Among older couples, frailty in one partner may impact frailty in the other, setting the stage for potentially unmanageable and compromised caregiving capacity on the couple as they both become frail. In our research we are examining the co-evolution of frailty in community-dwelling older couples in New Brunswick. Using administrative health data, we identified community-dwelling older couples over age 65 living in NB between April 1, 2017 and March 31, 2019. A validated frailty algorithm, the Hospital Frailty Risk Score was used to quantify risk of frailty into four categories (no, low, intermediate, and high frailty risk) for all hospitalized seniors. Relationships between couples’ frailty was examined using regression models, adjusting for age. We identified over 37,000 community-dwelling older couples, half of which were hospitalized over the 2-year study period. In 23% the male partner was hospitalized, in 18% the female partner was and in 10% both were hospitalized. Among those that both partners were hospitalized, 11% of males and 10% of females were categorized as high or intermediate frailty. Age was positively associated with frailty. Males were, on average, older than females in each frailty category. Our research shows an increase likelihood of having high or intermediate frailty in one partner, when the other also had a high or intermediate frailty risk. Our results suggest that frailty in one partner has a significant impact on frailty in their spouse, consistent with findings from emerging evidence. If one is frail, their partner is more likely to be frail. While aging in place is a key priority, risk of concordant frailty may create additional burden on couples without additional supports in place.

1. Concordance of Frailty among Community-Dwelling Older
Couples: An Administrative Data Study
May 25, 2022
Department of Health Knowledge Translation Event
Presenter: Sandra Magalhaes and Molly Gallibois

2. Background

3. Aging is inevitable,
…..but is aging frail?

4. What is Frailty?

5. World Health Organization Definition
“….a clinically recognizable state in which
the ability of older people to cope with
everyday or acute stressors is compromised
by an increased vulnerability brought by
age-associated declines in physiological
reserve and function across multiple organ
systems.”
5

6. Clegg et al. Lancet 2013; 381: 752–62
Model of Frailty

7. 7
BIG wave is coming….

8. 8
Policies/programs should
focus on:
 Prevention of decline
in intrinsic capacity
 Maintenance of
functional ability

9. Measuring Frailty
• Problematic…..decades and decades of research
• Latent construct with unclear operationalization
• No consensus on how to measure frailty
• Two approaches have emerged:
i. phenotypic
ii. cumulative deficits
9

10. Measuring Frailty
10
Phenotypic (Fried Model)
Weight loss
Self-reported exhaustion
Low energy expenditure
Slow gait speed
Weak grip strength
Cumulative Deficits (Searle Model)
Associated with health status
Prevalence increase with age
Must not saturate too early
Cover range of biological systems
Consistent over time

11. Frailty in Administrative Data
• Limited to cumulative deficits approach
• Two validated algorithms
• Hospital Frailty Risk Score (HFRS)
• CIHI Hospital Frailty Risk Measure (HFRM)
• Algorithms search for specific ICD-10 codes in administrative data over a 2-year period
• Provide a frailty score and classification of frailty risk
• no, low, intermediate, high
11

12. Prevalence of Frailty in NB
• Prevalence among hospitalized older adults in NB was estimated using the HFRS
• Administrative hospital claims data were searched to identify hospitalized older
adults aged 65 or older between April 1, 2017, and March 31, 2019
• 55,675 older adults identified
• 52% females
• Prevalence of high/intermediate frailty was 21%
• Upcoming open access publication in the Canadian Geriatrics Journal
12

13. Prevalence of Frailty in NB by Age
13
Frailty is defined as those with high or intermediate frailty risk

14. Prevalence of Frailty in NB by Sex
14
Females Males

15. Objective:
To examine concordance in frailty among
community-dwelling older couples

16. Methods

17. Methods
• Cross-sectional study with 37,000 community-dwelling older couples over age 65 years
• Administrative data access at the New Brunswick Institute for Research, Data and Training
• Citizen Medicare Registry and Discharge Abstract Database (DAD)
• Between April 1, 2017 and March 31, 2019
• Married couples living in the community were identified using Citizen Medicare Registry
• Validated claims-based HFRS was estimated using ICD-10 codes in DAD
• Continuous score stratified into four risk categories
• Linear and logistic regression, adjusted for age, compared frailty in one spouse to frailty in
the other spouse
17

18. Results

19. Average Age by Frailty Risk and Sex
F M F M F M F M F M

20. Hospitalizations by Frailty Risk and Sex
20
F M
F M F M F M

21. Linear regression - Frailty Risk Score in Hospitalized Older Couples
Linear regression, adjusting for age of both partners, suggested a slight increase (0.08) increase in
an individuals HFRS when the HFRS of their partner increases by 1

22. Concordance of Frailty Risk Categories
No Low Inter High
Male Partner’s HFRS Category
Not hosp.

23. Logistic Regression - Frailty Risk Categories in Hospitalized Couples
Logistic regression, adjusting for age of both partners, demonstrated a 23% increased risk of
intermediate or high frailty risk in one partner if the other is also categorized as intermediate or high
frailty risk (OR=1.23, 95%CI: 1.08-1.38)
No Low Inter High
Male Partner
6%

24. Conclusions

25. Summary
• Majority of couples over age 65 were not hospitalized over two year study period
• Male partners were older and had more hospitalizations than female partners, in
every frailty category
• Frailty risk categories were more informative than frailty risk scores to quantify
concordance among hospitalized couples
• Regression modelling suggest concordance in cross-sectional frailty among
hospitalized older couples
25

26. Next Steps
• Develop and validate a GNB/NB-IRDT frailty index
• 15-year longitudinal study design to examine co-evolution of frailty
• Characterize burden at system and individual level
• Impact of programs and services in delaying frailty progression
• Long-term care, extramural program, others?
• Relationships with admissions to nursing home
26

27. Potential Impact
• Several audiences - policy makers, health systems administrators and academics
• Improved understanding of frailty in community dwelling older couples living in
NB will help support aging in place
• Resources should be allocated appropriately to prevent decline in intrinsic
capacity and encourage maintenance of functional ability
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28. Thank you!
Comments/Questions for me?
Questions for you:
Would a better understanding of frailty in NB help your work, in what way?
Are there programs/services you’re aware of that support frail community-dwelling
seniors in NB?
UNB.ca/nbirdt