| Application: | 22224, Prospective studies of ageing and age-related diseases |
| Title: | A Frailty Index for UK Biobank Participants |
| Size: | 520340 B |
| Archived: | 3 Nov 2020 |
| Stability: | Complete |
| Personal: | No individual-level data |
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Notes
Background: Frailty indices (FIs) measure variation in health between aging individuals. Researching FIs in resources with large-scale genetic and phenotypic data will provide insights into the causes and consequences of frailty. Thus, we aimed to develop an FI using UK Biobank data, a cohort study of 500,000 middle-aged and older adults.Methods: An FI was calculated using 49 self-reported questionnaire items on traits covering health, presence of diseases and disabilities, and mental well-being, according to standard protocol. We used multiple imputation to derive FI values for the entire eligible sample in the presence of missing item data (N = 500,336). To validate the measure, we assessed associations of the FI with age, sex, and risk of all-cause mortality (follow-up = 9.7 years) using linear and Cox proportional hazards regression models.
Results: Mean FI in the cohort was 0.125 (SD = 0.075), and there was a curvilinear trend toward higher values in older participants. FI values were also marginally higher on average in women than in men. In survival models, 10% higher baseline frailty (ie, a 0.1 FI increment) was associated with higher risk of death (hazard ratio = 1.65; 95% confidence interval: 1.62 1.68). Associations were stronger in younger participants than in older participants, and in men than in women (hazard ratios: 1.72 vs. 1.56, respectively).
Conclusions: The FI is a valid measure of frailty in UK Biobank. The cohort s data are open access for researchers to use, and we provide script for deriving this tool to facilitate future studies on frailty.
Application 22224
Prospective studies of ageing and age-related diseases
This research will identify metabolic, genetic and lifestyle measures that predict, and may determine, the onset of various age-related degenerative diseases. We will establish studies of participants within UK Biobank that have developed these diseases since the baseline assessment and examine how they differ in terms of their genetics, metabolism and lifestyle compared to similar participants who have aged free of these diseases in the same period. We will also investigate why some participants? physiology appears to age more rapidly than others across the same chronological time period, according to age-related general health measures in the cohort. Findings could shed new light on the aetiology of several age-related diseases, improve disease risk prediction and/or inform strategies for developing novel treatments. Gathering more information about how the ageing process underlies the development of many chronic, degenerative conditions will also aid efforts to extend both the lifespan and health-span (years spent in good health) of individuals. We will derive large ?case-cohort? studies of incident cases and characteristic-matched controls for several diseases and conditions of interest. We will then examine which factors measured at baseline are linked to future development of disease, avoiding some biases that affect conventional case-control studies. So-called ?biological ages? will be calculated for the full cohort from baseline health data on several variables, including blood pressure and anthropometry. Genetic data will be used both to understand the genetic contribution underlying diseases and traits, and to aid causal inference when considering how different exposures affect disease risk (?Mendelian randomisation?). Data on the full cohort are required for several analyses. Several case-cohort sub-sets of data will be derived from these.
| Lead investigator: | Dr Sara Hagg |
| Lead institution: | Karolinska Institutet |
1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 2742 | A Frailty Index for UK Biobank Participants | Williams DM et al. | 2019 | J Gerontol A Biol Sci Med Sci |
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