: 10.1111/j.1464-5491.2011.03278.x.
    1. Iodice V, Low DA, Vichayanrat E. et al.Cardiovascular autonomic dysfunction in MSA and Parkinson’s disease: similarities and differences. J Neurol Sci. 2011;310:133–138. doi: 10.1016/j.jns.2011.07.014.
    1. Ziegler D, Zentai C, Perz S. et al.Selective contribution of diabetes and other cardiovascular risk factors to cardiac autonomic dysfunction in the general population. Exp Clin Endocrinol Diabetes. 2006;114:153–159. doi: 10.1055/s-2006-924083.
    1. Kamphuis MH, Geerlings MI, Dekker JM. et al.Autonomic dysfunction: a link between depression and cardiovascular mortality? The FINE Study. Eur J Cardiovasc Prev Rehabil. 2007;14:796–802. doi: 10.1097/HJR.0b013e32829c7d0c.
    1. Lakka HM, Laaksonen DE, Lakka TA. et al.The metabolic syndrome and total and cardiovascular disease mortality in middle-aged men. JAMA. 2002;288:2709–2716. doi: 10.1001/jama.288.21.2709.
    1. Aurigemma GP, Gaasch WH. Clinical practice. Diastolic heart failure. N Engl J Med. 2004;351:1097–1105. doi: 10.1056/NEJMcp022709.
    1. Maser RE, Lenhard MJ. Cardiovascular autonomic neuropathy due to diabetes mellitus: clinical manifestations, consequences, and treatment. J Clin Endocrinol Metab. 2005;90:5896–5903. doi: 10.1210/jc.2005-0754.
    1. Vinik AI, Ziegler D. Diabetic cardiovascular autonomic neuropathy. Circulation. 2007;115:387–397. doi: 10.1161/CIRCULATIONAHA.106.634949.
    1. Rasic-Milutinovic ZR, Milicevic DR, Milovanovic BD. et components of metabolic syndrome contribute to cardiac autonomic neuropathy in non-diabetic patients? Saudi Med J. 2010;31:650–657.
    1. Chang CJ, Yang YC, Lu FH. et al.Altered cardiac autonomic function may precede insulin resistance in metabolic syndrome. Am J Med. 2010;123:432–438. doi: 10.1016/j.amjmed.2009.07.031.
    1. Li Z, Tang ZH, Zeng F, Associations between the severity of metabolic syndrome and cardiovascular autonomic function in a Chinese population. J Endocrinol Invest. 2013. [Epub ahead of print]
    1. Pickering TG, Hall JE, Appel LJ. et al.Recommendations for blood pressure measurement in humans: an AHA scientific statement from the Council on High Blood Pressure Research Professional and Public Education Subcommittee. J Clin Hypertens (Greenwich) 2005;7:102–109. doi: 10.1111/j.1524-6175.2005.04377.x.
    1. Grundy SM, Hansen B, Smith SC Jr. et al.Clinical management of metabolic syndrome: report of the American Heart Association/National Heart, Lung, and Blood Institute/American Diabetes Association conference on scientific issues related to management. Circulation. 2004;109:551–556. doi: 10.1161/01.CIR.0000112379.88385.67.
    1. Boudina S, Abel ED. Diabetic cardiomyopathy revisited. Circulation. 2007;115:3213–3223. doi: 10.1161/CIRCULATIONAHA.106.679597.
    1. Brownlee M. The pathobiology of diabetic complications: a unifying mechanism. Diabetes. 2005;54:1615–1625. doi: 10.2337/diabetes.54.6.1615.
    1. Ouwens DM, Diamant M. Myocardial insulin action and the contribution of insulin resistance to the pathogenesis of diabetic cardiomyopathy. Arch Physiol Biochem. 2007;113:76–86. doi: 10.1080/13813450701422633.
    1. Houstis N, Rosen ED, Lander ES. Reactive oxygen species have a causal role in multiple forms of insulin resistance. Nature. 2006;440:944–948. doi: 10.1038/nature04634.
    1. Palmieri V, Russo C, Bella JN. Treatment of isolated left ventricular diastolic dysfunction in hypertension: reaching blood pressure target matters. Hypertension. 2010;55:224–225. doi: 10.1161/HYPERTENSIONAHA.109.144717.
    1. Owan TE, Hodge DO, Herges RM. et al.Trends in prevalence and outcome of heart failure with preserved ejection fraction. N Engl J Med. 2006;355:251–259. doi: 10.1056/NEJMoa052256.
    1. Widlansky ME, Gokce N, Keaney JF Jr. et al.The clinical implications of endothelial dysfunction. J Am Coll Cardiol. 2003;42:1149–1160. doi: 10.1016/S0735-1097(03)00994-X.

Source: PubMed

3
購読する