Are Gujarati Asian Indians older for their vascular age as compared to their Chronological age?

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1 Q J Med 2015; 108: doi: /qjmed/hcu158 Advance Access Publication 1 August 2014 Are Gujarati Asian Indians older for their vascular age as compared to their Chronological age? K.H. SHARMA, S. SAHOO, K.H. SHAH, A.K. PATEL, N.D. JADHAV, M.M. PARMAR and K.H. PATEL From the U. N. Mehta Institute of Cardiology and Research Centre (UNMICRC), Asarwa, Ahmedabad, , India Address correspondence to K.H. Sharma, Department of Cardiology, U. N. Mehta Institute of Cardiology and Research Centre, Civil Hospital Campus, Ahmedabad , Gujarat, India. kamalsharma1975@gmail.com Received 19 June 2014 and in revised form 23 July 2014 Summary Background: South Asians are known to carry higher burden of cardiovascular diseases when compared with their Caucasian counterparts. Aim: This study was designed to evaluate whether vascular age is advanced for Gujarati Asian Indians as matched to their chronological age in apparently healthy, asymptomatic population. We have also assessed the contributing risk factors for premature vascular ageing. Design: It was cross-sectional study of 2483 individuals of Gujarat state in Western India having no past or present history of major illness including cardiovascular diseases. Method: The vascular age of the population was calculated using Framingham vascular age calculator. A relationship between risk factor prevalence and vascular ageing was evaluated using univariate analysis of variance. Results: The mean chronological age of the study population was 46.8 (10.35) years whereas mean Introduction Cardiovascular diseases (CVD) including coronary artery disease (CAD) and stroke, are leading cause of mortality and morbidity in the developing countries of the world. 1 The origin of emerging CVD risks in Indians lies in epidemic transition which is a result of affluence, urbanization and vascular age was (16.05) years, and the difference ( ) between both was statistically significant (P < ). Contributory risk factors for advanced vascular age apart from chronological age (75.4%) and male gender (66.2%) were the presence of dyslipidemia (60.4%) hypertension (57.34%) and increased waist circumference (WC) (male 39.7%, female 29%). Results of regression analysis showed that vascular age progression was highly associated with blood pressure (19.9, 95% CI: ), followed by smoking (15.23, 95% CI: ), and blood sugar (12.97, 95% CI: ). Conclusion: The Gujarati Asian Indians are subjected to premature vascular ageing and henceforth routine screening for vascular age and risk factors prevalence is strongly advocated in this ethnic group. mechanization. 2 In case of CAD, the unique phenotypic profile of Asians differentiate them from other populations which suggest possible involvement of ethnicity based causative factors. 3 Earlier reports have also indicated the presence of CVD and neurological disorder genes in Indians, especially in Guajaratis. 4,5! The Author Published by Oxford University Press on behalf of the Association of Physicians. All rights reserved. For Permissions, please journals.permissions@oup.com

2 106 K.H. Sharma et al. Prognosis and prediction of coronary heart disease (CHD) and other cardiovascular events are complex processes involving the study of interactions between genetic and environmental factors over an extended period of time. One of the most accepted model for CHD risk prediction was proposed and developed by Framingham investigators in The original study was a communitybased study of 5209 white subjects selected from a suburb west of Boston. In spite of this, the accuracy of Framingham equation in predicting the CHD risk in culturally diverse population is fairly high and uniform due to its systematic validation in various populations. 7,8 This simplified coronary prediction model, uses a multivariate statistical analysis involving blood pressure, cholesterol and low density lipoprotein cholesterol (LDL-C) categories as proposed by the Joint National Committee on Detection, Evaluation, and Treatment of High Blood Pressure (JNC-V) and NCEP ATP II for 10 years CHD risk estimation. 6 Vascular age or Heart age is a novel concept derived from Framingham cardiovascular risk tables in This process is accelerated in presence of different cardiovascular risk factors is associated with changes in the mechanical and the structural properties of the vascular wall, which leads to the loss of arterial elasticity. 10 In Framingham vascular age calculations, the CVD risk of an individual is transformed to the age of a person with the same risk but all other risk factors at the normal level. The identification of expressed risk factors in case of silent or asymptomatic CADs by Framingham vascular age multivariate algorithm provides prognostic value for the management of the disease. 11 In spite of great degree of susceptibility of Gujarati Asian Indians to CADs 12 none of the study has addressed the issue of gap between vascular age and actual age in apparently healthy individuals. Due to this lacuna in epidemiological research, this study was planned to screen asymptomatic Gujarati population for progressive vascular aging at a large scale. Materials and Methods Design and data collection This cross-sectional and randomized screening study, conducted by U.N. Mehta Institute of cardiology and research center was approved and clear by institutional ethics committee (UNMICRC/ CARDIO/14/52). Total 2483 individuals of both the genders (1477 males and 1006 females), who were apparently healthy, asymptomatic, disease free and ranging in age from 30 to 74 years were included in the study. The subjects taking any medications and with abnormal stress test were excluded from the investigation. All patients had normal baseline electrocardiography (ECG) and 2D echocardiography. The details of demographic data, ethnicity, family history of CAD and smoking were collected for each individual. Cardiovascular risk factors Subjects were advised to fast at least for 12 h before blood investigations. Total cholesterol (TC), triglycerides (TG), total lipid (TL), lipoproteins low density lipoproteins (LDL), high density lipoprotein (HDL), and very low density lipoprotein (VLDL) and glucose concentrations were measured by International Federation of Clinical Chemistry (IFCC) approved enzymatic methods using commercially available kit on auto analyzer (ARCHITECH PLUS ci4100, Germany). Lipids levels were classified according to the recommendations of National Cholesterol Education Program (NCEP) and Adult Treatment Panel III (ATP III) guidelines. Blood pressure of the population was measured as per the earlier reported guidelines and hypertension was diagnosed if the systolic blood pressure was higher than 140 mmhg or the diastolic blood pressure was above 90 mmhg. 13 Individuals having body mass index (BMI) greater than 30 were considered to be obese as per World Health Organization standards. 14 Abnormal (High) WC was defined using two cutoff points of >90 cm in men and >80 cm in women. 15 The Vascular age was calculated by using Framingham vascular age calculator. Framingham vascular age assessment In Gujarati Asian Indian cohort study, the calculations of vascular age were performed according to definition of D Agostino et al. 9 in the tables from the 2008 FHS. ( risk-functions/cardiovascular-disease/10-year risk. php). We had enrolled the population having age between 30 and 74 years as indicated by Framingham vascular age calculators. The risk factors assessed were age, gender, smoking, TC level, systolic blood pressure and diabetes. The prediction calculation for risk factors were done using continuous functions rather than the point system to add more accuracy. Categorization of the population The study population was categorized in three cohorts based on their age. Cohort I: Vascular age lesser than the chronological age

3 Are Gujarati Asian Indians older for their vascular age? 107 Cohort II: Vascular age equal to the chronological age Cohort III: Vascular age greater than the chronological age Statistical analysis The statistical calculations were performed using SPSS software v 20.0 (Chicago, IL, USA) Quantitative data was expressed as mean SD whereas qualitative data was expressed as percentage. Univariate analysis of the continuous data was performed using student s t-test, whereas chi-square test was used for the categorical data. One-way analysis of variance (ANOVA) was applied to compare the results of three cohorts. The cut off value of P < 0.05 was considered for the statistical significance. Linear regression model was applied to the data to measure the strength of particular risk factors in predicting premature vascular ageing. Results The demographic and clinical presentation of the population are presented in Table 1. The mean age of the overall cohort was 46.8 (10.35) years and mean vascular age was (16.05) years. Table 1 The difference between both the ages ( ) was statistically significant (P < ). The life style induced risk factors such as centripetal obesity (males 56.46%, females 78.28%) hypertension (43.89%) and various dyslipidemias (10 88%) were highly prevalent in Gujarati Asian community. Family history of CAD was found in 34.55% of the population, 13.37% individuals were obese and 10.79% subjects were having habit of smoking. Distribution and comparison trend analysis of various risk factors within all three cohort revealed that most of the individuals (72.45%) were having vascular age greater than their chronological age (Table 2). Only and 5.19% of the population was having vascular age lesser or equal to the actual chronological age, respectively. From the results, it was also prominent that the population affected by advanced vascular age were more male (66.2%) and relatively older (75.4%). Almost all risk factors such as dyslipidemia, diabetes, family history, smoking, hypertension and BMI and WC were significantly higher in advanced vascular age group when compared withequal and lesser vascular age group individuals. The key contributors of vascular age progression were abnormalities of various lipids as follows (TC: 49.3%, TG: 13.4%, HDL in males: 60.4%, HDL in females: 8.4%, LDL: 59.9%, VLDL: Demographic and clinical characteristics of the study population at the time of vascular age calculation a Variables Mean SD/number (%) Chronological age Vascular age * Difference Blood sugar 107 (4.3) Cholesterol 975 (39.26) Triglyceride (TG) 249 (10) High density lipoprotein (HDL) Males 1307 (88) Female 212 (21.1) Low density lipoprotein (LDL) 1014 (40.83) Low density lipoprotein/high density lipoprotein ratio (LDL/HDL) 1155 (46.5) Total cholesterol/high density lipoprotein (TC/HDL) 1323 (53.28) Triglyceride/high density lipoprotein (TG/HDL) 554 (22.31) Very low density lipoprotein (VLDL) 369 (14.86) Total lipids (TL) 617 (24.8) Family history 858 (34.55) Smoking 268 (10.79) Hypertension 1090 (43.89) Body mass index (BMI) (kg/m 2 ) 332 (13.37) Waist circumference (WC) (cm) Male 834 (56.46) Female 786 (78.28) a Values are expressed as mean SD or number and percentage. Values in the parentheses denote percentage. Significantly different (*P < ) when compared with chronological age.

4 108 K.H. Sharma et al. Table 2 Distribution and comparison trends of various risk factors according to vascular age deviations a Variables Cohort I (575) N (%) Cohort II (129) N (%) Cohort III (1779) N (%) Significance P-value Chronological age Vascular age Difference Gender Male 227 (39.5) 72 (55.8) 1178 (66.2) < Female 348 (60.5) 57 (44.2) 601 (33.8) < Age years (47.7) 65 (50.4) 438 (24.6) < > (52.3) 64 (49.4) 1341 (75.4) < Blood sugar 3 (0.5) 0 (0) 104 (5.8) < Cholesterol 76 (13.2) 23 (17.8) 877 (49.3) < Triglyceride (TG) 6 (1.0) 5 (3.9) 239 (13.4) < High density lipoprotein (HDL) Males 169 (29.4) 63 (48.8) 1075 (60.4) < Females 53 (9.2) 10 (7.8) 149 (8.4) Low density lipoprotein (LDL) 69 (12.0) 22 (17.1) 924 (59.9) < Low density lipoprotein/high density lipoprotein (LDL/HDL) 60 (10.4) 25 (19.4) 1071 (60.2) < Total cholesterol/high density lipoprotein (TC/HDL) 79 (13.7) 32 (24.8) 1213 (68.2) < Triglyceride/high density lipoprotein (TG/HDL) 54 (9.4) 16 (12.4) 485 (27.3) < Very low density lipoprotein (VLDL) 17 (3.0) 6 (4.7) 347 (19.5) < Total lipids (TL) 31 (5.4) 5 (3.9) 582 (32.7) < Family history 175 (30.4) 48 (37.2) 635 (35.7) Smoking 11 (1.9) 6 (4.7) 251 (14.1) < Hypertension 44 (7.7) 26 (20.15) 1019 (57.34) < Body mass index (BMI) (kg/m 2 ) 60 (10.4) 13 (10.1) 260 (14.6) Waist circumference (WC) (cm) Males 94 (16.3) 34 (26.4) 706 (39.7) < Females 231 (40.2) 40 (31) 516 (29) < a Values are presented as number, percentage. Cohort I, Individuals having vascular age lesser than their chronological age; Cohort II, Individuals having vascular age equals to their chronological age; Cohort III, Individuals having vascular age greater than their chronological age. 19.5%, TL: 32.7%, LDL/HDL ratio: 60.2%, TC/HDL ratio: 68.2% and TG/HDL ratio: 27.3%), whereas hypertension in 57.34% and increased WC in 39.7% males and in 29% females. Prevalence of diabetes (5.8%) and smoking (14.1%) increases as the gap between vascular age and real age widens, however their contribution in the vascular age advancement was not as strong as the other risk factors. The distribution of various risk factors in advanced vascular age group was further categorized according to gender and age and is indicated in Tables 3 and 4, respectively. Table 3 shows that chronological age of male and females suffering from premature vascular ageing was almost similar, however mean vascular age of the females was significantly (P = ) higher ( ) than males ( ). Moreover the older males (72.9%) and females (80.2%) were having higher vascular age when compared with young ones (27.07% males, 19.8% females). Distribution of various risk factors such as elevated TG (15.8 vs. 8.8%), LDL/HDL ratio (66.2 vs. 48.4%), TC/HDL ratio (75.6 vs. 53.7%), TG/HDL ratio (32.3 vs. 17.3%), VLDL (22.6 vs. 13.5%), TL (33.8 vs. 30.6%), low HDL (91.3 vs. 24.8%), family history of CAD (37 vs. 33.1%) and smoking (17.4 vs. 7.7%) was higher in males when compared with females. However, hypertension, obesity and increased WC were more prevalent in females (61.4, 18.8 and 85.9%) than in males (55.2, 12.5 and 59.9%), respectively. Table 4 shows that vascular age deviation increases with natural aging and were associated with elevation in TC (52.2%), high LDL (54.9%), hypertension (60.4%), and high WC (males: 40.5%; females: 31.2%). We have also observed that the gap between vascular and chronological age was greater in older individuals ( ) when compared

5 Are Gujarati Asian Indians older for their vascular age? 109 Table 3 Genderwise distribution of risk factors in population having advanced vascular age a Variables for positive difference (1779) Males (1178) N (%) Females (601) N (%) Significance P-value Chronological age Vascular age Difference Age years (27.07) 119 (19.8) > (72.9) 482 (80.2) Blood sugar 75 (6.4) 29 (4.8) Cholesterol 562 (47.7) 315 (52.4) Triglyceride (TG) 186 (15.8) 53 (8.8) High density lipoprotein (HDL) 1075 (91.3) 149 (24.8) < Low density lipoprotein (LDL) 605 (51.4) 319 (53.1) Low density lipoprotein/high density lipoprotein (LDL/HDL) 780 (66.2) 291 (48.4) < Total cholesterol/high density lipoprotein (TC/HDL) 890 (75.6) 323 (53.7) < Triglyceride/high density lipoprotein (TG/HDL) 381 (32.3) 104 (17.3) < Very low density lipoprotein (VLDL) 266 (22.6) 81 (13.5) < Total lipids (TL) 398 (33.8) 184 (30.6) Family history 436 (37) 199 (33.1) Smoking 205 (17.4) 46 (7.7) < Hypertension 650 (55.2) 369 (61.4) Body mass index (BMI) (kg/m 2 ) 147 (12.5) 113 (18.8) Waist circumference (WC) (cm) 706 (59.9) 516 (85.9) < a Values are presented as number, percentage. with the young ( ). Combined results of Tables 3 and 4 revealed that ageing of vessels targets males at younger age (72.8%) and this could be due to abnormality of HDL, which was higher (69.4%) in young males when compared with their older counterparts (57.5%). The strength of association of individual risk factor in the vascular ageing was estimated with the by logistic regression analysis (Table 5). It showed that vascular age progression was highly associated with hypertension 19.9 (95% CI ), followed by smoking (95% CI ) and elevated blood sugar (95% CI ). In spite of the fact that their weak association with increased vascular age in the study population, the results of odds ratio point out that individuals with diabetes or smoking had relatively higher chances of developing vascular diseases when compared with others. Discussion To the best of our knowledge, this is the first ever large cross sectional study designed to assess individuals for increased vascular age in Gujarati Asian Indian cohort. This work also provides some of the most relevant findings regarding the factors involved in advanced vascular age in apparently healthy and asymptomatic Gujarati Asian Indians. Surprisingly, we found that only 23.15% of the population was having vascular age lesser than their chronological age, where as 72.45% of the population was suffering from premature vascular ageing making them susceptible for occurrence of CVD. D Agostino et al. had developed a simple algorithm involving classical risk factors of CHD such age, lipids, systolic blood pressure, treatment for hypertension, smoking and diabetes to quantify a multivariable risk of CHD in the form of vascular age. 9 This study observation of Gujarati Asian Indians cohort lead us to identify dyslipidemia (60.4%), hypertension (57.34%) and centripetal obesity (male 39.7%, females 29%) as key contributors of increased vascular age. On the contrary, in spite of their proven role in CHD in other ethnic cohort diabetes (5.8%) and smoking (14.1%) were found to be weakly associated with vascular age in Gujarati Asian Indians. Disturbance in lipid metabolism often leads to the manifestation of various types of dyslipidemias triggering inflammatory processes causing atherosclerotic disorders. 16 One of the first land mark finding of Framingham study was the establishment of relationship between TC and CHD risk. Nowadays, the cholesterol centric approach to CVD is an obsolete concept as the high levels of LDL, elevated TG, TL,

6 110 K.H. Sharma et al. Table 4 Agewise distribution of risk factors in population having advanced vascular age a Variables Age 40 years (438) N (%) Age >40 years (1341) N (%) Significance P value Chronological age Vascular age Difference Gender Males 319 (72.8) 859 (64.1) Females 119 (27.2) 482 (35.9) Blood sugar 11 (2.5) 93 (6.9) Cholesterol 177 (40.4) 700 (52.2) < Triglyceride (TG) 63 (14.4) 176 (13.1) High density lipoprotein (HDL) Males 304 (69.4) 771 (57.5) < Females 42 (9.6) 107 (8.0) Low density lipoprotein (LDL) 188 (42.9) 736 (54.9) < Low density lipoprotein/high density lipoprotein (LDL/HDL) 269 (61.4) 802 (59.8) Total cholesterol/high density lipoprotein (TC/HDL) 308 (70.3) 905 (67.5) Triglyceride/high density lipoprotein (TG/HDL) 120 (27.4) 365 (27.2) Very low density lipoprotein (VLDL) 94 (21.5) 253 (18.9) Total lipids (TL) 136 (31.1) 446 (33.3) Family history 188 (42.9) 447 (33.3) Smoking 74 (16.9) 177 (13.2) Hypertension 209 (47.7) 810 (60.4) < Body mass index (BMI) (kg/m 2 ) 49 (11.2) 211 (15.7) Waist circumference (WC) (cm) Males 163 (37.2) 543 (40.5) Females 97 (22.1) 419 (31.2) a Values are presented as number, percentage. Table 5 Multivariate logistic regression analysis for premature vascular ageing by gender, age, blood sugar, lipid profile, family history, smoking, hypertension, and body mass index and waist circumference a Variables B Sig. Exp(B) 95% CI for EXP(B) Lower Upper Gender Age Blood sugar Cholesterol Triglyceride (TG) High density lipoprotein (HDL) Low density lipoprotein cholesterol (LDL) Low density lipoprotein cholesterol/high density lipoprotein (LDL/HDL) Total cholesterol/high density lipoprotein (TC/HDL) Triglyceride/high density lipoprotein (TG/HDL) Very low density lipoprotein (VLDL) Total Lipids (TL) Family history Smoking Hypertension Body mass index (BMI) (kg/m 2 ) Waist circumference (WC) (cm) a Linear regression model analysis. B, Beta coefficient; Exp (B), exponentiation of the coefficients/odds ratios of the predictors, CI, confidence interval.

7 Are Gujarati Asian Indians older for their vascular age? 111 VLDLs and low levels of HDL are also known to contribute in vascular age progression which was later updated by Framingham investigators also. 17 In the same line, we have also observed key association between various dyslipidemias (8.4% to 68.2%) and growing vascular age in Gujarati Asian Indians. Outcomes of present investigation states that the dyslipidemia prevalence are subjected to gender variance as majority of the responders of lipid abnormalities were male which is in agreement with previous reports. 18 We have also observed that females had better cardiovascular risk factor profile especially in case of lipids when compared with males, where abnormalities of HDL were alarmingly high (91%) in Gujarati Asian Indian males. The fairer lipid profile in females could be partly explained by the antioxidant, DNA protective and vascular flexibility enhancing properties of estrogen which helps in delaying onset of CVD events in females by years when compared with men. 19,20,21 HDL being anti-atherogenic lipoprotein provides cardio-protection through various mechanisms such as reverse transport of cholesterol, preventing endothelial dysfunction and antioxidative properties. Numerous clinical and epidemiological studies have shown inverse correlation between HDL level and coronary events. 22 HDL abnormality was found to target the population at relatively early age in both the gender indicating early need for diet and life style modification. Hypertension has long been recognized as an attributable risk factor of CVD and several epidemiological studies such as INTERHEART and Framingham had recommended its use as a powerful prognosticator of future CVD events. 17,23 Likewise this study also establishes hypertension as one of the strongest predictor of advanced vascular age showing higher frequencies in older individuals (60.4%) when compared with young (47.7%), which is in accordance with earlier reported studies. 24 The overall population affected by high blood pressure reported in our study (57.34%) was relatively higher than other documented studies (16.9%). 25 However in contrast to others, 24 we have found that Gujarati females (61.4%) are more likely to be hypertensive than males (55.2%). This remarkable loss of the estrogen protective effect in Gujarati females could be partially explained by less effective baroreflex buffering of blood pressure in women than men and presence of associated comorbidities. 26 Centripetal obesity, as defined by WC is one of prime indicator of disturbed lipid metabolism and is an independent risk factor of atherosclerotic. 27 Although not incorporated in Framingham equation, the IDEA study presented that visceral obesity is linearly related to the incidence of CAD regardless of BMI. 28 Similar to other reports from India, in our study population also the centripetal obesity was contributing risk factor for progressive vascular age, which was more prevalent in males (39.7%) than in females (29%). 29 We have observed that the increase in vascular age was greater in older individuals as 75.4% of the population affected with advanced vascular age were having chronological age above 40 years. Natural ageing allied changes in lipids were observed in TC and LDL whereas levels of TG, VLDL, TL were unaffected by the age of an individual. Ageing induces dysfunctional arteries by increasing arterial stiffness, oxidative stress and reducing arterial compliance and promotes CVD risk factors. 10 Our results clearly states that the gap between vascular age and chronological age gets widened as people grow older due to greater expression of framingham equation risk factors. Conclusion 1. Gujarati Asian Indians are older for their vascular age by 6.54 (9.5) years when compared with their chronological age. 2. The risk factors contributing to the advanced vascular age for Gujarati Asian Indians are dyslipidemia, hypertension and centripetal obesity, apart from chronological ageing and male gender. 3. Diabetes and smoking showed lesser influence in the study group and this could be partly explained by the fact that distribution of CVD risk factors are highly prone to ethnic and genetic variation making some population more susceptible to certain diseases. 4. These finding may explain earlier occurrence of CVD in Asian Indians approximately by a decade than Caucasian population. In the light of our findings, routine screening for advanced vascular age and potential at risk population in asymptomatic patients is strongly advocated. Acknowledgements The authors are grateful to the Director, Dr. R. K. Patel, Yogini Kandre, Pratik Shah and Himanshu Acharya for their valuable support in the completion of this project. Funding This work was supported by U.N. Mehta Institute of Cardiology and Research Centre, Gujarat, India. Conflict of interest: None declared.

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