Model Building by Deletion
use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.EDUC_cat i.race_eth i.SMK_cat i.AL_cat bmxbmi hei2015 indfmpir ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.EDUC_cat _IEDUC_cat_1-5 (naturally coded; _IEDUC_cat_1 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.SMK_cat _ISMK_cat_0-4 (naturally coded; _ISMK_cat_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 65,338
Number of PSUs = 214 Population size = 277,846,206
Subpop. no. obs = 16,168
Subpop. size = 112,825,614
Design df = 109
F( 22, 88) = 87.87
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .8815766 .0489931 -2.27 0.025 .7896305 .9842291
_IMJ_2 | 1.032565 .0917559 0.36 0.719 .8658224 1.23142
_IMJ_3 | 1.096764 .1848401 0.55 0.585 .7853223 1.531718
_IMJ_4 | 1.131927 .1376864 1.02 0.311 .8894402 1.440522
gndr | 2.681409 .126656 20.88 0.000 2.441773 2.944563
_IEDUC_cat_2 | 1.021784 .0997264 0.22 0.826 .8420715 1.23985
_IEDUC_cat_3 | 1.011383 .1033243 0.11 0.912 .8259984 1.238374
_IEDUC_cat_4 | 1.059466 .1145256 0.53 0.594 .8551477 1.312601
_IEDUC_cat_5 | .8499164 .1017293 -1.36 0.177 .6704236 1.077465
_Irace_eth_2 | 1.4401 .0814052 6.45 0.000 1.287468 1.610828
_Irace_eth_3 | .8429897 .0527579 -2.73 0.007 .7446504 .9543158
_Irace_eth_4 | .9932813 .0663983 -0.10 0.920 .8700272 1.133997
_ISMK_cat_1 | 1.07454 .076715 1.01 0.316 .9327606 1.23787
_ISMK_cat_2 | 1.04475 .0855945 0.53 0.594 .8881618 1.228946
_ISMK_cat_3 | 1.089722 .091812 1.02 0.310 .9221356 1.287766
_ISMK_cat_4 | 1.17111 .1845349 1.00 0.318 .8569703 1.600404
_IAL_cat_1 | 1.146538 .068109 2.30 0.023 1.019192 1.289796
_IAL_cat_2 | 1.3602 .1040603 4.02 0.000 1.168831 1.582902
bmxbmi | 1.073619 .0042742 17.84 0.000 1.065181 1.082124
hei2015 | .9975714 .0016953 -1.43 0.155 .9942171 1.000937
indfmpir | 1.009014 .0163384 0.55 0.581 .9771455 1.041921
ridageyr | 1.049165 .0026368 19.10 0.000 1.043952 1.054404
_cons | .0108648 .002171 -22.63 0.000 .0073119 .0161441
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.Store full model ORs in a vector for future:
OR0 <- c(.8815766, 1.032565, 1.096764, 1.131927)use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ EDUC_cat i.race_eth i.SMK_cat i.AL_cat bmxbmi hei2015 indfmpir ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.SMK_cat _ISMK_cat_0-4 (naturally coded; _ISMK_cat_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 65,338
Number of PSUs = 214 Population size = 277,846,206
Subpop. no. obs = 16,168
Subpop. size = 112,825,614
Design df = 109
F( 18, 92) = 55.97
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .9582243 .05253 -0.78 0.438 .8595682 1.068204
_IMJ_2 | 1.224804 .1026346 2.42 0.017 1.03738 1.44609
_IMJ_3 | 1.374418 .2361775 1.85 0.067 .9777052 1.932102
_IMJ_4 | 1.410263 .1665602 2.91 0.004 1.115937 1.782217
EDUC_cat | .9332385 .0232888 -2.77 0.007 .8882037 .9805566
_Irace_eth_2 | 1.392598 .0767511 6.01 0.000 1.248493 1.553335
_Irace_eth_3 | .9038265 .0531653 -1.72 0.088 .804365 1.015587
_Irace_eth_4 | 1.032784 .0670995 0.50 0.621 .9080016 1.174715
_ISMK_cat_1 | 1.152438 .0786405 2.08 0.040 1.006655 1.319332
_ISMK_cat_2 | 1.058554 .0827041 0.73 0.468 .9066979 1.235843
_ISMK_cat_3 | 1.094606 .0927182 1.07 0.288 .9254388 1.294696
_ISMK_cat_4 | 1.294694 .1978487 1.69 0.094 .9563801 1.752685
_IAL_cat_1 | .9613666 .0543667 -0.70 0.487 .8594328 1.07539
_IAL_cat_2 | 1.393904 .1055909 4.38 0.000 1.199579 1.619708
bmxbmi | 1.069637 .0042041 17.13 0.000 1.061337 1.078002
hei2015 | .9934137 .0016878 -3.89 0.000 .990074 .9967646
indfmpir | 1.034852 .0158163 2.24 0.027 1.003975 1.066679
ridageyr | 1.046076 .0025847 18.23 0.000 1.040965 1.051211
_cons | .0311916 .0059282 -18.24 0.000 .0214014 .0454603
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_G <- c(.9582243,1.224804, 1.374418, 1.410263)
D_OR <- (OR0-OR_G)/OR0
100*D_OR[1] -8.694389 -18.617617 -25.315747 -24.589572100*mean(abs(D_OR))[1] 19.30433use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.race_eth i.SMK_cat i.AL_cat bmxbmi hei2015 indfmpir ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.SMK_cat _ISMK_cat_0-4 (naturally coded; _ISMK_cat_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 65,341
Number of PSUs = 214 Population size = 277,875,985
Subpop. no. obs = 16,171
Subpop. size = 112,855,393
Design df = 109
F( 18, 92) = 95.65
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .8771625 .0482202 -2.38 0.019 .786614 .9781342
_IMJ_2 | 1.036842 .0916481 0.41 0.683 .87022 1.235368
_IMJ_3 | 1.095188 .1854012 0.54 0.592 .7830211 1.531806
_IMJ_4 | 1.138981 .139828 1.06 0.291 .8929863 1.452741
gndr | 2.678317 .1248015 21.14 0.000 2.442043 2.937451
_Irace_eth_2 | 1.458263 .0821436 6.70 0.000 1.304216 1.630505
_Irace_eth_3 | .8577796 .0493628 -2.67 0.009 .7653173 .9614128
_Irace_eth_4 | .9905667 .0656405 -0.14 0.887 .8686506 1.129594
_ISMK_cat_1 | 1.093364 .0781404 1.25 0.214 .9489606 1.259741
_ISMK_cat_2 | 1.063089 .087611 0.74 0.459 .9028867 1.251717
_ISMK_cat_3 | 1.123767 .0954879 1.37 0.172 .9495912 1.329891
_ISMK_cat_4 | 1.208418 .1899114 1.20 0.231 .8849994 1.650028
_IAL_cat_1 | 1.154161 .0681712 2.43 0.017 1.026656 1.2975
_IAL_cat_2 | 1.384095 .1048864 4.29 0.000 1.191071 1.608399
bmxbmi | 1.074622 .0042409 18.24 0.000 1.06625 1.083061
hei2015 | .9964676 .001727 -2.04 0.044 .9930507 .9998963
indfmpir | .9929596 .0146752 -0.48 0.634 .9642956 1.022476
ridageyr | 1.049301 .0026479 19.07 0.000 1.044066 1.054562
_cons | .0112336 .0019519 -25.83 0.000 .0079609 .0158518
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_E <- c(.8771625,1.036842, 1.095188, 1.138981)
D_OR <- (OR0-OR_E)/OR0
100*D_OR[1] 0.5007052 -0.4142112 0.1436955 -0.6231851100*mean(abs(D_OR))[1] 0.4204492use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.EDUC_cat i.SMK_cat i.AL_cat bmxbmi hei2015 indfmpir ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.EDUC_cat _IEDUC_cat_1-5 (naturally coded; _IEDUC_cat_1 omitted)
i.SMK_cat _ISMK_cat_0-4 (naturally coded; _ISMK_cat_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 65,338
Number of PSUs = 214 Population size = 277,846,206
Subpop. no. obs = 16,168
Subpop. size = 112,825,614
Design df = 109
F( 19, 91) = 83.58
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .8979156 .0498039 -1.94 0.055 .8044382 1.002255
_IMJ_2 | 1.083719 .0956766 0.91 0.364 .9097553 1.290949
_IMJ_3 | 1.166191 .1946209 0.92 0.359 .8377633 1.623372
_IMJ_4 | 1.182622 .1436576 1.38 0.170 .9295794 1.504546
gndr | 2.646719 .1246591 20.67 0.000 2.41083 2.905689
_IEDUC_cat_2 | 1.132162 .1044481 1.35 0.181 .9429721 1.359309
_IEDUC_cat_3 | 1.127397 .1056206 1.28 0.203 .9363467 1.35743
_IEDUC_cat_4 | 1.186111 .1187247 1.71 0.091 .9726732 1.446383
_IEDUC_cat_5 | .9462565 .1038809 -0.50 0.616 .7612269 1.176261
_ISMK_cat_1 | 1.046444 .0737098 0.64 0.521 .9100929 1.203224
_ISMK_cat_2 | 1.052718 .0858522 0.63 0.530 .8956014 1.237398
_ISMK_cat_3 | 1.076271 .0907295 0.87 0.385 .9106677 1.271989
_ISMK_cat_4 | 1.142517 .1793433 0.85 0.398 .8370426 1.559472
_IAL_cat_1 | 1.126049 .0663365 2.02 0.046 1.001957 1.265509
_IAL_cat_2 | 1.299133 .0966399 3.52 0.001 1.121046 1.50551
bmxbmi | 1.074555 .0042189 18.31 0.000 1.066226 1.082949
hei2015 | .9972133 .0016598 -1.68 0.096 .993929 1.000508
indfmpir | 1.002173 .0158039 0.14 0.891 .9713344 1.03399
ridageyr | 1.049381 .0026244 19.27 0.000 1.044193 1.054596
_cons | .0101883 .0019257 -24.27 0.000 .0070051 .014818
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_R <- c(.8979156,1.083719 , 1.166191 , 1.182622 )
D_OR <- (OR0-OR_R)/OR0
100*D_OR[1] -1.853384 -4.954071 -6.330168 -4.478646100*mean(abs(D_OR))[1] 4.404067use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.EDUC_cat i.race_eth i.AL_cat bmxbmi hei2015 indfmpir ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.EDUC_cat _IEDUC_cat_1-5 (naturally coded; _IEDUC_cat_1 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 65,377
Number of PSUs = 214 Population size = 278,014,313
Subpop. no. obs = 16,207
Subpop. size = 112,993,721
Design df = 109
F( 18, 92) = 88.75
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .9031076 .0466635 -1.97 0.051 .8152002 1.000495
_IMJ_2 | 1.063007 .0847213 0.77 0.445 .9076828 1.244911
_IMJ_3 | 1.132914 .1901917 0.74 0.459 .8122588 1.580154
_IMJ_4 | 1.183061 .1381983 1.44 0.153 .9385519 1.491268
gndr | 2.68605 .1264794 20.98 0.000 2.446714 2.948798
_IEDUC_cat_2 | 1.013884 .0993736 0.14 0.888 .8348777 1.23127
_IEDUC_cat_3 | .998288 .1010875 -0.02 0.987 .8167606 1.22016
_IEDUC_cat_4 | 1.041148 .1120519 0.37 0.709 .8411525 1.288695
_IEDUC_cat_5 | .8300564 .0980425 -1.58 0.118 .6568085 1.049002
_Irace_eth_2 | 1.417796 .0790596 6.26 0.000 1.269451 1.583476
_Irace_eth_3 | .8302139 .0525504 -2.94 0.004 .7323292 .9411822
_Irace_eth_4 | .9900997 .0660707 -0.15 0.882 .8674399 1.130104
_IAL_cat_1 | 1.152408 .0676279 2.42 0.017 1.025873 1.29455
_IAL_cat_2 | 1.377707 .1025994 4.30 0.000 1.188654 1.59683
bmxbmi | 1.073522 .004223 18.03 0.000 1.065184 1.081924
hei2015 | .9973273 .0016704 -1.60 0.113 .9940221 1.000643
indfmpir | 1.006869 .0160796 0.43 0.669 .9754988 1.039248
ridageyr | 1.049785 .0025029 20.38 0.000 1.044836 1.054758
_cons | .0111743 .0022189 -22.63 0.000 .0075387 .0165632
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_S <- c(.9031076,1.063007 , 1.132914 , 1.183061 )
D_OR <- (OR0-OR_S)/OR0
100*D_OR[1] -2.442329 -2.948192 -3.296060 -4.517429100*mean(abs(D_OR))[1] 3.301003use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.EDUC_cat i.race_eth i.SMK_cat bmxbmi hei2015 indfmpir ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.EDUC_cat _IEDUC_cat_1-5 (naturally coded; _IEDUC_cat_1 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.SMK_cat _ISMK_cat_0-4 (naturally coded; _ISMK_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 67,099
Number of PSUs = 214 Population size = 289,046,209
Subpop. no. obs = 17,929
Subpop. size = 124,025,616
Design df = 109
F( 20, 90) = 85.95
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .9256275 .0518896 -1.38 0.171 .8282915 1.034402
_IMJ_2 | 1.09918 .0930872 1.12 0.267 .9293372 1.300064
_IMJ_3 | 1.153825 .1910305 0.86 0.389 .8310565 1.601952
_IMJ_4 | 1.200428 .1406226 1.56 0.122 .9517077 1.514148
gndr | 2.51484 .107227 21.63 0.000 2.311052 2.736599
_IEDUC_cat_2 | 1.072559 .0974893 0.77 0.443 .8957428 1.284278
_IEDUC_cat_3 | 1.035709 .1005354 0.36 0.718 .854446 1.255425
_IEDUC_cat_4 | 1.068921 .1122761 0.63 0.527 .8680295 1.316306
_IEDUC_cat_5 | .8549497 .0951837 -1.41 0.162 .6856622 1.066034
_Irace_eth_2 | 1.406647 .0752011 6.38 0.000 1.265226 1.563876
_Irace_eth_3 | .8719623 .0544189 -2.20 0.030 .7705096 .9867733
_Irace_eth_4 | 1.029244 .0635018 0.47 0.641 .9107764 1.163121
_ISMK_cat_1 | 1.084751 .0713369 1.24 0.219 .9521905 1.235767
_ISMK_cat_2 | 1.095428 .0814272 1.23 0.223 .9453677 1.269309
_ISMK_cat_3 | 1.134573 .0912615 1.57 0.119 .9673773 1.330666
_ISMK_cat_4 | 1.315374 .189961 1.90 0.060 .987966 1.751283
bmxbmi | 1.074691 .0040549 19.09 0.000 1.066685 1.082758
hei2015 | .9973574 .0016045 -1.64 0.103 .9941824 1.000543
indfmpir | 1.014134 .0158421 0.90 0.371 .9832167 1.046024
ridageyr | 1.046173 .0025035 18.86 0.000 1.041223 1.051147
_cons | .0124959 .0023468 -23.33 0.000 .0086122 .0181309
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_A <- c(.9256275,1.09918 , 1.153825 , 1.200428 )
D_OR <- (OR0-OR_A)/OR0
100*D_OR[1] -4.996832 -6.451410 -5.202669 -6.051715100*mean(abs(D_OR))[1] 5.675656use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.EDUC_cat i.race_eth i.SMK_cat i.AL_cat hei2015 indfmpir ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.EDUC_cat _IEDUC_cat_1-5 (naturally coded; _IEDUC_cat_1 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.SMK_cat _ISMK_cat_0-4 (naturally coded; _ISMK_cat_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 65,407
Number of PSUs = 214 Population size = 278,229,824
Subpop. no. obs = 16,237
Subpop. size = 113,209,232
Design df = 109
F( 21, 89) = 68.99
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .8701768 .0446819 -2.71 0.008 .7859759 .9633981
_IMJ_2 | .9422543 .0832826 -0.67 0.502 .7908403 1.122658
_IMJ_3 | .9894801 .1650398 -0.06 0.950 .7109475 1.377135
_IMJ_4 | 1.010763 .1173273 0.09 0.927 .8030344 1.272226
gndr | 2.50383 .1126104 20.41 0.000 2.290299 2.73727
_IEDUC_cat_2 | 1.060303 .1065529 0.58 0.561 .8688208 1.293988
_IEDUC_cat_3 | 1.079032 .1094426 0.75 0.455 .8825322 1.319283
_IEDUC_cat_4 | 1.147754 .1228018 1.29 0.200 .9284395 1.418874
_IEDUC_cat_5 | .833549 .0987328 -1.54 0.127 .6591368 1.054112
_Irace_eth_2 | 1.594676 .0880809 8.45 0.000 1.429319 1.779164
_Irace_eth_3 | .9125952 .0566575 -1.47 0.144 .8069357 1.03209
_Irace_eth_4 | .9539848 .0603426 -0.74 0.458 .8415807 1.081402
_ISMK_cat_1 | 1.105844 .0758094 1.47 0.145 .9653525 1.266781
_ISMK_cat_2 | .9644785 .075622 -0.46 0.646 .8256634 1.126632
_ISMK_cat_3 | .9265422 .0803802 -0.88 0.381 .7801748 1.100369
_ISMK_cat_4 | 1.000964 .1574231 0.01 0.995 .7329018 1.367071
_IAL_cat_1 | 1.143082 .0656398 2.33 0.022 1.020116 1.28087
_IAL_cat_2 | 1.425331 .1082504 4.67 0.000 1.226149 1.656869
hei2015 | .992761 .0016733 -4.31 0.000 .9894502 .996083
indfmpir | .9939876 .0162023 -0.37 0.712 .9623884 1.026624
ridageyr | 1.053851 .0025764 21.45 0.000 1.048757 1.058969
_cons | .0983399 .0150807 -15.12 0.000 .0725655 .133269
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_B <- c(.8701768,.9422543 , .9894801, 1.010763)
D_OR <- (OR0-OR_B)/OR0
100*D_OR[1] 1.293115 8.746248 9.781858 10.704224100*mean(abs(D_OR))[1] 7.631361use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.EDUC_cat i.race_eth i.SMK_cat i.AL_cat bmxbmi indfmpir ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.EDUC_cat _IEDUC_cat_1-5 (naturally coded; _IEDUC_cat_1 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.SMK_cat _ISMK_cat_0-4 (naturally coded; _ISMK_cat_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 66,572
Number of PSUs = 214 Population size = 285,338,724
Subpop. no. obs = 17,402
Subpop. size = 120,318,132
Design df = 109
F( 21, 89) = 94.70
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .8818887 .0489866 -2.26 0.026 .7899524 .9845248
_IMJ_2 | .991081 .0836449 -0.11 0.916 .8384231 1.171534
_IMJ_3 | 1.092312 .1664816 0.58 0.564 .8075268 1.477531
_IMJ_4 | 1.088388 .1145545 0.80 0.423 .8834615 1.340849
gndr | 2.755303 .1257563 22.21 0.000 2.516999 3.016169
_IEDUC_cat_2 | 1.079326 .1068345 0.77 0.442 .8870592 1.313266
_IEDUC_cat_3 | 1.030982 .1069276 0.29 0.769 .8394176 1.266263
_IEDUC_cat_4 | 1.073103 .1148473 0.66 0.511 .8680004 1.326669
_IEDUC_cat_5 | .852359 .1022948 -1.33 0.186 .6719234 1.081248
_Irace_eth_2 | 1.417995 .0802861 6.17 0.000 1.267474 1.586391
_Irace_eth_3 | .8388233 .0503605 -2.93 0.004 .7447201 .9448175
_Irace_eth_4 | .9683539 .0613356 -0.51 0.613 .8541098 1.097879
_ISMK_cat_1 | 1.078263 .075399 1.08 0.284 .9387179 1.238553
_ISMK_cat_2 | 1.054566 .0825712 0.68 0.499 .9029787 1.231601
_ISMK_cat_3 | 1.065488 .0830843 0.81 0.418 .9129117 1.243565
_ISMK_cat_4 | 1.178186 .186048 1.04 0.301 .8615711 1.611152
_IAL_cat_1 | 1.173619 .0667838 2.81 0.006 1.048447 1.313735
_IAL_cat_2 | 1.424292 .1067293 4.72 0.000 1.227716 1.652341
bmxbmi | 1.074826 .0039839 19.47 0.000 1.066959 1.082751
indfmpir | 1.011832 .0153658 0.77 0.440 .9818313 1.042749
ridageyr | 1.047906 .0024491 20.02 0.000 1.043063 1.052771
_cons | .0093475 .0017815 -24.52 0.000 .0064069 .0136378
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_H <- c(.8818887,.991081 , 1.092312 , 1.088388)
D_OR <- (OR0-OR_H)/OR0
100*D_OR[1] -0.03540248 4.01756790 0.40592142 3.84644946100*mean(abs(D_OR))[1] 2.076335use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.EDUC_cat i.race_eth i.SMK_cat i.AL_cat bmxbmi hei2015 ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.EDUC_cat _IEDUC_cat_1-5 (naturally coded; _IEDUC_cat_1 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.SMK_cat _ISMK_cat_0-4 (naturally coded; _ISMK_cat_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 66,566
Number of PSUs = 214 Population size = 284,467,242
Subpop. no. obs = 17,396
Subpop. size = 119,446,650
Design df = 109
F( 21, 89) = 85.25
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .8842544 .0462907 -2.35 0.021 .7971069 .9809298
_IMJ_2 | 1.072015 .0921257 0.81 0.420 .904128 1.271077
_IMJ_3 | 1.123433 .1854692 0.70 0.482 .809922 1.558299
_IMJ_4 | 1.065008 .1339647 0.50 0.618 .8300045 1.36655
gndr | 2.644178 .1149913 22.36 0.000 2.425815 2.882197
_IEDUC_cat_2 | 1.00087 .0914281 0.01 0.992 .83512 1.199518
_IEDUC_cat_3 | 1.015437 .0990087 0.16 0.875 .8370013 1.231913
_IEDUC_cat_4 | 1.044839 .1077816 0.43 0.672 .8516413 1.281863
_IEDUC_cat_5 | .8228114 .0922686 -1.74 0.085 .6588347 1.0276
_Irace_eth_2 | 1.435809 .079806 6.51 0.000 1.286037 1.603023
_Irace_eth_3 | .8262702 .0518312 -3.04 0.003 .7296718 .9356568
_Irace_eth_4 | .994878 .0635794 -0.08 0.936 .8765197 1.129219
_ISMK_cat_1 | 1.082503 .0751607 1.14 0.256 .9433321 1.242205
_ISMK_cat_2 | 1.031175 .0769629 0.41 0.682 .8893829 1.195573
_ISMK_cat_3 | 1.07238 .089457 0.84 0.404 .9089608 1.26518
_ISMK_cat_4 | 1.152865 .1856337 0.88 0.379 .8378759 1.58627
_IAL_cat_1 | 1.149405 .0671543 2.38 0.019 1.023725 1.290515
_IAL_cat_2 | 1.332649 .1002728 3.82 0.000 1.14802 1.54697
bmxbmi | 1.072637 .0042944 17.51 0.000 1.06416 1.081183
hei2015 | .9973415 .0016272 -1.63 0.106 .9941215 1.000572
ridageyr | 1.049524 .0025486 19.91 0.000 1.044485 1.054588
_cons | .0117072 .0022517 -23.12 0.000 .0079965 .0171398
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_I <- c(.8842544,1.072015, 1.123433 , 1.065008)
D_OR <- (OR0-OR_I)/OR0
100*D_OR[1] -0.3037513 -3.8205827 -2.4316079 5.9119537100*mean(abs(D_OR))[1] 3.116974use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.EDUC_cat i.race_eth i.SMK_cat i.AL_cat bmxbmi hei2015 indfmpir, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.EDUC_cat _IEDUC_cat_1-5 (naturally coded; _IEDUC_cat_1 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.SMK_cat _ISMK_cat_0-4 (naturally coded; _ISMK_cat_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 65,338
Number of PSUs = 214 Population size = 277,846,206
Subpop. no. obs = 16,168
Subpop. size = 112,825,614
Design df = 109
F( 21, 89) = 63.18
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .8669408 .0454519 -2.72 0.008 .781379 .9618718
_IMJ_2 | .8614717 .0723481 -1.78 0.079 .7293785 1.017488
_IMJ_3 | .8768699 .1437832 -0.80 0.425 .6335691 1.213602
_IMJ_4 | .9240537 .1095409 -0.67 0.507 .7305664 1.168785
gndr | 2.515523 .1117382 20.77 0.000 2.30353 2.747026
_IEDUC_cat_2 | .8907427 .0840783 -1.23 0.223 .7387616 1.07399
_IEDUC_cat_3 | .8719048 .0899787 -1.33 0.187 .7106254 1.069787
_IEDUC_cat_4 | .8306155 .0891551 -1.73 0.087 .6714437 1.02752
_IEDUC_cat_5 | .6646448 .0794157 -3.42 0.001 .5244947 .8422443
_Irace_eth_2 | 1.40506 .0794537 6.01 0.000 1.256089 1.571698
_Irace_eth_3 | .763815 .0461767 -4.46 0.000 .6775647 .8610444
_Irace_eth_4 | .9125038 .0609525 -1.37 0.173 .7993531 1.041671
_ISMK_cat_1 | 1.289172 .0840896 3.89 0.000 1.132832 1.467087
_ISMK_cat_2 | 1.130211 .0922279 1.50 0.137 .9614346 1.328616
_ISMK_cat_3 | 1.403253 .1131565 4.20 0.000 1.195984 1.646441
_ISMK_cat_4 | 1.740422 .2694205 3.58 0.001 1.280583 2.365382
_IAL_cat_1 | 1.01746 .0586169 0.30 0.764 .9076704 1.140529
_IAL_cat_2 | 1.063923 .07671 0.86 0.392 .9222501 1.22736
bmxbmi | 1.082661 .0041962 20.49 0.000 1.074376 1.09101
hei2015 | 1.003978 .0016366 2.44 0.016 1.00074 1.007227
indfmpir | 1.087211 .0180855 5.03 0.000 1.051951 1.123653
_cons | .0435125 .0076682 -17.79 0.000 .0306847 .0617029
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_A <- c(.8669408,.8614717, .8768699 , .9240537)
D_OR <- (OR0-OR_A)/OR0
100*D_OR[1] 1.660185 16.569737 20.049354 18.364550100*mean(abs(D_OR))[1] 14.16096Of the variables above, education has the least average change in OR; it will be excluded from the next cycle.
OR1 <- OR_Euse "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ i.race_eth i.SMK_cat i.AL_cat bmxbmi hei2015 indfmpir ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.SMK_cat _ISMK_cat_0-4 (naturally coded; _ISMK_cat_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 65,341
Number of PSUs = 214 Population size = 277,875,985
Subpop. no. obs = 16,171
Subpop. size = 112,855,393
Design df = 109
F( 17, 93) = 58.32
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .9449547 .0515865 -1.04 0.302 .848049 1.052934
_IMJ_2 | 1.213666 .101621 2.31 0.023 1.028082 1.432752
_IMJ_3 | 1.360849 .2351932 1.78 0.077 .9661544 1.916784
_IMJ_4 | 1.398623 .1649934 2.84 0.005 1.107027 1.767025
_Irace_eth_2 | 1.406654 .0773818 6.20 0.000 1.261351 1.568695
_Irace_eth_3 | .9559936 .0528169 -0.81 0.417 .8568399 1.066621
_Irace_eth_4 | 1.038743 .0669479 0.59 0.557 .9141796 1.180279
_ISMK_cat_1 | 1.170211 .0803576 2.29 0.024 1.021307 1.340824
_ISMK_cat_2 | 1.080835 .0843341 1.00 0.321 .9259704 1.261599
_ISMK_cat_3 | 1.134117 .0962235 1.48 0.141 .9585773 1.341801
_ISMK_cat_4 | 1.354647 .2063949 1.99 0.049 1.001568 1.832195
_IAL_cat_1 | .9638547 .054503 -0.65 0.516 .8616649 1.078164
_IAL_cat_2 | 1.416889 .106452 4.64 0.000 1.220862 1.644391
bmxbmi | 1.069805 .0042012 17.18 0.000 1.061511 1.078164
hei2015 | .9926454 .0016929 -4.33 0.000 .9892958 .9960064
indfmpir | 1.018571 .0142838 1.31 0.192 .9906502 1.047278
ridageyr | 1.046604 .0025869 18.43 0.000 1.04149 1.051744
_cons | .02528 .0045095 -20.62 0.000 .0177515 .0360014
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_G <- c(.9449547,1.213666, 1.360849, 1.398623)
D_OR <- (OR1-OR_G)/OR1
100*D_OR[1] -7.728579 -17.054093 -24.257114 -22.795990100*mean(abs(D_OR))[1] 17.95894use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.SMK_cat i.AL_cat bmxbmi hei2015 indfmpir ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.SMK_cat _ISMK_cat_0-4 (naturally coded; _ISMK_cat_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 65,341
Number of PSUs = 214 Population size = 277,875,985
Subpop. no. obs = 16,171
Subpop. size = 112,855,393
Design df = 109
F( 15, 95) = 96.75
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .8977321 .0490527 -1.97 0.051 .8055905 1.000413
_IMJ_2 | 1.095606 .0960304 1.04 0.300 .920892 1.303468
_IMJ_3 | 1.172163 .1964037 0.95 0.345 .8409344 1.633855
_IMJ_4 | 1.197926 .1468047 1.47 0.143 .939604 1.527267
gndr | 2.638453 .1225058 20.90 0.000 2.406488 2.892779
_ISMK_cat_1 | 1.062349 .0749744 0.86 0.393 .9236771 1.221841
_ISMK_cat_2 | 1.070008 .0878706 0.82 0.412 .9092858 1.259139
_ISMK_cat_3 | 1.107035 .0943599 1.19 0.235 .934961 1.310779
_ISMK_cat_4 | 1.17286 .1838268 1.02 0.311 .8596787 1.600132
_IAL_cat_1 | 1.133488 .0662764 2.14 0.034 1.009456 1.27276
_IAL_cat_2 | 1.318603 .0971664 3.75 0.000 1.139425 1.525957
bmxbmi | 1.075716 .0041802 18.78 0.000 1.067463 1.084033
hei2015 | .9960574 .0016976 -2.32 0.022 .9926985 .9994276
indfmpir | .9877547 .0139641 -0.87 0.385 .9604624 1.015823
ridageyr | 1.049395 .0026392 19.17 0.000 1.044177 1.054639
_cons | .0117069 .0019849 -26.23 0.000 .0083656 .0163827
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_R <- c(.8977321,1.095606 , 1.172163 , 1.197926)
D_OR <- (OR1-OR_R)/OR1
100*D_OR[1] -2.345016 -5.667594 -7.028474 -5.175240100*mean(abs(D_OR))[1] 5.054081use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.race_eth i.AL_cat bmxbmi hei2015 indfmpir ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 65,380
Number of PSUs = 214 Population size = 278,044,093
Subpop. no. obs = 16,210
Subpop. size = 113,023,501
Design df = 109
F( 14, 96) = 109.11
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .9037291 .0461187 -1.98 0.050 .8167939 .9999173
_IMJ_2 | 1.077233 .085144 0.94 0.349 .9210342 1.259922
_IMJ_3 | 1.143289 .1926983 0.79 0.429 .8186109 1.59674
_IMJ_4 | 1.204507 .1426968 1.57 0.119 .9524368 1.523289
gndr | 2.685962 .1246258 21.29 0.000 2.449975 2.94468
_Irace_eth_2 | 1.431848 .079548 6.46 0.000 1.282557 1.598517
_Irace_eth_3 | .8458046 .0494443 -2.86 0.005 .7532716 .9497045
_Irace_eth_4 | .9863017 .0650855 -0.21 0.835 .865384 1.124115
_IAL_cat_1 | 1.162759 .0676393 2.59 0.011 1.03614 1.304852
_IAL_cat_2 | 1.411063 .1031912 4.71 0.000 1.220672 1.631149
bmxbmi | 1.074445 .0041845 18.44 0.000 1.066184 1.082771
hei2015 | .9960669 .0017033 -2.30 0.023 .9926967 .9994485
indfmpir | .9882983 .0141851 -0.82 0.414 .9605801 1.016816
ridageyr | 1.050156 .0025138 20.44 0.000 1.045185 1.05515
_cons | .0114965 .0019968 -25.71 0.000 .0081481 .0162208
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_S <- c(.9037291,1.077233 , 1.143289 , 1.204507 )
D_OR <- (OR1-OR_S)/OR1
100*D_OR[1] -3.028698 -3.895579 -4.392031 -5.753037100*mean(abs(D_OR))[1] 4.267336use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.race_eth i.SMK_cat bmxbmi hei2015 indfmpir ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.SMK_cat _ISMK_cat_0-4 (naturally coded; _ISMK_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 67,103
Number of PSUs = 214 Population size = 289,078,692
Subpop. no. obs = 17,933
Subpop. size = 124,058,100
Design df = 109
F( 16, 94) = 104.72
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .9226442 .0510834 -1.45 0.149 .8267559 1.029654
_IMJ_2 | 1.109299 .093057 1.24 0.219 .9393801 1.309954
_IMJ_3 | 1.15981 .1921749 0.89 0.373 .8351483 1.610684
_IMJ_4 | 1.210831 .1433523 1.62 0.109 .9575842 1.531052
gndr | 2.515814 .1058554 21.93 0.000 2.314522 2.734613
_Irace_eth_2 | 1.425579 .0763647 6.62 0.000 1.281984 1.585257
_Irace_eth_3 | .8909232 .0524457 -1.96 0.052 .7928123 1.001175
_Irace_eth_4 | 1.0262 .0625756 0.42 0.672 .9093783 1.158028
_ISMK_cat_1 | 1.10735 .0735046 1.54 0.127 .9708422 1.263051
_ISMK_cat_2 | 1.122034 .0829262 1.56 0.122 .9691477 1.299039
_ISMK_cat_3 | 1.179333 .0955432 2.04 0.044 1.004391 1.384747
_ISMK_cat_4 | 1.36938 .1983625 2.17 0.032 1.027634 1.824777
bmxbmi | 1.075826 .0040232 19.54 0.000 1.067881 1.083829
hei2015 | .9961584 .0016338 -2.35 0.021 .9929256 .9994017
indfmpir | .996072 .0139843 -0.28 0.780 .9687377 1.024178
ridageyr | 1.046243 .0024923 18.98 0.000 1.041315 1.051194
_cons | .0132456 .0021673 -26.43 0.000 .009577 .0183194
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_A <- c(.9226442,1.109299 , 1.15981 , 1.210831)
D_OR <- (OR1-OR_A)/OR1
100*D_OR[1] -5.185094 -6.988239 -5.900539 -6.308270100*mean(abs(D_OR))[1] 6.095536use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.race_eth i.SMK_cat i.AL_cat hei2015 indfmpir ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.SMK_cat _ISMK_cat_0-4 (naturally coded; _ISMK_cat_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 65,410
Number of PSUs = 214 Population size = 278,259,603
Subpop. no. obs = 16,240
Subpop. size = 113,239,011
Design df = 109
F( 17, 93) = 76.39
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .8662722 .0440312 -2.82 0.006 .7832556 .9580877
_IMJ_2 | .9497693 .08311 -0.59 0.557 .7985409 1.129638
_IMJ_3 | .9908113 .166594 -0.05 0.956 .7100094 1.382668
_IMJ_4 | 1.021799 .1196945 0.18 0.854 .8100939 1.288829
gndr | 2.493749 .1104029 20.64 0.000 2.284259 2.722451
_Irace_eth_2 | 1.626859 .0897593 8.82 0.000 1.45834 1.81485
_Irace_eth_3 | .9279654 .0533342 -1.30 0.196 .8280573 1.039928
_Irace_eth_4 | .9466042 .0598549 -0.87 0.387 .8351063 1.072989
_ISMK_cat_1 | 1.133889 .0772099 1.85 0.068 .9907381 1.297723
_ISMK_cat_2 | .987174 .0774507 -0.16 0.870 .8450088 1.153257
_ISMK_cat_3 | .9648922 .084234 -0.41 0.683 .8115881 1.147155
_ISMK_cat_4 | 1.039882 .1633238 0.25 0.804 .7617168 1.419628
_IAL_cat_1 | 1.152884 .0657033 2.50 0.014 1.029748 1.290745
_IAL_cat_2 | 1.461211 .110791 5.00 0.000 1.25733 1.698153
hei2015 | .9910991 .0017063 -5.19 0.000 .987723 .9944868
indfmpir | .972498 .0146501 -1.85 0.067 .9438911 1.001972
ridageyr | 1.054063 .0026083 21.28 0.000 1.048906 1.059245
_cons | .1129794 .013403 -18.38 0.000 .089307 .1429266
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_B <- c(.8662722,.9497693 , .9908113, 1.021799)
D_OR <- (OR1-OR_B)/OR1
100*D_OR[1] 1.241537 8.397875 9.530482 10.288319100*mean(abs(D_OR))[1] 7.364554use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.race_eth i.SMK_cat i.AL_cat bmxbmi indfmpir ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.SMK_cat _ISMK_cat_0-4 (naturally coded; _ISMK_cat_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 66,576
Number of PSUs = 214 Population size = 285,370,796
Subpop. no. obs = 17,406
Subpop. size = 120,350,204
Design df = 109
F( 17, 93) = 106.50
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .8764779 .0482782 -2.39 0.018 .7858301 .9775823
_IMJ_2 | .994088 .0836778 -0.07 0.944 .8413374 1.174572
_IMJ_3 | 1.093146 .1676601 0.58 0.563 .8066037 1.48148
_IMJ_4 | 1.09625 .1165248 0.86 0.389 .8880072 1.353328
gndr | 2.761783 .1238839 22.65 0.000 2.526848 3.018563
_Irace_eth_2 | 1.440252 .0814983 6.45 0.000 1.287453 1.611185
_Irace_eth_3 | .8533143 .0478238 -2.83 0.006 .7636038 .9535644
_Irace_eth_4 | .9619244 .0603323 -0.62 0.537 .8494814 1.089251
_ISMK_cat_1 | 1.098552 .0768462 1.34 0.182 .956332 1.261922
_ISMK_cat_2 | 1.081986 .0851774 1.00 0.319 .9256786 1.264688
_ISMK_cat_3 | 1.114768 .0881624 1.37 0.172 .9530394 1.303942
_ISMK_cat_4 | 1.238726 .1934514 1.37 0.173 .9089729 1.688105
_IAL_cat_1 | 1.183767 .0669218 2.98 0.004 1.058291 1.32412
_IAL_cat_2 | 1.45586 .1082391 5.05 0.000 1.25639 1.686997
bmxbmi | 1.076222 .0039639 19.94 0.000 1.068395 1.084107
indfmpir | .9924533 .0136198 -0.55 0.582 .965823 1.019818
ridageyr | 1.047879 .002456 19.95 0.000 1.043022 1.052758
_cons | .0092636 .0014575 -29.76 0.000 .0067819 .0126534
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_H <- c(.8764779,.994088 , 1.093146 , 1.09625)
D_OR <- (OR1-OR_H)/OR1
100*D_OR[1] 0.07804711 4.12348265 0.18645201 3.75168681100*mean(abs(D_OR))[1] 2.034917use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.race_eth i.SMK_cat i.AL_cat bmxbmi hei2015 ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.SMK_cat _ISMK_cat_0-4 (naturally coded; _ISMK_cat_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 66,571
Number of PSUs = 214 Population size = 284,502,347
Subpop. no. obs = 17,401
Subpop. size = 119,481,755
Design df = 109
F( 17, 93) = 101.78
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .8729685 .045144 -2.63 0.010 .7879271 .9671883
_IMJ_2 | 1.075685 .0916203 0.86 0.394 .9085966 1.273501
_IMJ_3 | 1.122345 .1858211 0.70 0.487 .8083788 1.558252
_IMJ_4 | 1.069243 .1363815 0.52 0.601 .8303997 1.376784
gndr | 2.628376 .1128327 22.51 0.000 2.413994 2.861796
_Irace_eth_2 | 1.481415 .0799821 7.28 0.000 1.33108 1.648729
_Irace_eth_3 | .8646855 .0473265 -2.66 0.009 .7757945 .9637617
_Irace_eth_4 | 1.002022 .0633285 0.03 0.975 .8840494 1.135736
_ISMK_cat_1 | 1.109923 .0768381 1.51 0.135 .9676184 1.273156
_ISMK_cat_2 | 1.067379 .0797966 0.87 0.385 .9203841 1.237851
_ISMK_cat_3 | 1.133501 .0937399 1.52 0.133 .9621384 1.335383
_ISMK_cat_4 | 1.219033 .1949738 1.24 0.218 .8878606 1.673733
_IAL_cat_1 | 1.155174 .0672997 2.48 0.015 1.029201 1.296566
_IAL_cat_2 | 1.364234 .1024378 4.14 0.000 1.175591 1.583148
bmxbmi | 1.073958 .0042687 17.95 0.000 1.065531 1.082452
hei2015 | .9958633 .001621 -2.55 0.012 .9926557 .9990812
ridageyr | 1.049204 .0025604 19.68 0.000 1.044142 1.054291
_cons | .0115847 .0019917 -25.93 0.000 .0082395 .016288
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_I <- c(.8729685,1.075685 , 1.122345 , 1.069243 )
D_OR <- (OR1-OR_I)/OR1
100*D_OR[1] 0.4781326 -3.7462796 -2.4796656 6.1228414100*mean(abs(D_OR))[1] 3.20673use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.race_eth i.SMK_cat i.AL_cat bmxbmi hei2015 indfmpir, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.SMK_cat _ISMK_cat_0-4 (naturally coded; _ISMK_cat_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 65,341
Number of PSUs = 214 Population size = 277,875,985
Subpop. no. obs = 16,171
Subpop. size = 112,855,393
Design df = 109
F( 17, 93) = 74.87
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .853067 .0442291 -3.07 0.003 .76976 .9453898
_IMJ_2 | .8540309 .0711063 -1.90 0.061 .7241144 1.007256
_IMJ_3 | .8667479 .1427867 -0.87 0.387 .6253064 1.201414
_IMJ_4 | .9192416 .1094749 -0.71 0.481 .7259718 1.163964
gndr | 2.523541 .1105023 21.14 0.000 2.313764 2.752338
_Irace_eth_2 | 1.430207 .0808254 6.33 0.000 1.278659 1.599716
_Irace_eth_3 | .8168245 .0450319 -3.67 0.000 .732276 .911135
_Irace_eth_4 | .9139344 .0597596 -1.38 0.172 .8028465 1.040393
_ISMK_cat_1 | 1.327567 .0865203 4.35 0.000 1.1667 1.510615
_ISMK_cat_2 | 1.168177 .0963399 1.88 0.062 .9920226 1.37561
_ISMK_cat_3 | 1.490468 .1194666 4.98 0.000 1.271539 1.747091
_ISMK_cat_4 | 1.861055 .2844723 4.06 0.000 1.374636 2.519595
_IAL_cat_1 | 1.021769 .0586326 0.38 0.708 .9119261 1.144843
_IAL_cat_2 | 1.091413 .0778152 1.23 0.223 .9475869 1.257069
bmxbmi | 1.083741 .0041662 20.92 0.000 1.075515 1.092029
hei2015 | 1.002561 .0016744 1.53 0.129 .9992479 1.005885
indfmpir | 1.060349 .0164394 3.78 0.000 1.028262 1.093437
_cons | .0380697 .0058129 -21.40 0.000 .0281288 .051524
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_A <- c(.853067,.8540309, .8667479 , .9192416)
D_OR <- (OR1-OR_A)/OR1
100*D_OR[1] 2.746982 17.631529 20.858528 19.292631100*mean(abs(D_OR))[1] 15.13242Of the variables above, diet quality has the least average change in OR; it will be excluded from the next cycle.
OR2 <- OR_Huse "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ i.race_eth i.SMK_cat i.AL_cat bmxbmi indfmpir ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.SMK_cat _ISMK_cat_0-4 (naturally coded; _ISMK_cat_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 66,576
Number of PSUs = 214 Population size = 285,370,796
Subpop. no. obs = 17,406
Subpop. size = 120,350,204
Design df = 109
F( 16, 94) = 71.48
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .9492018 .051819 -0.95 0.342 .8518594 1.057668
_IMJ_2 | 1.161927 .0927508 1.88 0.063 .9919024 1.361096
_IMJ_3 | 1.387317 .2164246 2.10 0.038 1.018347 1.889975
_IMJ_4 | 1.348905 .1349785 2.99 0.003 1.106241 1.644801
_Irace_eth_2 | 1.397354 .0771256 6.06 0.000 1.252558 1.558889
_Irace_eth_3 | .9479215 .0510358 -0.99 0.323 .8519801 1.054667
_Irace_eth_4 | .9967296 .0607052 -0.05 0.957 .8833921 1.124608
_ISMK_cat_1 | 1.18276 .079924 2.48 0.015 1.034503 1.352264
_ISMK_cat_2 | 1.119855 .0841424 1.51 0.135 .9649111 1.29968
_ISMK_cat_3 | 1.170288 .0904471 2.03 0.044 1.004079 1.364009
_ISMK_cat_4 | 1.442219 .2208336 2.39 0.018 1.06471 1.953579
_IAL_cat_1 | .9836928 .0538447 -0.30 0.764 .8825594 1.096415
_IAL_cat_2 | 1.513681 .1112387 5.64 0.000 1.308514 1.751018
bmxbmi | 1.072064 .0039013 19.12 0.000 1.064359 1.079824
indfmpir | 1.014069 .0133154 1.06 0.290 .9880191 1.040806
ridageyr | 1.044442 .0024029 18.90 0.000 1.039691 1.049215
_cons | .0176393 .0027965 -25.47 0.000 .0128832 .0241514
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_G <- c(.9492018,1.161927 , 1.387317 , 1.348905 )
D_OR <- (OR2-OR_G)/OR2
100*D_OR[1] -8.297288 -16.883717 -26.910495 -23.047206100*mean(abs(D_OR))[1] 18.78468use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.SMK_cat i.AL_cat bmxbmi indfmpir ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.SMK_cat _ISMK_cat_0-4 (naturally coded; _ISMK_cat_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 66,576
Number of PSUs = 214 Population size = 285,370,796
Subpop. no. obs = 17,406
Subpop. size = 120,350,204
Design df = 109
F( 14, 96) = 115.96
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .8986689 .049341 -1.95 0.054 .8060096 1.00198
_IMJ_2 | 1.04899 .0873047 0.57 0.567 .8894725 1.237114
_IMJ_3 | 1.170444 .1774457 1.04 0.302 .866673 1.580688
_IMJ_4 | 1.155208 .1226399 1.36 0.177 .9360086 1.42574
gndr | 2.724206 .1219792 22.38 0.000 2.492864 2.977017
_ISMK_cat_1 | 1.06849 .0737152 0.96 0.339 .9319374 1.225051
_ISMK_cat_2 | 1.092603 .08546 1.13 0.260 .9356997 1.275816
_ISMK_cat_3 | 1.106028 .0878788 1.27 0.207 .9448764 1.294664
_ISMK_cat_4 | 1.211716 .1873303 1.24 0.217 .8919255 1.646165
_IAL_cat_1 | 1.164775 .0654611 2.71 0.008 1.041998 1.302018
_IAL_cat_2 | 1.387717 .100414 4.53 0.000 1.202312 1.601712
bmxbmi | 1.077492 .0038978 20.63 0.000 1.069795 1.085246
indfmpir | .9878462 .0130237 -0.93 0.356 .962368 1.013999
ridageyr | 1.047934 .0024505 20.02 0.000 1.043088 1.052802
_cons | .0093241 .0013861 -31.45 0.000 .0069446 .0125188
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_R <- c(.8986689,1.04899 , 1.170444 , 1.155208)
D_OR <- (OR2-OR_R)/OR2
100*D_OR[1] -2.531838 -5.522851 -7.071151 -5.378153100*mean(abs(D_OR))[1] 5.125998use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.race_eth i.AL_cat bmxbmi indfmpir ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 66,620
Number of PSUs = 214 Population size = 285,567,745
Subpop. no. obs = 17,450
Subpop. size = 120,547,153
Design df = 109
F( 13, 97) = 131.12
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .9047354 .045319 -2.00 0.048 .8192292 .9991662
_IMJ_2 | 1.035177 .0775106 0.46 0.645 .8924091 1.200785
_IMJ_3 | 1.148847 .1745335 0.91 0.363 .8501498 1.552491
_IMJ_4 | 1.163604 .1188553 1.48 0.141 .9503503 1.42471
gndr | 2.773064 .1236754 22.87 0.000 2.538464 3.029344
_Irace_eth_2 | 1.415445 .0780006 6.30 0.000 1.268994 1.578799
_Irace_eth_3 | .8414017 .0478591 -3.04 0.003 .7516978 .9418105
_Irace_eth_4 | .9543591 .0595813 -0.75 0.456 .8432846 1.080064
_IAL_cat_1 | 1.195191 .0668721 3.19 0.002 1.069737 1.335357
_IAL_cat_2 | 1.490981 .107293 5.55 0.000 1.292798 1.719544
bmxbmi | 1.076134 .0039247 20.12 0.000 1.068384 1.083941
indfmpir | .9866729 .0131802 -1.00 0.317 .9608929 1.013144
ridageyr | 1.048746 .0023481 21.26 0.000 1.044102 1.05341
_cons | .0092914 .0014542 -29.89 0.000 .0068133 .0126707
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_S <- c(.9047354,1.035177 , 1.148847 , 1.163604)
D_OR <- (OR2-OR_S)/OR2
100*D_OR[1] -3.223983 -4.133336 -5.095477 -6.144036100*mean(abs(D_OR))[1] 4.649208use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.race_eth i.SMK_cat bmxbmi indfmpir ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.SMK_cat _ISMK_cat_0-4 (naturally coded; _ISMK_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 68,473
Number of PSUs = 214 Population size = 297,340,157
Subpop. no. obs = 19,303
Subpop. size = 132,319,565
Design df = 109
F( 15, 95) = 115.73
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .9256823 .0503621 -1.42 0.159 .8310596 1.031079
_IMJ_2 | 1.084228 .0880271 1.00 0.321 .9230749 1.273516
_IMJ_3 | 1.178992 .1789477 1.08 0.280 .8727001 1.592784
_IMJ_4 | 1.192619 .1239348 1.70 0.093 .9706293 1.46538
gndr | 2.592103 .1086216 22.73 0.000 2.385516 2.81658
_Irace_eth_2 | 1.400491 .0745261 6.33 0.000 1.260306 1.55627
_Irace_eth_3 | .8861233 .0503294 -2.13 0.036 .7917817 .9917059
_Irace_eth_4 | .9879913 .0561807 -0.21 0.832 .8826883 1.105857
_ISMK_cat_1 | 1.122411 .072779 1.78 0.078 .9870499 1.276336
_ISMK_cat_2 | 1.138906 .0802555 1.85 0.068 .99045 1.309613
_ISMK_cat_3 | 1.187517 .0924153 2.21 0.029 1.01778 1.385563
_ISMK_cat_4 | 1.357111 .2037521 2.03 0.044 1.007823 1.827455
bmxbmi | 1.076899 .0037231 21.43 0.000 1.069545 1.084303
indfmpir | .9923301 .0127281 -0.60 0.550 .9674213 1.01788
ridageyr | 1.044669 .0023148 19.72 0.000 1.040091 1.049267
_cons | .0112244 .0016797 -30.00 0.000 .0083436 .0150999
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_A <- c(.9256823,1.084228, 1.178992 , 1.192619 )
D_OR <- (OR2-OR_A)/OR2
100*D_OR[1] -5.613878 -9.067608 -7.853114 -8.790787100*mean(abs(D_OR))[1] 7.831347use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.race_eth i.SMK_cat i.AL_cat indfmpir ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.SMK_cat _ISMK_cat_0-4 (naturally coded; _ISMK_cat_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 66,658
Number of PSUs = 214 Population size = 285,825,605
Subpop. no. obs = 17,488
Subpop. size = 120,805,013
Design df = 109
F( 16, 94) = 83.62
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .8641434 .0446314 -2.83 0.006 .7800622 .9572874
_IMJ_2 | .896223 .074509 -1.32 0.190 .7600734 1.056761
_IMJ_3 | .9647389 .1481579 -0.23 0.816 .7115749 1.307973
_IMJ_4 | .9823915 .0987493 -0.18 0.860 .804937 1.198967
gndr | 2.594114 .1108099 22.32 0.000 2.383532 2.8233
_Irace_eth_2 | 1.623961 .091343 8.62 0.000 1.452649 1.815477
_Irace_eth_3 | .9250797 .0520795 -1.38 0.169 .8274102 1.034278
_Irace_eth_4 | .905103 .0545557 -1.65 0.101 .8031844 1.019954
_ISMK_cat_1 | 1.145004 .0759168 2.04 0.044 1.004006 1.305802
_ISMK_cat_2 | 1.018341 .0756149 0.24 0.807 .878981 1.179797
_ISMK_cat_3 | 1.005552 .0799558 0.07 0.945 .8589382 1.177191
_ISMK_cat_4 | 1.11624 .1701426 0.72 0.472 .8251951 1.509935
_IAL_cat_1 | 1.18708 .0655518 3.11 0.002 1.064016 1.324378
_IAL_cat_2 | 1.535836 .1146836 5.75 0.000 1.324556 1.780816
indfmpir | .9684146 .0136625 -2.27 0.025 .9417111 .9958754
ridageyr | 1.051582 .0024006 22.03 0.000 1.046834 1.05635
_cons | .0763417 .0083309 -23.57 0.000 .0614936 .0947749
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_B <- c(.8641434,.896223 , .9647389, .9823915)
D_OR <- (OR2-OR_B)/OR2
100*D_OR[1] 1.407280 9.844702 11.746565 10.386180100*mean(abs(D_OR))[1] 8.346182use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.race_eth i.SMK_cat i.AL_cat bmxbmi ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.SMK_cat _ISMK_cat_0-4 (naturally coded; _ISMK_cat_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 67,941
Number of PSUs = 214 Population size = 292,707,116
Subpop. no. obs = 18,771
Subpop. size = 127,686,524
Design df = 109
F( 16, 94) = 114.73
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .8715256 .04498 -2.66 0.009 .7867847 .9653936
_IMJ_2 | 1.018565 .0834913 0.22 0.823 .8658306 1.198242
_IMJ_3 | 1.106916 .1700224 0.66 0.510 .816398 1.500814
_IMJ_4 | 1.007019 .1118922 0.06 0.950 .8079734 1.2551
gndr | 2.713086 .1118222 24.22 0.000 2.500269 2.944018
_Irace_eth_2 | 1.464051 .0793199 7.04 0.000 1.314988 1.630011
_Irace_eth_3 | .8600189 .0453991 -2.86 0.005 .7745863 .9548741
_Irace_eth_4 | .9654443 .0573445 -0.59 0.555 .8582242 1.08606
_ISMK_cat_1 | 1.110762 .0750171 1.56 0.123 .9716023 1.269854
_ISMK_cat_2 | 1.088447 .0786404 1.17 0.243 .9432294 1.256021
_ISMK_cat_3 | 1.137615 .0896678 1.64 0.105 .9730824 1.329967
_ISMK_cat_4 | 1.228665 .2001034 1.26 0.209 .8897095 1.696753
_IAL_cat_1 | 1.187824 .065848 3.10 0.002 1.06423 1.325773
_IAL_cat_2 | 1.430815 .1039518 4.93 0.000 1.238932 1.652416
bmxbmi | 1.075684 .0040319 19.46 0.000 1.067722 1.083704
ridageyr | 1.047528 .0023701 20.52 0.000 1.042841 1.052236
_cons | .0093341 .0014287 -30.54 0.000 .0068916 .0126423
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_I <- c(.8715256,1.018565 , 1.106916 , 1.007019 )
D_OR <- (OR2-OR_I)/OR2
100*D_OR[1] 0.5650228 -2.4622569 -1.2596671 8.1396579100*mean(abs(D_OR))[1] 3.106651use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.race_eth i.SMK_cat i.AL_cat bmxbmi indfmpir, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.SMK_cat _ISMK_cat_0-4 (naturally coded; _ISMK_cat_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 66,576
Number of PSUs = 214 Population size = 285,370,796
Subpop. no. obs = 17,406
Subpop. size = 120,350,204
Design df = 109
F( 16, 94) = 80.10
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .8509172 .0436453 -3.15 0.002 .7686654 .9419706
_IMJ_2 | .829701 .0675252 -2.29 0.024 .7061044 .9749319
_IMJ_3 | .8584919 .1291169 -1.01 0.313 .6372042 1.156628
_IMJ_4 | .8800438 .0928769 -1.21 0.229 .7139418 1.08479
gndr | 2.566588 .108348 22.33 0.000 2.360583 2.790569
_Irace_eth_2 | 1.408094 .0795242 6.06 0.000 1.258981 1.574868
_Irace_eth_3 | .8210774 .0448496 -3.61 0.000 .7368296 .914958
_Irace_eth_4 | .9093024 .0560238 -1.54 0.126 .8047769 1.027404
_ISMK_cat_1 | 1.335107 .0845307 4.56 0.000 1.177656 1.51361
_ISMK_cat_2 | 1.166527 .0924424 1.94 0.055 .9969727 1.364917
_ISMK_cat_3 | 1.41749 .1060534 4.66 0.000 1.222138 1.644069
_ISMK_cat_4 | 1.803394 .2738536 3.88 0.000 1.334691 2.436692
_IAL_cat_1 | 1.047061 .0564944 0.85 0.396 .9408702 1.165237
_IAL_cat_2 | 1.147178 .0807064 1.95 0.054 .9978714 1.318824
bmxbmi | 1.083186 .0038972 22.21 0.000 1.07549 1.090938
indfmpir | 1.064385 .0156055 4.26 0.000 1.0339 1.095768
_cons | .0432163 .0055442 -24.49 0.000 .0335136 .0557281
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_A <- c(.8509172,.829701, .8584919 , .8800438)
D_OR <- (OR2-OR_A)/OR2
100*D_OR[1] 2.916297 16.536464 21.465943 19.722344100*mean(abs(D_OR))[1] 15.16026Of the variables above, Income has the least average change in OR; it will be excluded from the next cycle.
OR3 <- OR_Iuse "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ i.race_eth i.SMK_cat i.AL_cat bmxbmi ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.SMK_cat _ISMK_cat_0-4 (naturally coded; _ISMK_cat_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 67,941
Number of PSUs = 214 Population size = 292,707,116
Subpop. no. obs = 18,771
Subpop. size = 127,686,524
Design df = 109
F( 15, 95) = 75.16
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .95096 .0491342 -0.97 0.333 .8583977 1.053503
_IMJ_2 | 1.191889 .0931612 2.25 0.027 1.020838 1.391602
_IMJ_3 | 1.411954 .2212835 2.20 0.030 1.034955 1.926282
_IMJ_4 | 1.240874 .1296602 2.07 0.041 1.008756 1.526403
_Irace_eth_2 | 1.395836 .074125 6.28 0.000 1.25639 1.550759
_Irace_eth_3 | .926874 .0463654 -1.52 0.132 .8393878 1.023479
_Irace_eth_4 | .9884425 .0569071 -0.20 0.840 .8818514 1.107917
_ISMK_cat_1 | 1.194937 .0781379 2.72 0.008 1.049686 1.360287
_ISMK_cat_2 | 1.108693 .0779317 1.47 0.145 .9645112 1.274428
_ISMK_cat_3 | 1.167537 .0882059 2.05 0.043 1.005175 1.356126
_ISMK_cat_4 | 1.397069 .2201642 2.12 0.036 1.022283 1.909258
_IAL_cat_1 | .9934992 .0528482 -0.12 0.903 .8940883 1.103963
_IAL_cat_2 | 1.485767 .1061166 5.54 0.000 1.289655 1.711701
bmxbmi | 1.071503 .0039498 18.74 0.000 1.063703 1.07936
ridageyr | 1.044723 .0023077 19.81 0.000 1.040159 1.049307
_cons | .0185177 .0028224 -26.17 0.000 .0136897 .0250484
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_G <- c(.95096,1.191889 , 1.411954 , 1.240874 )
D_OR <- (OR3-OR_G)/OR3
100*D_OR[1] -9.114408 -17.016489 -27.557466 -23.222501100*mean(abs(D_OR))[1] 19.22772use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.SMK_cat i.AL_cat bmxbmi ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.SMK_cat _ISMK_cat_0-4 (naturally coded; _ISMK_cat_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 67,941
Number of PSUs = 214 Population size = 292,707,116
Subpop. no. obs = 18,771
Subpop. size = 127,686,524
Design df = 109
F( 13, 97) = 130.38
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .8925672 .0457181 -2.22 0.029 .806403 .9879381
_IMJ_2 | 1.076866 .0872889 0.91 0.363 .9170437 1.264542
_IMJ_3 | 1.188852 .1795897 1.15 0.255 .8812525 1.603818
_IMJ_4 | 1.063824 .1165876 0.56 0.574 .8561248 1.321913
gndr | 2.673077 .1099395 23.91 0.000 2.463825 2.900101
_ISMK_cat_1 | 1.079423 .0718895 1.15 0.254 .9459439 1.231738
_ISMK_cat_2 | 1.105892 .0794385 1.40 0.164 .9591421 1.275096
_ISMK_cat_3 | 1.132822 .0901003 1.57 0.120 .9676095 1.326242
_ISMK_cat_4 | 1.203511 .194639 1.15 0.255 .8734607 1.658277
_IAL_cat_1 | 1.167431 .0643886 2.81 0.006 1.046542 1.302283
_IAL_cat_2 | 1.363704 .0971483 4.35 0.000 1.184135 1.570505
bmxbmi | 1.07716 .0039715 20.16 0.000 1.069317 1.08506
ridageyr | 1.047415 .0023575 20.58 0.000 1.042752 1.052098
_cons | .0093027 .0013535 -32.15 0.000 .0069723 .0124122
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_R <- c(.8925672,1.076866 , 1.188852 , 1.063824 )
D_OR <- (OR3-OR_R)/OR3
100*D_OR[1] -2.414341 -5.723837 -7.402188 -5.640906100*mean(abs(D_OR))[1] 5.295318use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.race_eth i.AL_cat bmxbmi ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 67,991
Number of PSUs = 214 Population size = 292,944,878
Subpop. no. obs = 18,821
Subpop. size = 127,924,286
Design df = 109
F( 12, 98) = 145.02
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .9008402 .0427715 -2.20 0.030 .8199349 .9897288
_IMJ_2 | 1.065697 .0775084 0.87 0.384 .9226362 1.23094
_IMJ_3 | 1.171644 .178301 1.04 0.300 .8665739 1.584112
_IMJ_4 | 1.077879 .1163135 0.69 0.489 .8703338 1.334916
gndr | 2.722419 .1117439 24.40 0.000 2.509715 2.95315
_Irace_eth_2 | 1.445952 .0762632 6.99 0.000 1.302433 1.605286
_Irace_eth_3 | .8539244 .0459672 -2.93 0.004 .7675106 .9500674
_Irace_eth_4 | .9601631 .0567304 -0.69 0.493 .8540591 1.079449
_IAL_cat_1 | 1.19993 .0660538 3.31 0.001 1.075903 1.338255
_IAL_cat_2 | 1.471866 .1040276 5.47 0.000 1.279477 1.693185
bmxbmi | 1.075577 .0039873 19.65 0.000 1.067703 1.083509
ridageyr | 1.048363 .0022979 21.55 0.000 1.043819 1.052928
_cons | .0092218 .0013955 -30.97 0.000 .0068322 .0124472
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_S <- c(.9008402,1.065697 , 1.171644 , 1.077879)
D_OR <- (OR3-OR_S)/OR3
100*D_OR[1] -3.363596 -4.627294 -5.847598 -7.036610100*mean(abs(D_OR))[1] 5.218775use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.race_eth i.SMK_cat bmxbmi ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.SMK_cat _ISMK_cat_0-4 (naturally coded; _ISMK_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 70,029
Number of PSUs = 214 Population size = 305,720,293
Subpop. no. obs = 20,859
Subpop. size = 140,699,700
Design df = 109
F( 14, 96) = 123.54
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .9215587 .0474467 -1.59 0.115 .8321598 1.020562
_IMJ_2 | 1.120635 .0865014 1.48 0.143 .961662 1.305887
_IMJ_3 | 1.19904 .1788696 1.22 0.226 .8921304 1.611533
_IMJ_4 | 1.112326 .1187614 1.00 0.321 .9001815 1.374465
gndr | 2.536739 .0980884 24.07 0.000 2.349593 2.73879
_Irace_eth_2 | 1.428177 .0733461 6.94 0.000 1.289961 1.581203
_Irace_eth_3 | .8924284 .0480463 -2.11 0.037 .8021067 .9929208
_Irace_eth_4 | .9957015 .0545228 -0.08 0.937 .8932965 1.109846
_ISMK_cat_1 | 1.121132 .0694253 1.85 0.068 .9916421 1.267531
_ISMK_cat_2 | 1.134052 .0734463 1.94 0.055 .9974396 1.289376
_ISMK_cat_3 | 1.1993 .09233 2.36 0.020 1.029583 1.396994
_ISMK_cat_4 | 1.345636 .2121171 1.88 0.062 .9845629 1.839127
bmxbmi | 1.076641 .0037402 21.26 0.000 1.069254 1.08408
ridageyr | 1.044424 .0022112 20.53 0.000 1.040051 1.048816
_cons | .0111999 .0016446 -30.59 0.000 .0083719 .0149832
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_A <- c(.9215587,1.120635 , 1.19904 , 1.112326 )
D_OR <- (OR3-OR_A)/OR3
100*D_OR[1] -5.740864 -10.020961 -8.322583 -10.457300100*mean(abs(D_OR))[1] 8.635427use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.race_eth i.SMK_cat i.AL_cat ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.SMK_cat _ISMK_cat_0-4 (naturally coded; _ISMK_cat_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 68,033
Number of PSUs = 214 Population size = 293,207,892
Subpop. no. obs = 18,863
Subpop. size = 128,187,300
Design df = 109
F( 15, 95) = 95.35
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .8525604 .0409787 -3.32 0.001 .7750905 .9377734
_IMJ_2 | .9170568 .0744154 -1.07 0.288 .7808171 1.077068
_IMJ_3 | .9763369 .1493085 -0.16 0.876 .7210518 1.322005
_IMJ_4 | .9083168 .0954446 -0.92 0.362 .737548 1.118625
gndr | 2.549513 .1021531 23.36 0.000 2.35488 2.760234
_Irace_eth_2 | 1.684756 .0915052 9.60 0.000 1.512816 1.876238
_Irace_eth_3 | .9581874 .050741 -0.81 0.422 .862718 1.064222
_Irace_eth_4 | .9184648 .052357 -1.49 0.139 .8203423 1.028324
_ISMK_cat_1 | 1.157892 .0743315 2.28 0.024 1.019557 1.314997
_ISMK_cat_2 | 1.044546 .0717566 0.63 0.527 .9115838 1.196902
_ISMK_cat_3 | 1.056807 .0833636 0.70 0.485 .9038511 1.235647
_ISMK_cat_4 | 1.148418 .1784989 0.89 0.375 .8439417 1.562744
_IAL_cat_1 | 1.185131 .0650206 3.10 0.002 1.063022 1.321267
_IAL_cat_2 | 1.52412 .1116208 5.75 0.000 1.318198 1.762211
ridageyr | 1.050682 .002324 22.35 0.000 1.046086 1.055298
_cons | .0710004 .0072701 -25.83 0.000 .0579593 .0869758
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_B <- c(.8525604,.9170568 , .9763369, .9083168)
D_OR <- (OR3-OR_B)/OR3
100*D_OR[1] 2.176092 9.965805 11.796658 9.801424100*mean(abs(D_OR))[1] 8.434995use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.race_eth i.SMK_cat i.AL_cat bmxbmi indfmpir, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.SMK_cat _ISMK_cat_0-4 (naturally coded; _ISMK_cat_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 66,576
Number of PSUs = 214 Population size = 285,370,796
Subpop. no. obs = 17,406
Subpop. size = 120,350,204
Design df = 109
F( 16, 94) = 80.10
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .8509172 .0436453 -3.15 0.002 .7686654 .9419706
_IMJ_2 | .829701 .0675252 -2.29 0.024 .7061044 .9749319
_IMJ_3 | .8584919 .1291169 -1.01 0.313 .6372042 1.156628
_IMJ_4 | .8800438 .0928769 -1.21 0.229 .7139418 1.08479
gndr | 2.566588 .108348 22.33 0.000 2.360583 2.790569
_Irace_eth_2 | 1.408094 .0795242 6.06 0.000 1.258981 1.574868
_Irace_eth_3 | .8210774 .0448496 -3.61 0.000 .7368296 .914958
_Irace_eth_4 | .9093024 .0560238 -1.54 0.126 .8047769 1.027404
_ISMK_cat_1 | 1.335107 .0845307 4.56 0.000 1.177656 1.51361
_ISMK_cat_2 | 1.166527 .0924424 1.94 0.055 .9969727 1.364917
_ISMK_cat_3 | 1.41749 .1060534 4.66 0.000 1.222138 1.644069
_ISMK_cat_4 | 1.803394 .2738536 3.88 0.000 1.334691 2.436692
_IAL_cat_1 | 1.047061 .0564944 0.85 0.396 .9408702 1.165237
_IAL_cat_2 | 1.147178 .0807064 1.95 0.054 .9978714 1.318824
bmxbmi | 1.083186 .0038972 22.21 0.000 1.07549 1.090938
indfmpir | 1.064385 .0156055 4.26 0.000 1.0339 1.095768
_cons | .0432163 .0055442 -24.49 0.000 .0335136 .0557281
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_A <- c(.8509172,.829701, .8584919 , .8800438)
D_OR <- (OR3-OR_A)/OR3
100*D_OR[1] 2.364635 18.542165 22.442904 12.609017100*mean(abs(D_OR))[1] 13.98968Of the variables above, smoking has the least average change in OR; it will be excluded from the next cycle.
OR4 <- OR_Suse "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ i.race_eth i.AL_cat bmxbmi ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 67,991
Number of PSUs = 214 Population size = 292,944,878
Subpop. no. obs = 18,821
Subpop. size = 127,924,286
Design df = 109
F( 11, 99) = 93.40
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .9997446 .0473145 -0.01 0.996 .9102324 1.098059
_IMJ_2 | 1.271005 .0879447 3.47 0.001 1.108125 1.457826
_IMJ_3 | 1.537365 .2372203 2.79 0.006 1.132294 2.087346
_IMJ_4 | 1.360446 .138497 3.02 0.003 1.11187 1.664595
_Irace_eth_2 | 1.365571 .0707416 6.01 0.000 1.232321 1.513229
_Irace_eth_3 | .918571 .0470872 -1.66 0.100 .8298299 1.016802
_Irace_eth_4 | .9807279 .0563314 -0.34 0.735 .8752014 1.098978
_IAL_cat_1 | 1.006606 .0531149 0.12 0.901 .9066522 1.11758
_IAL_cat_2 | 1.540519 .1065286 6.25 0.000 1.343212 1.766808
bmxbmi | 1.071479 .003915 18.90 0.000 1.063747 1.079266
ridageyr | 1.045966 .0022464 20.93 0.000 1.041523 1.050427
_cons | .0181792 .002754 -26.45 0.000 .0134641 .0245455
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_G <- c(.9997446,1.271005 , 1.537365 , 1.360446 )
D_OR <- (OR4-OR_G)/OR4
100*D_OR[1] -10.97913 -19.26514 -31.21434 -26.21509100*mean(abs(D_OR))[1] 21.91843use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.AL_cat bmxbmi ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 67,991
Number of PSUs = 214 Population size = 292,944,878
Subpop. no. obs = 18,821
Subpop. size = 127,924,286
Design df = 109
F( 9, 101) = 171.42
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .9195897 .0431616 -1.79 0.077 .8379031 1.00924
_IMJ_2 | 1.125541 .0807243 1.65 0.102 .9763994 1.297464
_IMJ_3 | 1.256641 .187487 1.53 0.129 .9349512 1.689016
_IMJ_4 | 1.136796 .1206675 1.21 0.230 .9211185 1.402973
gndr | 2.678669 .1097468 24.05 0.000 2.469751 2.905259
_IAL_cat_1 | 1.178936 .0645598 3.01 0.003 1.057679 1.314093
_IAL_cat_2 | 1.404028 .0972246 4.90 0.000 1.22397 1.610573
bmxbmi | 1.076922 .0039402 20.25 0.000 1.069141 1.08476
ridageyr | 1.048122 .0022665 21.73 0.000 1.043639 1.052623
_cons | .0092223 .0013177 -32.80 0.000 .0069479 .0122412
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_R <- c(.9195897,1.125541 , 1.256641 , 1.136796 )
D_OR <- (OR4-OR_R)/OR4
100*D_OR[1] -2.081335 -5.615480 -7.254507 -5.466012100*mean(abs(D_OR))[1] 5.104334use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.race_eth bmxbmi ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 70,080
Number of PSUs = 214 Population size = 305,959,182
Subpop. no. obs = 20,910
Subpop. size = 140,938,589
Design df = 109
F( 10, 100) = 166.70
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .9671812 .0453606 -0.71 0.478 .8813299 1.061395
_IMJ_2 | 1.20545 .0813543 2.77 0.007 1.054527 1.377973
_IMJ_3 | 1.310135 .1960042 1.81 0.074 .9739608 1.762344
_IMJ_4 | 1.228613 .1277532 1.98 0.050 .9997978 1.509796
gndr | 2.550909 .0984551 24.26 0.000 2.363051 2.753701
_Irace_eth_2 | 1.403748 .0704649 6.76 0.000 1.270811 1.550591
_Irace_eth_3 | .8879768 .0480192 -2.20 0.030 .7977272 .9884367
_Irace_eth_4 | .9883466 .0538039 -0.22 0.830 .8872603 1.10095
bmxbmi | 1.076436 .0037414 21.19 0.000 1.069046 1.083877
ridageyr | 1.045265 .0021573 21.45 0.000 1.040998 1.04955
_cons | .0112235 .001637 -30.78 0.000 .0084058 .0149856
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_A <- c(.9671812,1.20545 , 1.310135 , 1.228613 )
D_OR <- (OR4-OR_A)/OR4
100*D_OR[1] -7.364347 -13.113765 -11.820229 -13.984315100*mean(abs(D_OR))[1] 11.57066use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.race_eth i.AL_cat ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 68,083
Number of PSUs = 214 Population size = 293,445,655
Subpop. no. obs = 18,913
Subpop. size = 128,425,062
Design df = 109
F( 11, 99) = 125.27
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .8825243 .0378787 -2.91 0.004 .8105545 .9608843
_IMJ_2 | .9491352 .0690822 -0.72 0.475 .821634 1.096422
_IMJ_3 | 1.020527 .1554441 0.13 0.894 .7545982 1.380171
_IMJ_4 | .9561007 .0970679 -0.44 0.659 .7818356 1.169208
gndr | 2.56154 .1025656 23.49 0.000 2.366115 2.773105
_Irace_eth_2 | 1.656981 .0884833 9.46 0.000 1.490572 1.841969
_Irace_eth_3 | .955664 .0515213 -0.84 0.402 .8588167 1.063433
_Irace_eth_4 | .9153065 .0520016 -1.56 0.122 .8178319 1.024399
_IAL_cat_1 | 1.194147 .0653169 3.24 0.002 1.071462 1.330881
_IAL_cat_2 | 1.545072 .1108688 6.06 0.000 1.340244 1.781204
ridageyr | 1.05158 .0022663 23.34 0.000 1.047098 1.056081
_cons | .0697174 .0070696 -26.26 0.000 .057024 .0852365
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_B <- c(.8825243,.9491352 , 1.020527 , .9561007)
D_OR <- (OR4-OR_B)/OR4
100*D_OR[1] 2.033202 10.937612 12.897860 11.297956100*mean(abs(D_OR))[1] 9.291657use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.race_eth i.AL_cat bmxbmi indfmpir, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.race_eth _Irace_eth_1-4 (naturally coded; _Irace_eth_1 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 66,620
Number of PSUs = 214 Population size = 285,567,745
Subpop. no. obs = 17,450
Subpop. size = 120,547,153
Design df = 109
F( 12, 98) = 100.31
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .929861 .0428316 -1.58 0.117 .84873 1.018748
_IMJ_2 | .9209674 .0665825 -1.14 0.257 .7980218 1.062854
_IMJ_3 | .9745637 .1480893 -0.17 0.866 .7211311 1.317062
_IMJ_4 | 1.017064 .1073789 0.16 0.873 .8250343 1.25379
gndr | 2.600123 .1088726 22.82 0.000 2.393052 2.825111
_Irace_eth_2 | 1.329777 .0719617 5.27 0.000 1.194533 1.480332
_Irace_eth_3 | .7811936 .0423633 -4.55 0.000 .7015856 .8698347
_Irace_eth_4 | .8848302 .0536862 -2.02 0.046 .7845747 .9978966
_IAL_cat_1 | 1.068888 .0578136 1.23 0.221 .9602312 1.18984
_IAL_cat_2 | 1.205082 .0827465 2.72 0.008 1.051751 1.380766
bmxbmi | 1.083248 .0038822 22.31 0.000 1.07558 1.090969
indfmpir | 1.051686 .0149628 3.54 0.001 1.022444 1.081763
_cons | .0471104 .0060684 -23.72 0.000 .0364956 .0608126
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_A <- c(.929861,.9209674, .9745637 , 1.017064)
D_OR <- (OR4-OR_A)/OR4
100*D_OR[1] -3.221526 13.580746 16.820835 5.642099100*mean(abs(D_OR))[1] 9.816301Of the variables above, race/ethnicity has the least average change in OR; it will be excluded from the next cycle.
OR5 <- OR_Ruse "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ i.AL_cat bmxbmi ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 67,991
Number of PSUs = 214 Population size = 292,944,878
Subpop. no. obs = 18,821
Subpop. size = 127,924,286
Design df = 109
F( 8, 102) = 99.70
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | 1.009946 .0471021 0.21 0.832 .9207761 1.107752
_IMJ_2 | 1.319251 .0903153 4.05 0.000 1.151862 1.510965
_IMJ_3 | 1.612652 .2449228 3.15 0.002 1.193473 2.179058
_IMJ_4 | 1.408112 .1409049 3.42 0.001 1.154793 1.717
_IAL_cat_1 | .995409 .0524549 -0.09 0.931 .89669 1.104996
_IAL_cat_2 | 1.487766 .1009319 5.86 0.000 1.300588 1.701882
bmxbmi | 1.072757 .0038712 19.46 0.000 1.065111 1.080457
ridageyr | 1.045685 .002211 21.13 0.000 1.041312 1.050076
_cons | .0181979 .0025789 -28.27 0.000 .0137417 .0240992
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_G <- c(1.009946,1.319251 , 1.612652 , 1.408112 )
D_OR <- (OR5-OR_G)/OR5
100*D_OR[1] -9.825719 -17.210390 -28.330366 -23.866727100*mean(abs(D_OR))[1] 19.8083use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr bmxbmi ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 70,080
Number of PSUs = 214 Population size = 305,959,182
Subpop. no. obs = 20,910
Subpop. size = 140,938,589
Design df = 109
F( 7, 103) = 209.35
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .9741905 .0445573 -0.57 0.569 .8897639 1.066628
_IMJ_2 | 1.246359 .0826781 3.32 0.001 1.092809 1.421484
_IMJ_3 | 1.36807 .2019934 2.12 0.036 1.020984 1.833149
_IMJ_4 | 1.266254 .1293705 2.31 0.023 1.034139 1.550467
gndr | 2.519126 .0968387 24.03 0.000 2.334324 2.718558
bmxbmi | 1.077551 .0036974 21.77 0.000 1.070247 1.084904
ridageyr | 1.045197 .0021175 21.82 0.000 1.041008 1.049402
_cons | .0111882 .0015324 -32.80 0.000 .0085285 .0146775
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_A <- c(.9741905,1.246359 , 1.36807 , 1.266254 )
D_OR <- (OR5-OR_A)/OR5
100*D_OR[1] -5.937518 -10.734216 -8.867210 -11.387971100*mean(abs(D_OR))[1] 9.231729use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.AL_cat ridageyr, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 68,083
Number of PSUs = 214 Population size = 293,445,655
Subpop. no. obs = 18,913
Subpop. size = 128,425,062
Design df = 109
F( 8, 102) = 154.55
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .894893 .0383556 -2.59 0.011 .8220127 .9742349
_IMJ_2 | 1.00085 .0723496 0.01 0.991 .8672539 1.155025
_IMJ_3 | 1.096039 .1625644 0.62 0.538 .8168809 1.470597
_IMJ_4 | 1.005481 .1001634 0.05 0.956 .82533 1.224956
gndr | 2.510727 .1003495 23.03 0.000 2.319511 2.717706
_IAL_cat_1 | 1.172589 .0637246 2.93 0.004 1.052854 1.305942
_IAL_cat_2 | 1.477613 .1033961 5.58 0.000 1.286261 1.697432
ridageyr | 1.051039 .0022176 23.59 0.000 1.046653 1.055443
_cons | .0749875 .0068302 -28.44 0.000 .0626019 .0898237
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_B <- c(.894893,1.00085 , 1.096039 , 1.005481 )
D_OR <- (OR5-OR_B)/OR5
100*D_OR[1] 2.685622 11.078317 12.780261 11.551325100*mean(abs(D_OR))[1] 9.523881use "data\NHANES0518_new.dta", clear
svyset sdmvpsu [pw=wtmec12yr], strata(sdmvstra)
xi: svy,subpop(if include==1): logit BP_cat i.MJ gndr i.AL_cat bmxbmi indfmpir, or pweight: wtmec12yr
VCE: linearized
Single unit: missing
Strata 1: sdmvstra
SU 1: sdmvpsu
FPC 1: <zero>
i.MJ _IMJ_0-4 (naturally coded; _IMJ_0 omitted)
i.AL_cat _IAL_cat_0-2 (naturally coded; _IAL_cat_0 omitted)
(running logit on estimation sample)
Survey: Logistic regression
Number of strata = 105 Number of obs = 66,620
Number of PSUs = 214 Population size = 285,567,745
Subpop. no. obs = 17,450
Subpop. size = 120,547,153
Design df = 109
F( 9, 101) = 118.83
Prob > F = 0.0000
------------------------------------------------------------------------------
| Linearized
BP_cat | Odds Ratio Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
_IMJ_1 | .9619515 .0440727 -0.85 0.399 .8784494 1.053391
_IMJ_2 | .9781208 .0698408 -0.31 0.757 .8490471 1.126817
_IMJ_3 | 1.05203 .1567575 0.34 0.734 .7830167 1.413465
_IMJ_4 | 1.081387 .1130711 0.75 0.456 .8789803 1.330402
gndr | 2.556899 .1066919 22.50 0.000 2.353947 2.777349
_IAL_cat_1 | 1.051098 .0568805 0.92 0.359 .9441979 1.170101
_IAL_cat_2 | 1.14898 .077502 2.06 0.042 1.005199 1.313328
bmxbmi | 1.08422 .0038513 22.76 0.000 1.076613 1.09188
indfmpir | 1.053271 .0144658 3.78 0.000 1.024987 1.082336
_cons | .0452901 .0053826 -26.04 0.000 .0357853 .0573194
------------------------------------------------------------------------------
Note: _cons estimates baseline odds.OR_A <- c(.9619515,.9781208, 1.05203 , 1.081387 )
D_OR <- (OR5-OR_A)/OR5
100*D_OR[1] -4.606598 13.097719 16.282375 4.874137100*mean(abs(D_OR))[1] 9.715207Of the variables above, alcohol use has the least average change in OR. However, alcohol use has a greater than 10% change in OR for heavy marijuana use. Therefore no further deletion will be performed. The variables included in step 5 will produce the final models. Model 1 will be the crude model; model 2 will include gender and age as confounders; and model 3 will include gender and age, as well as the mediators BMI and alcohol use.