After the weird results of the first round of analyses, where more inequality seemed to predict better psychological health (http://rpubs.com/mts/18108), I conducted revised analyses.
I have backwards eliminated from this beast of a term: Gini2 x BelowMedianIncome x PovStat x Race
Where BelowMedianIncome is whether participant's household is above or below the median household income of the neighborhood (census tract). This is a proxy for status in their immediate proximity.
We aim to examine the relation of neighborhood-level income inequality with psychosocial and biomedical risk factors of CVD within a racially and socioeconomically diverse cohort of adults in Baltimore, Maryland.
Psychosocial risk factors include: depressive symptoms, anger, anxiety, and perceived stress.
Biomedical risk factors include: blood pressure, cholesterol (LDL, HDL, Total Chol), glucose, and body mass index (BMI)
Covariates include: demographic (age, sex, race, education), medical conditions, medications, and substance use.
Examined:
Below are the final models and graphs after backwards elimination.
Psychosocial:
Biomedical:
NDModel = lm(paste(c("NDSum ~ Gini100C*PovStat*Race*BelowMedianIncome + I(Gini100C^2)*PovStat*Race*BelowMedianIncome",
demographicNames, neighborhoodNames), collapse = " + "), analysisData)
finalNDModel = SelectModel(NDModel, keep = c(demographicNames, neighborhoodNames),
verbose = F)
summary(finalNDModel)
##
## Call:
## lm(formula = NDSum ~ Gini100C + PovStat + Race + BelowMedianIncome +
## I(Gini100C^2) + Age0 + Sex + HseHldEducationDich + MedianHouseholdIncome2C +
## Gini100C:PovStat + Gini100C:Race + Gini100C:BelowMedianIncome +
## Race:BelowMedianIncome + PovStat:I(Gini100C^2) + Race:I(Gini100C^2) +
## Gini100C:Race:BelowMedianIncome, data = analysisData)
##
## Residuals:
## Min 1Q Median 3Q Max
## -29.22 -9.36 -0.42 8.77 31.43
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 26.29734 1.79869 14.62 < 2e-16
## Gini100C -0.69775 0.11770 -5.93 0.00000000369
## PovStat 5.07202 0.81502 6.22 0.00000000061
## Race -6.16292 1.04935 -5.87 0.00000000512
## BelowMedianIncome 0.53168 0.98133 0.54 0.58803
## I(Gini100C^2) -0.00088 0.01080 -0.08 0.93505
## Age0 -0.08444 0.03125 -2.70 0.00696
## Sex 0.17813 0.57961 0.31 0.75863
## HseHldEducationDich -1.19383 0.66388 -1.80 0.07231
## MedianHouseholdIncome2C -3.83102 0.29443 -13.01 < 2e-16
## Gini100C:PovStat 0.63230 0.12369 5.11 0.00000035441
## Gini100C:Race 0.04888 0.15872 0.31 0.75816
## Gini100C:BelowMedianIncome -0.29900 0.15558 -1.92 0.05480
## Race:BelowMedianIncome 0.38671 1.23568 0.31 0.75436
## PovStat:I(Gini100C^2) -0.05462 0.01292 -4.23 0.00002479416
## Race:I(Gini100C^2) 0.05153 0.01354 3.81 0.00015
## Gini100C:Race:BelowMedianIncome 0.54906 0.19152 2.87 0.00420
##
## Residual standard error: 11.9 on 1728 degrees of freedom
## (47 observations deleted due to missingness)
## Multiple R-squared: 0.186, Adjusted R-squared: 0.179
## F-statistic: 24.7 on 16 and 1728 DF, p-value: <2e-16
##
## ************************************************************
## ************************************************************
## BEGIN: CESimp
## ************************************************************
## ************************************************************
##
## Call:
## lm(formula = "CESimp ~ Gini100C*PovStat*Race*BelowMedianIncome + I(Gini100C^2)*PovStat*Race*BelowMedianIncome + Age0 + Sex + Race + HseHldEducationDich + PovStat + CVDclusterdich + DMMclusterdich + PhysBMI + rxPsych + rxHTN + rxDiabetes + rxHypercholesterolemia + SmokingCurr + AlcoholCurr + IllicitDrugCurr + MedianHouseholdIncome2C",
## data = analysisData)
##
## Residuals:
## Min 1Q Median 3Q Max
## -21.88 -7.32 -2.00 5.67 43.11
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) 15.72349 2.12544 7.40
## Gini100C -0.16937 0.12467 -1.36
## PovStat 6.05943 2.16698 2.80
## Race 1.12545 1.18871 0.95
## BelowMedianIncome 2.61979 1.43682 1.82
## I(Gini100C^2) 0.00281 0.01283 0.22
## Age0 -0.04089 0.02957 -1.38
## Sex -1.34520 0.51394 -2.62
## HseHldEducationDich -3.58897 0.57008 -6.30
## CVDclusterdich -0.13423 1.35173 -0.10
## DMMclusterdich 0.76211 0.66389 1.15
## PhysBMI -0.00567 0.03519 -0.16
## rxPsych 7.51360 0.73124 10.28
## rxHTN -0.65471 0.66835 -0.98
## rxDiabetes 0.67252 1.08230 0.62
## rxHypercholesterolemia -1.05492 0.91591 -1.15
## SmokingCurr -1.83880 0.64625 -2.85
## AlcoholCurr 0.53196 0.52329 1.02
## IllicitDrugCurr 2.26255 0.72174 3.13
## MedianHouseholdIncome2C -0.21845 0.26186 -0.83
## Gini100C:PovStat -0.05468 0.30254 -0.18
## Gini100C:Race 0.18255 0.18508 0.99
## PovStat:Race -4.47692 2.46073 -1.82
## Gini100C:BelowMedianIncome -0.06821 0.19204 -0.36
## PovStat:BelowMedianIncome -3.96706 2.74814 -1.44
## Race:BelowMedianIncome -2.74469 1.85433 -1.48
## PovStat:I(Gini100C^2) -0.05005 0.03599 -1.39
## Race:I(Gini100C^2) -0.02925 0.01925 -1.52
## BelowMedianIncome:I(Gini100C^2) -0.00603 0.02157 -0.28
## Gini100C:PovStat:Race 0.02438 0.38660 0.06
## Gini100C:PovStat:BelowMedianIncome 0.34700 0.37934 0.91
## Gini100C:Race:BelowMedianIncome 0.01203 0.26953 0.04
## PovStat:Race:BelowMedianIncome 6.35404 3.20569 1.98
## PovStat:Race:I(Gini100C^2) 0.08435 0.04132 2.04
## PovStat:BelowMedianIncome:I(Gini100C^2) 0.05335 0.04387 1.22
## Race:BelowMedianIncome:I(Gini100C^2) 0.05436 0.03111 1.75
## Gini100C:PovStat:Race:BelowMedianIncome -0.25863 0.48483 -0.53
## PovStat:Race:BelowMedianIncome:I(Gini100C^2) -0.12288 0.05252 -2.34
## Pr(>|t|)
## (Intercept) 2.1e-13
## Gini100C 0.1745
## PovStat 0.0052
## Race 0.3439
## BelowMedianIncome 0.0684
## I(Gini100C^2) 0.8269
## Age0 0.1668
## Sex 0.0089
## HseHldEducationDich 3.9e-10
## CVDclusterdich 0.9209
## DMMclusterdich 0.2511
## PhysBMI 0.8721
## rxPsych < 2e-16
## rxHTN 0.3274
## rxDiabetes 0.5344
## rxHypercholesterolemia 0.2496
## SmokingCurr 0.0045
## AlcoholCurr 0.3095
## IllicitDrugCurr 0.0017
## MedianHouseholdIncome2C 0.4043
## Gini100C:PovStat 0.8566
## Gini100C:Race 0.3241
## PovStat:Race 0.0690
## Gini100C:BelowMedianIncome 0.7225
## PovStat:BelowMedianIncome 0.1490
## Race:BelowMedianIncome 0.1390
## PovStat:I(Gini100C^2) 0.1645
## Race:I(Gini100C^2) 0.1289
## BelowMedianIncome:I(Gini100C^2) 0.7799
## Gini100C:PovStat:Race 0.9497
## Gini100C:PovStat:BelowMedianIncome 0.3605
## Gini100C:Race:BelowMedianIncome 0.9644
## PovStat:Race:BelowMedianIncome 0.0476
## PovStat:Race:I(Gini100C^2) 0.0414
## PovStat:BelowMedianIncome:I(Gini100C^2) 0.2241
## Race:BelowMedianIncome:I(Gini100C^2) 0.0808
## Gini100C:PovStat:Race:BelowMedianIncome 0.5938
## PovStat:Race:BelowMedianIncome:I(Gini100C^2) 0.0194
##
## Residual standard error: 10.3 on 1754 degrees of freedom
## Multiple R-squared: 0.163, Adjusted R-squared: 0.145
## F-statistic: 9.2 on 37 and 1754 DF, p-value: <2e-16
##
## ***************** END: CESimp *****************************
##
##
## ************************************************************
## ************************************************************
## BEGIN: acasiPDSQanx
## ************************************************************
## ************************************************************
##
## Call:
## lm(formula = "acasiPDSQanx ~ Gini100C*PovStat*Race*BelowMedianIncome + I(Gini100C^2)*PovStat*Race*BelowMedianIncome + Age0 + Sex + Race + HseHldEducationDich + PovStat + CVDclusterdich + DMMclusterdich + PhysBMI + rxPsych + rxHTN + rxDiabetes + rxHypercholesterolemia + SmokingCurr + AlcoholCurr + IllicitDrugCurr + MedianHouseholdIncome2C",
## data = analysisData)
##
## Residuals:
## Min 1Q Median 3Q Max
## -6.690 -2.260 -0.949 2.042 8.425
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) 4.635393 0.624579 7.42
## Gini100C -0.016383 0.036636 -0.45
## PovStat 1.473008 0.636784 2.31
## Race -0.218839 0.349313 -0.63
## BelowMedianIncome 0.667991 0.422220 1.58
## I(Gini100C^2) -0.001305 0.003769 -0.35
## Age0 -0.034956 0.008688 -4.02
## Sex -0.635161 0.151026 -4.21
## HseHldEducationDich -0.758410 0.167522 -4.53
## CVDclusterdich -0.011895 0.397218 -0.03
## DMMclusterdich 0.293542 0.195090 1.50
## PhysBMI -0.000298 0.010341 -0.03
## rxPsych 1.701852 0.214882 7.92
## rxHTN -0.140817 0.196399 -0.72
## rxDiabetes -0.125143 0.318042 -0.39
## rxHypercholesterolemia 0.090979 0.269148 0.34
## SmokingCurr -0.271332 0.189905 -1.43
## AlcoholCurr 0.228432 0.153774 1.49
## IllicitDrugCurr 0.350560 0.212090 1.65
## MedianHouseholdIncome2C 0.013783 0.076950 0.18
## Gini100C:PovStat 0.025500 0.088903 0.29
## Gini100C:Race 0.036685 0.054388 0.67
## PovStat:Race -1.116801 0.723105 -1.54
## Gini100C:BelowMedianIncome -0.054710 0.056432 -0.97
## PovStat:BelowMedianIncome -1.150230 0.807562 -1.42
## Race:BelowMedianIncome -0.344468 0.544909 -0.63
## PovStat:I(Gini100C^2) -0.019380 0.010577 -1.83
## Race:I(Gini100C^2) -0.004487 0.005658 -0.79
## BelowMedianIncome:I(Gini100C^2) -0.002306 0.006339 -0.36
## Gini100C:PovStat:Race -0.032935 0.113606 -0.29
## Gini100C:PovStat:BelowMedianIncome 0.000550 0.111473 0.00
## Gini100C:Race:BelowMedianIncome 0.054509 0.079203 0.69
## PovStat:Race:BelowMedianIncome 1.332932 0.942019 1.41
## PovStat:Race:I(Gini100C^2) 0.025670 0.012142 2.11
## PovStat:BelowMedianIncome:I(Gini100C^2) 0.019760 0.012892 1.53
## Race:BelowMedianIncome:I(Gini100C^2) 0.011053 0.009143 1.21
## Gini100C:PovStat:Race:BelowMedianIncome -0.013457 0.142471 -0.09
## PovStat:Race:BelowMedianIncome:I(Gini100C^2) -0.031091 0.015434 -2.01
## Pr(>|t|)
## (Intercept) 1.8e-13
## Gini100C 0.655
## PovStat 0.021
## Race 0.531
## BelowMedianIncome 0.114
## I(Gini100C^2) 0.729
## Age0 6.0e-05
## Sex 2.7e-05
## HseHldEducationDich 6.4e-06
## CVDclusterdich 0.976
## DMMclusterdich 0.133
## PhysBMI 0.977
## rxPsych 4.2e-15
## rxHTN 0.473
## rxDiabetes 0.694
## rxHypercholesterolemia 0.735
## SmokingCurr 0.153
## AlcoholCurr 0.138
## IllicitDrugCurr 0.099
## MedianHouseholdIncome2C 0.858
## Gini100C:PovStat 0.774
## Gini100C:Race 0.500
## PovStat:Race 0.123
## Gini100C:BelowMedianIncome 0.332
## PovStat:BelowMedianIncome 0.155
## Race:BelowMedianIncome 0.527
## PovStat:I(Gini100C^2) 0.067
## Race:I(Gini100C^2) 0.428
## BelowMedianIncome:I(Gini100C^2) 0.716
## Gini100C:PovStat:Race 0.772
## Gini100C:PovStat:BelowMedianIncome 0.996
## Gini100C:Race:BelowMedianIncome 0.491
## PovStat:Race:BelowMedianIncome 0.157
## PovStat:Race:I(Gini100C^2) 0.035
## PovStat:BelowMedianIncome:I(Gini100C^2) 0.126
## Race:BelowMedianIncome:I(Gini100C^2) 0.227
## Gini100C:PovStat:Race:BelowMedianIncome 0.925
## PovStat:Race:BelowMedianIncome:I(Gini100C^2) 0.044
##
## Residual standard error: 3.02 on 1754 degrees of freedom
## Multiple R-squared: 0.121, Adjusted R-squared: 0.102
## F-statistic: 6.5 on 37 and 1754 DF, p-value: <2e-16
##
## ***************** END: acasiPDSQanx *****************************
##
##
## ************************************************************
## ************************************************************
## BEGIN: acasiPerStr
## ************************************************************
## ************************************************************
##
## Call:
## lm(formula = "acasiPerStr ~ Gini100C*PovStat*Race*BelowMedianIncome + I(Gini100C^2)*PovStat*Race*BelowMedianIncome + Age0 + Sex + Race + HseHldEducationDich + PovStat + CVDclusterdich + DMMclusterdich + PhysBMI + rxPsych + rxHTN + rxDiabetes + rxHypercholesterolemia + SmokingCurr + AlcoholCurr + IllicitDrugCurr + MedianHouseholdIncome2C",
## data = analysisData)
##
## Residuals:
## Min 1Q Median 3Q Max
## -7.735 -2.315 -0.138 2.115 10.230
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) 6.36283 0.65030 9.78
## Gini100C -0.00782 0.03814 -0.20
## PovStat 2.23634 0.66301 3.37
## Race -0.23636 0.36370 -0.65
## BelowMedianIncome 1.41676 0.43961 3.22
## I(Gini100C^2) -0.00139 0.00392 -0.35
## Age0 -0.01440 0.00905 -1.59
## Sex -0.10462 0.15725 -0.67
## HseHldEducationDich -0.92811 0.17442 -5.32
## CVDclusterdich 0.58673 0.41358 1.42
## DMMclusterdich -0.09324 0.20312 -0.46
## PhysBMI -0.01270 0.01077 -1.18
## rxPsych 1.21067 0.22373 5.41
## rxHTN -0.15953 0.20449 -0.78
## rxDiabetes 0.41231 0.33114 1.25
## rxHypercholesterolemia -0.35547 0.28023 -1.27
## SmokingCurr -0.49490 0.19773 -2.50
## AlcoholCurr 0.34636 0.16011 2.16
## IllicitDrugCurr 0.27058 0.22082 1.23
## MedianHouseholdIncome2C -0.08337 0.08012 -1.04
## Gini100C:PovStat 0.08540 0.09256 0.92
## Gini100C:Race 0.00127 0.05663 0.02
## PovStat:Race -1.54290 0.75288 -2.05
## Gini100C:BelowMedianIncome 0.00297 0.05876 0.05
## PovStat:BelowMedianIncome -2.16806 0.84082 -2.58
## Race:BelowMedianIncome -0.58214 0.56735 -1.03
## PovStat:I(Gini100C^2) -0.02014 0.01101 -1.83
## Race:I(Gini100C^2) -0.00479 0.00589 -0.81
## BelowMedianIncome:I(Gini100C^2) -0.00791 0.00660 -1.20
## Gini100C:PovStat:Race -0.14498 0.11828 -1.23
## Gini100C:PovStat:BelowMedianIncome -0.11111 0.11606 -0.96
## Gini100C:Race:BelowMedianIncome 0.04534 0.08246 0.55
## PovStat:Race:BelowMedianIncome 1.87161 0.98081 1.91
## PovStat:Race:I(Gini100C^2) 0.02990 0.01264 2.37
## PovStat:BelowMedianIncome:I(Gini100C^2) 0.02894 0.01342 2.16
## Race:BelowMedianIncome:I(Gini100C^2) 0.01489 0.00952 1.56
## Gini100C:PovStat:Race:BelowMedianIncome 0.16630 0.14834 1.12
## PovStat:Race:BelowMedianIncome:I(Gini100C^2) -0.04445 0.01607 -2.77
## Pr(>|t|)
## (Intercept) < 2e-16
## Gini100C 0.83764
## PovStat 0.00076
## Race 0.51585
## BelowMedianIncome 0.00129
## I(Gini100C^2) 0.72307
## Age0 0.11169
## Sex 0.50592
## HseHldEducationDich 0.000000116
## CVDclusterdich 0.15617
## DMMclusterdich 0.64627
## PhysBMI 0.23829
## rxPsych 0.000000071
## rxHTN 0.43541
## rxDiabetes 0.21325
## rxHypercholesterolemia 0.20480
## SmokingCurr 0.01241
## AlcoholCurr 0.03065
## IllicitDrugCurr 0.22063
## MedianHouseholdIncome2C 0.29821
## Gini100C:PovStat 0.35632
## Gini100C:Race 0.98210
## PovStat:Race 0.04058
## Gini100C:BelowMedianIncome 0.95967
## PovStat:BelowMedianIncome 0.01000
## Race:BelowMedianIncome 0.30500
## PovStat:I(Gini100C^2) 0.06759
## Race:I(Gini100C^2) 0.41630
## BelowMedianIncome:I(Gini100C^2) 0.23090
## Gini100C:PovStat:Race 0.22047
## Gini100C:PovStat:BelowMedianIncome 0.33852
## Gini100C:Race:BelowMedianIncome 0.58250
## PovStat:Race:BelowMedianIncome 0.05652
## PovStat:Race:I(Gini100C^2) 0.01812
## PovStat:BelowMedianIncome:I(Gini100C^2) 0.03120
## Race:BelowMedianIncome:I(Gini100C^2) 0.11807
## Gini100C:PovStat:Race:BelowMedianIncome 0.26240
## PovStat:Race:BelowMedianIncome:I(Gini100C^2) 0.00573
##
## Residual standard error: 3.14 on 1754 degrees of freedom
## Multiple R-squared: 0.114, Adjusted R-squared: 0.0952
## F-statistic: 6.1 on 37 and 1754 DF, p-value: <2e-16
##
## ***************** END: acasiPerStr *****************************
##
##
## ************************************************************
## ************************************************************
## BEGIN: acasiAnger
## ************************************************************
## ************************************************************
## Warning: All variables have been thrown out of the model.
## No model could be specified.
##
## Call:
## lm(formula = acasiAnger ~ Gini100C + PovStat + Race + BelowMedianIncome +
## Age0 + Sex + HseHldEducationDich + CVDclusterdich + DMMclusterdich +
## PhysBMI + rxPsych + rxHTN + rxDiabetes + rxHypercholesterolemia +
## SmokingCurr + AlcoholCurr + IllicitDrugCurr + MedianHouseholdIncome2C,
## data = analysisData)
##
## Residuals:
## Min 1Q Median 3Q Max
## -13.29 -4.75 -0.73 4.21 20.42
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 13.3977 1.1756 11.40 < 2e-16
## Gini100C -0.0347 0.0238 -1.46 0.14523
## PovStat 0.7499 0.3219 2.33 0.01993
## Race -1.3816 0.3252 -4.25 0.00002271
## BelowMedianIncome 0.5472 0.3145 1.74 0.08207
## Age0 -0.0719 0.0176 -4.10 0.00004411
## Sex -0.0571 0.3049 -0.19 0.85150
## HseHldEducationDich -1.6539 0.3357 -4.93 0.00000092
## CVDclusterdich 0.5243 0.7982 0.66 0.51135
## DMMclusterdich 0.0729 0.3932 0.19 0.85290
## PhysBMI 0.0221 0.0208 1.06 0.28930
## rxPsych 1.5826 0.4319 3.66 0.00026
## rxHTN -0.3876 0.3974 -0.98 0.32960
## rxDiabetes 0.5925 0.6416 0.92 0.35583
## rxHypercholesterolemia 0.1768 0.5460 0.32 0.74605
## SmokingCurr -0.4878 0.3852 -1.27 0.20549
## AlcoholCurr 0.4718 0.3104 1.52 0.12871
## IllicitDrugCurr 1.1299 0.4289 2.63 0.00850
## MedianHouseholdIncome2C -0.0958 0.1496 -0.64 0.52195
##
## Residual standard error: 6.14 on 1773 degrees of freedom
## Multiple R-squared: 0.0734, Adjusted R-squared: 0.064
## F-statistic: 7.8 on 18 and 1773 DF, p-value: <2e-16
##
## ***************** END: acasiAnger *****************************
##
##
## ************************************************************
## ************************************************************
## BEGIN: Discrim01d
## ************************************************************
## ************************************************************
## Warning: All variables have been thrown out of the model.
## No model could be specified.
##
## Call:
## lm(formula = Discrim01d ~ Gini100C + PovStat + Race + BelowMedianIncome +
## Age0 + Sex + HseHldEducationDich + CVDclusterdich + DMMclusterdich +
## PhysBMI + rxPsych + rxHTN + rxDiabetes + rxHypercholesterolemia +
## SmokingCurr + AlcoholCurr + IllicitDrugCurr + MedianHouseholdIncome2C,
## data = analysisData)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.672 -0.855 -0.347 0.816 2.609
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.11764 0.20110 5.56 3.1e-08
## Gini100C 0.00254 0.00407 0.62 0.5328
## PovStat 0.07943 0.05506 1.44 0.1493
## Race 0.44264 0.05564 7.96 3.1e-15
## BelowMedianIncome 0.22870 0.05380 4.25 2.2e-05
## Age0 0.00206 0.00300 0.69 0.4931
## Sex 0.04335 0.05215 0.83 0.4060
## HseHldEducationDich -0.05375 0.05743 -0.94 0.3495
## CVDclusterdich 0.11506 0.13654 0.84 0.3995
## DMMclusterdich 0.13540 0.06726 2.01 0.0443
## PhysBMI 0.00947 0.00356 2.66 0.0079
## rxPsych 0.21233 0.07389 2.87 0.0041
## rxHTN -0.05704 0.06799 -0.84 0.4016
## rxDiabetes -0.21041 0.10975 -1.92 0.0554
## rxHypercholesterolemia -0.07749 0.09340 -0.83 0.4069
## SmokingCurr -0.09286 0.06589 -1.41 0.1589
## AlcoholCurr 0.01676 0.05311 0.32 0.7523
## IllicitDrugCurr 0.15405 0.07336 2.10 0.0359
## MedianHouseholdIncome2C 0.03104 0.02559 1.21 0.2252
##
## Residual standard error: 1.05 on 1773 degrees of freedom
## Multiple R-squared: 0.0733, Adjusted R-squared: 0.0639
## F-statistic: 7.79 on 18 and 1773 DF, p-value: <2e-16
##
## ***************** END: Discrim01d *****************************
##
##
## ************************************************************
## ************************************************************
## BEGIN: Discrim01b
## ************************************************************
## ************************************************************
##
## Call:
## lm(formula = Discrim01b ~ Gini100C + PovStat + Race + BelowMedianIncome +
## I(Gini100C^2) + Age0 + Sex + HseHldEducationDich + CVDclusterdich +
## DMMclusterdich + PhysBMI + rxPsych + rxHTN + rxDiabetes +
## rxHypercholesterolemia + SmokingCurr + AlcoholCurr + IllicitDrugCurr +
## MedianHouseholdIncome2C + Gini100C:Race + Gini100C:BelowMedianIncome +
## PovStat:BelowMedianIncome + Race:BelowMedianIncome + Race:I(Gini100C^2) +
## BelowMedianIncome:I(Gini100C^2) + Gini100C:Race:BelowMedianIncome +
## Race:BelowMedianIncome:I(Gini100C^2), data = analysisData)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.988 -0.641 -0.350 0.560 2.651
##
## Coefficients:
## Estimate Std. Error t value
## (Intercept) 1.31991 0.19032 6.94
## Gini100C 0.00905 0.01021 0.89
## PovStat -0.16670 0.07617 -2.19
## Race 0.82904 0.09260 8.95
## BelowMedianIncome -0.07435 0.11126 -0.67
## I(Gini100C^2) -0.00202 0.00107 -1.89
## Age0 0.00254 0.00268 0.95
## Sex 0.18811 0.04673 4.03
## HseHldEducationDich 0.10179 0.05168 1.97
## CVDclusterdich -0.10628 0.12256 -0.87
## DMMclusterdich 0.05872 0.06026 0.97
## PhysBMI 0.00321 0.00319 1.01
## rxPsych 0.10809 0.06623 1.63
## rxHTN -0.05326 0.06068 -0.88
## rxDiabetes -0.01922 0.09824 -0.20
## rxHypercholesterolemia 0.06107 0.08331 0.73
## SmokingCurr 0.09571 0.05876 1.63
## AlcoholCurr -0.00382 0.04757 -0.08
## IllicitDrugCurr 0.04854 0.06568 0.74
## MedianHouseholdIncome2C 0.03495 0.02341 1.49
## Gini100C:Race -0.02420 0.01451 -1.67
## Gini100C:BelowMedianIncome 0.01172 0.01439 0.81
## PovStat:BelowMedianIncome 0.20252 0.09733 2.08
## Race:BelowMedianIncome -0.00143 0.12944 -0.01
## Race:I(Gini100C^2) 0.00391 0.00138 2.84
## BelowMedianIncome:I(Gini100C^2) 0.00295 0.00155 1.90
## Gini100C:Race:BelowMedianIncome 0.00577 0.01950 0.30
## Race:BelowMedianIncome:I(Gini100C^2) -0.00492 0.00194 -2.53
## Pr(>|t|)
## (Intercept) 0.0000000000057
## Gini100C 0.3756
## PovStat 0.0288
## Race < 2e-16
## BelowMedianIncome 0.5040
## I(Gini100C^2) 0.0591
## Age0 0.3446
## Sex 0.0000593577286
## HseHldEducationDich 0.0490
## CVDclusterdich 0.3860
## DMMclusterdich 0.3300
## PhysBMI 0.3146
## rxPsych 0.1029
## rxHTN 0.3802
## rxDiabetes 0.8449
## rxHypercholesterolemia 0.4636
## SmokingCurr 0.1036
## AlcoholCurr 0.9360
## IllicitDrugCurr 0.4600
## MedianHouseholdIncome2C 0.1356
## Gini100C:Race 0.0956
## Gini100C:BelowMedianIncome 0.4155
## PovStat:BelowMedianIncome 0.0376
## Race:BelowMedianIncome 0.9912
## Race:I(Gini100C^2) 0.0046
## BelowMedianIncome:I(Gini100C^2) 0.0570
## Gini100C:Race:BelowMedianIncome 0.7673
## Race:BelowMedianIncome:I(Gini100C^2) 0.0114
##
## Residual standard error: 0.935 on 1764 degrees of freedom
## Multiple R-squared: 0.196, Adjusted R-squared: 0.183
## F-statistic: 15.9 on 27 and 1764 DF, p-value: <2e-16
##
## ***************** END: Discrim01b *****************************
##
## ************************************************************
## ************************************************************
## BEGIN: PhysMeanSBPsitimp
## ************************************************************
## ************************************************************
##
## Call:
## lm(formula = PhysMeanSBPsitimp ~ Gini100C + PovStat + Race +
## BelowMedianIncome + Age0 + Sex + HseHldEducationDich + CVDclusterdich +
## DMMclusterdich + PhysBMI + rxPsych + rxHTN + rxDiabetes +
## rxHypercholesterolemia + SmokingCurr + AlcoholCurr + IllicitDrugCurr +
## MedianHouseholdIncome2C + PovStat:BelowMedianIncome, data = analysisData)
##
## Residuals:
## Min 1Q Median 3Q Max
## -43.44 -10.30 -1.86 9.33 63.48
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 71.6647 3.0516 23.48 < 2e-16
## Gini100C 0.0226 0.0617 0.37 0.71460
## PovStat 3.8015 1.2474 3.05 0.00234
## Race 3.1147 0.8475 3.68 0.00024
## BelowMedianIncome 2.0916 1.0341 2.02 0.04325
## Age0 0.5763 0.0455 12.67 < 2e-16
## Sex 3.6536 0.7901 4.62 0.000004
## HseHldEducationDich -1.3889 0.8710 -1.59 0.11099
## CVDclusterdich -0.3382 2.0688 -0.16 0.87015
## DMMclusterdich -0.7130 1.0189 -0.70 0.48417
## PhysBMI 0.5187 0.0540 9.61 < 2e-16
## rxPsych -0.4143 1.1214 -0.37 0.71184
## rxHTN 2.7146 1.0301 2.64 0.00848
## rxDiabetes 0.6610 1.6638 0.40 0.69121
## rxHypercholesterolemia -0.6644 1.4150 -0.47 0.63875
## SmokingCurr -0.0125 0.9981 -0.01 0.99002
## AlcoholCurr 1.2206 0.8046 1.52 0.12944
## IllicitDrugCurr 2.6996 1.1114 2.43 0.01524
## MedianHouseholdIncome2C -0.1303 0.3876 -0.34 0.73683
## PovStat:BelowMedianIncome -3.7871 1.5902 -2.38 0.01735
##
## Residual standard error: 15.9 on 1772 degrees of freedom
## Multiple R-squared: 0.182, Adjusted R-squared: 0.174
## F-statistic: 20.8 on 19 and 1772 DF, p-value: <2e-16
##
## ***************** END: PhysMeanSBPsitimp *****************************
##
##
## ************************************************************
## ************************************************************
## BEGIN: PhysMeanDBPsitimp
## ************************************************************
## ************************************************************
## Warning: All variables have been thrown out of the model.
## No model could be specified.
##
## Call:
## lm(formula = PhysMeanDBPsitimp ~ Gini100C + PovStat + Race +
## BelowMedianIncome + Age0 + Sex + HseHldEducationDich + CVDclusterdich +
## DMMclusterdich + PhysBMI + rxPsych + rxHTN + rxDiabetes +
## rxHypercholesterolemia + SmokingCurr + AlcoholCurr + IllicitDrugCurr +
## MedianHouseholdIncome2C, data = analysisData)
##
## Residuals:
## Min 1Q Median 3Q Max
## -32.26 -7.69 -0.21 7.18 39.64
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 57.4187 1.9808 28.99 < 2e-16
## Gini100C -0.0180 0.0401 -0.45 0.65270
## PovStat 0.8358 0.5423 1.54 0.12344
## Race 1.0043 0.5480 1.83 0.06703
## BelowMedianIncome 0.2114 0.5299 0.40 0.69001
## Age0 0.0892 0.0296 3.02 0.00259
## Sex 4.1130 0.5137 8.01 2.1e-15
## HseHldEducationDich -0.3301 0.5657 -0.58 0.55963
## CVDclusterdich -0.8679 1.3449 -0.65 0.51881
## DMMclusterdich -0.4429 0.6625 -0.67 0.50388
## PhysBMI 0.2580 0.0351 7.36 2.9e-13
## rxPsych 0.2719 0.7278 0.37 0.70870
## rxHTN 2.4817 0.6697 3.71 0.00022
## rxDiabetes -2.8953 1.0810 -2.68 0.00747
## rxHypercholesterolemia -1.2472 0.9200 -1.36 0.17539
## SmokingCurr 0.6792 0.6490 1.05 0.29544
## AlcoholCurr 0.7369 0.5231 1.41 0.15909
## IllicitDrugCurr 1.0350 0.7226 1.43 0.15223
## MedianHouseholdIncome2C -0.3418 0.2520 -1.36 0.17520
##
## Residual standard error: 10.3 on 1773 degrees of freedom
## Multiple R-squared: 0.084, Adjusted R-squared: 0.0747
## F-statistic: 9.03 on 18 and 1773 DF, p-value: <2e-16
##
## ***************** END: PhysMeanDBPsitimp *****************************
##
##
## ************************************************************
## ************************************************************
## BEGIN: LabResGlucoseimp
## ************************************************************
## ************************************************************
##
## Call:
## lm(formula = LabResGlucoseimp ~ Gini100C + PovStat + Race + BelowMedianIncome +
## Age0 + Sex + HseHldEducationDich + CVDclusterdich + DMMclusterdich +
## PhysBMI + rxPsych + rxHTN + rxDiabetes + rxHypercholesterolemia +
## SmokingCurr + AlcoholCurr + IllicitDrugCurr + MedianHouseholdIncome2C +
## PovStat:BelowMedianIncome, data = analysisData)
##
## Residuals:
## Min 1Q Median 3Q Max
## -128.8 -11.6 -4.1 4.6 385.9
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 64.6624 6.5273 9.91 < 2e-16
## Gini100C -0.1746 0.1321 -1.32 0.18640
## PovStat 7.2426 2.6681 2.71 0.00670
## Race -5.1491 1.8127 -2.84 0.00456
## BelowMedianIncome 4.4959 2.2118 2.03 0.04223
## Age0 0.2101 0.0973 2.16 0.03099
## Sex 5.7820 1.6899 3.42 0.00064
## HseHldEducationDich -0.6384 1.8631 -0.34 0.73191
## CVDclusterdich -3.2830 4.4251 -0.74 0.45825
## DMMclusterdich 6.8003 2.1795 3.12 0.00184
## PhysBMI 0.6850 0.1154 5.94 0.0000000035
## rxPsych -8.3212 2.3986 -3.47 0.00053
## rxHTN 3.8490 2.2034 1.75 0.08084
## rxDiabetes 63.3520 3.5589 17.80 < 2e-16
## rxHypercholesterolemia -7.1679 3.0266 -2.37 0.01798
## SmokingCurr 0.6229 2.1350 0.29 0.77051
## AlcoholCurr 0.8995 1.7210 0.52 0.60128
## IllicitDrugCurr -1.8608 2.3772 -0.78 0.43387
## MedianHouseholdIncome2C -0.7248 0.8291 -0.87 0.38213
## PovStat:BelowMedianIncome -8.1751 3.4015 -2.40 0.01635
##
## Residual standard error: 34 on 1772 degrees of freedom
## Multiple R-squared: 0.29, Adjusted R-squared: 0.282
## F-statistic: 38 on 19 and 1772 DF, p-value: <2e-16
##
## ***************** END: LabResGlucoseimp *****************************
##
##
## ************************************************************
## ************************************************************
## BEGIN: LabResGlucoseimpsqrt
## ************************************************************
## ************************************************************
##
## Call:
## lm(formula = LabResGlucoseimpsqrt ~ Gini100C + PovStat + Race +
## BelowMedianIncome + Age0 + Sex + HseHldEducationDich + CVDclusterdich +
## DMMclusterdich + PhysBMI + rxPsych + rxHTN + rxDiabetes +
## rxHypercholesterolemia + SmokingCurr + AlcoholCurr + IllicitDrugCurr +
## MedianHouseholdIncome2C + PovStat:BelowMedianIncome, data = analysisData)
##
## Residuals:
## Min 1Q Median 3Q Max
## -6.275 -0.522 -0.153 0.255 11.059
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 8.20864 0.24858 33.02 < 2e-16
## Gini100C -0.00576 0.00503 -1.14 0.2526
## PovStat 0.29754 0.10161 2.93 0.0035
## Race -0.21587 0.06903 -3.13 0.0018
## BelowMedianIncome 0.18445 0.08423 2.19 0.0287
## Age0 0.01148 0.00371 3.10 0.0020
## Sex 0.26299 0.06436 4.09 4.6e-05
## HseHldEducationDich -0.01696 0.07095 -0.24 0.8111
## CVDclusterdich -0.11726 0.16852 -0.70 0.4866
## DMMclusterdich 0.26819 0.08300 3.23 0.0013
## PhysBMI 0.03194 0.00439 7.27 5.5e-13
## rxPsych -0.31871 0.09135 -3.49 0.0005
## rxHTN 0.15582 0.08391 1.86 0.0635
## rxDiabetes 2.45663 0.13553 18.13 < 2e-16
## rxHypercholesterolemia -0.26644 0.11526 -2.31 0.0209
## SmokingCurr 0.02250 0.08131 0.28 0.7821
## AlcoholCurr 0.03150 0.06554 0.48 0.6308
## IllicitDrugCurr -0.08057 0.09053 -0.89 0.3736
## MedianHouseholdIncome2C -0.02024 0.03158 -0.64 0.5217
## PovStat:BelowMedianIncome -0.33427 0.12954 -2.58 0.0099
##
## Residual standard error: 1.3 on 1772 degrees of freedom
## Multiple R-squared: 0.312, Adjusted R-squared: 0.305
## F-statistic: 42.4 on 19 and 1772 DF, p-value: <2e-16
##
## ***************** END: LabResGlucoseimpsqrt *****************************
##
##
## ************************************************************
## ************************************************************
## BEGIN: PhysBMI
## ************************************************************
## ************************************************************
## Warning: PhysBMI cannot be found in the model
## These terms are ignored in the model selection.
##
## Call:
## lm(formula = PhysBMI ~ Gini100C + PovStat + Race + BelowMedianIncome +
## I(Gini100C^2) + Age0 + Sex + HseHldEducationDich + CVDclusterdich +
## DMMclusterdich + rxPsych + rxHTN + rxDiabetes + rxHypercholesterolemia +
## SmokingCurr + AlcoholCurr + IllicitDrugCurr + MedianHouseholdIncome2C +
## PovStat:Race, data = analysisData)
##
## Residuals:
## Min 1Q Median 3Q Max
## -16.79 -4.79 -0.88 3.91 32.26
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 35.04764 1.05897 33.10 < 2e-16
## Gini100C -0.01025 0.03764 -0.27 0.78547
## PovStat 1.00596 0.58114 1.73 0.08362
## Race 0.74539 0.46481 1.60 0.10897
## BelowMedianIncome -0.49369 0.35814 -1.38 0.16822
## I(Gini100C^2) -0.01054 0.00348 -3.03 0.00251
## Age0 -0.09052 0.01981 -4.57 5.2e-06
## Sex -2.94031 0.33958 -8.66 < 2e-16
## HseHldEducationDich -0.15025 0.38139 -0.39 0.69366
## CVDclusterdich -0.29739 0.90666 -0.33 0.74295
## DMMclusterdich 0.64083 0.44666 1.43 0.15155
## rxPsych -0.26278 0.49095 -0.54 0.59255
## rxHTN 3.45526 0.44417 7.78 1.2e-14
## rxDiabetes 2.33845 0.72736 3.21 0.00133
## rxHypercholesterolemia 1.32121 0.61930 2.13 0.03303
## SmokingCurr 1.93442 0.43492 4.45 9.2e-06
## AlcoholCurr -0.95496 0.35197 -2.71 0.00673
## IllicitDrugCurr -1.62778 0.48613 -3.35 0.00083
## MedianHouseholdIncome2C 0.06024 0.17415 0.35 0.72944
## PovStat:Race -2.32845 0.72042 -3.23 0.00125
##
## Residual standard error: 6.96 on 1772 degrees of freedom
## Multiple R-squared: 0.181, Adjusted R-squared: 0.172
## F-statistic: 20.5 on 19 and 1772 DF, p-value: <2e-16
##
## ***************** END: PhysBMI *****************************
##
##
## ************************************************************
## ************************************************************
## BEGIN: LabResLDLcalcimp
## ************************************************************
## ************************************************************
## Warning: All variables have been thrown out of the model.
## No model could be specified.
##
## Call:
## lm(formula = LabResLDLcalcimp ~ Gini100C + PovStat + Race + BelowMedianIncome +
## Age0 + Sex + HseHldEducationDich + CVDclusterdich + DMMclusterdich +
## PhysBMI + rxPsych + rxHTN + rxDiabetes + rxHypercholesterolemia +
## SmokingCurr + AlcoholCurr + IllicitDrugCurr + MedianHouseholdIncome2C,
## data = analysisData)
##
## Residuals:
## Min 1Q Median 3Q Max
## -92.21 -23.02 -1.75 19.43 153.12
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 79.3487 6.5083 12.19 < 2e-16
## Gini100C -0.0608 0.1317 -0.46 0.6446
## PovStat -2.0471 1.7819 -1.15 0.2508
## Race -3.9770 1.8007 -2.21 0.0273
## BelowMedianIncome -3.5379 1.7413 -2.03 0.0423
## Age0 0.5277 0.0972 5.43 0.000000064
## Sex -3.1315 1.6879 -1.86 0.0637
## HseHldEducationDich 1.9056 1.8587 1.03 0.3054
## CVDclusterdich -10.8023 4.4190 -2.44 0.0146
## DMMclusterdich -3.3836 2.1768 -1.55 0.1203
## PhysBMI 0.4984 0.1153 4.32 0.000016163
## rxPsych -1.5518 2.3914 -0.65 0.5165
## rxHTN 2.7825 2.2004 1.26 0.2062
## rxDiabetes -7.7827 3.5520 -2.19 0.0286
## rxHypercholesterolemia -8.3306 3.0229 -2.76 0.0059
## SmokingCurr 0.6255 2.1324 0.29 0.7693
## AlcoholCurr -4.1028 1.7187 -2.39 0.0171
## IllicitDrugCurr -0.0794 2.3743 -0.03 0.9733
## MedianHouseholdIncome2C 1.5002 0.8281 1.81 0.0702
##
## Residual standard error: 34 on 1773 degrees of freedom
## Multiple R-squared: 0.0646, Adjusted R-squared: 0.0552
## F-statistic: 6.81 on 18 and 1773 DF, p-value: <2e-16
##
## ***************** END: LabResLDLcalcimp *****************************
##
##
## ************************************************************
## ************************************************************
## BEGIN: LabResHDLimp
## ************************************************************
## ************************************************************
##
## Call:
## lm(formula = LabResHDLimp ~ Gini100C + PovStat + Race + BelowMedianIncome +
## I(Gini100C^2) + Age0 + Sex + HseHldEducationDich + CVDclusterdich +
## DMMclusterdich + PhysBMI + rxPsych + rxHTN + rxDiabetes +
## rxHypercholesterolemia + SmokingCurr + AlcoholCurr + IllicitDrugCurr +
## MedianHouseholdIncome2C + Gini100C:PovStat + Gini100C:Race +
## PovStat:Race + PovStat:I(Gini100C^2) + Race:I(Gini100C^2) +
## Gini100C:PovStat:Race + PovStat:Race:I(Gini100C^2), data = analysisData)
##
## Residuals:
## Min 1Q Median 3Q Max
## -50.53 -9.63 -2.07 7.27 112.24
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 63.92624 3.03478 21.06 < 2e-16
## Gini100C 0.17467 0.13814 1.26 0.2062
## PovStat -4.32046 1.93576 -2.23 0.0257
## Race 1.58355 1.39811 1.13 0.2575
## BelowMedianIncome -1.02557 0.79021 -1.30 0.1945
## I(Gini100C^2) -0.00866 0.01484 -0.58 0.5596
## Age0 0.19814 0.04393 4.51 0.0000069
## Sex -9.92883 0.76410 -12.99 < 2e-16
## HseHldEducationDich -0.00861 0.84522 -0.01 0.9919
## CVDclusterdich -4.25511 1.99562 -2.13 0.0331
## DMMclusterdich -2.56329 0.98501 -2.60 0.0093
## PhysBMI -0.61634 0.05231 -11.78 < 2e-16
## rxPsych -1.43766 1.08402 -1.33 0.1849
## rxHTN -0.57479 0.99341 -0.58 0.5629
## rxDiabetes -1.22164 1.60775 -0.76 0.4474
## rxHypercholesterolemia -0.18967 1.36340 -0.14 0.8894
## SmokingCurr 1.24009 0.96187 1.29 0.1975
## AlcoholCurr 3.79699 0.77695 4.89 0.0000011
## IllicitDrugCurr 2.03208 1.07315 1.89 0.0584
## MedianHouseholdIncome2C -0.48166 0.38700 -1.24 0.2135
## Gini100C:PovStat -0.10512 0.25812 -0.41 0.6839
## Gini100C:Race -0.48547 0.19302 -2.52 0.0120
## PovStat:Race 9.68764 2.26600 4.28 0.0000201
## PovStat:I(Gini100C^2) 0.01966 0.02767 0.71 0.4775
## Race:I(Gini100C^2) 0.04256 0.02180 1.95 0.0511
## Gini100C:PovStat:Race 0.76054 0.33238 2.29 0.0222
## PovStat:Race:I(Gini100C^2) -0.09252 0.03444 -2.69 0.0073
##
## Residual standard error: 15.3 on 1765 degrees of freedom
## Multiple R-squared: 0.217, Adjusted R-squared: 0.206
## F-statistic: 18.8 on 26 and 1765 DF, p-value: <2e-16
##
## ***************** END: LabResHDLimp *****************************
##
##
## ************************************************************
## ************************************************************
## BEGIN: LabResHDLimplog
## ************************************************************
## ************************************************************
##
## Call:
## lm(formula = LabResHDLimplog ~ Gini100C + PovStat + Race + BelowMedianIncome +
## I(Gini100C^2) + Age0 + Sex + HseHldEducationDich + CVDclusterdich +
## DMMclusterdich + PhysBMI + rxPsych + rxHTN + rxDiabetes +
## rxHypercholesterolemia + SmokingCurr + AlcoholCurr + IllicitDrugCurr +
## MedianHouseholdIncome2C + Gini100C:PovStat + Gini100C:Race +
## PovStat:Race + PovStat:I(Gini100C^2) + Race:I(Gini100C^2) +
## Gini100C:PovStat:Race + PovStat:Race:I(Gini100C^2), data = analysisData)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.6918 -0.0706 -0.0032 0.0717 0.5191
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.7951794 0.0226897 79.12 < 2e-16
## Gini100C 0.0016794 0.0010328 1.63 0.1041
## PovStat -0.0400397 0.0144728 -2.77 0.0057
## Race 0.0124707 0.0104530 1.19 0.2330
## BelowMedianIncome -0.0076115 0.0059080 -1.29 0.1978
## I(Gini100C^2) -0.0000794 0.0001110 -0.72 0.4743
## Age0 0.0015490 0.0003284 4.72 0.00000259
## Sex -0.0830298 0.0057128 -14.53 < 2e-16
## HseHldEducationDich -0.0000289 0.0063193 0.00 0.9964
## CVDclusterdich -0.0376160 0.0149203 -2.52 0.0118
## DMMclusterdich -0.0166059 0.0073645 -2.25 0.0243
## PhysBMI -0.0045486 0.0003911 -11.63 < 2e-16
## rxPsych -0.0116809 0.0081047 -1.44 0.1497
## rxHTN -0.0061926 0.0074273 -0.83 0.4045
## rxDiabetes -0.0132428 0.0120204 -1.10 0.2707
## rxHypercholesterolemia -0.0029486 0.0101935 -0.29 0.7724
## SmokingCurr 0.0101535 0.0071915 1.41 0.1582
## AlcoholCurr 0.0295060 0.0058089 5.08 0.00000042
## IllicitDrugCurr 0.0178810 0.0080234 2.23 0.0260
## MedianHouseholdIncome2C -0.0038502 0.0028934 -1.33 0.1835
## Gini100C:PovStat -0.0009170 0.0019298 -0.48 0.6347
## Gini100C:Race -0.0038526 0.0014431 -2.67 0.0077
## PovStat:Race 0.0744332 0.0169419 4.39 0.00001182
## PovStat:I(Gini100C^2) 0.0002182 0.0002069 1.05 0.2917
## Race:I(Gini100C^2) 0.0003221 0.0001630 1.98 0.0484
## Gini100C:PovStat:Race 0.0047442 0.0024851 1.91 0.0564
## PovStat:Race:I(Gini100C^2) -0.0006982 0.0002575 -2.71 0.0068
##
## Residual standard error: 0.114 on 1765 degrees of freedom
## Multiple R-squared: 0.233, Adjusted R-squared: 0.221
## F-statistic: 20.6 on 26 and 1765 DF, p-value: <2e-16
##
## ***************** END: LabResHDLimplog *****************************
##
##
## ************************************************************
## ************************************************************
## BEGIN: LabResCholimp
## ************************************************************
## ************************************************************
##
## Call:
## lm(formula = LabResCholimp ~ Gini100C + PovStat + Race + BelowMedianIncome +
## I(Gini100C^2) + Age0 + Sex + HseHldEducationDich + CVDclusterdich +
## DMMclusterdich + PhysBMI + rxPsych + rxHTN + rxDiabetes +
## rxHypercholesterolemia + SmokingCurr + AlcoholCurr + IllicitDrugCurr +
## MedianHouseholdIncome2C + Gini100C:PovStat + PovStat:I(Gini100C^2),
## data = analysisData)
##
## Residuals:
## Min 1Q Median 3Q Max
## -106.7 -26.5 -2.6 21.3 471.6
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 157.0961 8.1333 19.32 < 2e-16
## Gini100C -0.3564 0.2761 -1.29 0.1970
## PovStat 2.3562 2.7653 0.85 0.3943
## Race -5.8175 2.2590 -2.58 0.0101
## BelowMedianIncome -4.3847 2.1385 -2.05 0.0405
## I(Gini100C^2) 0.0308 0.0297 1.04 0.3002
## Age0 0.7425 0.1192 6.23 0.00000000058
## Sex -7.5071 2.0742 -3.62 0.0003
## HseHldEducationDich 0.6174 2.2894 0.27 0.7875
## CVDclusterdich -16.0188 5.4224 -2.95 0.0032
## DMMclusterdich -4.7920 2.6728 -1.79 0.0732
## PhysBMI 0.1334 0.1418 0.94 0.3469
## rxPsych -0.4090 2.9453 -0.14 0.8896
## rxHTN 3.7554 2.6979 1.39 0.1641
## rxDiabetes -2.2733 4.3599 -0.52 0.6021
## rxHypercholesterolemia -7.8464 3.7066 -2.12 0.0344
## SmokingCurr 3.2398 2.6145 1.24 0.2154
## AlcoholCurr 0.0465 2.1070 0.02 0.9824
## IllicitDrugCurr 2.2123 2.9160 0.76 0.4481
## MedianHouseholdIncome2C 0.6243 1.0366 0.60 0.5471
## Gini100C:PovStat 0.5716 0.4133 1.38 0.1668
## PovStat:I(Gini100C^2) -0.0889 0.0409 -2.17 0.0298
##
## Residual standard error: 41.6 on 1770 degrees of freedom
## Multiple R-squared: 0.0565, Adjusted R-squared: 0.0453
## F-statistic: 5.05 on 21 and 1770 DF, p-value: 7.01e-13
##
## ***************** END: LabResCholimp *****************************
##
##
## ************************************************************
## ************************************************************
## BEGIN: LabResCholimplog
## ************************************************************
## ************************************************************
## Warning: All variables have been thrown out of the model.
## No model could be specified.
##
## Call:
## lm(formula = LabResCholimplog ~ Gini100C + PovStat + Race + BelowMedianIncome +
## Age0 + Sex + HseHldEducationDich + CVDclusterdich + DMMclusterdich +
## PhysBMI + rxPsych + rxHTN + rxDiabetes + rxHypercholesterolemia +
## SmokingCurr + AlcoholCurr + IllicitDrugCurr + MedianHouseholdIncome2C,
## data = analysisData)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.3286 -0.0571 0.0048 0.0556 0.5770
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.202916 0.017884 123.18 < 2e-16
## Gini100C -0.000358 0.000362 -0.99 0.3221
## PovStat -0.003448 0.004896 -0.70 0.4813
## Race -0.014299 0.004948 -2.89 0.0039
## BelowMedianIncome -0.011769 0.004785 -2.46 0.0140
## Age0 0.001727 0.000267 6.47 0.00000000013
## Sex -0.021323 0.004638 -4.60 0.00000457550
## HseHldEducationDich 0.000433 0.005107 0.08 0.9325
## CVDclusterdich -0.039017 0.012143 -3.21 0.0013
## DMMclusterdich -0.011927 0.005981 -1.99 0.0463
## PhysBMI 0.000262 0.000317 0.83 0.4077
## rxPsych -0.003404 0.006571 -0.52 0.6045
## rxHTN 0.010051 0.006046 1.66 0.0966
## rxDiabetes -0.010418 0.009760 -1.07 0.2859
## rxHypercholesterolemia -0.016261 0.008306 -1.96 0.0504
## SmokingCurr 0.006162 0.005859 1.05 0.2931
## AlcoholCurr 0.000173 0.004723 0.04 0.9707
## IllicitDrugCurr 0.005209 0.006524 0.80 0.4247
## MedianHouseholdIncome2C 0.001776 0.002275 0.78 0.4353
##
## Residual standard error: 0.0933 on 1773 degrees of freedom
## Multiple R-squared: 0.0621, Adjusted R-squared: 0.0526
## F-statistic: 6.52 on 18 and 1773 DF, p-value: 5.22e-16
##
## ***************** END: LabResCholimplog *****************************
Whites above poverty
In general, for Whites above poverty, with greater inequality, ND ratings decrease. The slope is somewhat steeper for those below NMI as compared to those above NMI.
Whites below poverty
For Whites below poverty, ND initially increases then dramatically decreases. The inflection point differs based on NMI status. For those above NMI, the inflection point is around Gini=45. For those below NMI, the inflection point is at around Gini=43.
Blacks:
Blacks above poverty
For Blacks above poverty, ND initially decreases then increases with increasing inequality. The Gini inflection point differs based on NMI status, and is somewhat lower for those below NMI as compared to those above NMI.
Blacks below poverty
For Blacks below poverty and above NMI, ND more or less stays the same, with a very slight decrease.
For Blacks below poverty and below NMI, ND increases with increasing inequality.
Insanity for 3 of the 4 psychological outcomes!! Let me know if there might be another way to frame these results that is more understandable.
Whites:
Whites above poverty
For Whites above poverty, with greater inequality, depressive symptoms decrease. For Whites above poverty, those above neighborhood median income (NMI) have fewer depressive symptoms than those below NMI.
Whites below poverty
For Whites below poverty and above NMI, depressive symptoms increase until about Gini=43, then dramatically decrease. For Whites below poverty and below NMI, depressive symptoms increase with greater inequality.
Blacks:
Blacks above poverty
For Blacks above poverty and above NMI, depressive symptoms initially increase until Gini= 43, then decrease. The opposite is depicted for Blacks above poverty and below NMI.
Blacks below poverty
For Blacks below poverty and above NMI, depressive symptoms appear to modestly increase with greater inequality.
For Blacks below poverty and below NMI, depressive symptoms initially increase until Gini= 43, then decrease.
Whites:
Whites above poverty
For Whites above poverty, with greater inequality, anxiety symptoms decrease. This decrease is more dramatic for those below NMI as compared to those above NMI. (Similar to CESD results above for Whites above poverty)
Whites below poverty
For Whites below poverty and above NMI, anxiety symptoms increase until about Gini=43, then dramatically decrease. (same as CESD result for this group) For Whites below poverty and below NMI, anxiety symptoms decrease with greater inequality. (opposite of CESD result for this group)
Blacks:
Blacks above poverty
For Blacks above poverty and above NMI, anxiety symptoms initially increase until Gini= 43, then decrease. The opposite is depicted for Blacks above poverty and below NMI. (Same as CESD results above for Blacks above poverty)
Blacks below poverty
For Blacks below poverty and above NMI, anxiety symptoms appear to modestly increase with greater inequality. (same as CESD result for this group)
For Blacks below poverty and below NMI, anxiety symptoms seem to stay around the same with increasing inequality. (curve not as steep as that for CESD for this group)
Whites:
Whites above poverty
For Whites above poverty and above NMI, with greater inequality, PSS decreases slightly. For Whites above poverty and below NMI, PSS increases until about Gini=43, then dramatically decreases. (Different than CESD and anxiety results for Whites above poverty)
Whites below poverty
For Whites below poverty and above NMI, PSS symptoms increase until about Gini=43, then dramatically decrease. (same as CESD and anxiety results for this group) For Whites below poverty and below NMI, PSS symptoms decrease with greater inequality. (same as anxiety, opposite of CESD result for this group)
Blacks:
Blacks above poverty
For Blacks above poverty and above NMI, PSS initially increases until Gini= 43, then decreases. For Blacks above poverty and below NMI, PSS increases with increasing inequality. (Similar to CESD and anxiety results for Blacks above poverty)
Blacks below poverty
For Blacks below poverty and above NMI, PSS decreases with increasing inequality until Gini=48, then levels off. (opposite of anxiety and CESD result)
For Blacks below poverty and below NMI, PSS initially increases until Gini= 43, then decreases. (similar to CESD for this group)
(One through four scale, with higher numbers indicating more frequent discrimination)
Whites:
For Whites above NMI, discrimination due to race ratings increase until about Gini=45, then decrease. For Whites below NMI, discrimination ratings increase with greater inequality. (similar to CESD results for Whites below poverty)
Blacks:
For Blacks above NMI, discrimination ratings initially decrease till Gini=48, then increase. For Blacks below NMI, discrimination rates are more or less the same with increasing inequality.
For those above NMI, those below poverty have lesser SBP than those above poverty. (unexpected!) For those below NMI, there is no difference in SBP for those above and below poverty.
For those above NMI, those below poverty have greater glucose levels than those above poverty. For those below NMI, there is no difference in glucose for those above and below poverty.
Same as Glucose.
For all groups, BMI initially increases till about Gini=45, and then decreases. Overall, Blacks below poverty have the lowest BMI, and Whites below Poverty have the higest BMI. This seems to correspond with Allyssa's findings on food insecurity in her diss.
For Whites, increasing inequality more or less corresponds with better HDL, with Whites below poverty having lower HDL than Whites above poverty. The story is different for Blacks. For Blacks above poverty, HDL initially decreases till about Gini=48ish, then increases. The reverse is depicted for Blacks below poverty.
See HDL.
For those above poverty, total cholesterol initially decreases till about Gini=48ish, then increases. The reverse is depicted for those below poverty. This mirrors the HDL results for Blacks above.
CholesterolLog did not backwards eliminate to the same terms as Cholesterol above. Only BelowMedianIncome and Race were significant terms of interest for CholesterolLog. Thus, I'm looking at a graph below with the same terms as Cholesterol in the CholesterolLog model.
The difference between Above and Below Poverty is pretty small in this CholesterolLog model, which is probably why PovStat x Gini2 was not significant. What to do?
