A frailty index counts deficits in health. These deficits were defined as symptoms, signs, disabilities and diseases [5 ]. All health deficits, including continuous, ordinal and binary variables, were taken from the PEP survey data dictionary. Restricted activity, disability in Activities Daily Living (ADL) and Instrumental ADL, impairments in general cognition and physical performance (e.g. impaired grip strength, impaired walking), co-morbidity, self-rated health, and depression/mood were evaluated.
Variables can be included in a frailty index if they satisfy the following 5 criteria:
1) The variables must be deficits associated with health status. Attributes such as graying hair, while age-related, are attributes and therefore not included. 2) A deficit's prevalence must generally increase with age, although some clearly age-related adverse conditions can decrease in prevalence at very advanced ages due to survivor effects. 3) Similarly, the chosen deficits must not saturate too early. For instance, age-related lens changes resulting in problems with accommodation (presbyopia) are nearly universal by age 55; in other words, as a variable, presbyopia saturates too early to be considered as a deficit here. 4) When considering the candidate deficits as a group, the deficits that make up a frailty index must cover a range of systems – if all variables were related to cognition, for example, the resulting index might well describe changes in cognition over time, but would be a cognitive impairment index [18 (link)] not a frailty index. 5) If a single frailty index is to be used serially on the same people, the items that make up the frailty index need to be the same from one iteration to the next [19 (link)]. The requirement to use the same items need not apply to comparisons between samples – i.e. samples that use difference frailty indexes appear to yield similar results [5 ].
Deficits should be added until there are at least 30–40 total deficits. There needs to be a minimum number of deficits. In general, the more variables that are included in a frailty index, the more precise estimates become. Similarly, estimates are unstable when the number of deficits is small – about 10 or less. Even so, an index with 30–40 variables has been shown to be sufficiently accurate for predicting adverse outcomes [6 (link),14 (link)]. Furthermore, a frailty index can be constructed using information that is readily available in most health surveys, and is clinically tractable – i.e. it uses an amount that would be gathered in many routine health assessments of older adults [5 ].
Variables can be included in a frailty index if they satisfy the following 5 criteria:
1) The variables must be deficits associated with health status. Attributes such as graying hair, while age-related, are attributes and therefore not included. 2) A deficit's prevalence must generally increase with age, although some clearly age-related adverse conditions can decrease in prevalence at very advanced ages due to survivor effects. 3) Similarly, the chosen deficits must not saturate too early. For instance, age-related lens changes resulting in problems with accommodation (presbyopia) are nearly universal by age 55; in other words, as a variable, presbyopia saturates too early to be considered as a deficit here. 4) When considering the candidate deficits as a group, the deficits that make up a frailty index must cover a range of systems – if all variables were related to cognition, for example, the resulting index might well describe changes in cognition over time, but would be a cognitive impairment index [18 (link)] not a frailty index. 5) If a single frailty index is to be used serially on the same people, the items that make up the frailty index need to be the same from one iteration to the next [19 (link)]. The requirement to use the same items need not apply to comparisons between samples – i.e. samples that use difference frailty indexes appear to yield similar results [5 ].
Deficits should be added until there are at least 30–40 total deficits. There needs to be a minimum number of deficits. In general, the more variables that are included in a frailty index, the more precise estimates become. Similarly, estimates are unstable when the number of deficits is small – about 10 or less. Even so, an index with 30–40 variables has been shown to be sufficiently accurate for predicting adverse outcomes [6 (link),14 (link)]. Furthermore, a frailty index can be constructed using information that is readily available in most health surveys, and is clinically tractable – i.e. it uses an amount that would be gathered in many routine health assessments of older adults [5 ].
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