Contact: Emiel Hoogendijk


Frailty is an age-related condition characterized by a decline in multiple physiological systems and increased vulnerability to stressors.1,2 Frailty is related to all kind of adverse health outcomes, such as falls, functional decline, hospital admissions and mortality. From the many operational definitions of frailty that exist,3 the most commonly used and well-validated definitions (e.g., the frailty phenotype and the frailty index) may be operationalized with LASA data.

Frailty phenotype (Fried 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.4 Several studies have been performed with LASA data using the frailty phenotype as predictor or outcome measure.5-8 The measures and cut-offs in LASA were identical or similar to those by Fried et al.4 For those measures not identical (gait speed, physical activity), the lowest quintile approach was used. Weight loss was present if a participant lost 5% or more body weight over a 3-year follow-up. 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. Exhaustion was measured using two items from the Center for Epidemiologic Studies Depression Scale (CES-D). 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. 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).9 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.

We have an SPSS syntax available to create the frailty phenotype in LASA (pdf).

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.10 In 2017, a LASA frailty index (LASA-FI) has been developed and validated.11

For the construction of the LASA-FI, a standard procedure described by Searle et al. was followed.12 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. See Hoogendijk et al. (2017) 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.13

An SPSS syntax to create the LASA frailty index is available here (pdf).

For an overview of the availability of the frailty index across LASA waves, click here (pdf).

Other frailty measures

Nine frailty markers: For studies that were conducted by Puts et al. in 200514-16, 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. 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.

Functional domains approach: In one LASA study, the functional domains approach was used.17 The functional domains approach sees frailty as a grouping of problems and losses of capability which make the individual more vulnerable to environmental challenge.18 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 frail 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 was constructed with LASA data. This is a multidimensional frailty instrument including physical, psychological and social markers.19 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.

Single markers: Sometimes, single markers of frailty have been used to identify frail older persons. Slow gait speed is one such example.20,21

Availability of frailty measures per wave


Frailty phenotype

-2Ma/Me3Ma/Me Ma/Me Ma/Me Ma/Me Ma/Me Ma/Me -2-2Ma/Me Ma/Me
Frailty index

Ma4Ma Ma Ma Ma Ma Ma Ma Ma Ma5Ma Ma
nine frailty markers

Ma/Me6Ma/Me7Ma/Me Ma/Me -6-6Ma/Me Ma/Me -6-6-6-6

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 and LASA MB, measured weight loss is not available at LASA 3B.
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.
4 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.
5 At LASA MB (migrant cohort), an adapted 30-item frailty index can be constructed. See the document on availability of the frailty index.
6 Peak flow is not available at waves 2B, F, 3B, MB, I, J.
7 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
J, K=under construction

Ma/Me= data collected in main interview and medical interview, respectively

Previous use in LASA

Frailty phenotype

Frailty index

Other frailty measures


  1. Clegg A, Young J, Iliffe S, Rikkert MO, Rockwood K. Frailty in elderly people. Lancet 2013;381(9868):752-62.
  2. Hoogendijk EO, Afilalo J, Ensrud KE, Kowal P, Onder G, Fried LP. Frailty: implications for clinical practice and public health. Lancet 2019;394(10206):1365-75.
  3. Dent E, Kowal P, Hoogendijk EO. Frailty measurement in research and clinical practice: A review. Eur J Intern Med 2016;31:3-10.
  4. Fried LP, Tangen CM, Walston J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001;56(3):M146-56.
  5. Hoogendijk EO, van Hout HP, Heymans MW, et al. Explaining the association between educational level and frailty in older adults: results from a 13-year longitudinal study in the Netherlands. Ann Epidemiol 2014;24(7):538-44.
  6. Hoogendijk EO, Suanet B, Dent E, Deeg DJ, Aartsen MJ. Adverse effects of frailty on social functioning in older adults: Results from the Longitudinal Aging Study Amsterdam. Maturitas 2016;83:45-50.
  7. Hoogendijk EO, Huisman M, van Ballegooijen AJ. The role of frailty in explaining the association between the metabolic syndrome and mortality in older adults. Exp Gerontol 2017;91:5-8.
  8. Stenholm S, Ferrucci L, Vahtera J, et al. Natural Course of Frailty Components in People Who Develop Frailty Syndrome: Evidence From Two Cohort Studies. J Gerontol A Biol Sci Med Sci 2019;74(5):667-74.
  9. Stel VS, Smit JH, Pluijm SM, Visser M, Deeg DJ, Lips P. Comparison of the LASA Physical Activity Questionnaire with a 7-day diary and pedometer. J Clin Epidemiol 2004;57(3):252-8.
  10. Rockwood K, Mitnitski A. Frailty in relation to the accumulation of deficits. J Gerontol A Biol Sci Med Sci 2007;62(7):722-7.
  11. Hoogendijk EO, Theou O, Rockwood K, Onwuteaka-Philipsen BD, Deeg DJH, Huisman M. Development and validation of a frailty index in the Longitudinal Aging Study Amsterdam. Aging Clin Exp Res 2017;29(5):927-33.
  12. Searle SD, Mitnitski A, Gahbauer EA, Gill TM, Rockwood K. A standard procedure for creating a frailty index. BMC Geriatr 2008;8:24.
  13. Rockwood K, Andrew M, Mitnitski A. A comparison of two approaches to measuring frailty in elderly people. J Gerontol A Biol Sci Med Sci 2007;62(7):738-43.
  14. Puts MT, Lips P, Deeg DJ. Sex differences in the risk of frailty for mortality independent of disability and chronic diseases. J Am Geriatr Soc 2005;53(1):40-7.
  15. Puts MT, Lips P, Deeg DJ. Static and dynamic measures of frailty predicted decline in performance-based and self-reported physical functioning. J Clin Epidemiol 2005;58(11):1188-98.
  16. Puts MT, Visser M, Twisk JW, Deeg DJ, Lips P. Endocrine and inflammatory markers as predictors of frailty. Clin Endocrinol (Oxf) 2005;63(4):403-11.
  17. Hoogendijk EO, Heymans MW, Deeg DJH, Huisman M. Socioeconomic Inequalities in Frailty among Older Adults: Results from a 10-Year Longitudinal Study in the Netherlands. Gerontology 2018;64(2):157-64.
  18. Strawbridge WJ, Shema SJ, Balfour JL, Higby HR, Kaplan GA. Antecedents of frailty over three decades in an older cohort. J Gerontol B Psychol Sci Soc Sci 1998;53(1):S9-16.
  19. Gobbens RJ, van Assen MA, Luijkx KG, Wijnen-Sponselee MT, Schols JM. The Tilburg Frailty Indicator: psychometric properties. J Am Med Dir Assoc 2010;11(5):344-55.
  20. Sanders JB, Comijs HC, Bremmer MA, Deeg DJ, Beekman AT. 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 2015;30(7):751-7.
  21. Hoogendijk EO, Rijnhart JJM, Skoog J, et al. Gait speed as predictor of transition into cognitive impairment: Findings from three longitudinal studies on aging. Exp Gerontol 2020;129:110783.

Date of last update: April, 2020