1
Appendix 1. Denominator models for computing of Inverse Probability of Death and
Censoring Weights in Estimating Effects of Baseline Diabetes on Dementia Risks
Mortality1
Censoring2
Estimate
OR
p
Estimate
OR
p
Baseline Covariates
1998 diabetes status
.42
1.52
<.001
male
.46
1.59
<.001
age
.04
1.04
<.001
black
-.52
0.60
<.001
Years of education
.04
<.001
-.06
<.001
Baseline Wealth (reference=highest quintile)
lowest quintile
.03
.65
2nd
-.12
.09
3rd
.15
.01
4th
-.02
.72
Year of Assessment (reference=2008)
2002
-.01
.90
.70
.23
<.001
2004
-.12
.80
.001
.01
.84
2006
.02
.92
.61
-.18
.004
Baseline BMI
.05
1.05
<.001
Baseline Smoking
.48
1.62
<.001
Time-varying covariates
Marital Status (reference=married)
Widowed
.09
1.10
.09
Divorced/Separated
.28
1.32
.002
Never married
.39
1.48
.003
Currently working
-.24
.79
.007
-.20
.05
Self-rated health
.34
1.41
<.0001
.09
.005
Disability
.70
2.01
<.0001
Wealth (reference=highest quintile)
lowest quintile
.16
1.48
<.001
2nd
.05
1.33
0.61
3rd
.02
1.28
0.67
4th
-.01
1.24
0.78
BMI
-.10
.91
<.001
Heart Problems
.38
1.46
<.001
Prior wave memory
-.63
.52
.002
-0.26
<.001
score
Missing indicator 1
.26
1.30
.0
0.56
<.001
Missing indicator 2
0.51
.02
Note. Blank cells mean the effects were not significant at .10 level in numerator or
denominator models.
1
Estimates were from logistic models of estimating a person’s probability of mortality based
on the person’s basic demographic variables and prior wave time-varying covariates, given
that this person was alive and participated in the survey last wave. Participants were weighted
by the inverse of the probability of not dying.
2
Estimates were from logistic models of estimating a person’s probability of being censored
based on the person’s basic demographic variables and prior wave time-varying covariates,
2
given that this person participated last wave and was still alive this wave. Participants were
weighted by the inverse of the probability of not censored.
3
Appendix 2. Denominator models for computing Inverse Probabiltiy of Death and Censoring
Weights in Estimating Effects of Baseline Diabetes on Memory Scores
mortality
censoring
Estimate
OR
p
Estimate
OR
p
Baseline Covariates
1998 diabetes status
.42
1.52
<.001
male
.46
1.58
<.001
age
.04
1.04
<.001
black
-.51
0.57
<.001
-.21
.81
.04
Years of education
.04
<.001
-.04
.97
.002
Baseline Wealth (reference=highest quintile)
lowest quintile
.04
1.13
.62
2nd
-.08
1.01
.21
3rd
.17
1.29
.006
4th
-.03
1.07
.71
Year of Assessment (reference=2008)
2002
-.01
0.89
.93
.24
1.42
<.001
2004
-.12
0.8 .002
.03
1.16
.58
2006
.02
0.91
.57
-.15
.96
.01
Baseline BMI
.05
1.05 <.001
Baseline Smoking
.47
1.6 <.001
Time-varying covariates
Marital Status (reference=married)
Widowed
.09
1.09
.09
Divorced/Separated
.29
1.33 .002
Never married
.38
2.06 .005
Currently working
-.24
0.8 .006
-.18
.84
.09
Self-rated health
.34
1.39 <.001
.09
1.09
.007
Disability
.70
2.05 <.001
Wealth (reference=highest quintile)
lowest quintile
.17
1.39 <.001
2nd
.05
1.24 0.22
3rd
.02
1.22 0.70
4th
-.01
1.19 0.78
BMI
-.10
0.9 <.001
Heart Problems
.38
1.46 <.001
Prior wave memory score
-.66
0.53 <.001
-.31
.74
<.001
Missing indicator 1
.25
1.28 .001
.42
1.52
<.001
Missing indicator 2
.63
1.89
.002
Note. Blank cells mean the effects were not significant at .10 level in numerator or
denominator models.
1
Estimates were from logistic models of estimating a person’s probability of mortality based
on the person’s basic demographic variables and prior wave time-varying covariates, given
that this person was alive and participated in the survey last wave.
2
Estimates were from logistic models of estimating a person’s probability of being censored
based on the person’s basic demographic variables and prior wave time-varying covariates,
given that this person participated last wave and was still alive this wave.
4
Appendix 3. Denominator models for computing of Inverse Probability of Death, Censoring and
exposure Weights in Estimating Effects of Incident Diabetes on Dementia Risks
Mortali
Censori
Exposu
ty1
ng2
re3
Estima
Estima
Estima
OR
p
OR
p
OR
te
te
te
Baseline
Covariates
<.00
male
.52
1.68
.40
1.49
1
<.00
age
.04
1.04
-.03
.97
1
<.00
black
-.50
.61
1
Years of
<.00
<.00
.04
1.04
-.05
.95
education
1
1
Baseline Wealth (reference=highest
quintile)
lowest quintile
2nd
3rd
4th
Year of Assessment (reference=2008)
2000
NA
NA
-.11
.87
<.00
2002
.01
.89
.73
.21
1.29
.15
1.13
1
<.00
2004
-.15
.75
.03
1.08
.65
-.03
.95
1
2006
.01
.88
.87
-.19
.87
.004
-.04
.94
<.00
Baseline BMI
.05
1.05
.04
1.04
1
Baseline
.35
1.42
hypertension
Baseline
<.00
.48
1.62
Smoking
1
Time-varying
covariates
Prior wave
<.00
.35
1.41
diabetes status
1
Marital Status (reference=married)
Widowed
.04
1.04
.54
.08
1.09
Divorced/Separ
.26
1.29
.01
-.01
.99
ated
Never married
.31
1.36
.03
.46
1.58
Currently
-.23
.80
.02
-.18
.84
working
Self-rated
<.00
<.00
.35
1.42
.13
1.14
.16
1.18
health
1
1
<.00
Disability
.69
2.00
1
Wealth (reference=highest quintile)
lowest quintile
.16
1.47
.001
2nd
.08
1.35
.10
3rd
.03
1.30
.48
p
<.00
1
<.00
1
.14
.03
.70
.66
.03
.02
.40
.98
.04
.10
<.00
1
5
4th
BMI
-.05
1.20
-.11
.90
.36
<.00
1
Hypertension
Heart Problems
.37
1.45
<.00
1
<.00
1
.05
1.05
.002
.34
1.40
.03
.22
1.25
.008
Prior wave
<.00
-.66
.52
-.29
.75
memory score
1
Missing
<.00
.24
1.28
.004
.55
1.73
.39
1.47
.003
indicator 1
1
Missing
.52
1.68
.02
.36
1.43
.04
indicator 2
Note. Blank cells mean the effects were not significant at .10 level in numerator or denominator
models.
1
Estimates were from logistic models of estimating a person’s probability of mortality based on the
person’s basic demographic variables and prior wave time-varying covariates, given that this person
was alive and participated in the survey last wave.
2
Estimates were from logistic models of estimating a person’s probability of being censored based on
the person’s basic demographic variables and prior wave time-varying covariates, given that this
person participated last wave and was still alive this wave.
6
Appendix 4. Denominator models for computing of Inverse Probability of Death, Censoring and
Exposure Weights in Estimating Effects of Incident Diabetes on Dementia Risks
Mortali
Censori
Exposu
ty1
ng2
re3
Estima
Estima
Estima
OR
p
OR
p
OR
te
te
te
Baseline
Covariates
<.00
male
.52
1.68
.41
1.51
1
<.00
age
.04
1.04
-.03
.97
1
<.00
black
-.49
.61
-.19
.82
.07
1
Years of
<.00
<.00
.04
1.04
-.04
.96
education
1
1
Baseline Wealth (reference=highest
quintile)
lowest quintile
-.07
.97
.33
2nd
-.01
1.02
.80
3rd
.02
1.05
.70
4th
.09
1.13
.09
Year of Assessment (reference=2008)
2000
NA
NA
-.11
.85
<.00
2002
.02
.90
.70
.21
1.37
.15
1.10
1
<.00
2004
-.15
.76
.04
1.16
.52
-.03
.92
1
2006
.01
.90
.77
-.13
.98
.03
-.05
.91
<.00
Baseline BMI
.05
1.05
.04
1.04
1
Baseline
.35
1.42
hypertension
Baseline
<.00
.48
1.61
Smoking
1
Time-varying
covariates
Prior wave
<.00
.35
1.43
diabetes status
1
Marital Status (reference=married)
Widowed
.04
1.04
.50
.09
1.10
Divorced/Separ
.26
1.30
.01
-.01
.99
ated
Never married
.30
1.36
.04
.49
1.64
Currently
-.23
.79
.01
-.17
.84
working
Self-rated
<.00
<.00
.35
1.42
.13
1.14
.17
1.19
health
1
1
<.00
Disability
.68
1.98
1
Wealth (reference=highest quintile)
lowest quintile
.21
1.52
.001
2nd
.08
1.33
.16
3rd
.01
1.25
.85
p
<.00
1
<.00
1
.12
.04
.66
.58
.03
.02
.35
.97
.03
.10
<.00
1
7
4th
BMI
-.08
1.15
-.11
.90
.16
<.00
1
Hypertension
Heart Problems
.36
1.44
<.00
1
<.00
1
-.02
.98
.02
.05
1.05
.002
.33
1.39
.04
.21
1.23
.01
Prior wave
<.00
-.67
.51
-.31
.73
memory score
1
Missing
<.00
.22
1.25
.01
.40
1.49
.40
1.49
.002
indicator 1
1
Missing
<.00
.72
2.06
indicator 2
.31
1.36
.08
1
Note. Blank cells mean the effects were not significant at .10 level in numerator or denominator
models.
1
Estimates were from logistic models of estimating a person’s probability of mortality based on the
person’s basic demographic variables and prior wave time-varying covariates, given that this person
was alive and participated in the survey last wave.
2
Estimates were from logistic models of estimating a person’s probability of being censored based on
the person’s basic demographic variables and prior wave time-varying covariates, given that this
person participated last wave and was still alive this wave.