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Frailty in community-dwelling older adults and associations with admission to long-term care

Category(s): Health
Status: Active
Principal: Sandra Magalhaes
Project Number: P0046
Year Approved: 2020

Project Description

As the population of New Brunswick (NB) ages, a growing number of New Brunswickers are at risk of experiencing frailty. Associated with, but not directly tied to the aging process, frailty is a state of vulnerability in which individuals demonstrate decreased resilience in the face of stressors, and thus even minor changes in life circumstances can result in major (negative) changes in health (Junius-Walker et al., 2018). An increasing rate of frailty means more older adults will experience a decreased quality of life, which will also have detrimental effects on both informal caregivers and the health care system. With frailty comes decreased functional status, increased risk of comorbidity, hospitalization, institutionalization in long-term care (LTC) and premature mortality (Clegg et al., 2013; Junius-Walker et al., 2018). 

The epidemiology of frailty in NB is a salient topic in need of more research. One study placed the prevalence of frailty among community dwelling older adults (greater than 65 years) in NB at 24-30%, noting that this was higher than most other provinces (Hoover et al., 2013). In consultation with stakeholders from the Department of Health, Horizon Health, the New Brunswick Nursing Home Association and York Care Centre/ Centre for Innovation and Research in Aging, we identified frailty in NB as a priority research area. 

These consultations resulted in the development of research questions focused on characterizing prevalence of frailty among community dwelling older adults and in those admitted to LTC facilities in NB. Population-based administrative data available through the NB-IRDT represents one avenue for developing a better understanding of frailty in NB. 

The first step is identifying a valid and reliable measure of frailty. Estimating the prevalence of frailty among community dwelling older adults can be difficult. This difficulty arises in part due to the nature of frailty as a latent variable with unclear operationalization. Researchers have yet to achieve a consensus on how to measure 
frailty, though two approaches have emerged: (i) a phenotypic approach and (ii) an approach based on cumulative deficits. Researchers have developed frailty indices using administrative data from acute care. 

Using NB-IRDT Discharge abstract Database (DAD) data, we will replicate two validated frailty scores: the Hospital Frailty Risk Score (HFRS) and Frailty Syndrome Model (FSS) (Eckart et al., 2019; Gilbert et al., 2018; Soong et al., 2015). The availability of linked administrative and clinical data enables us to evaluate the concurrent and predictive validity of both scores. We will link the DAD to other NB-IRDT platform data (i.e. Physician billing, York Care inter-RAI (YCRAI), and the Social Development LTC Database) and external data from Horizon Health: the Health and Aging database (HaAD) and Memory Clinic Data (MCD). We will evaluate the validity of the two frailty scores in three health care settings: a memory care clinic, a chronic care facility and a long term care facility. Concurrent validity within these settings will be tested using existing frailty measures: the Clinical frailty scale (K. Rockwood, 2005), and the interRAI CHESS score (Change in decision-making, Change in ADL status, and End-stage disease) (Hirdes et al., 2003). The Clinical Frailty Scale is one of the most widely used measures of frailty and has been found to be a valid measure of frailty in several populations (Clegg et al., 2013; K. Rockwood, 2005). The CHESS score has shown predictive validity for premature mortality similar to two frailty indexes (Armstrong et al., 2010): Rockwood’s Frailty index (Kenneth Rockwood & Mitnitski, 2007), and the Edmonton Frailty score (Rolfson et al., 2006). We will use the validated frailty measures derived to understand the level of frailty among older adults admitted to LTC. 

Read the report:


  • Armstrong, J. J., Stolee, P., Hirdes, J. P., & Poss, J. W. (2010). Examining three frailty conceptualizations in their ability to predict negative outcomes for home-care clients. Age and Ageing, 39(6), 755–758.
  • Clegg, A., Young, J., Iliffe, S., Rikkert, M. O., & Rockwood, K. (2013). Frailty in elderly people. The Lancet, 381(9868), 752–762.
  • Eckart, A., Hauser, S. I., Haubitz, S., Struja, T., Kutz, A., Koch, D., Neeser, O., Meier, M. A., Mueller, B., & Schuetz, P. (2019). Validation of the hospital frailty risk score in a tertiary care hospital in Switzerland: Results of a prospective, observational study. BMJ Open, 9(1), e026923.
  • Gilbert, T., Neuburger, J., Kraindler, J., Keeble, E., Smith, P., Ariti, C., Arora, S., Street, A., Parker, S., Roberts, H. C., Bardsley, M., & Conroy, S. (2018). Development and validation of a Hospital Frailty Risk Score focusing on older people in acute care settings using electronic hospital records: An observational study. Lancet (London, England), 391(10132), 1775–1782.
  •  Hirdes, J. P., Frijters, D. H., & Teare, G. F. (2003). The MDS-CHESS Scale: A New Measure to Predict Mortality in Institutionalized Older People. Journal of the American Geriatrics Society, 51(1), 96–100.
  • Hoover, M., Rotermann, M., Sanmartin, C., & Bernier, J. (2013). Validation of an index to estimate the prevalence of frailty among community-dwelling seniors. Health Reports, 24(9), 10.
  • Junius-Walker, U., Onder, G., Soleymani, D., Wiese, B., Albaina, O., Bernabei, R., & Marzetti, E. (2018). The essence of frailty: A systematic review and qualitative synthesis on frailty concepts anddefinitions. European Journal of Internal Medicine, 56, 3–10.
  • Rockwood, K. (2005). A global clinical measure of fitness and frailty in elderly people. Canadian Medical Association Journal, 173(5), 489–495. 
  •  Rockwood, Kenneth, & Mitnitski, A. (2007). Frailty in Relation to the Accumulation of Deficits. The Journals of Gerontology: Series A, 62(7), 722–727.
  • Rolfson, D. B., Majumdar, S. R., Tsuyuki, R. T., Tahir, A., & Rockwood, K. (2006). Validity and reliability of the Edmonton Frail Scale. Age and Ageing, 35(5), 526–529.
  • Soong, J., Poots, A. J., Scott, S., Donald, K., & Bell, D. (2015). Developing and validating a risk prediction model for acute care based on frailty syndromes. BMJ Open, 5(10), e008457.