Post on 26-Mar-2018
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.