Frailty


Contact: Emiel Hoogendijk

Background
Frailty is a geriatric condition characterized by an increased vulnerability to external stressors, caused by the loss of reserve capacity in one or more domains of functioning (Clegg et al. 2013; Fried et al. 2001; Morley et al. 2013). The loss of reserve capacity may be only physical or in multiple domains, including the cognitive and psychosocial domain. Frailty is related to all kind of adverse health outcomes, such as falls, functional decline, hospital admissions and mortality (Clegg et al. 2013; Fried et al. 2001). From the many operational definitions of frailty that exist (Dent et al. 2016), the most commonly used and well-validated definitions (e.g., the frailty phenotype and the frailty index) may be operationalized with LASA data.

Measurement of frailty in LASA
Different approaches have been taken to define frailty by researchers who used LASA data, including physical frailty and broader frailty definitions which also contain cognitive and psychosocial markers (Hoogendijk et al. 2016a). The following frailty measures have been operationalized so far:

1. Frailty phenotype (Fried`s frailty criteria)
A well-known operational definition of physical frailty is the frailty phenotype (also known as Fried`s frailty criteria) based on the presence of at least three of the following five criteria: weight loss, weak grip strength, exhaustion, slow gait speed, and low physical activity (Fried et al. 2001). Several studies have been performed with LASA data using the frailty phenotype as predictor or outcome measure (Hoogendijk et al. 2016b; Hoogendijk et al. 2014a; Hoogendijk et al. 2014b). The measures and cut-offs in LASA were identical or similar to those by Fried et al. (Fried et al. 2001). For those measures not identical (gait speed, physical activity), the lowest quintile approach was used (Saum et al. 2012). Weight loss was present if a participant lost 5% or more body weight over a 3-year follow-up (Gruenewald et al. 2009). Body weight was measured with respondents wearing only underclothes using a calibrated bathroom scale. Grip strength was assessed with a handheld dynamometer (the sum of the highest values of two measurements on each hand). Original cut-off points stratified by sex and body mass index were applied to indicate weak grip strength (Fried et al. 2001). Exhaustion was measured using two items from the Center for Epidemiologic Studies Depression Scale (CES-D) (Radloff 1977). The exhaustion criterion was considered present if a participant answered “often” or “most of the time” to the following two statements: “In the last week I felt that everything I did was an effort” and “In the last week I could not get going.” Gait speed was assessed by recording the time taken (in seconds) to walk 3 m, turn around, then walk the 3 m back as quickly as possible (Sanders et al. 2012). Slow gait was defined by the lowest quintile, stratified by sex and height. Finally, physical activity was assessed using the LASA Physical Activity Questionnaire (LAPAQ) (Stel et al. 2004). Low physical activity was defined by the lowest quintile of average time spent on physical activities per day during two weeks before the interview. Respondents are considered to be frail if three out of five Fried's criteria are present (Fried et al. 2001).

An SPSS syntax to create the frailty phenotype is available here (PDF).

The frailty phenotype may be constructed at the following LASA waves1:

 

B2

C

D

E

2B*

F

G

H

3B*

MB*

I*

Frailty phenotype

 -   

Ma/Me3

Ma/Me

Ma/Me

Ma/Me

Ma/Me

Ma/Me

Ma/Me

Ma/Me

 -

Ma/Me

1 More information about the LASA data collection waves is available here.

2 Grip strength and measured weight loss are not available at LASA B.

3 At LASA C, the frailty phenotype can only be constructed in people aged 65 years and over, because at this measurement wave the LASA medical interview was performed only in people ≥65 years.

* 2B=baseline second cohort;
   3B=baseline third cohort;
   MB=migrants: baseline first cohort (Under Construction);
   I=Under Construction

Ma/Me= data was collected in main interview and medical interview.

2. Frailty Index (deficit accumulation approach)
Another widely used frailty instrument is the frailty index, also known as the deficit accumulation approach. It involves the accumulation of diseases, symptoms, signs, disabilities or any deficiency in health with age, based on the idea that a greater number of health deficits indicate higher frailty (Rockwood and Mitnitski 2007). In 2016, a LASA frailty index (LASA-FI) has been developed and validated (Hoogendijk et al. 2016c).

For the construction of the LASA-FI a standard procedure described by Searle et al. was followed (Searle et al. 2008). Health deficits were included in the LASA–FI, if they (a) were biologically meaningful in representing several organ systems, and (b) were accumulating with age, and not becoming too prevalent at some younger age, and (c) did not contain too many missing values at item level (<5%), and (d) were available in the main interview of LASA at different measurement waves (to have the opportunity to study changes in LASA–FI score in future research). A 32-item frailty index was constructed. Variables included self-reported chronic conditions: cardiac disease, peripheral arterial disease, stroke, diabetes, lung disease, cancer, arthritis, hypertension, a maximum of two other diseases and incontinence; functional limitations: the ability to walk 15 stairs without resting, to (un)dress self, to sit and stand up from a chair, to cut own toenails, to walk outside for 5 min without stopping and to use public transportation (van Sonsbeek 1988); self-rated health: the questions “How is your health in general?” and “How is your health compared to other people of your age?”; six items from the CES-D depression scale: the extent to which people feel depressed, feel everything is an effort, feel happy, feel lonely, enjoy life and could not get going; physical activity: based on the LASA physical activity questionnaire (LAPAQ) (Stel et al. 2004); self-reported memory complaints; four items from the Mini-Mental State Examination (MMSE): orientation in time, orientation in place, attention and recall (Folstein et al. 1975); and physical performance measured by gait speed. See Hoogendijk et al. (Hoogendijk et al. 2016c) for an overview of all included variables and cutoff values. All deficits were scored between 0 and 1, where 0 indicates the absence of the deficit and 1 the presence of a deficit.

A frailty score was calculated for each participant by dividing the sum of the health deficit scores by the total number of health deficits measured. This resulted in a score between 0 (no deficits present) and 1 (all deficits present). For example, if a person has six points out of 32, the LASA–FI score was 6/32 = 0.19. The LASA–FI may be used as a continuous score, or as a dichotomous variable by applying a generally used cutoff point of ≥0.25 to indicate frailty (Rockwood et al. 2007).

An SPSS syntax to create the LASA Frailty Index is available (PDF).

The frailty index may be constructed at the following LASA waves1:

 

B

C

D

E

2B*

F

G

H

3B*

MB*

I*

Frailty Index

Ma2

Ma

Ma

Ma

Ma

Ma

Ma

Ma

Ma

Ma

Ma

1 More information about the LASA data collection waves is available here.

2 At LASA B, only a 31-item frailty index can be constructed, because hypertension was not measured separately. It was part of the category “other diseases” at LASA B. From LASA C onwards, hypertension was measured in a separate question.

* 2B=baseline second cohort;
   3B=baseline third cohort;
   MB=migrants: baseline first cohort (Under Construction);
   I=Under Construction

Ma=data was collected in main interview.

3. Nine frailty markers (Puts et al.)
For studies that were conducted by Puts et al. (Puts et al. 2005a; Puts et al. 2005b; Puts et al. 2005c), nine frailty markers were selected on the basis of the then existing literature on frailty. These markers included: low body weight, low peak expiratory flow, poor cognition, vision and hearing problems, incontinence, low mastery, depressive symptoms and low physical activity. The items on body weight, physical activity and depressive symptoms were selected because they are part of the validated model of the frailty phenotype (Fried et al. 2001). Whereas Fried et al. only included 2 items of the CES-D on exhaustion into their frailty model, the full CES-D was included in the model of Puts et al. in order to incorporate an extra psychological marker of frailty. Psychological frailty was further represented in the Puts et al. model by incorporating a measure of mastery. Peak expiratory flow was included as a frailty marker in the Puts et al. model as a surrogate of muscle weakness instead of the grip strength measure that has been used by Fried et al., because information on grip strength was not available in the LASA baseline measurement. The measure of incontinence was included in the model of Puts because it was shown to be a predictor of disability and mortality in previous research that included it as a frailty marker (Miles et al. 2001; Rockwood et al. 1999). Measures of vision and hearing were included, following the frailty model that was proposed by Strawbridge et al. (Strawbridge et al. 1998); and cognitive functioning was included following the approach of Rockwood et al. Frailty is defined as present when participants have scores above the relevant cut-off on three or more of the nine frailty markers in the model of Puts.

The nine frailty markers may be constructed at the following LASA waves1:

 

B2

C

D

E

2B2*

F

G

H

3B2*

MB2*

I2*

Nine frailty markers

Ma/Me 

Ma/Me3

Ma/Me

Ma/Me

-

-

Ma/Me

Ma/Me

-

 -

-

1 More information about the LASA data collection waves is available here.

2 Peak flow is not available at waves 2B, F, 3B, MB and I.

3 At LASA C, indicators can only be constructed for those aged ≥65 years at the time, because data are partly derived from the LASA medical interview, which was only performed in those aged 65 years and over at LASA C.

* 2B=baseline second cohort;
   3B=baseline third cohort;
   MB=migrants: baseline first cohort (Under Construction);
   I=Under Construction

Ma/Me= data was collected in main interview and medical interview.

4. Other frailty definitions

- Functional domains approach

In one LASA study, the functional domains approach was used. The functional domains approach sees frailty as a grouping of problems and losses of capability which make the individual more vulnerable to environmental challenge (Strawbridge et al. 1998). These problems and losses are postulated to be multi-systemic and encompass deficiencies in four domains: physical, nutritive, cognitive, and sensory. Our measure indicated for each measurement point who was frail and who was not on the basis of several specific frailty markers. The measure included the following markers: physical activity, exhaustion, and grip strength (physical domain), Body Mass Index (nutritive domain), cognitive functioning (cognitive domain), vision and hearing problems (sensory domain). Respondents were considered frail if they had frailty markers present in two or more domains.

- Tilburg Frailty Indicator

In 2011, for a report of the Netherlands Institute of Social Research (SCP), the Tilburg Frailty Indicator (Gobbens et al. 2010) was constructed with LASA data. This is a multidimensional frailty instrument including physical, psychological and social markers. The TFI was used to describe trajectories in frailty and subdomains of frailty: physical, social and psychological frailty. See for more information the SCP report (van Campen 2011).

- Single markers

Sometimes, single markers of frailty have been used to identify frail older persons. Slow gait speed is one such example (Sanders et al. 2015).

Previous uses in LASA

  • Hoogendijk EO, Suanet B, Dent E, Deeg DJ, Aartsen MJ (2016b) Adverse effects of frailty on social functioning in older adults: Results from the Longitudinal Aging Study Amsterdam. Maturitas 83:45-50
  • doi:10.1016/j.maturitas.2015.09.002
  • Hoogendijk EO, Theou O, Rockwood K, Onwuteaka-Philipsen BD, Deeg DJ, Huisman M (2016c) Development and validation of a frailty index in the Longitudinal Aging Study Amsterdam. Aging Clin Exp Res
  • doi:10.1007/s40520-016-0689-0
  • Hoogendijk EO, et al. (2014a) Explaining the association between educational level and frailty in older adults: results from a 13-year longitudinal study in the Netherlands. Ann Epidemiol 24(7):538-44 e2
  • doi:10.1016/j.annepidem.2014.05.002
  • Hoogendijk EO, et al. (2014b) Do psychosocial resources modify the effects of frailty on functional decline and mortality? J Psychosom Res 77(6):547-51 doi:10.1016/j.jpsychores.2014.09.017
  • Hoogendijk EO, Huisman M, van Ballegooijen AJ (2017) The role of frailty in explaining the association between the metabolic syndrome and mortality in older adults. Exp Gerontol 91:5-8
  • doi: 10.1016/j.exger.2017.02.007
  • Puts MT, Lips P, Deeg DJ (2005a) Sex differences in the risk of frailty for mortality independent of disability and chronic diseases. J Am Geriatr Soc 53(1):40-7
    doi:10.1111/j.1532-5415.2005.53008.x
  • Puts MT, Lips P, Deeg DJ (2005b) Static and dynamic measures of frailty predicted decline in performance-based and self-reported physical functioning. J Clin Epidemiol 58(11):1188-98 doi:10.1016/j.jclinepi.2005.03.008
  • Puts MT, Visser M, Twisk JW, Deeg DJ, Lips P (2005c) Endocrine and inflammatory markers as predictors of frailty. Clin Endocrinol (Oxf) 63(4):403-11
  • doi:10.1111/j.1365-2265.2005.02355.x
  • Sanders JB, Comijs HC, Bremmer MA, Deeg DJ, Beekman AT (2015) A 13-year prospective cohort study on the effects of aging and frailty on the depression-pain relationship in older adults. Int J Geriatr Psychiatry 30(7):751-7
  • doi:10.1002/gps.4224.
  • Sourial N, et al. (2012) Contribution of frailty markers in explaining differences among individuals in five samples of older persons. J Gerontol A Biol Sci Med Sci 67(11):1197-204 doi:10.1093/gerona/gls084.
  • van Campen Cr (2011) Kwetsbare ouderen (Frail older persons in the Netherlands) (in Dutch). Sociaal en Cultureel Plan bureau: Den Haag.
  • de Vries OJ, Peeters GM, Lips P, Deeg DJ (2013) Does frailty predict increased risk of falls and fractures? A prospective population-based study. Osteoporos Int 24(9):2397-403 doi:10.1007/s00198-013-2303-z

References

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  9. Hoogendijk EO, Theou O, Rockwood K, Onwuteaka-Philipsen BD, Deeg DJ, Huisman M (2016c) Development and validation of a frailty index in the Longitudinal Aging Study Amsterdam. Aging Clin Exp Res doi:10.1007/s40520-016-0689-0
  10. Hoogendijk EO, et al. (2014a) Explaining the association between educational level and frailty in older adults: results from a 13-year longitudinal study in the Netherlands. Ann Epidemiol 24(7):538-44 e2 doi:10.1016/j.annepidem.2014.05.002
  11. Hoogendijk EO, et al. (2014b) Do psychosocial resources modify the effects of frailty on functional decline and mortality? J Psychosom Res 77(6):547-51 doi:10.1016/j.jpsychores.2014.09.017
  12. Miles TP, Palmer RF, Espino DV, Mouton CP, Lichtenstein MJ, Markides KS (2001) New-onset incontinence and markers of frailty: data from the Hispanic Established Populations for Epidemiologic Studies of the Elderly. J Gerontol A Biol Sci Med Sci 56(1):M19-24
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  15. Puts MT, Lips P, Deeg DJ (2005b) Static and dynamic measures of frailty predicted decline in performance-based and self-reported physical functioning. J Clin Epidemiol 58(11):1188-98 doi:10.1016/j.jclinepi.2005.03.008
  16. Puts MT, Visser M, Twisk JW, Deeg DJ, Lips P (2005c) Endocrine and inflammatory markers as predictors of frailty. Clin Endocrinol (Oxf) 63(4):403-11 doi:10.1111/j.1365-2265.2005.02355.x
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  26. Stel VS, Smit JH, Pluijm SM, Visser M, Deeg DJ, Lips P (2004) Comparison of the LASA Physical Activity Questionnaire with a 7-day diary and pedometer. J Clin Epidemiol 57(3):252-8 doi:10.1016/j.jclinepi.2003.07.008
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