Table 3 Criterion validity results; the predictive ability of the frailty index for adverse health outcomes

Armstrong et al. [21]

Mortality: 1676

Cox proportional hazards regression

Age, gender

FI: HR = 1.93

1.79-2.08

Most frail (15%) vs. least frail (60%) group

Institutionalization: 4550

(EFS: HR = 2.49)

(2.32-2.68)

(CHESS: HR = 2.32)

(2.15-2.51)

Drubbel et al. [22]

Mortality/ED visits/institutionalization/out-of-hours GP surgery visits: 508

Cox proportional hazards regression

Age, gender, consultation gap

HR = 1.166

1.129-1.210

Per deficit increase in FI score

Fang et al. [32]

Recurrent falls: 109

Logistic regression

Age, gender, education

OR = 1.54

1.34-1.76

Per one-unit increment in FI score

Recurrent fractures: 174

Logistic regression

Age, gender, education

OR = 1.07

0.94-1.22

Per one-unitincrement in FI score

Mortality: 1101

Cox proportional hazards regression

Age, gender, education, falls, fractures

HR = 1.29

1.25-1.33

Per one-unit increment FI score

García-González et al. [33]

Mortality: 279

Cox proportional hazards regression

Age, gender

HR = 6.45

4.10-10.14

Most frail (FI 0.35-0.65) vs. least frail group (0.00-0.07)

Gu et al. [23]

Mortality: 5,753

Weibull proportional hazards regression

Age, ethnicity, urban–rural residence, SES, family/social connection and support, health practices

Men (65–79):

Most frail vs. least frail quartile

HR = 4.56

0.96

Women (65–79):

HR = 3.84

1.01

Hogan et al. [37]

Mortality: 170

Logistic regression

Age, gender, co-morbidity

RR = 2.35

1.56-3.54

All analyses: most frail (FI > 0.30) vs. least frail group (FI < 0.20)

≥ 1 hospitalization: 424

Logistic regression

Age, gender, co-morbidity

RR = 1.28

1.04-1.57

Institutionalization: 204

Logistic regression

Age, gender, co-morbidity

RR = 3.30

2.29-4.76

Kulminski et al. [24]

Mortality: 421

Cox proportional hazards regression

Age, gender, FP

FI: RR = 1.035

1.026-1.045

(FP: RR = 1.014)

(1.009-1.019)

Per 1% increment in FI score (or FP)

Kulminski et al. [25]

Mortality: 2146

Cox proportional hazards regression

Age, gender

RR = 1.029

1.001

Per 1% increment in FI score

Lucicesare et al. [26]

Mortality: 147

Cox proportional hazards regression

Age, gender, CSBA score

FI: HR = 5.26

1.05-26.42

?

(CSBA score: HR = 1.52)

(1.28-1.81)

Mitnitski et al. [34]

Mortality (%/yr) 3.7-20.6

Cox proportional hazards regression

Age, gender

CSHA-s: HR = 1.031

0.003

Per deficit increase in FI score

CSHA-c: HR = 1.054

0.007

CSHA-i: HR = 1.046

0.009

SOPSA: HR =1.079

0.022

NHANES: HR = 1.011

0.003

Searle et al. [19]

Mortality: ?

Cox proportional hazards regression

Age, gender

HR = 1.03

1.02-1.04

Per 0.01 increase in FI score

Shi et al. [35]

Mortality: 1,155

Cox proportional hazards regression

Age, gender

HR = 1.13

1.09-1.47

Per deficit increase in FI score

Song et al. [29]

Mortality: 1,208

Cox proportional hazards regression

Age, gender

FI: RR = 1.57

1.41-1.74

Per FI level (FI ≤ 0.08; FI between 0.08-0.25; FI ≥ 0.25).

Theou et al. [36]

Mortality: 1002

Cox proportional hazards regression

Age, gender, nr. of ADL disabilities, nr. of chronic diseases

FI 1: HR = 1.11

1.06-1.17

Per 0.1 increase in FI score

Woo et al. [31]

Change in ADL score 0–3 yrs^a

Linear regression

Age, gender, ADL score at baseline

B = −4.99

−7.68 - −2.30

Per 1.0 increase in FI score

Change in mental score 0-3 yrs^a

Linear regression

Age, gender, mental score at baseline

B = −2.23

−4.11 - −0.35

Per 1.0 increase in FI score

Change in hospital days 0–3 yrs^a

Linear regression

Age, gender, hospital days at baseline

B = 45.74

28.16 – 63.33

Per 1.0 increase in FI score

New diseases at three yrs^a

Ordinal logistic regression

-

For FI = 0.00, predicted probability ≥ 1 new disease = 17.4%

Predicted probabilities for new diseases at 3 years

For FI = 0.50, predicted probability ≥ 1 new disease = 52.2%