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DOI: 10.1177/1358863X11400781

2011 16: 87 originally published online 29 March 2011Vasc Med Kai Chew, Tien Y Wong and E. Shyong Tai

vintharan Subramaniam, Ei Ei Khaing Nang, Su Chi Lim, Yi Wu, Chin Meng Khoo, Jeannette Lee, Derrick Heng, SuokAsian population

brachial index and the risk factors of peripheral artery disease in a multi-ethnicistribution of ankle

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1Department of Medicine, Khoo Teck Puat Hospital, Singapore2Department of Epidemiology and Public Health, Yong Loo Lin School ofMedicine, National University of Singapore, Singapore

3Department of Medicine, National University Hospital, Singapore4Epidemiology and Disease Control Division, Ministry of Health,Singapore

5Centre for Eye Research Australia, University of Melbourne,Melbourne, Victoria, Australia

6Singapore Eye Research Institute, Yong Loo Lin School of Medicine,National University of Singapore, Singapore

Corresponding author:S TavintharanDepartment of MedicineKhoo Teck Puat Hospital90 Yishun CentralSingapore 768828SingaporeEmail: [email protected]

Vascular Medicine16(2) 8795

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Distribution of anklebrachial index andthe risk factors of peripheral artery diseasein a multi-ethnic Asian population

Tavintharan Subramaniam 1, Ei Ei Khaing Nang 2, Su Chi Lim 1,Yi Wu 2, Chin Meng Khoo 3, Jeannette Lee 2, Derrick Heng 4,Suok Kai Chew 4, Tien Y Wong 5,6 and E Shyong Tai 2,3

AbstractPeripheral artery disease (PAD) is a manifestation of systemic atherosclerosis and is associated with increasedcardiovascular morbidity and mortality. We describe the prevalence and risk factors of PAD in a multi-ethnic Asianpopulation (Chinese, Malays and Indians) in Singapore. The Singapore Prospective Study Program recruited 4132individuals between 2004 and 2006 in which the anklebrachial index (ABI) was measured using the Smartdop 20EXbi-directional blood flow detector. PAD was defined as 0.9 and a high ABI > 1.4, with ABI 1.111.20 as reference. Themean age (SD) of individuals in the study was 49.9 (11.8) years, with 51.8% females. PAD was present in 4.3% of thepopulation and a high ABI (> 1.4) was rare. Malays and Indians had a higher risk (especially in females). Compared tothose with an ABI between 1.11 and 1.20, those with PAD were more likely to be of Malay and Indian ethnicity, femalesex, with higher systolic blood pressure and pulse pressure, with increased prevalence of diabetes mellitus, hypertension,albuminuria and renal impairment, and with a past history of stroke. In conclusion, in this large multi-ethnic Asianpopulation, we document the distribution and risk factor associations for PAD. PAD shows an ethnic distribution similarto that of coronary artery disease in Singapore, with differences in sex distribution. Apart from traditional vascular riskfactors, pulse pressure, renal impairment and a past history of stroke are important determinants of PAD.

Keywordsanklebrachial index; distribution; peripheral artery disease; risk factors

IntroductionThe anklebrachial index (ABI), the ratio of systolic blood

pressure at the ankle to that in the arm, has been shown in stud-ies to predict cardiovascular diseases (CVD) and mortality. 13 Because the measurement of ABI is non-invasive, relativelyinexpensive and quick, recent guidelines by the American HeartAssociation and the American College of Cardiology, amongothers, have suggested that measurement of ABI should beconsidered for the purposes of cardiovascular risk assessment.

The cut-offs for defining ABI risk, however, haveremained controversial. An ABI lower than 0.9 or 1.0 has

been used for many years to define peripheral artery dis-ease (PAD) in the legs. 2,4 Studies have shown that low ABI

below these cut-offs, not only predicts poorer walkingendurance, 5 but is also associated with CVD risk factorsand predicts CVD events. More recently, however, it is rec-ognized that the relationship between ABI and CVD andmortality may be non-linear. Studies carried out in native

and elderly Americans6,7

and a meta-analysis of 16 popula-tion cohort studies, 8 suggests there exists a J or U-shapedassociation in which both low and high ABI are associatedwith increased cardiovascular morbidity and mortality.

Most previous studies have been conducted in Western populations, and there are limited data on the distribution ofABI and the relationship with CVD risk factors in Asian

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88 Vascular Medicine 16(2)

populations. It has been suggested that the distribution ofABI varies by race/ethnicity. In the Strong Heart study,among 4393 American Indians, high ABI was more com-mon than low ABI. 7 In contrast, in other US and Europeanwhite populations, 6,8 high ABI was less common than lowABI. There are further variations in the distribution of ABIamong white, black, Hispanic and Chinese individuals. 9,10

The aims of this study were to describe the distributionof ABI in a multi-ethnic Asian population of Chinese,Malays and Indians (three major racial/ethnic groups inAsia) in Singapore and to examine the risk factor profilesassociated with PAD in this population.

MethodsStudy design and populationThe Singapore Prospective Study Program is a population-

based cross-sectional study of CVD in a multi-ethnic popu-

lation in Singapore, previously described in detail,1113

and

illustrated in Figure 1. In brief, we invited 10,747subjects from four previously conducted population-basedcross-sectional surveys carried out in Singapore (1982 1998) to participate in a repeat examination between 2004and 2007. 1417 Briefly, all studies included a randomsample of individuals from the Singapore population, withdisproportionate sampling stratified by ethnicity to increasethe number in the minority ethnic groups (Malays andAsian Indians). All subjects were interviewed in theirhomes and were subsequently invited to attend a healthexamination for additional tests and collection of biologicalspecimens. In total, 7744 (76.8% response rate) subjectswere interviewed, and 5164 (66.7%) attended the healthexamination. During the period 2 April 2005 up to 20February 2006, owing to limitations in resources, examina-tion of ABI was carried out only for every alternateChinese participant. However, in order to maintain ade-quate numbers for other ethnic groups, all subjects who

were non-Chinese had ABI measured.

Thyroid and Heart Study1982 1984(N = 2034)

National University of Singapore Heart Study

1993 1995(N = 982)

National HealthSurvey1992

(N = 3568)

National HealthSurvey1998

(N = 4723)

Total of 10,747 Subjects Available for the Study

10,080 Subjects Eligible

559 Died

102 Errors in IdentityCard Number

6 Emigrated

7,744 Subjects Contactable And Completed

Questionnaire

2,306 Subjects NotContactable

5,164 Subjects AttendedHealth Examination

2,580 Subjects Did Not Attend Health

Examination

5140 Subjects HadBlood Samples

24 Subjects Had NoBlood Samples

30 Subjects Refused

5023 Subjects HadUrine Samples

4132 Subjects Had Ankle-Brachial

Doppler Readings

Figure 1. Flowchart of study participation.

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Tavintharan S et al. 89

Ethics approval was obtained from two InstitutionalReview Boards (National University of Singapore andSingapore General Hospital) prior to study commence-ment. Informed consent was obtained from all participants

before the commencement of the study.

Measurement of ABIAnkle pressures were measured using a standardized Dopplerultrasonic device (8 MHz; Smartdop 20EX bi-directional

blood flow detector; Hadeco, Japan). Measurements werecarried out after a 5-minute rest in the supine position. TheABI was calculated as the ratio of the higher of the two sys-tolic pressures (from posterior tibial and dorsalis pedis) at theankle to the average of the right and left brachial artery pres-sures, unless there was a discrepancy 10 mmHg in blood

pressure values between the two arms. In such cases, thehigher reading was used for ABI. Pressures in each leg were

measured and the ABI was calculated separately for each leg.

Data collectionData on demographic and lifestyle (alcohol intake, smok-ing) factors, as well as medical history (including historyof hypertension, diabetes mellitus, hyperlipidemia, dura-tion of diabetes, and current medications) were collectedusing interviewer-administered questionnaires. Smokingwas categorized as never-, ex-, or current-smoker.

For health examination, participants were examined fol-lowing a 10-hour overnight fast. Venous blood was drawnand collected in plain and fluoride oxalate tubes and storedat 4C for a maximum of 4 hours prior to processing.A random urine specimen was collected. All biochemicalanalyses on blood were carried out at the National UniversityHospital Referral Laboratory, which is accredited by theCollege of American Pathologists. Serum total cholesterol(TC), triglyceride (TG), high-density lipoprotein cholesterol(HDL-C) and low-density lipoprotein cholesterol (LDL-C)levels were measured using an automatized autoanalyzer(ADVIA 2400; Bayer Diagnostics, Tarrytown, NY, USA).Glycated hemoglobin A1C (HbA1C) was measured on a Bio-Rad VARIANT II analyzer (Bio-Rad Laboratories, Hercules,CA, USA). Plasma glucose was obtained by the enzymaticmethod (ADVIA 2400; Bayer Diagnostics) using bloodcollected in fluoride oxalate tubes, while high-sensitivityC-reactive protein (hs-CRP) was measured using immunotur-

bidimetric assay (Roche Integra 400; Roche Diagnostics,Rotkreuz, Switzerland). Insulin was assayed by microparticleenzyme immunoassay using the Abbot AXSYM (AbbottLabora tories, Chicago, IL, USA). Insulin resistance wasassessed by homeostasis model assessment [insulin resis-tance, HOMA-IR = (fasting insulin fasting glucose)/22.5].Random urinary spot albumin and creatinine were measuredusing commercial assays (Siemens Healthcare Diagnostics,Inc., USA [Immulite] and Roche Diagnostics GmbH,

Germany) for urinary albumin and creatinine, respectively.Two readings of blood pressure were taken from parti-cipants after 5 minutes of resting using an automated

blood pressure monitor (Dinamap Pro100V2; Criticon,

Norderstedt, Germany) by trained observers. A third read-ing was performed if the difference between two readingsof systolic blood pressure was greater than 10 mmHg ordiastolic blood pressure was greater than 5 mmHg. Themean values of the closest two readings were calculated.

DefinitionsThe lower ABI between the two legs was used to definePAD, taken as an ABI of 0.90. 2 To evaluate the nature ofthe association of ABI with CVD risk factors, we catego-rized ABI into 0.1-unit increments as follows: 0.90,0.911.0, 1.011.10, 1.111.20, 1.211.30, and 1.311.40.Only three participants had an ABI above 1.4 and wereexcluded from the analysis.

Diabetes was defined as a fasting glucose level 7.0mmol/l or a known history of diabetes, hypertension asa systolic blood pressure > 140 mmHg or diastolic blood

pressure > 90 mmHg or a history of hypertension, orcurrently taking anti-hypertensive medications. Coronaryartery disease (CAD) was taken as present if the subjectanswered yes to the question of whether he/she had ahistory of blockage of arteries to the heart, heart attack,balloon angioplasty of artery to the heart, or heart bypassoperation. Stroke was taken as present if the subjectanswered yes to a direct question of whether he/she had

been told by a physician to have had a stroke before. A urinealbumin:creatinine ratio (A/C) of 30 g/mg or above wastaken to indicate the presence of albuminuria. Renal impair-ment was defined as present if the glomerular filtration rate(eGFR) (estimated using the 4-variable Modification ofDiet in Renal Disease Study (MDRD) equation) was below60 ml/min/1.73 m 2 body surface area.

Statistical methodsAll statistical analyses were performed using Stata 10 forWindows (Stata Corporation, College Station, TX, USA).A total of 4132 subjects were screened for ABI and threesubjects with a high ABI (ABI > 1.4) were excluded fromthe analysis. Analysis of variance (ANOVA) was used tocompare continuous variables between the groups. Thedistribution of data for fasting glucose, triglycerides, hs-CRP and HOMA-IR were skewed and log transformationwas done for analysis. The transformed variables were backtransformed before reporting (for clinical relevance) andexpressed in mean (range).

The TukeyKrammer post hoc test and chi-square testwere conducted respectively to assess the mean and propor-tion difference between the reference group and other ABIgroups. Odds ratios (OR) and 95% confidence intervals(95% CI) were obtained using the logistic regression modelto determine the association between categories of ABI andrisk factors (e.g. diabetes, hypertension, smoking), usingthe ABI 1.111.20 category as the reference group.

Multivariate logistic regression and stepwise multivariatelogistic regression with backward selection were per-formed, with low ABI as the dependent variable and 13covariates in the model, to determine independent risk

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90 Vascular Medicine 16(2)

factors for low ABI. All statistical tests were two-sidedwith a level of significance defined as a p-value < 0.05. Allvalues are given as means (SD) unless stated otherwise.

ResultsA total of 4129 subjects were included in the analysis. Themean age (SD) was 49.9 (11.8) years, with 51.8% females.There were 59% Chinese, 21.2% Malays and 19.8%Indians.

The distribution of ABI in each ethnic group is shown inFigure 2. PAD (defined as ABI 0.9) was present in 4.3%of the population and very few people had high ABI (> 1.4).The prevalence of PAD increased with age, and affectedone in 711 of those aged > 60 years (Table 1A). The preva-lence of PAD also differed by ethnic group and sex. Malaysand Indians had a higher prevalence (and this was espe-cially pronounced in women (Table 1B).

Table 2 describes the baseline characteristics of theoverall study population and those with PAD. Comparedto the overall population, those with PAD were more likelyto be older, have a higher systolic blood pressure and

pulse pressure, and a higher prevalence of diabetes, hyper-tension, chronic renal disease, CAD and stroke. As can

be seen in Table 3, these differences were statisticallysignificant when compared to the reference group (ABI1.111.20).

Table 4 describes the association of risk factors of PADaccording to ethnicity. As seen in the unadjusted model,risk factor age, sex, BMI, pulse pressure, hypertension, dia-

betes, chronic kidney disease, history of coronary diseaseand stroke were associated with PAD in all three majorethnic groups. We carried out two sets of multivariate anal-ysis. In the first, we included all potential risk factors inthe model except HOMA-IR. In the second, we used back-

ward stepwise regression to select the most parsimoniousmodel. The associations for several of the risk factors thatwere statistically significant in univariate analyses (age,hypertension, diabetes mellitus and renal impairment) were

no longer statistically significant following multivariateanalysis, in one or more ethnic groups. Pulse pressure wasidentified as a common independent risk factor for PAD inall ethnic groups. A past history of stroke was also associ-ated with PAD (except in Malays, where there were noindividuals with stroke amongst those with PAD). Renalimpairment seemed more important in Indians. BMI wasassociated with PAD in Chinese and Indians but the direc-

tion of the association was opposite with low BMI associ-ated with PAD in Chinese but high BMI associated withPAD in Indians. Interaction between ethnicity and BMIwas noted for PAD ( p = 0.003). No other statistically

3.55.2 6.2

3.2

25.628.3

26.1

30.8

51.248.7 49.2

47.1

15.7 15.3 15.8

2.4 1.9 3.1 2.70.3 5.03.04.0

17.0

0.0

10.0

20.0

30.0

40.0

50.0

Chinese Malay Indian Others

P e r c e n t

ABI 0.9 ABI 0.91-1.00 ABI 1.01-1.10.9 - . . - . ABI 1.11-1.20 ABI 1. 21-1. 30 ABI >1. 3

Figure 2. Distribution of anklebrachial index (ABI) by ethnicity.

Table 1. (A) Prevalence of PAD by ethnicity, age and sex;(B) prevalence of PAD by ethnicity and sex(A)

Ethnicity Sex Age

1839(n = 772)

4060(n = 2586)

> 60(n = 770)

Chinese, n (%) Male 4 (1.77) 11 (1.6) 20 (8.23)Female 7 (2.4) 28 (3.61) 15 (7.11)

Malay, n (%) Male 1 (1.52) 8 (2.76) 9 (11.54)Female 5 (6.02) 14 (4.95) 8 (11.27)

Indian, n (%) Male 2 (4.26) 9 (3.52) 8 (8.6)Female 2 (3.57) 14 (4.83) 10 (13.7)

(B) a

Sex Ethnicity

Chinese Malay Indian p-value

Overall, n (%) 85 (3.49) 45 (5.15) 46 (5.63) 0.01Male, n (%) 35 (3.03) 18 (4.14) 19 (4.79) 0.2Female, n (%) 50 (3.91) 27 (6.18) 27 (6.43) 0.04

aThe sex of one participant was missing.



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significant interactions were noted for any of the other riskfactors.

DiscussionThe results of this population-based study involving amulti-ethnic Singapore population show that the preva-

lence of PAD was 4.3% in the overall population. The prev-alence of PAD was higher in Malays and Indians (3.5% inChinese, 5.2% in Malays and 5.6% in Indians) and theethnic difference was most marked in women. Older age,

female sex, higher systolic blood pressure and pulse pres-sure, diabetes, hypertension, chronic renal disease, CADand stroke are significantly associated with an increasedrisk of PAD in all three ethnic groups.

The prevalence of PAD defined (by a low ABI 0.9) inthe overall population was comparable with other studieswhich included subjects below 50 years of age. 10,18,19 Ourstudy shows an ethnic difference in the distribution of ABI.PAD, compared with Chinese, was more common in Malaysand Indians. Both these latter ethnic groups in Singaporeshow an increased propensity to develop myocardial infarc-tion and our study suggests that this increased risk for CVDextends to PAD. 20

We found that female sex was associated with an increasedrisk of PAD (Table 4) and this association remained statisti-cally significant after multivariate analysis. This contrastswith data on the prevalence of myocardial infarction in theSingapore population. 20 While in myocardial infarction,

compared with females, males had a nearly four timesincreased risk, in PAD we found females had a nearly two-fold higher risk than males. It has been shown that there is asex difference in the degree of calcification between coro-nary artery and peripheral arteries (e.g. thoracic aorta), 21 withmen having greater coronary calcification and women hav-ing greater calcification of the thoracic aorta. This raises the

possibility that the associations between sex and atheroscle-rosis may differ between vascular beds, and in part mayexplain why, compared with men, women are more likelyto develop PAD but less likely to develop CAD. This sexdifference needs to be further explored in clinical studies.

Our finding in those with PAD is consistent with our previous work in Malays with diabetes, 22 and is also seen inWestern and Japanese populations in individuals with andwithout diabetes. 13,23 The finding that individuals withPAD were significantly more likely to have pre-existingatherosclerotic disease, characterized by a history of CADor stroke, is important as it suggests that they may have anumber of common risk factors. Our data further supportsthis, showing older age, presence of hypertension, diabetes,albuminuria and renal impairment as important risk factorsfor PAD.

In patients with diabetes, hyperglycemia has been postu-lated as being responsible for the non-enzymatic glycationof proteins such as elastin and collagen. 24 Hyperinsulinemiacontributes to vascular smooth muscle proliferation, associ-ated with the pathogenesis of atherosclerosis. Consistentwith this, we found that patients with PAD had significantlyhigher fasting blood glucose levels, and higher insulinresistance assessed by HOMA-IR levels.

In addition to an increased prevalence of hypertensionand higher systolic blood pressure, we noted greater pulse

pressure in those with PAD. In fact, after multivariate ana-lysis, pulse pressure was the risk factor that was the mostconsistently associated with PAD across all three ethnicgroups. Well established as a marker of central arterial

stiffness, elevated pulse pressure is an important determi-nant of endothelial function and atherosclerotic risk. 25,26 Elevated pulse pressure has been shown prospectively to

be the strongest predictor of atherosclerosis-related aortic

Table 2. Characteristics of the population

Overallpopulation

PAD (ABI 0.9)

n(%) 4129 176 (4.26)Age, years 49.9 11.8 56.75 14.2Female sex, % 51.78 59.09Ethnicity, % Chinese Malay Indian Others

59.0021.1419.790.07

48.3025.5726.140

BMI, kg/m2 24.2 4.4 24.54 5.2Systolic BP, mmHg 132.62 20.9 146.75 25.5Diastolic BP, mmHg 78.05 10.7 79.11 11.4Pulse pressure, mmHg 54.57 15.64 67.64 19.9Fasting glucose, mmol/l 5.05 (4.066.30) 5.37 (4.107.03)Total cholesterol, mmol/l 5.23 1.0 5.21 1.0HDL-C, mmol/l 1.39 0.34 1.35 0.34LDL-C, mmol/l 3.21 0.85 3.22 0.91Triglycerides, mmol/l 1.20 (0.702.03) 1.25 (0.791.95)hs-CRP, mg/l 1.32 (0.394.44) 1.45 (0.425.00)HOMA-IR 1.54 (0.733.25) 1.84 (0.844.01)eGFR < 60 ml/min/

1.73 m, %6.55 15.52

Albuminuria, % 13.14 24.85Hypertension, % 41.65 64.94Diabetes mellitus, % 12.39 29.55Coronary artery disease, % 4.10 7.39Stroke, % 0.92 5.11Smoking status No smoker, % 78.65 80.11 Current smoker, % 12.51 13.64 Ex-smoker, % 8.83 6.25Age group, years < 40 18.70 12.00 4060 62.65 48.00 > 60 18.65 40.00

PAD, peripheral artery disease; ABI, anklebrachial index; BMI, bodymass index; BP, blood pressure; HDL-C, high-density lipoproteincholesterol; LDL-C, low-density lipoprotein cholesterol; hs-CRP,high-sensitivity C-reactive protein; HOMA-IR, homeostasis modelassessmentinsulin resistance; eGFR, estimated glomerularfiltration rate.All data presented are as range and mean 1 SD.



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T a

b l e 4 . A s s o c i a t i o n

b e t w e e n r i s

k f a c t o r s a n

d l o w

A B I ( A B I

0 . 9

) v e r s u s n o r m a l

A B I ( A B I 1

. 1 1 1 . 2 0 ) b y e t

h n i c i t y

C h i n e s e

M a l a y

I n d i a n

U n i v a r i a t e

a n a l y s i s

M u l t i v a r

i a t e

a n a l y s i s

S t e p w

i s e

r e g r e s s i o n

U n i v a r i a t e

a n a l y s i s

M u l t i v a r

i a t e

a n a l y s i s

S t e p w

i s e

r e g r e s s i o n

U n i v a r i a t e

a n a l y s i s

M u l t i v a r

i a t e

a n a l y s i s

S t e p w

i s e

r e g r e s s i o n

O R ( C I )

O R ( C I )

O R ( C I )

O R ( C I )

O R ( C I )

O R ( C I )

O R ( C I )

O R ( C I )

O R ( C I )

8 5 ( 1 7

. 0 3 )

4 5

( 2 5

. 2 8 )

4 6 ( 2 6

. 1 4 )

F e m a l e s e x

1 . 9 9 * *

2 . 1 8 *

2 . 0 2 * *

2 . 1 9 *

2 . 5 2

2 . 0 6 *

3 . 7 1 *

( 1 . 2

4 3 . 2 0 )

( 1 . 1

5 4 . 1 3 )

( 1 . 1

9 3 . 4 3 )

( 1 . 1

0 4 . 3 7 )

( 0 . 8

8 7 . 2 6 )

( 1 . 0

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( 1 . 0

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. 6 8 )

A g e , y e a r s

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1 . 0 2

1 . 0 3 *

0 . 9 7

1 . 0 6 * * *

1 . 0 3

( 1 . 0

3 1 . 0 7 )

( 0 . 9

9 1 . 0 5 )

( 1 . 0

0 1 . 0 6 )

( 0 . 9

3 1 . 0 2 )

( 1 . 0

3 1 . 1 0 )

( 0 . 9

7 1 . 0 8 )

B M I , k g / m

0 . 9 3 *

0 . 8 9 *

0 . 9 1 *

0 . 9 5

0 . 9 5

1 . 0 9 *

1 . 0 8

1 . 1 1 *

( 0 . 8

7 0 . 9 9 )

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( 0 . 8

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( 0 . 8

8 1 . 0 3 )

( 0 . 8

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P u l s e p r e s s u r e , m

m H g

1 . 0 5 * * *

1 . 0 4 * * *

1 . 0 6 * * *

1 . 0 4 * * *

1 . 0 5 * * *

1 . 0 4 * * *

1 . 0 6 * * *

1 . 0 3

1 . 0 5 * * *

( 1 . 0

4 1 . 0 7 )

( 1 . 0

1 1 . 0 7 )

( 1 . 0

4 1 . 0 7 )

( 1 . 0

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( 1 . 0 2

1 . 0 6 )

( 1 . 0

4 1 . 0 9 )

( 0 . 9

9 1 . 0 7 )

( 1 . 0

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H O M A - I R

1 . 1 3 *

1 . 0 1

1 . 1 5 *

( 1 . 0

2 1 . 2 6 )

( 0 . 8

6 1 . 2 0 )

( 1 . 0

2 1 . 3 0 )

h s - C

R P , m

g / l

1 . 0 4

1 . 0 2

0 . 9 6

0 . 8 9

1 . 0 6 *

1 . 0 2

( 0 . 9

7 1 . 1 2 )

( 0 . 9

3 1 . 1 2 )

( 0 . 8

6 1 . 0 7 )

( 0 . 7

7 1 . 0 3 )

( 1 . 0

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( 0 . 9

5 1 . 1 1 )

H D L - C

, m m o l

/ l

1 . 1 4

0 . 6 8

0 . 9 6

0 . 5 2

1 . 0 0 3

0 . 5 2

( 0 . 5

8 2 . 2 4 )

( 0 . 2

8 1 . 6 3 )

( 0 . 3

0 3 . 0 7 )

( 0 . 1

0 2 . 6 6 )

( 0 . 3

0 3 . 3 2 )

( 0 . 1

0 2 . 6 7 )

L D L - C

, m m

o l / l

1 . 0 3

1 . 1 7

1 . 1 2

1 . 2 1

0 . 7 9

0 . 8 8

( 0 . 7

7 1 . 3 6 )

( 0 . 8

4 1 . 6 3 )

( 0 . 7

9 1 . 5 9 )

( 0 . 8

0 1 . 8 2 )

( 0 . 5

2 1 . 1 9 )

( 0 . 5

0 1 . 5 6 )

H y p e r t e n s

i o n

3 . 2 4 * * *

1 . 1 1

2 . 6 2 *

1 . 4 4

3 . 3 3 * *

1 . 0 5

( 2 . 0

0 5 . 2 6 )

( 0 . 5

0 2 . 4 4 )

( 1 . 2

6 5 . 4 5 )

( 0 . 4

3 4 . 8 9 )

( 1 . 6

3 6 . 7 9 )

( 0 . 3

6 3 . 1 3 )

D i a b e t e s

4 . 7 4 * * *

1 . 6 4

1 . 8 1

1 . 3 1

3 . 5 0 * *

1 . 5 9

( 2 . 5

8 8 . 6 8 )

( 0 . 7

2 3 . 7 0 )

( 0 . 7

9 4 . 1 5 )

( 0 . 4

0 4 . 3 3 )

( 1 . 6

4 7 . 4 9 )

( 0 . 5

7 4 . 4 6 )

C o r o n a r y a r t e r y

d i s e a s e

1 . 4 7

1 . 6 2

6 . 3 9 *

9 . 9 6

1 . 3 5

0 . 7 9

( 0 . 4

0 5 . 4 6 )

( 0 . 3

3 7 . 8 5 )

( 1 . 1

3 3 6

. 1 6 )

( 0 . 6

3 1 5 8 . 4 0 )

( 0 . 4

8 3 . 7 9 )

( 0 . 1

9 7 . 2 8 )

S t r o

k e

2 0 . 4

0 * *

1 1 . 9

2 *

1 4 . 1

4 *

N A

6 . 1 0 *

2 . 1 6

( 2 . 2

5 1 8 4 . 8 4 )

( 1 . 1

7 1 2 1 . 7 6 )

( 1 . 4

3 1 4 0 . 2 0 )

( 1 . 0

8 3 4

. 4 8 )

( 0 . 0

7 6 9

. 6 8 )

R e n a

l i m p a

i r m e n t

2 . 9 9 * * *

1 . 2 0

1 . 4 3

0 . 6 2

4 . 1 9 * * *

3 . 2 2 *

1 . 0 5 * * *

( 1 . 6

9 5 . 2 9 )

( 0 . 5

6 2 . 5 6 )

( 0 . 6

4 3 . 2 0 )

( 0 . 1

9 2 . 0 4 )

( 1 . 9

7 8 . 9 1 )

( 1 . 1

4 9 . 1 1 )

( 1 . 0

3 1 . 0 8 )

S m o k

i n g s t a t u s

N o s m o

k e r

R e f e r e n c e

R e f e r e n c e

R e f e r e n c e

C u r r e n t s m o k e r

0 . 6 7

0 . 6 5

1 . 4 3

3 . 3 6

1 . 1 2

3 . 9 8

( 0 . 2

9 1 . 5 4 )

( 0 . 2

1 2 . 0 1 )

( 0 . 6

0 3 . 4 0 )

( 0 . 9

3 1 2

. 1 8 )

( 0 . 4

3 0 . 9 1 )

( 0 . 8

7 1 8

. 2 7 )

E x

- s m o k e r

0 . 6 1

0 . 9 5

N A

N A

1 . 0 2

4 . 6 4

( 0 . 2

5 1 . 4 9 )

( 0 . 3

4 2 . 6 9 )

( 0 . 3

5 3 . 0 7 )

( 0 . 9

3 2 3

. 0 8 )

O R , o d

d s r a t

i o ; C

I , c o n f

i d e n c e

i n t e r v a l ;

B M I , b o d y m a s s i n

d e x ;

H O M A - I R

, h o m e o s t a s

i s m o d e l a s s e s s m e n t i n s u l

i n r e s i s t a n c e ;

h s - C

R P , h

i g h - s

e n s i t

i v i t y

C - r

e a c t

i v e p r o t e i n ;

H D L - C

, h i g h

- d e n s i t y

l i p o p r o t e

i n c h o l e s t e r o

l ;

L D L - C

, l o w - d

e n s i t y

l i p o p r o t e

i n c h o l e s t e r o

l .

* p

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