One way Anova with post hoc analysis of the 3 Duration groupsANOVA

Sum of

Squares df Mean Square F Sig.age Between Groups 776.000 2 388.000 3.276 .043

Within Groups 9593.571 81 118.439Total 10369.571 83

bmi Between Groups 7.850 2 3.925 .319 .728Within Groups 997.720 81 12.318Total 1005.571 83

durat Between Groups 2363.156 2 1181.578 181.968 .000Within Groups 525.959 81 6.493Total 2889.115 83

sbp Between Groups 4843.524 2 2421.762 5.407 .006Within Groups 36276.286 81 447.855Total 41119.810 83

dbp Between Groups 268.667 2 134.333 1.140 .325Within Groups 9542.143 81 117.804Total 9810.810 83

abpi Between Groups .096 2 .048 4.485 .014Within Groups .866 81 .011Total .962 83

tc Between Groups 19531.452 2 9765.726 1.467 .237Within Groups 539233.53

6 81 6657.204

Total 558764.988 83

tg Between Groups 784.357 2 392.179 .057 .945Within Groups 558761.67

9 81 6898.292

Total 559546.036 83

hd Between Groups 109.357 2 54.679 .331 .719Within Groups 13387.214 81 165.274Total 13496.571 83

ld Between Groups 15765.929 2 7882.964 1.786 .174Within Groups 357560.39

3 81 4414.326

Total 373326.321 83

tchd Between Groups 18.577 2 9.288 1.135 .327Within Groups 663.155 81 8.187Total 681.731 83

Post Hoc Paired T Tests: Bonferroni/Tukey - Multiple Comparisons

Dependent Variable

(I) VAR00001

(J) VAR00001

Mean Difference

(I-J) Std. Error Sig. 95% Confidence Interval

Lower Bound Upper Bound

age Tukey HSD 1.00 2.00 -6.14286 2.90860 .094 -13.0873 .8016 3.00 -6.71429 2.90860 .060 -13.6587 .2301

2.00 1.00 6.14286 2.90860 .094 -.8016 13.0873

3.00 -.57143 2.90860 .979 -7.5158 6.3730

3.00 1.00 6.71429 2.90860 .060 -.2301 13.6587

2.00 .57143 2.90860 .979 -6.3730 7.5158

Bonferroni 1.00 2.00 -6.14286 2.90860 .113 -13.2535 .9678

3.00 -6.71429 2.90860 .071 -13.8250 .3964

2.00 1.00 6.14286 2.90860 .113 -.9678 13.2535

3.00 -.57143 2.90860 1.000 -7.6821 6.5393

3.00 1.00 6.71429 2.90860 .071 -.3964 13.8250

2.00 .57143 2.90860 1.000 -6.5393 7.6821bmi Tukey HSD 1.00 2.00 .74179 .93799 .710 -1.4977 2.9813

3.00 .28214 .93799 .951 -1.9574 2.5216

2.00 1.00 -.74179 .93799 .710 -2.9813 1.4977

3.00 -.45964 .93799 .876 -2.6991 1.7799

3.00 1.00 -.28214 .93799 .951 -2.5216 1.9574

2.00 .45964 .93799 .876 -1.7799 2.6991

Bonferroni 1.00 2.00 .74179 .93799 1.000 -1.5513 3.0349

3.00 .28214 .93799 1.000 -2.0110 2.5753

2.00 1.00 -.74179 .93799 1.000 -3.0349 1.5513

3.00 -.45964 .93799 1.000 -2.7528 1.8335

3.00 1.00 -.28214 .93799 1.000 -2.5753 2.0110

2.00 .45964 .93799 1.000 -1.8335 2.7528durat Tukey HSD 1.00 2.00 -6.34821(*) .68103 .000 -7.9742 -4.7222

3.00 -12.99107(*) .68103 .000 -14.6171 -11.3651

2.00 1.00 6.34821(*) .68103 .000 4.7222 7.9742

3.00 -6.64286(*) .68103 .000 -8.2689 -5.0169

3.00 1.00 12.99107(*) .68103 .000 11.3651 14.6171

2.00 6.64286(*) .68103 .000 5.0169 8.2689

Bonferroni 1.00 2.00 -6.34821(*) .68103 .000 -8.0131 -4.6833

3.00 -12.99107(*) .68103 .000 -14.6560 -11.3261

2.00 1.00 6.34821(*) .68103 .000 4.6833 8.0131

3.00 -6.64286(*) .68103 .000 -8.3078 -4.9779

3.00 1.00 12.99107(*) .68103 .000 11.3261 14.6560

2.00 6.64286(*) .68103 .000 4.9779 8.3078sbp Tukey HSD 1.00 2.00 -16.00000(*) 5.65594 .016 -29.5038 -2.4962 3.00 -16.21429(*) 5.65594 .014 -29.7181 -2.7105

2.00 1.00 16.00000(*) 5.65594 .016 2.4962 29.5038

3.00 -.21429 5.65594 .999 -13.7181 13.2895

3.00 1.00 16.21429(*) 5.65594 .014 2.7105 29.7181

2.00 .21429 5.65594 .999 -13.2895 13.7181

Bonferroni 1.00 2.00 -16.00000(*) 5.65594 .018 -29.8272 -2.1728

3.00 -16.21429(*) 5.65594 .016 -30.0414 -2.3871

2.00 1.00 16.00000(*) 5.65594 .018 2.1728 29.8272

3.00 -.21429 5.65594 1.000 -14.0414 13.6129

3.00 1.00 16.21429(*) 5.65594 .016 2.3871 30.0414

2.00 .21429 5.65594 1.000 -13.6129 14.0414dbp Tukey HSD 1.00 2.00 -4.35714 2.90079 .295 -11.2829 2.5686

3.00 -2.57143 2.90079 .650 -9.4972 4.3543

2.00 1.00 4.35714 2.90079 .295 -2.5686 11.2829

3.00 1.78571 2.90079 .812 -5.1401 8.7115

3.00 1.00 2.57143 2.90079 .650 -4.3543 9.4972

2.00 -1.78571 2.90079 .812 -8.7115 5.1401

Bonferroni 1.00 2.00 -4.35714 2.90079 .411 -11.4487 2.7345

3.00 -2.57143 2.90079 1.000 -9.6630 4.5202

2.00 1.00 4.35714 2.90079 .411 -2.7345 11.4487

* The mean difference is significant at the .05 level.

Abbreviations used : bmi – body mass index; sbp – systolic blood pressure, dbp – diastolic blood pressure; abpi – ankle brachial pressure index; tc – total cholesterol; tg – triglyceride; hd – HDL cholesterol; ld – LDL cholesterol, tchd – ratio of tc/hd.

Homogeneous Subsets

age

VAR00001 N

Subset for alpha = .05

1Tukey HSD(a)

1.00 28 47.78572.00 28 53.92863.00 28 54.5000Sig. .060

Means for groups in homogeneous subsets are displayed.a Uses Harmonic Mean Sample Size = 28.000.

bmi

VAR00001 N

Subset for alpha = .05

1Tukey HSD(a)

2.00 28 22.29753.00 28 22.75711.00 28 23.0393Sig. .710

Means for groups in homogeneous subsets are displayed.a Uses Harmonic Mean Sample Size = 28.000.

durat

VAR00001 NSubset for alpha = .05

1 2 3Tukey HSD(a)

1.00 28 .25892.00 28 6.60713.00 28 13.2500Sig. 1.000 1.000 1.000

Means for groups in homogeneous subsets are displayed.a Uses Harmonic Mean Sample Size = 28.000.

sbp

VAR00001 NSubset for alpha = .05

1 2Tukey HSD(a)

1.00 28 133.21432.00 28 149.21433.00 28 149.4286Sig. 1.000 .999

Means for groups in homogeneous subsets are displayed.a Uses Harmonic Mean Sample Size = 28.000.

dbp

VAR00001 NSubset for alpha = .05

1Tukey HSD(a)

1.00 28 82.1429

3.00 28 84.7143

2.00 28 86.5000

Sig. .295Means for groups in homogeneous subsets are displayed.a Uses Harmonic Mean Sample Size = 28.000.

abpi

VAR00001 NSubset for alpha = .05

1 2Tukey HSD(a)

3.00 28 .83212.00 28 .83931.00 28 .9071Sig. .964 1.000

Means for groups in homogeneous subsets are displayed.a Uses Harmonic Mean Sample Size = 28.000.

tc

VAR00001 NSubset for alpha

= .05

1Tukey HSD(a)

1.00 28 169.8214

2.00 28 198.0000

3.00 28 205.1429

Sig. .243Means for groups in homogeneous subsets are displayed.a Uses Harmonic Mean Sample Size = 28.000.

tg

VAR00001 NSubset for alpha

= .05

1Tukey HSD(a)

3.00 28 155.7143

1.00 28 159.9286

2.00 28 163.1786

Sig. .940Means for groups in homogeneous subsets are displayed.a Uses Harmonic Mean Sample Size = 28.000.

hd

VAR00001 NSubset for alpha

= .05

1Tukey HSD(a)

1.00 28 39.8214

2.00 28 42.1071

3.00 28 42.3571

Sig. .742Means for groups in homogeneous subsets are displayed.a Uses Harmonic Mean Sample Size = 28.000.

ld

VAR00001 N Subset for alpha = .05

1Tukey HSD(a)

1.00 28 97.4643

2.00 28 125.7857

3.00 28 127.2143

Sig. .221Means for groups in homogeneous subsets are displayed.a Uses Harmonic Mean Sample Size = 28.000.

tchd

VAR00001 N Subset for alpha = .05

1Tukey HSD(a)

1.00 28 4.4154

2.00 28 4.8011

3.00 28 5.5482

Sig. .305Means for groups in homogeneous subsets are displayed.a Uses Harmonic Mean Sample Size = 28.000.

PAD Total Regression

Variables Entered/Removed(b)

ModelVariables Entered

Variables Removed Method

1 age, bmi, sm, tg, durat, gend(a)

. Enter

2

. bmi

Backward (criterion: Probability of F-to-remove >= .100).

3

. sm

Backward (criterion: Probability of F-to-remove >= .100).

4

. age

Backward (criterion: Probability of F-to-remove >= .100).

a All requested variables entered.b Dependent Variable: abpi

Model Summary

Model R R SquareAdjusted R

SquareStd. Error of the Estimate

1 .515(a) .265 .207 .095862 .514(b) .264 .217 .095293 .512(c) .262 .225 .094824 .504(d) .254 .226 .09471

a Predictors: (Constant), age, bmi, sm, tg, durat, gendb Predictors: (Constant), age, sm, tg, durat, gendc Predictors: (Constant), age, tg, durat, gendd Predictors: (Constant), tg, durat, gend

ANOVA(e)

Model Sum of

Squares df Mean Square F Sig.1 Regression .255 6 .042 4.621 .000(a)

Residual .708 77 .009Total .962 83

2 Regression .254 5 .051 5.597 .000(b)Residual .708 78 .009Total .962 83

3 Regression .252 4 .063 7.011 .000(c)Residual .710 79 .009Total .962 83

4 Regression .245 3 .082 9.095 .000(d)Residual .718 80 .009Total .962 83

a Predictors: (Constant), age, bmi, sm, tg, durat, gendb Predictors: (Constant), age, sm, tg, durat, gendc Predictors: (Constant), age, tg, durat, gendd Predictors: (Constant), tg, durat, gende Dependent Variable: abpi

Coefficients(a)

Model

Unstandardized Coefficients

Standardized Coefficients

t Sig.B Std. Error Beta1 (Constant) .816 .094 8.706 .000

gend -.088 .026 -.403 -3.361 .001durat -.004 .002 -.210 -2.038 .045tg .000 .000 .242 2.432 .017bmi .001 .003 .027 .266 .791sm .011 .025 .052 .450 .654age .001 .001 .092 .876 .384

2 (Constant) .836 .057 14.651 .000gend -.090 .025 -.412 -3.567 .001durat -.004 .002 -.212 -2.075 .041

tg .000 .000 .245 2.490 .015sm .012 .025 .053 .469 .640age .001 .001 .093 .882 .381

3 (Constant) .836 .057 14.722 .000gend -.084 .022 -.384 -3.873 .000durat -.004 .002 -.210 -2.070 .042tg .000 .000 .247 2.525 .014age .001 .001 .094 .905 .368

4 (Constant) .880 .029 30.235 .000gend -.080 .021 -.367 -3.774 .000durat -.003 .002 -.184 -1.891 .062tg .000 .000 .236 2.436 .017

a Dependent Variable: abpi

Excluded Variables(d)

Model Beta In t Sig.Partial

Correlation

Collinearity Statistics

Tolerance2 bmi .027(a) .266 .791 .030 .9033 bmi .030(b) .295 .769 .033 .906

sm .053(b) .469 .640 .053 .7284 bmi .030(c) .299 .766 .034 .906

sm .057(c) .505 .615 .057 .729

age .094(c) .905 .368 .101 .858a Predictors in the Model: (Constant), age, sm, tg, durat, gendb Predictors in the Model: (Constant), age, tg, durat, gendc Predictors in the Model: (Constant), tg, durat, gendd Dependent Variable: abpi

PAD- Males- Regression

Variables Entered/Removed(b)

ModelVariables Entered

Variables Removed Method

1 bmiM, DuratM, sbpM, tgM, tchdM(a)

. Enter

2

. bmiM

Backward (criterion: Probability of F-to-remove >= .100).

3

. sbpM

Backward (criterion: Probability of F-to-remove >= .100).

a All requested variables entered.

b Dependent Variable: abpiM

Model Summary

Model R R SquareAdjusted R

SquareStd. Error of the Estimate

1 .518(a) .268 .183 .085602 .511(b) .261 .194 .085063 .490(c) .241 .190 .08525

a Predictors: (Constant), bmiM, DuratM, sbpM, tgM, tchdMb Predictors: (Constant), DuratM, sbpM, tgM, tchdMc Predictors: (Constant), DuratM, tgM, tchdM

ANOVA(d)

Model Sum of

Squares df Mean Square F Sig.1 Regression .116 5 .023 3.154 .016(a)

Residual .315 43 .007Total .431 48

2 Regression .112 4 .028 3.880 .009(b)Residual .318 44 .007Total .431 48

3 Regression .104 3 .035 4.751 .006(c)Residual .327 45 .007Total .431 48

a Predictors: (Constant), bmiM, DuratM, sbpM, tgM, tchdMb Predictors: (Constant), DuratM, sbpM, tgM, tchdMc Predictors: (Constant), DuratM, tgM, tchdMd Dependent Variable: abpiM

Coefficients(a)

Model

Unstandardized Coefficients

Standardized Coefficients

t Sig.B Std. Error Beta1 (Constant) .783 .136 5.769 .000

tgM .000 .000 .269 1.840 .073sbpM -.001 .001 -.149 -1.086 .283DuratM -.005 .003 -.308 -1.874 .068tchdM .008 .004 .294 1.788 .081bmiM .003 .005 .097 .667 .508

2 (Constant) .853 .085 10.082 .000tgM .000 .000 .307 2.294 .027sbpM -.001 .001 -.149 -1.096 .279DuratM -.005 .003 -.289 -1.797 .079tchdM .007 .004 .261 1.675 .101

3 (Constant) .768 .033 22.933 .000tgM .000 .000 .299 2.230 .031DuratM -.005 .002 -.342 -2.227 .031tchdM .008 .004 .297 1.951 .057

a Dependent Variable: abpiM

Excluded Variables(c)

Model Beta In t Sig.Partial

Correlation

Collinearity Statistics

Tolerance2 bmiM .097(a) .667 .508 .101 .8053 bmiM .098(b) .670 .506 .100 .805 sbpM -.149(b) -1.096 .279 -.163 .905

a Predictors in the Model: (Constant), DuratM, sbpM, tgM, tchdMb Predictors in the Model: (Constant), DuratM, tgM, tchdMc Dependent Variable: abpiM

PAD- Female - Regression

Variables Entered/Removed(b)

ModelVariables Entered

Variables Removed Method

1 tchdF, DuratF, smF, tcF(a)

. Enter

2

. tcF

Backward (criterion: Probability of F-to-remove >= .100).

3

. tchdF

Backward (criterion: Probability of F-to-remove >= .100).

4

. DuratF

Backward (criterion: Probability of F-to-remove >= .100).

5

. smF

Backward (criterion: Probability of F-to-remove >= .100).

a All requested variables entered.b Dependent Variable: abpiF

Model Summary

Model R R SquareAdjusted R

SquareStd. Error of the Estimate

1 .340(a) .116 -.002 .106862 .339(b) .115 .029 .105163 .303(c) .092 .035 .104854 .227(d) .051 .023 .105535 .000(e) .000 .000 .10675

a Predictors: (Constant), tchdF, DuratF, smF, tcFb Predictors: (Constant), tchdF, DuratF, smFc Predictors: (Constant), DuratF, smFd Predictors: (Constant), smFe Predictor: (constant)

ANOVA(f)

Model Sum of

Squares df Mean Square F Sig.1 Regression .045 4 .011 .982 .432(a)

Residual .343 30 .011Total .387 34

2 Regression .045 3 .015 1.344 .278(b)Residual .343 31 .011Total .387 34

3 Regression .036 2 .018 1.621 .214(c)Residual .352 32 .011Total .387 34

4 Regression .020 1 .020 1.790 .190(d)Residual .368 33 .011Total .387 34

5 Regression .000 0 .000 . .(e)Residual .387 34 .011Total .387 34

a Predictors: (Constant), tchdF, DuratF, smF, tcFb Predictors: (Constant), tchdF, DuratF, smFc Predictors: (Constant), DuratF, smFd Predictors: (Constant), smFe Predictor: (constant)f Dependent Variable: abpiF

Coefficients(a)

Model Unstandardized

CoefficientsStandardized Coefficients t Sig.

B Std. Error Beta1 (Constant) .979 .077 12.742 .000

DuratF -.004 .003 -.197 -1.110 .276smF .081 .058 .245 1.409 .169tcF -4.44E-005 .000 -.039 -.148 .884tchdF -.011 .022 -.123 -.473 .640

2 (Constant) .982 .072 13.563 .000DuratF -.004 .003 -.203 -1.188 .244smF .081 .057 .244 1.425 .164tchdF -.013 .014 -.152 -.900 .375

3 (Constant) .921 .026 35.399 .000DuratF -.004 .003 -.203 -1.195 .241smF .084 .056 .255 1.498 .144

4 (Constant) .900 .019 47.484 .000smF .075 .056 .227 1.338 .190

5 (Constant) .909 .018 50.354 .000a Dependent Variable: abpiF

Excluded Variables(e)

Model Beta In t Sig.Partial

Correlation

Collinearity Statistics

Tolerance2 tcF -.039(a) -.148 .884 -.027 .4253 tcF -.133(b) -.773 .445 -.138 .978

tchdF -.152(b) -.900 .375 -.160 .9954 tcF -.159(c) -.937 .356 -.163 1.000

tchdF -.153(c) -.899 .375 -.157 .995

DuratF -.203(c) -1.195 .241 -.207 .9815 tcF -.158(d) -.920 .364 -.158 1.000

tchdF -.169(d) -.983 .333 -.169 1.000DuratF -.168(d) -.981 .334 -.168 1.000

smF .227(d) 1.338 .190 .227 1.000a Predictors in the Model: (Constant), tchdF, DuratF, smFb Predictors in the Model: (Constant), DuratF, smFc Predictors in the Model: (Constant), smFd Predictor: (constant)e Dependent Variable: abpiF

PAD- Smoker - RegressionVariables Entered/Removed(b)

ModelVariables Entered

Variables Removed Method

1 ageS, genS, tgS, sbpS(a)

. Enter

2

. ageS

Backward (criterion: Probability of F-to-remove >= .100).

3

. sbpS

Backward (criterion: Probability of F-to-remove >= .100).

a All requested variables entered.b Dependent Variable: abpiS

Model Summary

Model R R SquareAdjusted R

SquareStd. Error of the Estimate

1 .610(a) .372 .291 .083662 .610(b) .372 .313 .082343 .571(c) .326 .285 .08400

a Predictors: (Constant), ageS, genS, tgS, sbpSb Predictors: (Constant), genS, tgS, sbpSc Predictors: (Constant), genS, tgS

ANOVA(d)

Model Sum of

Squares df Mean Square F Sig.1 Regression .129 4 .032 4.594 .005(a)

Residual .217 31 .007Total .346 35

2 Regression .129 3 .043 6.323 .002(b)Residual .217 32 .007Total .346 35

3 Regression .113 2 .056 7.984 .001(c)Residual .233 33 .007Total .346 35

a Predictors: (Constant), ageS, genS, tgS, sbpSb Predictors: (Constant), genS, tgS, sbpSc Predictors: (Constant), genS, tgSd Dependent Variable: abpiS

Coefficients(a)

Model

Unstandardized Coefficients

Standardized Coefficients

t Sig.B Std. Error Beta1 (Constant) 1.043 .104 10.021 .000

genS -.145 .045 -.465 -3.199 .003sbpS -.001 .001 -.218 -1.401 .171tgS .000 .000 .294 1.971 .058ageS -1.24E-005 .001 -.001 -.009 .993

2 (Constant) 1.043 .092 11.340 .000genS -.145 .044 -.465 -3.257 .003sbpS -.001 .001 -.219 -1.533 .135tgS .000 .000 .295 2.102 .044

3 (Constant) .923 .049 18.742 .000genS -.158 .045 -.505 -3.532 .001

tgS .000 .000 .292 2.038 .050a Dependent Variable: abpiS

Excluded Variables(c)

Model Beta In t Sig.Partial

Correlation

Collinearity Statistics

Tolerance2 ageS -.001(a) -.009 .993 -.002 .7923 ageS -.083(b) -.551 .586 -.097 .913 sbpS -.219(b) -1.533 .135 -.261 .965

a Predictors in the Model: (Constant), genS, tgS, sbpSb Predictors in the Model: (Constant), genS, tgSc Dependent Variable: abpiS

PAD - Non-smoker - Regression

Variables Entered/Removed(b)

ModelVariables Entered

Variables Removed Method

1 hdSn, bmiSn, durSn, tgSn, genSn(a)

. Enter

2

. hdSn

Backward (criterion: Probability of F-to-remove >= .100).

3

. bmiSn

Backward (criterion: Probability of F-to-remove >= .100).

a All requested variables entered.b Dependent Variable: abpiSn

Model Summary

Model R R SquareAdjusted R

SquareStd. Error of the Estimate

1 .535(a) .286 .201 .100142 .531(b) .282 .215 .099283 .525(c) .276 .226 .09854

a Predictors: (Constant), hdSn, bmiSn, durSn, tgSn, genSn

b Predictors: (Constant), bmiSn, durSn, tgSn, genSnc Predictors: (Constant), durSn, tgSn, genSn

ANOVA(d)

Model Sum of

Squares df Mean Square F Sig.1 Regression .169 5 .034 3.368 .012(a)

Residual .421 42 .010Total .590 47

2 Regression .166 4 .042 4.215 .006(b)Residual .424 43 .010Total .590 47

3 Regression .163 3 .054 5.587 .002(c)Residual .427 44 .010Total .590 47

a Predictors: (Constant), hdSn, bmiSn, durSn, tgSn, genSnb Predictors: (Constant), bmiSn, durSn, tgSn, genSnc Predictors: (Constant), durSn, tgSn, genSnd Dependent Variable: abpiSn

Coefficients(a)

Model

Unstandardized Coefficients

Standardized Coefficients

t Sig.B Std. Error Beta1 (Constant) .844 .109 7.713 .000

genSn -.046 .032 -.200 -1.451 .154durSn -.007 .003 -.338 -2.515 .016tgSn .000 .000 .294 2.167 .036bmiSn .002 .004 .079 .586 .561hdSn -.001 .001 -.071 -.515 .609

2 (Constant) .823 .101 8.187 .000genSn -.047 .032 -.204 -1.498 .142durSn -.007 .003 -.350 -2.677 .010tgSn .000 .000 .277 2.123 .040bmiSn .002 .004 .079 .590 .558

3 (Constant) .878 .036 24.168 .000genSn -.052 .030 -.226 -1.731 .090durSn -.007 .003 -.354 -2.725 .009tgSn .000 .000 .276 2.133 .039

a Dependent Variable: abpiSn

Excluded Variables(c)

Model Beta In t Sig.Partial

Correlation

Collinearity Statistics

Tolerance2 hdSn -.071(a) -.515 .609 -.079 .9053 hdSn -.071(b) -.519 .607 -.079 .905 bmiSn .079(b) .590 .558 .090 .922

a Predictors in the Model: (Constant), bmiSn, durSn, tgSn, genSnb Predictors in the Model: (Constant), durSn, tgSn, genSnc Dependent Variable: abpiSn

PAD- High ABPI - Regression

Variables Entered/Removed(b)

ModelVariables Entered

Variables Removed Method

1 tcH, smH, durH, genH(a)

. Enter

2

. smH

Backward (criterion: Probability of F-to-remove >= .100).

3

. tcH

Backward (criterion: Probability of F-to-remove >= .100).

a All requested variables entered.b Dependent Variable: abpiH

Model Summary

Model R R SquareAdjusted R

SquareStd. Error of the Estimate

1 .511(a) .262 .175 .057902 .511(b) .261 .197 .057103 .503(c) .253 .212 .05659

a Predictors: (Constant), tcH, smH, durH, genHb Predictors: (Constant), tcH, durH, genHc Predictors: (Constant), durH, genH

ANOVA(d)

Model Sum of

Squares df Mean Square F Sig.1 Regression .040 4 .010 3.010 .031(a)

Residual .114 34 .003Total .154 38

2 Regression .040 3 .013 4.117 .013(b)Residual .114 35 .003Total .154 38

3 Regression .039 2 .020 6.097 .005(c)Residual .115 36 .003Total .154 38

a Predictors: (Constant), tcH, smH, durH, genHb Predictors: (Constant), tcH, durH, genHc Predictors: (Constant), durH, genH

d Dependent Variable: abpiH

Coefficients(a)

Model

Unstandardized Coefficients

Standardized Coefficients

t Sig.B Std. Error Beta1 (Constant) 1.018 .035 29.013 .000

genH -.038 .021 -.301 -1.790 .082durH -.003 .001 -.358 -2.348 .025smH -.004 .022 -.030 -.178 .860tcH .000 .000 -.090 -.596 .555

2 (Constant) 1.017 .035 29.458 .000genH -.040 .019 -.315 -2.155 .038durH -.003 .001 -.362 -2.444 .020tcH .000 .000 -.090 -.608 .547

3 (Constant) .998 .015 68.848 .000genH -.039 .018 -.308 -2.134 .040durH -.004 .001 -.380 -2.630 .012

a Dependent Variable: abpiH

Excluded Variables(c)

Model Beta In t Sig.Partial

Correlation

Collinearity Statistics

Tolerance2 smH -.030(a) -.178 .860 -.030 .7523 smH -.032(b) -.191 .850 -.032 .752 tcH -.090(b) -.608 .547 -.102 .960

a Predictors in the Model: (Constant), tcH, durH, genHb Predictors in the Model: (Constant), durH, genHc Dependent Variable: abpiH

PAD- Low ABPI - Regression

Variables Entered/Removed(b)

ModelVariables Entered

Variables Removed Method

1 genL, tgL, hdL, ageL, tcL(a)

. Enter

2

. tcL

Backward (criterion: Probability of F-to-remove >= .100).

3

. ageL

Backward (criterion: Probability of F-to-remove >= .100).

4

. genL

Backward (criterion: Probability of F-to-remove >= .100).

5

. tgL

Backward (criterion: Probability of F-to-remove >= .100).

a All requested variables entered.b Dependent Variable: abpiL

Model Summary

Model R R SquareAdjusted R

SquareStd. Error of the Estimate

1 .436(a) .190 .086 .042752 .435(b) .189 .108 .042243 .413(c) .170 .110 .042204 .359(d) .129 .087 .042725 .275(e) .076 .054 .04350

a Predictors: (Constant), genL, tgL, hdL, ageL, tcLb Predictors: (Constant), genL, tgL, hdL, ageLc Predictors: (Constant), genL, tgL, hdLd Predictors: (Constant), tgL, hdLe Predictors: (Constant), hdL

ANOVA(f)

Model Sum of

Squares df Mean Square F Sig.1 Regression .017 5 .003 1.828 .130(a)

Residual .071 39 .002Total .088 44

2 Regression .017 4 .004 2.331 .072(b)Residual .071 40 .002Total .088 44

3 Regression .015 3 .005 2.807 .052(c)Residual .073 41 .002Total .088 44

4 Regression .011 2 .006 3.104 .055(d)Residual .077 42 .002Total .088 44

5 Regression .007 1 .007 3.514 .068(e)Residual .081 43 .002Total .088 44

a Predictors: (Constant), genL, tgL, hdL, ageL, tcLb Predictors: (Constant), genL, tgL, hdL, ageLc Predictors: (Constant), genL, tgL, hdLd Predictors: (Constant), tgL, hdLe Predictors: (Constant), hdLf Dependent Variable: abpiL

Coefficients(a)

Model

Unstandardized Coefficients

Standardized Coefficients

t Sig.B Std. Error Beta1 (Constant) .774 .046 16.917 .000

tcL 2.51E-005 .000 .056 .202 .841tgL 8.77E-005 .000 .147 .656 .516hdL .001 .001 .182 .867 .391ageL -.001 .001 -.152 -.969 .338genL -.017 .015 -.174 -1.154 .256

2 (Constant) .770 .042 18.185 .000tgL .000 .000 .180 1.208 .234hdL .001 .000 .212 1.462 .151ageL -.001 .001 -.145 -.959 .343genL -.018 .015 -.180 -1.234 .224

3 (Constant) .739 .027 27.691 .000tgL .000 .000 .216 1.497 .142hdL .001 .000 .219 1.515 .137genL -.021 .014 -.206 -1.434 .159

4 (Constant) .720 .023 30.818 .000tgL .000 .000 .234 1.602 .117hdL .001 .000 .238 1.632 .110

5 (Constant) .734 .022 33.464 .000hdL .001 .000 .275 1.875 .068

a Dependent Variable: abpiL

Excluded Variables(e)

Model Beta In t Sig.Partial

Correlation

Collinearity Statistics

Tolerance2 tcL .056(a) .202 .841 .032 .2673 tcL -.002(b) -.009 .993 -.001 .281

ageL -.145(b) -.959 .343 -.150 .8914 tcL .059(c) .217 .829 .034 .288

ageL -.179(c) -1.196 .238 -.184 .921

genL -.206(c) -1.434 .159 -.218 .9825 tcL .243(d) 1.298 .201 .196 .605

ageL -.227(d) -1.565 .125 -.235 .989genL -.224(d) -1.541 .131 -.231 .989

tgL .234(d) 1.602 .117 .240 .975a Predictors in the Model: (Constant), genL, tgL, hdL, ageL

b Predictors in the Model: (Constant), genL, tgL, hdLc Predictors in the Model: (Constant), tgL, hdLd Predictors in the Model: (Constant), hdLe Dependent Variable: abpiL

PAD- Duration Group A(Early) - Regression

Variables Entered/Removed(b)

ModelVariables Entered

Variables Removed Method

1 tgA, genA, bmiA(a) . Enter

2

. bmiA

Backward (criterion: Probability of F-to-remove >= .100).

3

. tgA

Backward (criterion: Probability of F-to-remove >= .100).

a All requested variables entered.b Dependent Variable: abpiA

Model Summary

Model R R SquareAdjusted R

SquareStd. Error of the Estimate

1 .493(a) .243 .148 .117612 .491(b) .241 .180 .115393 .400(c) .160 .127 .11906

a Predictors: (Constant), tgA, genA, bmiAb Predictors: (Constant), tgA, genAc Predictors: (Constant), genA

ANOVA(d)

Model Sum of

Squares df Mean Square F Sig.1 Regression .107 3 .036 2.568 .078(a)

Residual .332 24 .014Total .439 27

2 Regression .106 2 .053 3.969 .032(b)Residual .333 25 .013Total .439 27

3 Regression .070 1 .070 4.938 .035(c)Residual .369 26 .014Total .439 27

a Predictors: (Constant), tgA, genA, bmiAb Predictors: (Constant), tgA, genAc Predictors: (Constant), genAd Dependent Variable: abpiA

Coefficients(a)

Model

Unstandardized Coefficients

Standardized Coefficients

t Sig.B Std. Error Beta1 (Constant) .847 .180 4.717 .000

bmiA .002 .008 .058 .253 .802genA -.102 .056 -.407 -1.834 .079tgA .000 .000 .266 1.331 .196

2 (Constant) .891 .051 17.488 .000genA -.110 .044 -.441 -2.503 .019tgA .000 .000 .288 1.637 .114

3 (Constant) .957 .032 30.079 .000genA -.100 .045 -.400 -2.222 .035

a Dependent Variable: abpiA

Excluded Variables(c)

Model Beta In t Sig.Partial

Correlation

Collinearity Statistics

Tolerance2 bmiA .058(a) .253 .802 .052 .5943 bmiA .193(b) .919 .367 .181 .736 tgA .288(b) 1.637 .114 .311 .980

a Predictors in the Model: (Constant), tgA, genAb Predictors in the Model: (Constant), genAc Dependent Variable: abpiA

PAD- Duration Group B (1-10yr) - RegressionVariables Entered/Removed(b)

ModelVariables Entered

Variables Removed Method

1bmiB, smB, sbpB(a) . Enter

2

. smB

Backward (criterion: Probability of F-to-remove >= .100).

a All requested variables entered.b Dependent Variable: abpiB

Model Summary

Model R R SquareAdjusted R

SquareStd. Error of the Estimate

1 .617(a) .381 .303 .069422 .556(b) .309 .254 .07183

a Predictors: (Constant), bmiB, smB, sbpBb Predictors: (Constant), bmiB, sbpB

ANOVA(c)

Model Sum of

Squares df Mean Square F Sig.1 Regression .071 3 .024 4.920 .008(a)

Residual .116 24 .005Total .187 27

2 Regression .058 2 .029 5.602 .010(b)Residual .129 25 .005Total .187 27

a Predictors: (Constant), bmiB, smB, sbpBb Predictors: (Constant), bmiB, sbpBc Dependent Variable: abpiB

Coefficients(a)

Model

Unstandardized Coefficients

Standardized Coefficients

t Sig.B Std. Error Beta1 (Constant) .846 .127 6.671 .000

smB -.046 .027 -.279 -1.663 .109sbpB -.001 .001 -.366 -2.170 .040bmiB .010 .004 .399 2.468 .021

2 (Constant) .875 .130 6.731 .000sbpB -.002 .001 -.444 -2.654 .014bmiB .010 .004 .393 2.347 .027

a Dependent Variable: abpiB

Excluded Variables(b)

Model Beta In t Sig.Partial

Correlation

Collinearity Statistics

Tolerance2 smB -.279(a) -1.663 .109 -.321 .918

a Predictors in the Model: (Constant), bmiB, sbpBb Dependent Variable: abpiB

PAD- Duration Group C (>10yr) - RegressionVariables Entered/Removed(b)

ModelVariables Entered

Variables Removed Method

1 bmiC, tgC, genC(a) . Enter

a All requested variables entered.b Dependent Variable: abpiC

Model Summary

Model R R SquareAdjusted R

SquareStd. Error of the Estimate

1 .690(a) .476 .411 .07252a Predictors: (Constant), bmiC, tgC, genC

ANOVA(b)

Model Sum of

Squares df Mean Square F Sig.1 Regression .115 3 .038 7.278 .001(a)

Residual .126 24 .005Total .241 27

a Predictors: (Constant), bmiC, tgC, genCb Dependent Variable: abpiC

Coefficients(a)

Model

Unstandardized Coefficients

Standardized Coefficients

t Sig.B Std. Error Beta1 (Constant) 1.130 .105 10.749 .000

genC -.105 .029 -.560 -3.570 .002tgC .000 .000 .408 2.721 .012bmiC -.013 .004 -.493 -3.097 .005

a Dependent Variable: abpiC

Abbreviations used : bmi – body mass index; sbp – systolic blood pressure, dbp – diastolic blood pressure; abpi – ankle brachial pressure index; tc – total cholesterol; tg – triglyceride; hd – HDL cholesterol; ld – LDL cholesterol, tchd – ratio of tc/hd ; gend/gen – gender(male); dur/Durat – duration of T2DM; sm – smoker/smoking status ; A, B, C – 3 duration groups - <1year, 1-10year, and >10 year respectively.