Significance of Heart Rate in the Prevalence of Metabolic Syndrome and Its Related Risk Factors in Japanese

Transcription

1 ORIGINAL ARTICLE Epidemiology Circ J 2009; 73: Significance of Heart Rate in the Prevalence of Metabolic Syndrome and Its Related Risk Factors in Japanese Eiji Oda, MD; Ryu Kawai, MD Background: Autonomic dysfunction is thought to be an important mechanism of metabolic syndrome (MetS), but there has not been a study on the direct association between MetS and heart rate (HR) in Japanese. Methods and Results: The association between MetS and HR was examined using medical check-up data from 1,880 men and 1,079 women. HR was significantly higher in MetS subjects than in non-mets subjects in both men and women (P< in men, P<0.001 in women). The prevalence of MetS increased linearly through the quartiles of HR in both men and women. HR was significantly correlated with MetS-related risk factors other than uric acid in men and other than uric acid, body mass index, waist circumference, and high-density lipoprotein cholesterol in women. Conclusions: The prevalence of MetS increased linearly with the increase in HR among Japanese men and women, and HR was significantly correlated with MetS-related risk factors. (Circ J 2009; 73: ) Key Words: Autonomic dysfunction; Heart rate; Metabolic syndrome Metabolic syndrome (MetS) may reveal itself through increased adiposity, insulin resistance, 1 leptin resistance, 2 low-grade systemic inflammation, 3 endothelial dysfunction, 4 and autonomic dysfunction, 5,6 However, there are many unresolved problems regarding the definition of MetS MetS may be a pre-disease state of diabetes, cardiovascular disease, fatty liver disease, 13 chronic kidney disease (CKD), 14 and chronic lung disease. 15 Carnethon et al reported that autonomic dysfunction may not only be a consequence of, but also a precursor to, diabetes. 6 Autonomic dysfunction may be not only one of the mechanisms by which MetS develops clustering of risk factors, 5 but also contribute to the development of diabetes and other diseases. In the present study, we examined the cross-sectional associations between heart rate (HR), a global indicator of autonomic dysfunction, and MetS in Japanese men and women. Methods Subjects Between April 1 and November 30 in 2008, 1,928 men and 1,113 women visited a medical check-up center for Ningen Dock, which is a medical check-up program. All were required to fill out a questionnaire compiled by the Ministry of Health, Labor and Welfare for the purpose of Special Health Examination and Instruction, which (Received December 10, 2008; accepted March 9, 2009; released online June 11, 2009) Medical Check-up Center, Tachikawa Medical Center, Nagaoka, Japan Grant: none. Mailing address: Eiji Oda, MD, Medical Check-up Center, Tachikawa Medical Center, Nagacho, Nagaoka , Japan. ijie@venus.sannet.ne.jp All rights are reserved to the Japanese Circulation Society. For permissions, please cj@j-circ.or.jp included questions about history of stroke, ischemic heart disease, chronic renal failure, smoking status, antihypertensive, antidiabetic, and antihyperlipidemic medications, and alcohol consumption. In total, 9 men and 13 women who did not give signed consent, 10 men and 10 women lacking respiratory function data, 3 men and 1 woman lacking data for percentage body fat, 1 man and 1 woman lacking renal function data, and 25 men and 9 women with high-sensitivity C-reactive protein (hs-crp) levels higher than 10 mg/l were excluded, resulting in 1,880 men and 1,079 women for analysis. The protocol for the present study was approved by the Ethics Committee of Tachikawa Medical Center and signed informed consent was given by each subject. Measurements After an overnight fast, blood samples were obtained to measure levels of routine medical check-up tests: glucose, triglycerides, high-density lipoprotein (HDL)-cholesterol, low-density lipoprotein (LDL)-cholesterol, hemoglobin A1c, uric acid, blood cell counts, electrolytes, liver and kidney function tests, including gamma glutamyltransferase (GGT), alanine aminotransferase (ALT), creatinine, and hs-crp. Simple qualitative urinalyses were performed with test papers. Chemical measurements were all performed at BML Nagaoka (Nagaoka, Japan), except for hs-crp, which was measured at BML General Laboratory (Tokyo, Japan) with nephelometry using N-latex CRP-2 (Siemens Healthcare Japan, Tokyo, Japan). The measurement limit of hs-crp was 0.02 mg/l and a value less than the measurement limit was considered as 0.01 mg/l. Respiratory function tests were performed with Autospirometer System 7 (Minato Medical Science, Osaka, Japan). Estimated glomerular filtration rate (egfr, ml min m 2 ) was calculated as 194 creatinine age in men, and 194 creatinine age in women according to the Japanese Society of Nephrology. Body fat percentage was measured with bioelectrical impedance analysis using TBF-210 (TANITA,

2 1432 ODA E et al. Table 1. Basal Data According to the Presence of Metabolic Syndrome in Men MetS (n=277) non-mets (n=1,603) Mean SD Mean SD P value Age, years <0.001 Body mass index, kg/m < Body fat, % < Waist circumference, cm < Systolic blood pressure, mmhg < Diastolic blood pressure, mmhg < Fasting glucose, mg/dl < Triglycerides, mg/dl (171) (95) 61.1 < HDL-cholesterol, mg/dl < hs-crp, mg/l 1.17 (0.62) (0.28) 0.91 < Gamma glutamyltransferase, U/L 73.2 (53) (33) 47.9 < Alanine aminotransferase, U/L 37.8 (31) (21) 16.0 < LDL-cholesterol, mg/dl <0.001 Uric acid, mg/dl < Hemoglobin A1c, % < White blood cell count, /L 6 6,209 1,529 5,451 1,444 < egfr, ml min m <0.01 Heart rate, beats/min < % vital capacity < n % n % Diabetes < JMetS < Current smoker <0.01 Antihypertensive medication < Antidiabetic medication < Antihyperlipidemic medication <0.01 Stroke NS Ischemic heart disease <0.01 Chronic renal failure <0.05 Data in parentheses are medians. MetS, metabolic syndrome defined by revised National Cholesterol Education Program criteria for Japanese; HDL, high-density lipoprotein; hs-crp, high-sensitivity C-reactive protein; LDL, low-density lipoprotein; egfr, estimated glomerular filtration rate (194 creatinine age in men; and 194 creatinine age in women); JMetS, Japanese metabolic syndrome defined by the Examination Committee for Criteria of Metabolic Syndrome. Tokyo, Japan). Average systolic and diastolic blood pressures (SBP/DBP) were calculated from 2 measurements taken while the subjects was seated after a 5-min rest. HR was automatically recorded by ECG. Body weight was measured with the subjects wearing light clothes provided by the center and the weight of the clothes was subtracted from the measured body weight. Waist circumference (WC) was measured at the level of the umbilicus. Body mass index (BMI) was calculated as weight in kilograms divided by the square of height in meters. Statistical Analysis MetS was defined by the revised National Cholesterol Education Program (NCEP) criteria 9 as 3 or more of 5 components where the cutpoint of WC was modified for Japanese as 90 cm in men and 80 cm in women according to the recommendation by the International Diabetes Federation (IDF). 7 The cutpoints of the other components were SBP 130 mmhg and/or DBP 85 mmhg; 150 mg/dl for triglycerides; <40 mg/dl in men and <50 mg/dl in women for HDL-cholesterol; and 100 mg/dl for fasting glucose. Subjects receiving antihypertensive or antidiabetic medication were considered to have the respective component. Japanese MetS (JMetS) defined by the Examination Committee for Criteria of Metabolic Syndrome 16 was also examined because this concept (visceral fat syndrome 17 ) is believed by Japanese medical societies to be the best definition of MetS. The criteria of JMetS are visceral adipose tissue (VAT) area 100 cm 2 or WC 85 in men and 90 in women, and 2 or more of the following 3 components: SBP 130 mmhg and/or DBP 85 mmhg; triglycerides 150 mg/dl; and/or HDL-cholesterol <40 mg/dl both for men and for women; and fasting glucose 110 mg/dl. Diabetes was defined as fasting glucose 126 mg/dl and/or with antidiabetic medication. Blood levels of the MetSrelated risk factors, HR, egfr, and % vital capacity (%VC) were compared between MetS and non-mets subjects, and the prevalence of diabetes, MetS, and JMetS, and blood levels of MetS-related risk factors, egfr, and %VC were compared between subjects with the lowest and highest quartile of HR. Spearman s correlation coefficients between HR and MetS-related risk factors were calculated with Dr- SPSS2. P-values less than 0.05 were considered as statistically significant. Results Baseline data in men are shown in Table 1. BMI, body fat %, WC, SBP, DBP, fasting glucose, triglycerides, hs-crp, GGT, ALT, LDL-cholesterol, uric acid, hemoglobin A1c, white blood cell count, and HR were significantly higher and HDL-cholesterol, egfr, and %VC were significantly lower in MetS subjects than in non-mets subjects. Both diabetes and current smokers were significantly more prevalent in MetS subjects than in non-mets subjects (P< and P<0.01, respectively).

3 MetS and Heart Rate 1433 Table 2. Basal Data According to the Presence of Metabolic Syndrome in Women MetS (n=76) non-mets (n=1,003) Mean SD Mean SD P value Age, years < Body mass index, kg/m < Body fat, % < Waist circumference, cm < Systolic blood pressure, mmhg < Diastolic blood pressure, mmhg < Fasting glucose, mg/dl < Triglycerides, mg/dl (125) (70) 43.5 < HDL-cholesterol, mg/dl < hs-crp, mg/l 0.77 (0.54) (0.20) 0.68 < Gamma glutamyltransferase, U/L 36.3 (26.5) (17) 17.4 < Alanine aminotransferase, U/L 26.2 (23) (15) 8.3 < LDL-cholesterol, mg/dl < Uric acid, mg/dl < Hemoglobin A1c, % < White blood cell count, /L 6 5,418 1,064 4,788 1,245 < egfr, ml min m <0.001 Heart rate, beats/min <0.001 % vital capacity NS n % n % Diabetes < JMetS < Current smoker NS Antihypertensive medication < Antidiabetic medication < Antihyperlipidemic medication < Stroke NS Ischemic heart disease NS Chronic renal failure NS Abbreviations as Table 1. Table 3. MetS-Related Data and Prevalence of MetS, JMetS, and Diabetes by Quartile of Heart Rate in Men Q1 Q2 Q3 Q4 Heart rate range, beats/min (n=419) (n=503) (n=501) (n=457) P value* Mean SD Mean SD Mean SD Mean SD Heart rate, beats/min < Age, years <0.05 Body mass index, kg/m < Body fat, % < Waist circumference, cm < Systolic blood pressure, mmhg < Diastolic blood pressure, mmhg < Fasting glucose, mg/dl < Triglycerides, mg/dl < HDL-cholesterol, mg/dl NS hs-crp, mg/l < Gamma glutamyltransferase, U/L < Alanine aminotransferase, U/L < Uric acid, mg/dl NS White blood cell count, /L 6 5,121 1,223 5,456 1,408 5,739 1,516 5,892 1,622 < egfr, ml min m <0.01 % vital capacity <0.05 n % n % n % n % MetS < JMetS < Diabetes < *Comparisons between Q1 and Q4. Abbreviations as in Table 1. Baseline data in women are shown in Table 2. BMI, body fat %, WC, SBP, DBP, fasting glucose, triglycerides, hs- CRP, GGT, ALT, LDL-cholesterol, uric acid, hemoglobin A1c, white blood cell count, and HR were significantly higher and HDL-cholesterol and egfr were significantly lower in MetS subjects than in non-mets subjects. However, %VC was not significantly different between MetS and non-mets subjects. The prevalence of diabetes was significantly higher in MetS subjects than in non-mets subjects (P<0.0001).

4 1434 ODA E et al. Figure. Prevalence of metabolic syndrome defined by revised National Cholesterol Education Program criteria for Japanese (MetS) and Japanese metabolic syndrome (JMetS) by the quartile of heart rate. Table 4. MetS-Related Data and Prevalence of MetS, JMetS, and Diabetes by Quartile of Heart Rate in Women Q1 Q2 Q3 Q4 Heart rate range, beats/min (n=296) (n=276) (n=245) (n=262) P value* Mean SD Mean SD Mean SD Mean SD Heart rate, beats/min < Age, years NS Body mass index, kg/m NS Body fat, % NS Waist circumference, cm NS Systolic blood pressure, mmhg < Diastolic blood pressure, mmhg < Fasting glucose, mg/dl < Triglycerides, mg/dl <0.05 HDL-cholesterol, mg/dl NS hs-crp, mg/l <0.001 Gamma glutamyltransferase, U/L NS Alanine aminotransferase, U/L <0.01 Uric acid, mg/dl <0.05 White blood cell count, /L 6 4,545 1,144 4,722 1,166 4,938 1,266 5,174 1,318 < egfr, ml min m <0.05 % vital capacity <0.05 n % n % n % n % MetS <0.01 JMetS <0.01 Diabetes NS *Comparisons between Q1 and Q4. Abbreviations as in Table 1. The prevalence of MetS or JMetS was 14.7% or 13.0%, respectively, in men and 7.0% or 1.9%, respectively, in women. The agreement of diagnosis between MetS and JMetS (MetS and JMetS/MetS or JMetS) was 57% in men and 26% in women. Table 3 shows the data by quartile of HR in men. BMI, body fat %, WC, SBP, DBP, fasting glucose, triglycerides, hs-crp, GGT, ALT, white blood cell count, and egfr were significantly higher in the highest quartile than in the lowest quartile of HR. The prevalence of MetS, JMetS, and diabetes was significantly higher in the highest quartile than in the lowest quartile of HR, and the trend was linear through the quartiles of HR (Figure). Table 4 shows the data by quartile of HR in women. Among the MetS-related risk factors, BMI, body fat %, WC, HDL-cholesterol, and GGT were not significantly different between the lowest and highest quartiles of HR. egfr was significantly higher in the highest quartile than in the lowest quartile of HR. The prevalence of MetS and JMetS was significantly higher in the highest quartile than in the lowest quartile of HR, and the trend was linear through the quartiles of HR (Figure). However, the prevalence of diabetes in women was not significantly different between the highest and lowest quartile.

5 MetS and Heart Rate 1435 Table 5. Spearman s Correlation Coefficients Between Heart Rate and MetS-Related Risk Factors Men (n=1,880) Women (n=1,079) r P value r P value Body mass index < NS Body fat, % < <0.05 Waist circumference < NS Systolic blood pressure < < Diastolic blood pressure < < Fasting glucose < < Triglycerides < <0.01 HDL-cholesterol < NS hs-crp < < Gamma glutamyltransferase < <0.05 Alanine aminotransferase < <0.001 Uric acid NS NS White blood cell count < < egfr < <0.05 % vital capacity < <0.05 r, Spearman s correlation coefficient. Other abbreviations as in Table 1. Spearman s correlation coefficients between HR and MetS-related risk factors are presented in Table 5. MetSrelated risk factors other than uric acid were significantly correlated with HR in men, and MetS-related risk factors other than BMI, WC, HDL-cholesterol, and uric acid were significantly correlated with HR in women. The correlation between HR and egfr was positive in both men and women. Discussion In 2005, the definition of insulin resistance syndrome 1 or MetS was thrown into turmoil. The IDF issued a new definition in which the presence of abdominal obesity is necessary, 7 but the American Heart Association and the National Heart, Lung, and Blood Institute jointly criticized the new definition 9 and, more importantly, the American Diabetes Association and the European Association for the Study of Diabetes jointly stated that no existing definition of MetS meets the criteria of a syndrome. 8 Major diagnostic problems arise from the dichotomous nature of the MetS diagnosis. 10,11 In 2005 in Japan, the Examination Committee for Criteria of Metabolic Syndrome proposed visceral fat syndrome 17 as a definition of JMetS. 16 An essential pitfall of visceral fat syndrome is that it regards subcutaneous adipose tissue (SAT) as a protective factor against the morbid effect of VAT and ignored the risk contribution of abdominal SAT. 18,19 This defect of JMetS is obvious in women, as shown in Figure, because their VAT volume is relatively small and the risk contribution of SAT is more important. Thus, JMetS (visceral fat syndrome) was only 1.9% in women. MetS may develop through increased adiposity, insulin resistance, 1 leptin resistance, 2 low-grade systemic inflammation, 3 endothelial dysfunction, 4 and autonomic dysfunction, 5,6 so we have proposed adipose tissue disease 12 as a generalized concept of MetS. Autonomic dysfunction may be 1 of the mechanisms by which MetS leads to clustering of cardiometabolic risk factors 5 and HR, a global marker of autonomic dysfunction, may be closely associated with MetS and MetS-related risk factors. In the present study, we investigated the association between MetS and HR. Besides the 5 established components of MetS, hs-crp, GGT, ALT, LDL-cholesterol, uric acid, white blood cell count, HR, and egfr were significantly associated with MetS in both men and women and %VC was significantly associated with MetS in men. The prevalence of MetS and JMetS was significantly higher in the highest quartile of HR and the trend was linear through the quartiles of HR in both men and women. MetS-related risk factors, other than uric acid, were significantly correlated with HR in men, and MetS-related risk factors, other than BMI, WC, HDL-cholesterol and uric acid, were significantly correlated with HR in women. The correlation between HR and egfr was positive in both men and women. HR is reported to be associated with insulin resistance syndrome or multiple risk factors in Western societies 20 and in Japan. 21,22 Inoue et al showed that an increased HR was closely associated with cardiovascular risk clustering that resembled MetS, 22 but they did not study the direct association between HR and MetS. We studied the direct association between HR and MetS, and between HR and JMetS, and clearly showed that the prevalence of MetS and JMetS increased linearly through the increase in HR (Figure). In contrast to other risk factors, glomerular filtration rate (GFR) increased with the increase in HR in both men and women in the study by Inoue et al, 22 as well as in our study, and the correlation between HR and egfr was positive in both men and women in our study. Autonomic dysfunction may transiently elevate renal function, as do obesity and insulin resistance. Ribsteinet al reported that being overweight is associated with renal hyperfiltration and hyperperfusion, 23 and Chagnac et al reported that renal plasma flow and GFR were 51% and 31%, respectively, increased in obese subjects. 24 It is reported that insulin resistance and hyperinsulinemia cause glomerular hypertrophy, independent of hyperglycemia. 25 In the present study, egfr was significantly lower in MetS than in non-mets subjects, but it may transiently increase in the early stage of MetSrelated CKD, as in the early stage of diabetic nephropathy. 26 Epididymal adipose tissue and fatty liver are reported to be important mediators of autonomic dysfunction in MetS according to studies of male rats. 5 However, in our present study BMI and WC were not significantly correlated with HR in women, which suggests that there may be some gender differences in the mechanisms of autonomic dysfunction in MetS. Recent large epidemiologic studies in Western societies

6 1436 ODA E et al. have confirmed that HR is a predictor of cardiovascular and all-cause mortality, independent of currently accepted risk factors and other potentially confounding demographic and physiological characteristics, in men and women with and without diagnosed cardiovascular disease. 27 However, 1 study reported that a crude association between HR and death from cardiovascular disease was greatly weakened when it was adjusted for the main risk factors of disease, especially in women. 28 In regard to Japanese, a study reported that HR was the strongest predictor of all-cause death among SBP and DBP, antihypertensive medication, HR, uric acid, VC, and serum cholesterol after adjustment for age. 29 Another epidemiological study in Japanese reported that a higher HR was independently associated with the development of hypertension in a logistic regression analysis adjusted for gender, age, alcohol consumption, exercise, atherosclerotic risk factors, and lifestyle. 30 Pathophysiological studies indicate that a relatively high HR has direct detrimental effects on the progression of coronary atherosclerosis, on the occurrence of myocardial ischemia and ventricular arrhythmias, and on left ventricular function. Although it may be difficult to define an optimal HR for a given individual, it seems desirable to maintain HR substantially below the traditionally defined tachycardia threshold of 90 or 100 beats/min. 24 These findings suggest that the potential role of HR in MetS and its modulation should be considered in future cardiovascular guidelines. 27 Study Limitations The present study was cross-sectional in design and the subjects were not a general population, but visitors to a medical check-up center in a central city of a rural region in Japan. These conditions may influence the low prevalence of MetS in these subjects. However, the prevalence of MetS is low in rural regions and the prevalence of obesity is very low in Japan, so the conclusions may be relevant in other regions and populations in Japan. Longitudinal studies including HR and a variety of risk factors in Japanese may be warranted. Acknowledgments We thank all subjects who participated in the study, the paramedical staff at our center who assisted with the study, and Dr Shinzo Tachikawa, Dr Shinpei Yoshii, and Dr Masaaki Okabe at Tachikawa Medical Center for their efforts in constructing the study environment. References 1. Reaven GM. Role of insulin resistance in human disease. Diabetes 1988; 37: Cnop M, Landchild MJ, Vidal J, Havel PJ, Knowles NG, Carr DR, et al. The concurrent accumulation of intra-abdominal and subcutaneous fat explains the association between insulin resistance and plasma leptin concentrations: Distinct metabolic effects of two fat compartments. Diabetes 2002; 51: Dandona P, Aljada A, Chaudhuri A, Mohanty P, Garg R. Metabolic syndrome: A comprehensive perspective based on interactions between obesity, diabetes, and inflammation. Circulation 2005; 111: Kim J, Montagnani M, Koh KK, Quon MJ. Reciprocal relationships between insulin resistance and endothelial dysfunction: Molecular and pathophysiological mechanisms. Circulation 2006; 113: Katagiri H, Yamada T, Oka Y. Adiposity and cardiovascular disorders: Disturbance of the regulatory system consisting of humoral and neuronal signals. Circ Res 2007; 101: Carnethon MR, Golden SH, Folsom AR, Haskell W, Liao D. A prospective investigation of autonomic nervous system function and the development of type 2 diabetes: Atherosclerosis Risk in Communities Study, Circulation 2003; 107: Alverti KGMM, Zimmet P, Shaw J. Metabolic syndrome: A new world-wide definition: A consensus statement from the International Diabetes Federation. Diabet Med 2006; 23: Kahn R, Buse J, Ferrannini E, Stern M. The metabolic syndrome: Time for a critical appraisal: Joint statement from the American Diabetes Association and the European Association for the Study of Diabetes. Diabetes Care 2005; 28: Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, et al. Diagnosis and management of the metabolic syndrome: A statement for health care professionals [an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement]. Circulation 2005; 112: Reaven GM. The metabolic syndrome: Is this diagnosis necessary? Am J Clin Nutr 2006; 83: Sattar N. Why metabolic syndrome criteria have not made prime time: A view from the clinic. Int J Obes 2008; 32(Suppl 2): S30 S Oda E. The metabolic syndrome as a concept of adipose tissue disease. Hypertens Res 2008; 31: Kotronen A, Yki-Jarvinen H. Fatty liver: A novel component of the metabolic syndrome. Arterioscler Thromb Vasc Biol 2008; 28: Chen J, Muntner P, Hamm LL, Jones DW, Batuman V, Fonseca V, et al. The metabolic syndrome and chronic kidney disease in U.S. adults. Ann Intern Med 2004; 140: Fabbri LM, Rabe KF. From COPD to chronic systemic inflammatory syndrome? Lancet 2007; 370: Japanese Society of Internal Medicine. The Examination Committee for Criteria of Metabolic Syndrome: Definition and criteria of metabolic syndrome. J Jpn Soc Intern Med 2005; 94: (in Japanese). 17. Matsuzawa YM. Pathophysiology and molecular mechanism of visceral fat syndrome: The Japanese experience. Diabetes Metab Rev 1997; 13: Fox CS, Massaro JM, Hoffmann U, Poe KM, Maurovich-Horvat P, Liu C, et al. Abdominal visceral and subcutaneous adipose tissue compartments: Association with metabolic risk factors in the Framingham Heart Study. Circulation 2007; 116: Pou KM, Massaro JM, Hoffmann U, Vasan RS, Maurovich-Horvat P, Larson MG, et al. Visceral and subcutaneous adipose tissue volumes are cross-sectionally related to markers of inflammation and oxidative stress: The Framingham Heart Study. Circulation 2007; 116: Palatini P, Casiglia E, Pauletto P, Staessen J, Kaciroti N, Julius S. Relationship of tachycardia with high blood pressure and metabolic abnormalities: A study with mixture analysis in three populations. Hypertension 1997; 30: Inoue T, Oshiro S, Iseki K, Tozawa M, Touma T, Ikemiya Y, et al. High heart rate relates to clustering of cardiovascular risk factors in a screened cohort. Jpn Circ J 2001; 65: Inoue T, Iseki K, Iseki C, Ohya Y, Kinjo K, Takishita S. Association between multiple risk factor syndrome: Cross-sectional analysis of a screened cohort in Okinawa, Japan. Circ J 2008; 72: Ribstein J, du Cailar G, Mimran A. Combined renal effects of overweight and hypertension. Hypertension 1995; 26: Chagnac A, Weinstein T, Korzets A, Ramadan E, Hirsch J, Gafter U. Glomerular hemodynamics in severe obesity. Am J Physiol 2000; 278: F817 F Cusumano AM, Bodkin NL, Hansen BC, Iotti R, Owens J, Klotman PE, et al. Glomerular hypertrophy is associated with hyperinsulinemia and precedes overt diabetes in aging rhesus monkeys. Am J Kidney Dis 2002; 40: Tozawa M, Iseki C, Tokashiki K, Chinen S, Kohagura K, Kinjo K, et al. Metabolic syndrome and risk of developing chronic kidney disease in Japanese adults. Hypertens Res 2007; 30: Fox K, Borer JS, Camm AJ, Danchin N, Ferrari R, Sendon JLL, et al. Resting heart rate in cardiovascular disease. J Am Coll Cardiol 2007; 50: Tverdal A, Hjellvik V, Selmer R. Heart rate and mortality from cardiovascular causes: A 12 year follow-up study of 379,843 men and women aged years. Eur Heart J 2008; 29: Inoue T, Iseki K, Iseki C, Kinjo K, Ohya Y, Takishita S. Higher heart rate predicts the risk of developing hypertension in a normotensive screened cohort. Circ J 2007; 71: Fujiura Y, Adachi H, Tsuruta M, Jacobs DR Jr, Hirai Y, Imaizumi T. Heart rate and mortality in a Japanese general population: An 18-year follow-up study. J Clin Epidemiol 2001; 54: