Screening for intrinsic capacity and frailty in the primary care population with multimorbidity using the Integrated Care for Older People Screening Tool and two different frailty measures – the Frailty Phenotype and Clinical Frailty Scale: a cross-sectional study

Screening for intrinsic capacity and frailty in the primary care population with multimorbidity using the Integrated Care for Older People Screening Tool and two different frailty measures – the Frailty Phenotype and Clinical Frailty Scale: a cross-sectional study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Screening for intrinsic capacity and frailty in the primary care population with multimorbidity using the Integrated Care for Older People Screening Tool and two different frailty measures – the Frailty Phenotype and Clinical Frailty Scale: a cross-sectional study Sai Zhen Sim, Xinyao Ng, Poay Sian Sabrina Lee, Hui Li Koh, Shu Yun Tan, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4524600/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 19 Nov, 2025 Read the published version in BMC Geriatrics → Version 1 posted 4 You are reading this latest preprint version Abstract Background Intrinsic capacity (IC) co-exists with frailty and multimorbidity in primary care. To improve health outcomes, guidelines recommend IC and frailty screening and it is thought that IC screening can support the concurrent and subsequent evaluation of frailty. For feasible implementation of such screening, it is important to understand the association between IC and frailty, including the discriminative ability of IC against frailty in a primary care population with multimorbidity. Method A cross-sectional study was conducted across three primary care clinics. Participants were elderly and had the multimorbidity triad of diabetes mellitus, hypertension, and hyperlipidemia. Data collected included sociodemographic variables, IC (Integrated Care Older People Screening Tool), social vulnerability, chronic conditions, functional disability, modified Frailty Phenotype (mFP), and Clinical Frailty Scale (CFS). Logistic regression was used to assess the association between IC and the two measurements of frailty while area under the curve of the receiver operating characteristic (AUC-ROC) was used to assess the discriminative ability of IC against frailty. Results 411 participants were included. Mean age was 69.9 (± 6.2) years and almost all (98.0%) the participants had reduced IC on screening, of which the most affected domains were the sensory (90.0%), locomotion (44.0%), and cognition (30.9%) domains. 12.4% were mFP frail while 7.4% were CFS frail. While higher IC was associated with reduced odds of frailty regardless of the frailty measure (p ≤ 0.001), the IC domains associated with frailty depended on the frailty measure used. Vitality and locomotion were associated with being mFP frail while the sensory and locomotion domains were associated with being CFS frail. An IC cut-off score of 3 was able to discriminate moderately against the mFP and CFS (AUC 0.72 and 0.74, respectively), but with a high false-positive rate 85.4% and 81.9%, respectively. Conclusions In a primary care population with multimorbidity, IC screening discriminates moderately against frailty. In view of the very high prevalence of IC losses, the high false-positive rate of frailty in this population and limited healthcare resources, IC screening followed by frailty screening of selected patients with IC losses may not be feasible and other approaches should be considered. intrinsic capacity frailty multimorbidity screening older adults Introduction In older adults, intrinsic capacity (IC) losses commonly co-exist with frailty 1 and both are associated with adverse health outcomes such as functional disability, mortality, poorer well-being, and higher healthcare utilisation. 2 , 3 Various guidelines have recommended screening and intervening for IC losses and frailty to improve health outcomes. 4 , 5 However, IC and frailty are distinct from each other and in view of limited healthcare resources, it is unclear how IC and frailty screening should be implemented. Being the more established of the two, frailty is commonly defined as a physiological state of increased vulnerability to stressors 6 and there is robust evidence that various interventions such as multimodal exercises and high protein diet can reduce frailty. 7 However, one of the challenges in frailty screening and management is the lack of a standardised frailty measurement instrument. 1 , 7 For rapid frailty identification in clinical practice, the Ministry of Health National Frailty Strategy Policy Report of Singapore recommended the Clinical Frailty Scale (CFS) as the national frailty screening tool. 8 In contrast to frailty, IC is the sum of an individual’s physical and mental capacities. 9 As a concept conceived to promote healthy ageing in a holistic manner, IC is hypothesised to interact with one’s external environment to influence functional ability, or the ability to lead a meaningful life in old age. 9 Unlike frailty which is seen as a state of vulnerability at a single time point in one’s later stages in life, IC holds a life-course approach and declines in its domains occur earlier from midlife onwards. 1 IC is operationalised with reference to care dependence and functional disability and consists of five domains: cognition, vision and hearing, locomotion, vitality, and psychological capacity. 10 To guide community and primary care providers in optimising and maintaining IC and functional ability in older adults, the Integrated Care for Older People (ICOPE) guideline was created to facilitate IC screening and optimisation. 5 It consists of five steps, of which the first step involves screening for potential declines in the five IC domains, followed by in-depth assessment of those with IC losses, the development and implementation of a personalised care plan, regular monitoring, utilising community resources to support the patient, and supporting caregivers. Both IC and frailty are seen to complement each other, and IC is thought to be a determinant of frailty, in which a clinically relevant reduction in IC and functional reserve leads to the development of frailty. 1 , 9 Having declines in locomotion, or two or more declines in any IC domains increases the risk of frailty. 11 , 12 , 13 Additionally, there is significant overlap between IC and frailty, with considerable proportions of robust and pre-frail adults already having IC impairments. 11 , 13 Thus, IC measurement and monitoring can support both concurrent and subsequent evaluation of frailty. 1 The ICOPE recommends screening for frailty in those with impaired locomotion. 5 However, most IC studies measured frailty using the frailty phenotype (FP) which is characterised by sarcopenia. Given the close relation between the IC and FP domains, it is unsurprising that there are significant associations between the two. While the FP measure is well validated and is one of the most common frailty measurements in research, it is not utilised in clinical practice due to the need for objective measurements that are not part of routine care. 14 It is unclear how IC correlates with more global assessments of frailty, such as the CFS, that are more applicable in clinical practice. Additionally, most IC studies were conducted in the general population, and it is unclear how their findings are applicable to a primary care population with high levels of multimorbidity that is also at risk of developing frailty. Multimorbidity is associated with reduced IC, frailty and other adverse outcomes, 10 , 17 , 18 and almost half of elderly primary care patients have multimorbidity. 15 For resource allocation and intervention planning in primary care, it is important to understand the extent of IC and frailty while screening this population, and their utility with regards to each other. Majority of older adults in the community already have some IC losses on screening, and the prevalence of IC losses will be even higher in primary care. It may be untenable to screen and then assess and optimise IC for all individuals in a primary care clinic. Instead, it may be more feasible to target specific high-risk subgroups e.g., individuals with multimorbidity. By screening for IC using the ICOPE tool and for frailty using two commonly used frailty measures (FP and CFS) in the primary care population with multimorbidity, we hope to understand the level of IC and frailty in this group, the extent of overlap between the two concepts, their association with each other, and if IC can concurrently discriminate against the frailty measures and functional disability. Materials and methods This cross-sectional study was conducted from August 2022 to October 2022 across three primary care clinics which are part of a bigger network of clinics in the central region of Singapore under the National Healthcare Group Polyclinics (NHGP). Participants were recruited by convenience sampling. They were (i) 60 years to 100 years old, (ii) had the most common multimorbidity triad in Singapore (i.e., diabetes mellitus, hypertension, and hyperlipidaemia), and (iii) were able to walk independently with or without walking aids. The questionnaire was administered by trained interviewers. Participants gave written informed consent in accordance with the Declaration of Helsinki, and the study was approved by the ethical review board of National Healthcare Group (NHG DSRB Ref: 2022/00379). Sociodemographic data Sociodemographic information and lifestyle risk factors including age, gender, ethnicity, education level, housing type, smoking, and alcohol consumption were collected using a self-reported questionnaire. Intrinsic capacity Intrinsic capacity was measured using the WHO ICOPE tool 5 : Cognitive domain was evaluated by two questions testing immediate recall and orientation to time and space. The domain was scored 0 (impaired) if one or both questions were answered incorrectly, or 1 (intact) if both questions were answered correctly. Locomotion was evaluated by the five times sit-to-stand test. The domain was scored 0 (impaired) if the time taken to complete the test was ≥ 12s, or 1 (intact) if it was < 12s using the Asia Working Group for Sarcopenia (AWSG) 2019 guideline cut-off 19 . Vitality was evaluated by self-reported unintentional weight loss of ≥ 3kg in the last three months and self-reported loss of appetite. The domain was scored 0 (impaired) if the participant answered “Yes” to one or both questions, or 1 (intact) if “No” to both questions. Sensory domain was evaluated by self-reported visual problems and the whisper test to both ears. The domain was scored score 0 (impaired) if there were impairments to either one or both sub-domains, or 1 (intact) if both vision and hearing were intact. Psychological domain was evaluated by the Patient Health Questionnaire-2 (PHQ-2), “Over the past few weeks, have you been bothered by feeling down, depressed and hopeless?” and “Over the past few week, have you been bothered by little interest or pleasure in doing things?”. 20 The domain was scored 0 (impaired) if the participant answered “Yes” to one or both questions, or 1 (intact) if “No” to both questions. The composite IC score was summed up by addition of the scores from all five domains, to give a range of 0 to 5, with higher scores indicating better IC. Social Vulnerability factors Social vulnerability factors included social network, loneliness and social participation. Social network was measured using the 6-item Lubben Social Network Scale 21 , which comprises of the family subscale and friend subscale. Each subscale has a set of three questions evaluating social connectedness, and each question has six response options ranging from 0 to 5 which correspond to the number of people that participants feel they are socially connected to. The score for each subscale is derived by adding up the responses to all the questions, giving a score range of 0 to 15, with higher scores indicating better social engagement. Loneliness was assessed using the 3-item UCLA Loneliness Scale 22 with questions about feeling a lack of companionship, feeling left out and feeling isolated from others. Each question has three options to reflect the frequency of feelings of loneliness: 1 (hardly ever) to 3 (Often). The values for each question were summed up to give a score ranging from 3 to 9. Participants were categorised as “not lonely” if they scored 3, “somewhat lonely” if they scored 4 to 5, and “lonely” if they scored 6 to 9. Social participation was measured using the social role domain of the Late-Life Function and Disability Instrument (Late-Life FDI) 23 which consist of nine items reflecting the frequency of performing various social and community activities, including keeping in touch with others, visiting friends and family in their homes, providing care or assistance to others, volunteering, participating in active recreation, travelling out of town, inviting people into your home, going out with others to public places, and participating in organised social activities. Each item has five response options from 1 (never) to 5 (very often). The scores from each question were summed up and transformed to a score from 0 to 100 based on a Rasch model, with lower scores indicating worse social participation. Multimorbidity The level of multimorbidity was measured using a simple count of self-reported conditions from a pre-determined list of 23 chronic conditions that are prevalent or of high impact to patients in primary care: hyperlipidaemia, hypertension, diabetes, arthritis, obesity, cardiovascular disease, asthma or chronic obstructive pulmonary disease, chronic hepatitis, stomach problems, thyroid disorders, stroke, heart failure, kidney disease, depression or anxiety, chronic urinary problem, physical disability, cancer, osteoporosis, dementia and colon problems. 16 To better identify patients with increased healthcare needs who may be at higher risk of poorer outcomes, participants with three or more conditions were considered as having multimorbidity. 16 Functional disability Functional disability was assessed by impairments in basic activities of daily living (bADLs) measured by the Barthel Index 24 and impairments in instrumental ADLs (iADLs) measured by the Lawton and Brody scale. 25 Those who required assistance or who were completely dependent were considered to have functional disability. Modified Frailty Phenotype (mFP) Frailty was operationalised using the mFP criteria 26 : Exhaustion was measured using two items from the Centre for Epidemiological Studies-Depression Scale (CES-D) 27 : “I felt that everything I did was an effort” and “I could not get going”. A positive response to either item indicated the presence of exhaustion. Gait speed was assessed over three metres, with AWSG 2019’s cut-off of < 1m/s for slow gait speed. 19 Hand grip strength was measured using a JAMAR® hydraulic hand dynamometer, with two attempts using the participants’ dominant hand. The maximum value was used for analysis, with a cut-off of < 28kg (males) and < 18kg (females) for weak hand grip strength, based on AWSG 2019 reference values. 19 Shrinking was measured by the BMI (Body Mass Index), with a cut-off value of < 18.5kg/m 2 considered as significant. Physical activity was measured using the Frenchay Activities Index 28 , a 15-item questionnaire that measures the frequency in which the participant partakes in activities of daily living. A score of < 29 was used as a cut-off to define low physical activity. 26 Frailty was defined as the presence of at least three of the components, pre-frailty as the presence of one or two components and robustness as the absence of any of the components. Clinical Frailty Scale (CFS) The CFS has nine stages representing the full spectrum of robustness (CFS 1, very fit) to severe frailty and terminal illness (CFS 9, terminally ill with life expectancy < six months). 29 Our assessment was guided by the National Health System CFS app which evaluates bADLs and iADLs, symptoms limiting activities, physical activity level, and active disease symptoms. 30 The assessment started from the most advanced stage (CFS 9) and moved sequentially down to the stage applicable to the participant. The CFS scores were based on the CFS version 2.0, 29 and they were subsequently categorised into robust (CFS 1 and 2), pre-frail (CFS 3), and frail (CFS ≥ 4). The CFS was administered by research staff who had received prior CFS training and standardisation exercise. Sample Size Based on a study 31 exploring the level of intrinsic capacity and frailty in community dwelling older adults, the proportion of those with reduced intrinsic capacity and pre-frailty was 24% while those with reduced intrinsic capacity and frailty was 10%. We estimated that in a primary care population with multimorbidity, the proportion of participants with reduced intrinsic capacity and pre-frailty and that of reduced intrinsic capacity and frailty will be 45% and 35% respectively, giving a difference of 10% between the two groups. Based on table 6B.1 from Browner et al 32 and assuming ß =0.2 and 2-sided α = 0.05, the calculated minimum sample size was 395. Statistical analysis Descriptive data were presented as means (± SD) for quantitative variables and as frequencies with percentages for categorical variables. The IC scores and IC domains across different frailty levels (FP and CFS) were analysed using Fisher exact test and Chi-square test respectively. The area under the curve of receiver operator characteristics (AUC-ROC) and sensitivity and specificity were used to assess the discriminative ability of intrinsic capacity in relation to frailty and functional disability. Lastly, the associations between intrinsic capacity (composite score and individual domains) and the different frailty measures were examined using multinomial logistic regression with adjustment for sociodemographic variables, social vulnerability factors and level of multimorbidity. In the regression analyses, robust participants were taken as the reference group. Odds ratio (ORs) with 95% confidence interval were calculated and a p-value < 0.05 was considered statistically significant. All analyses were performed using R studio (Ver. 2023.09.1 + 494, MacOS 13.4.1) using R-Base (4.2.2, MacOS 13.4.1). Results A total of 666 polyclinic patients were approached, of which 414 (62.2%) participants were recruited. Two participants were subsequently excluded as they did not fulfil the inclusion criteria and one participant was excluded due to incomplete data. A total of 411 participants were included in the final analysis. The mean age of the participants was 69.9 (± 6.2) years old and there were slightly more males (54.5%). Majority were Chinese (81.3%), married (74.5%), and owned their own homes (85.9%). Slightly more than half had GCE O-level qualifications and above (50.4%), stayed in four to five-room public/ hybrid apartments and private properties (54.7%), and were not working (59.6%). Table 1 describes the sociodemographic characteristics in more detail. With regards to the level of multimorbidity, the mean number of chronic conditions was 4.0 (± 1.2). The mean HbA1c was 7.1 (± 1.1), mean blood pressure was 137/72 (± 17/9) mmHg, and mean LDL-calculated was 2.1 (± 0.7) mmol/L. 76.4% of participants were mFP pre-frail and 12.4% were mFP frail. The proportions of CFS pre-frail and CFS frail participants were half of that categorised by the mFP i.e., 38.7% and 7.5% respectively. Refer to Table 1 for further details. 14.8% of participants had bADL disability while 10.7% had iADL disability. Almost all the participants (98.0%) had reduced IC (score ≤ 4) and the mean IC score was 3.0 (± 0.9). The intrinsic capacity domain with the most deficits was the sensory domain, with 83.0% of participants having hearing impairments, 46.0% with visual impairments, and 90.0% having impairments in one or both subdomains. Other significantly affected domains were locomotion (44.0%) and cognition (30.9%). The least affected domains were the psychological (10.9%) and vitality (10.7%) domains. There was significant overlap between IC losses and frailty (refer to Table 2 A). Although reduced IC was present in almost all participants from the robust to frail (94.5 to 97.8% for CFS robust /mFP robust /mFP pre-frail; and 100.0% for CFS pre-frail/ mFP frail /CFS frail), those with poorer IC scores were frailer, irrespective of the type of frailty measure. However, the affected IC domains differed slightly between mFP and CFS (Refer to Table 2 B). Participants with impaired vitality and impaired psychological domain were frailer according to mFP while those with impaired sensory domains were frailer according to CFS. Additionally, those with impaired locomotion and impaired cognition were frailer for both frailty measures (p < 0.05). In the multinomial logistic regression models in which robust participants were taken as the reference group (Table 3 ), IC score was significantly associated with both mFP and CFS measures. Better IC was associated with lower odds of being mFP frail (OR 0.36, 95% C.I. 0.20 to 0.64, p 0.05) for both measures. With regards to IC domains and frailty, vitality and locomotion remained significantly associated with mFP and the sensory domain and locomotion with the CFS, even after adjusting for other independent factors (Table 3 ). Those with impaired locomotion had higher odds of being mFP frail (OR 2.14, 95% C.I. 1.04 to 1.21, p = 0.001), and being CFS frail (OR 5.62, 95% C.I. 1.72 to 18.36, p = 0.004), but not pre-frail for both frailty measures (p 0.05), and those with impaired sensory domain had higher odds of being CFS pre-frail (OR 7.66, 95% C.I. 2.40 to 24.46, p < 0.001) and frail (OR 14.17, 95% C.I. 1.01 to 198.07, p = 0.048). With regards to the discriminative ability of IC against the different frailty measures and functional disability, IC had moderate AUC against the mFP (AUC 0.72, 95% C.I. 0.64 to 0.80) and CFS (AUC 0.74, 95% C.I. 0.66 to 0.82), p < 0.001. With a composite IC cut-off score of 3 (i.e,. those with scores of 0, 1, 2 and 3 were considered frail and with scores of 4 and 5 were considered non-frail), the sensitivity, specificity, and false-positive rates were 86.3%, 74.7% and 85.4% respectively for mFP and 93.5%, 65.3% and 81.9% respectively for CFS. For IC against functional disability, the AUC was 0.68 (95% C.I 0.60 to 0.76, p < 0.001) with sensitivity 0.55 and specificity 0.77 for the same IC cut-off value of 3 for iADL disability. The values were 0.68 (95% C.I 0.62 to 0.74, p < 0.001), 0.90 and 0.37 respectively for bADL disability (Refer to Table 4 ) Table 1 Baseline characteristics Variables Total (N = 411) Mean Age (SD) 69.9 (6.2) Gender Male 224 (54.5%) Female 187 (45.5%) Ethnicity Chinese 334 (81.3%) Malay/Indian/Eurasian/Others 77 (18.7%) Marital status Married 306 (74.5%) Not married 105 (25.5%) Education Below GCE O-level 204 (49.6%) GCE O-Level and Above 207 (50.4%) Dwelling 1–3 room HDB 120 (29.2%) 4–5 room HDB/Hybrid/Private 291 (70.8%) Employment Working 166 (40.4%) Not working 245 (59.6%) Home ownership Home owner 353 (85.9%) Not home owner 58 (14.1%) Loneliness Lonely 88 (21.4%) Not lonely 323 (78.6%) Mean family social network (SD) 7.0 (3.7) Mean friends social network (SD) 5.5 (3.9) Mean social participation score (SD) 39.9 (10.9) Mean Barthel Index (SD) 99.0 (2.7) Mean Lawton & Brody Score (SD) 7.8 (0.7) Mean no. of chronic condition (SD) 1.0 (1.2) Mean Composite intrinsic capacity score (SD) 3.0 (0.9) Modified FP 5.5 (3.9) Robust 46 (11.2%) Pre-frail 314 (76.4%) Frail 51 (12.4%) CFS Robust (CFS 1–2) 221 (53.8%) Pre-frail (CFS 3) 159 (38.7%) Frail (CFS ≥ 4) 31 (7.5%) Table 2 A. Composite IC scores across different measures of frailty (mFP and CFS). IC Score Total mFP CFS ¥ N(%) Robust N(%) Pre-frail N(%) Frail N(%) p-value Robust N(%) Pre-frail N(%) Frail N(%) p-value p-value 5 10 (2.0) 1 (2.2) 9 (2.9) 0 (0.0) < 0.001 10 (4.5) 0 (0.0) 0 (0.0) < 0.001 4 124 (30.2) 23 (50.0) 94 (29.9) 7 (13.7) 77 (34.8) 45 (28.3) 2 (6.5) 3 168 (40.9) 17 (37.0) 137 (43.6) 14 (27.5) 93 (42.1) 65 (40.9) 10 (32.2) 2 91 (22.1) 5 (10.9) 66 (21.0) 20 (38.2) 36 (16.3) 41 (25.2) 14 (45.2) 1 17 (4.1) 0 (0.0) 8 (2.5) 9 (17.6) 5 (2.3) 7 (4.4) 5 (16.1) 0 1 (0.2) 0 (0.0) 0 (0.0) 1 (2.0) 0 (0.0) 1 (0.6) 0 (0.0) IC = Intrinsic Capacity, mFP = modified Frailty Phenotype ¥ CFS = Clinical Frailty Scale, Robust = CFS 1–2, Pre-frail = CFS 3, Frail = CFS ≥ 4 Table 2 B. IC domains across different measures of frailty (mFP and CFS). IC Domains mFP CFS ¥ Robust N(%) Pre-frail N(%) Frail N(%) p-value Robust N(%) Pre-frail N(%) Frail N(%) p-value N(%) N(%) N(%) N(%) N(%) N(%) Hearing Intact 8 (17.4) 52 (16.6) 6 (11.8) 0.665 54 (24.4) 9 (5.7) 3 (9.7) < 0.001 Impaired 38 (82.6) 262 (83.4) 45 (88.2) 167 (75.6) 150 (94.3) 28 (90.3) Vision Intact 29 (63.0) 168 (53.5) 24 (47.1) 0.283 112 (50.7) 100 (62.9) 9 (29.0) < 0.001 Impaired 17 (37.0) 146 (46.5) 27 (52.9) 109 (49.3) 59 (37.1) 22 (71.0) Hearing and/or Vision Intact 3 (6.5) 33 (10.5) 5 (9.8) 0.813 36 (16.3) 4 (2.5) 1 (3.2) < 0.001 Impaired 43 (93.5) 281 (89.5) 46 (90.2) 185(83.7) 155 (97.5) 30 (96.8) Vitality Intact 43 (93.5) 287 (91.4) 37 (72.5) < 0.001 201 (91.0) 140 (88.1) 26 (83.9) 0.345 Impaired 3 (6.5) 27 (8.6) 14 (27.5) 20 (9.0) 19 (11.9) 5 (16.1) Locomotion Intact 34 (73.9) 148 (47.1) 12 (23.5) < 0.001 114 (51.6) 75 (47.2) 5 (16.1) < 0.001 Impaired 12 (26.1) 166 (52.9) 39 (76.5) 107 (48.4) 84 (52.8) 26 (83.9) Cognition Intact 36 (78.3) 220 (70.1) 25 (49.0) 0.003 164 (74.2) 103 (64.8) 14 (45.2) 0.003 Impaired 10 (21.7) 94 (29.9) 26 (51.0) 57 (25.8) 56 (35.2) 17 (54.8) Psychological Intact 42 (91.3) 284 (90.4) 40 (78.4) 0.048 199 (90.0) 142 (89.3) 25 (80.6) 0.272 Impaired 4 (8.7) 30 (9.6) 11 (21.6) 22 (10.0) 17 (10.7) 6 (19.4) IC = Intrinsic Capacity, mFP = modified Frailty Phenotype ¥ CFS = Clinical Frailty Scale, Robust = CFS 1–2, Pre-frail = CFS 3, Frail = CFS ≥ 4 Table 3 Multinomial regression ∞ of composite IC score and IC domains against frailty (mFP and CFS);with robust participants as benchmark. Variables mFP CFS Pre-frail Frail Pre-frail* Frail* OR 95% C.I p-value OR 95% C.I p-value OR 95% C.I p-value OR 95% C.I p-value Composite IC score 0.81 0.52 to 1.25 0.340 0.36 0.20 to 0.64 < 0.001 1.24 0.80 to 1.91 0.096 0.44 0.29 to 0.67 0.001 Vitality Intact REF REF REF REF Impaired 1.55 0.40 to 6.01 0.528 6.15 1.32 to 28.71 0.021 0.74 0.34 to 1.62 0.454 1.32 0.34 to 5.09 0.683 Sensory Intact REF REF REF REF Impaired 0.43 0.12 to 1.60 0.208 0.34 0.06 to 1.85 0.212 7.66 2.40 to 24.46 < 0.001 14.17 1.01 to 198.07 0.048 Locomotion Intact REF REF REF REF Impaired 2.14 1.00 to 4.58 0.051 5.81 1.99 to 16.99 0.001 1.36 0.82 to 2.24 0.236 5.62 1.72 to 18.36 0.004 Cognition Intact REF REF REF REF Impaired 1.12 0.50 to 2.51 0.785 2.14 0.77 to 5.95 0.147 1.2 0.71 to 2.03 0.487 2.52 0.96 to 6.60 0.060 Psychology Intact REF REF REF REF Impaired 0.84 0.25 to 2.79 0.772 1.76 0.41 to 7.51 0.445 0.93 0.42 to 2.09 0.864 1.02 0.26 to 3.94 0.976 IC = Intrinsic Capacity, mFP = modified Frailty Phenotype ¥ CFS = Clinical Frailty Scale, Robust = CFS 1–2, Pre-frail = CFS 3, Frail = CFS ≥ 4 ∞ Values are adjusted for sociodemographic variables including age, gender, ethnicity, education level, housing type; social vulnerability factors including social network, loneliness, social participation, and number of chronic conditions. Table 4 The AUC-ROC and discriminative parameters of IC and the locomotion domain against frailty and functional disability mFP CFS IADL BADL IC, cut-off 3 AUC-ROC (95% C.I.) 0.72 (0.64–0.80) 0.74 (0.66–0.82) 0.68 (0.60–0.76) 0.68 (0.62–0.74) Sensitivity 86.3 93.5 54.5 90.2 Specificity 64.7 65.3 76.8 36.6 Youden index 0.5 0.6 31.4 26.7 Positive predictive value 14.6 18.1 22.0 19.9 Negative predictive value 97.1 99.2 93.4 95.5 p-value < 0.001 < 0.001 < 0.001 < 0.001 Locomotion domain AUC-ROC (95% C.I.) 0.64 (0.57–0.70) 0.67 (0.60–0.74) 0.57 (0.50–0.65) 0.63 (0.57–0.70) Sensitivity 76.5 83.4 65.9 75.4 Specificity 50.5 49.7 48.8 51.1 Youden index 27.0 33.6 14.7 26.6 Positive predictive value 17.8 12.0 13.4 21.2 Negative predictive value 93.8 97.4 92.3 92.3 p-value < 0.001 < 0.001 0.063 < 0.001 AUC-ROC = area under curve of receiver operator characteristics, IC = Intrinsic Capacity, mFP = modified Frailty Phenotype, CFS = Clinical Frailty Scale, IADL = instrumental activities of daily living, BADL = basic activities of daily living Discussion This study explored the level of IC and frailty in the primary care population with multimorbidity and how IC is associated with two commonly used frailty measurements representing different aspects of frailty (i.e. mFP and CFS). Regardless of frailty status, almost all the participants had reduced IC and the most affected IC domains were the sensory domain followed by locomotion and cognition. Although lower IC was associated with frailty regardless of the frailty measure, the IC domains associated with frailty depended on the frailty measure used. We also found that an IC score cut-off of 3 i.e., having losses in two or more domains was able to discriminate moderately against the mFP, CFS and functional disability, but with a high false positive rate. Given that a significant proportion of those rated as robust in the general population already had IC losses on screening 16 , 17 , it is unsurprising that almost all the primary care participants with multimorbidity had reduced IC. The most affected IC domain was the sensory domain and this is similar to the findings from the INSPIRE-ICOPE care programme 33 in which 68.1% and 50.6% of participants had losses in the vision and hearing domains respectively. However, our prevalence of hearing and visual impairments was much higher and this was likely due to our population of patients with the multimorbidity triad of diabetes, hypertension and hyperlipidemia. 34 , 35 Additionally, our study found that the cognition and mobility domains were also commonly affected and this was similar to other studies, highlighting the importance of reduced mobility and cognitive abilities in older adults. 36 Our findings will help us plan and expand the resources required for implementation of IC screening and optimisation especially for these domains which will involve specialist referrals for further assessment. Like other studies on the community dwelling population, we found that locomotion, vitality, and lower IC were associated with mFP frailty. 10 , 11 , 13 The mFP assessment included handgrip strength and BMI, both of which are considered components of vitality. 10 , 37 The assessment also includes gait speed which is part of functional mobility and locomotion. Given such overlap in the IC and FP domains, the significant association between the two is expected. In comparison, sensory domain, locomotion and lower IC were associated with CFS frailty. The CFS is a more global, function-based assessment and our results supported the importance of locomotion 38 and hearing/visual impairment 39 in physical symptoms, physical activity, and activities of daily living. Given the close association between reduced IC and impaired locomotion with frailty, our study showed only moderate ability of IC and the locomotion domain in discriminating against frailty. Our findings differed from Ma et al., 40 who had better results in hospitalised participants, despite both studies having similar prevalences of frailty. This suggests that various screening approaches are required for different patient populations. Although the ICOPE guideline suggests screening for frailty in those with impaired locomotion, the false positive rate in our primary care population with multimorbidity was more than 50%, indicating low yield of such screening. Clinical implications Patients with multimorbidity make up more than half of the primary care population with chronic diseases 15 and in our study, almost all of them had losses in IC. This raises concerns about the resources required to support IC screening, assessment, management, and monitoring in primary care, especially if primary care were to support such screening in its own setting as well as in the community. To date, studies on the adoption of ICOPE screening 41 are still ongoing and it remains to be seen if the suggested IC workflow can be sustainably scaled up. Instead of screening for frailty after IC screening, healthcare providers can consider the reverse i.e., screen for frailty first and then identify IC losses in those who are pre-frail and frail. While this may be against the idea of providing holistic population-based care beyond disease/deficiency states, it can be a compromise to provide such care to higher risk adults in view of the limited healthcare resources and an ageing population. Further studies are required to prove the feasibility and cost-effectiveness of such an approach. Strengths and limitations One strength of this study is the use of different measurements of frailty, including the CFS which is easy to use in the busy primary care setting. Additionally, we used valid instruments e.g., JAMAR dynamometer to measure frailty and intrinsic capacity. However, this study also has a few limitations. Firstly, we sampled participants only from public polyclinics and did not include those from private primary care clinics. Polyclinics provide a wide range of highly subsidised services in-situ including medical, nursing, allied-health, laboratory and basic radiological services while private clinics, being individually-owned or group-owned, have varying services and limited subsidies for patients. Compared to private clinic attendees, polyclinic attendees are older and more likely to have chronic diseases. This is supported by the 2014 Primary care survey which showed that 29% of polyclinic attendees were elderly compared to 11% in private clinics, and 52% of polyclinic consults were for chronic disease management, compared to 20% in private clinics. 42 Thus the representativeness of our primary care sample may be limited. Secondly, we only included older participants who could communicate in English or Mandarin and this could have contributed to the under-representation of Malay and Tamil participants. Lastly, as the study was cross-sectional in nature, causal relationships could not be examined. Conclusions This study explored the association of IC and frailty screening in older adults from the public primary care population with multimorbidity. Our findings highlighted the very high prevalence of IC losses regardless of frailty status and the high false positive rate of frailty screening in those with impaired IC or impaired locomotion. This may suggest that even in an at-risk population, IC screening followed by frailty screening may not be feasible in primary care due to the healthcare resources required to support it and a modified approach may be required. Declarations Ethics approval and consent to participate This study involved human participants and was reviewed and approved by the National Healthcare Group Domain Specific Review Board (NHG DSRB Ref: 2022/00379). The patients/participants provided their written informed consent to participate in this study. Consent for publication Not applicable. Competing interests The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. FUNDING This work was supported by the Singapore Ministry of Health’s National Medical Research Council under the Centre Grant Programme [Reference Number: NMRC/CG/C019/2017]. AUTHORS’ CONTRIBUTIONS SZS, XN, ESL contributed to the design of the work. SYT, TYGD, SZS, XN were involved in the recruitment of participants. SZS, XN, ESL, HLK, PSSL, SYT contributed to the analysis and interpretation of data. SZS drafted the manuscript and all authors contributed to writing the paper and revising it critically and gave final approval of this version. ACKNOWLEDGEMENT We thank the staff at Ang Mo Kio, Geylang and Hougang Polyclinics for their kind assistance in the study recruitment. We also acknowledge the work of Mr Lum Joon Kit, Ms Chan Pui San, Ms Ong Sin Kee, Ms Nur Atiqah bte Surya Akmaja and Ms Caron Tan in study co-ordination, recruitment, data collection and data entry. AVAILABILITY OF DATA AND MATERIAL The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. References Belloni G, Cesari M. Frailty and Intrinsic Capacity: Two Distinct but Related Constructs. Front Med (Lausanne). 2019;6:133. 10.3389/fmed.2019.00133 . Chu W, Chang SF, Ho HY. Adverse Health Effects of Frailty: Systematic Review and Meta-Analysis of Middle-Aged and Older Adults With Implications for Evidence-Based Practice. Worldviews Evid Based Nurs. 2021;18(4):282–9. 10.1111/wvn.12508 . Yang Y, Ma G, Wei S, et al. Adverse outcomes of intrinsic capacity in older adults: A scoping review. Arch Gerontol Geriatr. 2024;120:105335. 10.1016/j.archger.2024.105335 . Dent E, Morley JE, Cruz-Jentoft AJ, et al. Physical Frailty: ICFSR International Clinical Practice Guidelines for Identification and Management. J Nutr Health Aging. 2019;23(9):771–87. 10.1007/s12603-019-1273-z . ; World Health Organisation. Integrated care for older people (ICOPE): Guidance for person-centred assessment and pathways in primary care (Internet). Geneva: WHO, 2019. (WHO/FWC/ALC/19.1) (cited 1/5/24). https://www.who.int/publications/i/item/WHO-FWC-ALC-19.1 . Morley JE. Frailty and Sarcopenia: The New Geriatric Giants. Rev Invest Clin. 2016;68:59–67. Sun X, Liu W, Gao Y, et al. Comparative effectiveness of non-pharmacological interventions for frailty: a systematic review and network meta-analysis. Age Ageing. 2023;52(2):afad004. 10.1093/ageing/afad004 . Ministry of Health Singapore. National Frailty Strategy Policy Report [Internet], Singapore. MOH; April 2023 (cited 1/5/2024). https://www.moh.gov.sg/resources-statistics/reports/frailty-strategy-policy-report . WHO Clinical Consortium on Healthy Ageing. Report of consortium meeting 1–2 December 2016 in Geneva, Switzerland. Geneva: World Health Organization; 2017. (WHO/FWC/ALC/17.2). Beard JR, Jotheeswaran AT, Cesari M, Araujo de Carvalho I. The structure and predictive value of intrinsic capacity in a longitudinal study of ageing. BMJ Open. 2019;9(11):e026119. 10.1136/bmjopen-2018-026119 . PMID: 31678933; PMCID: PMC6830681. Tay L, Tay EL, Mah SM, Latib A, Koh C, Ng YS. Association of Intrinsic Capacity with Frailty, Physical Fitness and Adverse Health Outcomes in Community-Dwelling Older Adults. J Frailty Aging. 2023;12(1):7–15. 10.14283/jfa.2022.28 . Yu R, Lai D, Leung G, Woo J. Trajectories of Intrinsic Capacity: Determinants and Associations with Disability. J Nutr Health Aging. 2023;27(3):174–81. 10.1007/s12603-023-1881-5 . Liu S, Kang L, Liu X, et al. Trajectory and Correlation of Intrinsic Capacity and Frailty in a Beijing Elderly Community. Front Med (Lausanne). 2021;8:751586. 10.3389/fmed.2021.751586 . Published 2021 Dec 9. Dent E, Kowal P, Hoogendijk EO. Frailty measurement in research and clinical practice: A review. Eur J Intern Med. 2016;31:3–10. 10.1016/j.ejim.2016.03.007 . Epub 2016 Mar 31. Lee ES, Lee PSS, Xie Y, Ryan BL, Fortin M, Stewart M. The prevalence of multimorbidity in primary care: a comparison of two definitions of multimorbidity with two different lists of chronic conditions in Singapore. BMC Public Health. 2021;21(1):1409. 10.1186/s12889-021-11464-7 . Tyagi S, Koh V, Koh GC, Low LL, Lee ES. Defining and measuring multimorbidity in primary care in Singapore: Results of an online Delphi study. PLoS ONE. 2022;17(12):e0278559. 10.1371/journal.pone.0278559 . Skou ST, Mair FS, Fortin M, Multimorbidity et al. Nat Rev Dis Primers. 2022;8(1):48. Published 2022 Jul 14. 10.1038/s41572-022-00376-4 . Vetrano DL, Palmer K, Marengoni A, et al. Frailty and Multimorbidity: A Systematic Review and Meta-analysis. J Gerontol Biol Sci Med Sci. 2019;74(5):659–66. 10.1093/gerona/gly110 . Chen L-K, Woo J, Assantachai P, et al. Asian Working Group for Sarcopenia: 2019 Consensus Update on Sarcopenia Diagnosis and Treatment. J Am Med Dir Assoc. 2020;21(3):300–e3072. 10.1016/j.jamda.2019.12.012 . Löwe B, Kroenke K, Gräfe K. Detecting and monitoring depression with a two-item questionnaire (PHQ-2). J Psychosom Res. 2005;58(2):163–71. 10.1016/j.jpsychores.2004.09.006 . Lubben J, Gironda M, Sabbath E, Kong J, Johnson C. Social isolation presents a grand challenge for social work (Grand Challenges for Social Work Initiative Working Paper No. 7) [Internet]. Cleveland, OH: American Academy of Social Work and Social Welfare; 2015 Feb [cited 2024 May 28]. http://grandchallengesforsocialwork.org/wp- content/uploads/2015/12/WP7-with-cover.Pdf . Hughes ME, Waite LJ, Hawkley LC, Cacioppo JT. A short scale for measuring loneliness in large surveys. Res Aging. 2004;26(6):655–72. 10.1177/0164027504268574 . Jette AM, Haley SM, Kooyoomjian JT, Late-Life FDI. Manual [Internet].MA: Boston University; 2006. [cited 2024 May 28]. https://www.bu.edu/sph/files/2011/06/LLFDI_ Manual_ 2006_ rev.pdf. Mahoney FI, Barthel DW. Functional evaluation: The Barthel Index. Md State Med J. 1965;14:61–5. Lawton MP, Brody EM. Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist. 1969;9:179–8635. Chew J, Lim JP, Yew S, et al. Disentangling the Relationship between Frailty and Intrinsic Capacity in Healthy Community-Dwelling Older Adults: A Cluster Analysis. J Nutr Health Aging. 2021;25(9):1112–8. 10.1007/s12603-021-1679-2 . Radloff LS, The CES-D, Scale. A Self-Report Depression Scale for Research in the General Population. Appl Psychol Meas. 1977;1(3):385–401. 10.1177/014662167700100306 . Holbrook M, Skilbeck CE. An activities index for use with stroke patients. Age Ageing. 1983;12(2):166–70. 10.1093/ageing/12.2.166 . Rockwood K, Theou O. Using the Clinical Frailty Scale in Allocating Scarce Health Care Resources. Can Geriatr J. 2020;23(3):210–5. 10.5770/cgj.23.463 . Clinical Frailty Scale [mobile application software]. Version 1. United Kingdom: NHS Elect. 2020. Prince MJ, Acosta D, Guerra M, et al. Intrinsic capacity and its associations with incident dependence and mortality in 10/66 Dementia Research Group studies in Latin America, India, and China: A population-based cohort study. PLoS Med. 2021;18(9):e1003097. 10.1371/journal.pmed.1003097 . Published 2021 Sep 14. Browner WS, Newman TB, Hulley SB. Estimating sample size and power: applications and examples. In Hulley SB: Designing Clinical Research (4th Edition). Philadelphia: Lippincott Williams amp; Wilkins; 2013. P 75 – 6. Tavassoli N, de Souto Barreto P, Berbon C, et al. Implementation of the WHO integrated care for older people (ICOPE) programme in clinical practice: a prospective study. Lancet Healthy Longev. 2022;3(6):e394–404. 10.1016/S2666-7568(22)00097-6 . American Diabetes Association (ADA). Diabetes and hearing loss [Internet]. Virginia, USA: ADA. [cited 2024 May 28]. https://diabetes.org/about-diabetes/complications/hearing-loss/diabetes-and-hearing-loss . Teo ZL, Tham YC, Yu M, et al. Global Prevalence of Diabetic Retinopathy and Projection of Burden through 2045: Systematic Review and Meta-analysis. Ophthalmology. 2021;128(11):1580–91. 10.1016/j.ophtha.2021.04.027 . Ganmore I, Elkayam I, Ravona-Springer R, et al. Deterioration in Motor Function Over Time in Older Adults With Type 2 Diabetes is Associated with Accelerated Cognitive Decline. Endocr Pract. 2020;26(10):1143–52. 10.4158/EP-2020-0289 . Cesari M, Araujo de Carvalho I, Amuthavalli Thiyagarajan J, et al. Evidence for the Domains Supporting the Construct of Intrinsic Capacity. J Gerontol Biol Sci Med Sci. 2018;73(12):1653–60. 10.1093/gerona/gly011 . Wang DXM, Yao J, Zirek Y, Reijnierse EM, Maier AB. Muscle mass, strength, and physical performance predicting activities of daily living: a meta-analysis. J Cachexia Sarcopenia Muscle. 2020;11(1):3–25. 10.1002/jcsm.12502 . Liu Chiung-ju, Chang P-S, Griffith CF, Hanley SI, Lu Y. October, The Nexus of Sensory Loss, Cognitive Impairment, and Functional Decline in Older Adults: A Scoping Review, The Gerontologist, 62, Issue 8, 2022, Pages e457–67, https://doi.org/10.1093/geront/gnab082 . Ma L, Chhetri JK, Zhang Y et al. Integrated Care for Older People Screening Tool for Measuring Intrinsic Capacity: Preliminary Findings From ICOPE Pilot in China. Front Med (Lausanne). 2020;7:576079. 2020 Nov 30. 10.3389/fmed.2020.576079 . Sum G, Lau LK, Jabbar KA et al. The World Health Organization (WHO) Integrated Care for Older People (ICOPE) Framework: A Narrative Review on Its Adoption Worldwide and Lessons Learnt. Int J Environ Res Public Health. 2022;20(1):154. 2022 Dec 22. 10.3390/ijerph20010154 . Wong PYA, Chan FYS, Ong L, Lee KH. A qualitative study of challenges and enablers faced by private general practitioners providing primary care to patients with complex needs in Singapore. BMC Prim Care. 2022;23(1):14. 2022 Jan 19. 10.1186/s12875-022-01625-x . Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4524600","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":316839683,"identity":"1eb221be-5ac9-415d-b7e4-e442d47142de","order_by":0,"name":"Sai Zhen 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02:23:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4524600/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4524600/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12877-025-06569-2","type":"published","date":"2025-11-19T15:58:53+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":96650977,"identity":"fa28d89d-8843-4256-ba98-60c0ed60471e","added_by":"auto","created_at":"2025-11-24 16:13:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1021859,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4524600/v1/891b7583-2a78-4ab2-b04f-73f718123ef1.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Screening for intrinsic capacity and frailty in the primary care population with multimorbidity using the Integrated Care for Older People Screening Tool and two different frailty measures – the Frailty Phenotype and Clinical Frailty Scale: a cross-sectional study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn older adults, intrinsic capacity (IC) losses commonly co-exist with frailty\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e and both are associated with adverse health outcomes such as functional disability, mortality, poorer well-being, and higher healthcare utilisation.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Various guidelines have recommended screening and intervening for IC losses and frailty to improve health outcomes.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e However, IC and frailty are distinct from each other and in view of limited healthcare resources, it is unclear how IC and frailty screening should be implemented.\u003c/p\u003e \u003cp\u003eBeing the more established of the two, frailty is commonly defined as a physiological state of increased vulnerability to stressors\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e and there is robust evidence that various interventions such as multimodal exercises and high protein diet can reduce frailty.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e However, one of the challenges in frailty screening and management is the lack of a standardised frailty measurement instrument.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e For rapid frailty identification in clinical practice, the Ministry of Health National Frailty Strategy Policy Report of Singapore recommended the Clinical Frailty Scale (CFS) as the national frailty screening tool.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn contrast to frailty, IC is the sum of an individual\u0026rsquo;s physical and mental capacities.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e As a concept conceived to promote healthy ageing in a holistic manner, IC is hypothesised to interact with one\u0026rsquo;s external environment to influence functional ability, or the ability to lead a meaningful life in old age.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e Unlike frailty which is seen as a state of vulnerability at a single time point in one\u0026rsquo;s later stages in life, IC holds a life-course approach and declines in its domains occur earlier from midlife onwards.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e IC is operationalised with reference to care dependence and functional disability and consists of five domains: cognition, vision and hearing, locomotion, vitality, and psychological capacity.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e To guide community and primary care providers in optimising and maintaining IC and functional ability in older adults, the Integrated Care for Older People (ICOPE) guideline was created to facilitate IC screening and optimisation.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e It consists of five steps, of which the first step involves screening for potential declines in the five IC domains, followed by in-depth assessment of those with IC losses, the development and implementation of a personalised care plan, regular monitoring, utilising community resources to support the patient, and supporting caregivers.\u003c/p\u003e \u003cp\u003eBoth IC and frailty are seen to complement each other, and IC is thought to be a determinant of frailty, in which a clinically relevant reduction in IC and functional reserve leads to the development of frailty.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e Having declines in locomotion, or two or more declines in any IC domains increases the risk of frailty.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e Additionally, there is significant overlap between IC and frailty, with considerable proportions of robust and pre-frail adults already having IC impairments.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e Thus, IC measurement and monitoring can support both concurrent and subsequent evaluation of frailty.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e The ICOPE recommends screening for frailty in those with impaired locomotion.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eHowever, most IC studies measured frailty using the frailty phenotype (FP) which is characterised by sarcopenia. Given the close relation between the IC and FP domains, it is unsurprising that there are significant associations between the two. While the FP measure is well validated and is one of the most common frailty measurements in research, it is not utilised in clinical practice due to the need for objective measurements that are not part of routine care.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e It is unclear how IC correlates with more global assessments of frailty, such as the CFS, that are more applicable in clinical practice. Additionally, most IC studies were conducted in the general population, and it is unclear how their findings are applicable to a primary care population with high levels of multimorbidity that is also at risk of developing frailty. Multimorbidity is associated with reduced IC, frailty and other adverse outcomes,\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e and almost half of elderly primary care patients have multimorbidity.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFor resource allocation and intervention planning in primary care, it is important to understand the extent of IC and frailty while screening this population, and their utility with regards to each other. Majority of older adults in the community already have some IC losses on screening, and the prevalence of IC losses will be even higher in primary care. It may be untenable to screen and then assess and optimise IC for all individuals in a primary care clinic. Instead, it may be more feasible to target specific high-risk subgroups e.g., individuals with multimorbidity. By screening for IC using the ICOPE tool and for frailty using two commonly used frailty measures (FP and CFS) in the primary care population with multimorbidity, we hope to understand the level of IC and frailty in this group, the extent of overlap between the two concepts, their association with each other, and if IC can concurrently discriminate against the frailty measures and functional disability.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e This cross-sectional study was conducted from August 2022 to October 2022 across three primary care clinics which are part of a bigger network of clinics in the central region of Singapore under the National Healthcare Group Polyclinics (NHGP). Participants were recruited by convenience sampling. They were (i) 60 years to 100 years old, (ii) had the most common multimorbidity triad in Singapore (i.e., diabetes mellitus, hypertension, and hyperlipidaemia), and (iii) were able to walk independently with or without walking aids. The questionnaire was administered by trained interviewers. Participants gave written informed consent in accordance with the Declaration of Helsinki, and the study was approved by the ethical review board of National Healthcare Group (NHG DSRB Ref: 2022/00379).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSociodemographic data\u003c/h2\u003e \u003cp\u003eSociodemographic information and lifestyle risk factors including age, gender, ethnicity, education level, housing type, smoking, and alcohol consumption were collected using a self-reported questionnaire.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eIntrinsic capacity\u003c/h2\u003e \u003cp\u003eIntrinsic capacity was measured using the WHO ICOPE tool\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e:\u003c/p\u003e \u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eCognitive domain was evaluated by two questions testing immediate recall and orientation to time and space. The domain was scored 0 (impaired) if one or both questions were answered incorrectly, or 1 (intact) if both questions were answered correctly.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eLocomotion was evaluated by the five times sit-to-stand test. The domain was scored 0 (impaired) if the time taken to complete the test was \u0026ge;\u0026thinsp;12s, or 1 (intact) if it was \u0026lt;\u0026thinsp;12s using the Asia Working Group for Sarcopenia (AWSG) 2019 guideline cut-off\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eVitality was evaluated by self-reported unintentional weight loss of \u0026ge;\u0026thinsp;3kg in the last three months and self-reported loss of appetite. The domain was scored 0 (impaired) if the participant answered \u0026ldquo;Yes\u0026rdquo; to one or both questions, or 1 (intact) if \u0026ldquo;No\u0026rdquo; to both questions.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eSensory domain was evaluated by self-reported visual problems and the whisper test to both ears. The domain was scored score 0 (impaired) if there were impairments to either one or both sub-domains, or 1 (intact) if both vision and hearing were intact.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003ePsychological domain was evaluated by the Patient Health Questionnaire-2 (PHQ-2), \u0026ldquo;Over the past few weeks, have you been bothered by feeling down, depressed and hopeless?\u0026rdquo; and \u0026ldquo;Over the past few week, have you been bothered by little interest or pleasure in doing things?\u0026rdquo;.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e The domain was scored 0 (impaired) if the participant answered \u0026ldquo;Yes\u0026rdquo; to one or both questions, or 1 (intact) if \u0026ldquo;No\u0026rdquo; to both questions.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e \u003cp\u003eThe composite IC score was summed up by addition of the scores from all five domains, to give a range of 0 to 5, with higher scores indicating better IC.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eSocial Vulnerability factors\u003c/h2\u003e \u003cp\u003eSocial vulnerability factors included social network, loneliness and social participation. Social network was measured using the 6-item Lubben Social Network Scale\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, which comprises of the family subscale and friend subscale. Each subscale has a set of three questions evaluating social connectedness, and each question has six response options ranging from 0 to 5 which correspond to the number of people that participants feel they are socially connected to. The score for each subscale is derived by adding up the responses to all the questions, giving a score range of 0 to 15, with higher scores indicating better social engagement.\u003c/p\u003e \u003cp\u003eLoneliness was assessed using the 3-item UCLA Loneliness Scale\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e with questions about feeling a lack of companionship, feeling left out and feeling isolated from others. Each question has three options to reflect the frequency of feelings of loneliness: 1 (hardly ever) to 3 (Often). The values for each question were summed up to give a score ranging from 3 to 9. Participants were categorised as \u0026ldquo;not lonely\u0026rdquo; if they scored 3, \u0026ldquo;somewhat lonely\u0026rdquo; if they scored 4 to 5, and \u0026ldquo;lonely\u0026rdquo; if they scored 6 to 9.\u003c/p\u003e \u003cp\u003eSocial participation was measured using the social role domain of the Late-Life Function and Disability Instrument (Late-Life FDI)\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e which consist of nine items reflecting the frequency of performing various social and community activities, including keeping in touch with others, visiting friends and family in their homes, providing care or assistance to others, volunteering, participating in active recreation, travelling out of town, inviting people into your home, going out with others to public places, and participating in organised social activities. Each item has five response options from 1 (never) to 5 (very often). The scores from each question were summed up and transformed to a score from 0 to 100 based on a Rasch model, with lower scores indicating worse social participation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eMultimorbidity\u003c/h2\u003e \u003cp\u003eThe level of multimorbidity was measured using a simple count of self-reported conditions from a pre-determined list of 23 chronic conditions that are prevalent or of high impact to patients in primary care: hyperlipidaemia, hypertension, diabetes, arthritis, obesity, cardiovascular disease, asthma or chronic obstructive pulmonary disease, chronic hepatitis, stomach problems, thyroid disorders, stroke, heart failure, kidney disease, depression or anxiety, chronic urinary problem, physical disability, cancer, osteoporosis, dementia and colon problems.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e To better identify patients with increased healthcare needs who may be at higher risk of poorer outcomes, participants with three or more conditions were considered as having multimorbidity.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eFunctional disability\u003c/h2\u003e \u003cp\u003eFunctional disability was assessed by impairments in basic activities of daily living (bADLs) measured by the Barthel Index\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e and impairments in instrumental ADLs (iADLs) measured by the Lawton and Brody scale.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e Those who required assistance or who were completely dependent were considered to have functional disability.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eModified Frailty Phenotype (mFP)\u003c/h2\u003e \u003cp\u003eFrailty was operationalised using the mFP criteria\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eExhaustion was measured using two items from the Centre for Epidemiological Studies-Depression Scale (CES-D)\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e: \u0026ldquo;I felt that everything I did was an effort\u0026rdquo; and \u0026ldquo;I could not get going\u0026rdquo;. A positive response to either item indicated the presence of exhaustion.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eGait speed was assessed over three metres, with AWSG 2019\u0026rsquo;s cut-off of \u0026lt;\u0026thinsp;1m/s for slow gait speed.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eHand grip strength was measured using a JAMAR\u0026reg; hydraulic hand dynamometer, with two attempts using the participants\u0026rsquo; dominant hand. The maximum value was used for analysis, with a cut-off of \u0026lt;\u0026thinsp;28kg (males) and \u0026lt;\u0026thinsp;18kg (females) for weak hand grip strength, based on AWSG 2019 reference values.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eShrinking was measured by the BMI (Body Mass Index), with a cut-off value of \u0026lt;\u0026thinsp;18.5kg/m\u003csup\u003e2\u003c/sup\u003e considered as significant.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003ePhysical activity was measured using the Frenchay Activities Index\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e, a 15-item questionnaire that measures the frequency in which the participant partakes in activities of daily living. A score of \u0026lt;\u0026thinsp;29 was used as a cut-off to define low physical activity.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eFrailty was defined as the presence of at least three of the components, pre-frailty as the presence of one or two components and robustness as the absence of any of the components.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eClinical Frailty Scale (CFS)\u003c/h2\u003e \u003cp\u003eThe CFS has nine stages representing the full spectrum of robustness (CFS 1, very fit) to severe frailty and terminal illness (CFS 9, terminally ill with life expectancy\u0026thinsp;\u0026lt;\u0026thinsp;six months).\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e Our assessment was guided by the National Health System CFS app which evaluates bADLs and iADLs, symptoms limiting activities, physical activity level, and active disease symptoms.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e The assessment started from the most advanced stage (CFS 9) and moved sequentially down to the stage applicable to the participant. The CFS scores were based on the CFS version 2.0,\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e and they were subsequently categorised into robust (CFS 1 and 2), pre-frail (CFS 3), and frail (CFS\u0026thinsp;\u0026ge;\u0026thinsp;4). The CFS was administered by research staff who had received prior CFS training and standardisation exercise.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eSample Size\u003c/h2\u003e \u003cp\u003eBased on a study\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e exploring the level of intrinsic capacity and frailty in community dwelling older adults, the proportion of those with reduced intrinsic capacity and pre-frailty was 24% while those with reduced intrinsic capacity and frailty was 10%. We estimated that in a primary care population with multimorbidity, the proportion of participants with reduced intrinsic capacity and pre-frailty and that of reduced intrinsic capacity and frailty will be 45% and 35% respectively, giving a difference of 10% between the two groups. Based on table 6B.1 from Browner et al \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e and assuming \u0026szlig; =0.2 and 2-sided α\u0026thinsp;=\u0026thinsp;0.05, the calculated minimum sample size was 395.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eDescriptive data were presented as means (\u0026plusmn;\u0026thinsp;SD) for quantitative variables and as frequencies with percentages for categorical variables. The IC scores and IC domains across different frailty levels (FP and CFS) were analysed using Fisher exact test and Chi-square test respectively. The area under the curve of receiver operator characteristics (AUC-ROC) and sensitivity and specificity were used to assess the discriminative ability of intrinsic capacity in relation to frailty and functional disability. Lastly, the associations between intrinsic capacity (composite score and individual domains) and the different frailty measures were examined using multinomial logistic regression with adjustment for sociodemographic variables, social vulnerability factors and level of multimorbidity. In the regression analyses, robust participants were taken as the reference group. Odds ratio (ORs) with 95% confidence interval were calculated and a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. All analyses were performed using R studio (Ver. 2023.09.1\u0026thinsp;+\u0026thinsp;494, MacOS 13.4.1) using R-Base (4.2.2, MacOS 13.4.1).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 666 polyclinic patients were approached, of which 414 (62.2%) participants were recruited. Two participants were subsequently excluded as they did not fulfil the inclusion criteria and one participant was excluded due to incomplete data. A total of 411 participants were included in the final analysis. The mean age of the participants was 69.9 (\u0026plusmn;\u0026thinsp;6.2) years old and there were slightly more males (54.5%). Majority were Chinese (81.3%), married (74.5%), and owned their own homes (85.9%). Slightly more than half had GCE O-level qualifications and above (50.4%), stayed in four to five-room public/ hybrid apartments and private properties (54.7%), and were not working (59.6%). Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e describes the sociodemographic characteristics in more detail.\u003c/p\u003e \u003cp\u003eWith regards to the level of multimorbidity, the mean number of chronic conditions was 4.0 (\u0026plusmn;\u0026thinsp;1.2). The mean HbA1c was 7.1 (\u0026plusmn;\u0026thinsp;1.1), mean blood pressure was 137/72 (\u0026plusmn;\u0026thinsp;17/9) mmHg, and mean LDL-calculated was 2.1 (\u0026plusmn;\u0026thinsp;0.7) mmol/L. 76.4% of participants were mFP pre-frail and 12.4% were mFP frail. The proportions of CFS pre-frail and CFS frail participants were half of that categorised by the mFP i.e., 38.7% and 7.5% respectively. Refer to Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e for further details. 14.8% of participants had bADL disability while 10.7% had iADL disability. Almost all the participants (98.0%) had reduced IC (score\u0026thinsp;\u0026le;\u0026thinsp;4) and the mean IC score was 3.0 (\u0026plusmn;\u0026thinsp;0.9). The intrinsic capacity domain with the most deficits was the sensory domain, with 83.0% of participants having hearing impairments, 46.0% with visual impairments, and 90.0% having impairments in one or both subdomains. Other significantly affected domains were locomotion (44.0%) and cognition (30.9%). The least affected domains were the psychological (10.9%) and vitality (10.7%) domains.\u003c/p\u003e \u003cp\u003eThere was significant overlap between IC losses and frailty (refer to Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Although reduced IC was present in almost all participants from the robust to frail (94.5 to 97.8% for CFS robust /mFP robust /mFP pre-frail; and 100.0% for CFS pre-frail/ mFP frail /CFS frail), those with poorer IC scores were frailer, irrespective of the type of frailty measure. However, the affected IC domains differed slightly between mFP and CFS (Refer to Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Participants with impaired vitality and impaired psychological domain were frailer according to mFP while those with impaired sensory domains were frailer according to CFS. Additionally, those with impaired locomotion and impaired cognition were frailer for both frailty measures (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eIn the multinomial logistic regression models in which robust participants were taken as the reference group (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e), IC score was significantly associated with both mFP and CFS measures. Better IC was associated with lower odds of being mFP frail (OR 0.36, 95% C.I. 0.20 to 0.64, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and being CFS frail (OR 0.44, 95% C.I. 0.29 to 0.67, p\u0026thinsp;=\u0026thinsp;0.001) but it was not associated being pre-frail (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) for both measures. With regards to IC domains and frailty, vitality and locomotion remained significantly associated with mFP and the sensory domain and locomotion with the CFS, even after adjusting for other independent factors (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Those with impaired locomotion had higher odds of being mFP frail (OR 2.14, 95% C.I. 1.04 to 1.21, p\u0026thinsp;=\u0026thinsp;0.001), and being CFS frail (OR 5.62, 95% C.I. 1.72 to 18.36, p\u0026thinsp;=\u0026thinsp;0.004), but not pre-frail for both frailty measures (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Those with impaired vitality had higher odds of being mFP frail (OR 6.15, 95% C.I. 1.32 to 28.71, p\u0026thinsp;=\u0026thinsp;0.021) but not mFP pre-frail (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), and those with impaired sensory domain had higher odds of being CFS pre-frail (OR 7.66, 95% C.I. 2.40 to 24.46, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and frail (OR 14.17, 95% C.I. 1.01 to 198.07, p\u0026thinsp;=\u0026thinsp;0.048).\u003c/p\u003e \u003cp\u003eWith regards to the discriminative ability of IC against the different frailty measures and functional disability, IC had moderate AUC against the mFP (AUC 0.72, 95% C.I. 0.64 to 0.80) and CFS (AUC 0.74, 95% C.I. 0.66 to 0.82), p\u0026thinsp;\u0026lt;\u0026thinsp;0.001. With a composite IC cut-off score of 3 (i.e,. those with scores of 0, 1, 2 and 3 were considered frail and with scores of 4 and 5 were considered non-frail), the sensitivity, specificity, and false-positive rates were 86.3%, 74.7% and 85.4% respectively for mFP and 93.5%, 65.3% and 81.9% respectively for CFS. For IC against functional disability, the AUC was 0.68 (95% C.I 0.60 to 0.76, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) with sensitivity 0.55 and specificity 0.77 for the same IC cut-off value of 3 for iADL disability. The values were 0.68 (95% C.I 0.62 to 0.74, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), 0.90 and 0.37 respectively for bADL disability (Refer to Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e4\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal (N\u0026thinsp;=\u0026thinsp;411)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean Age (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e69.9 (6.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e224 (54.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e187 (45.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthnicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChinese\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e334 (81.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMalay/Indian/Eurasian/Others\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e77 (18.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e306 (74.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot married\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e105 (25.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBelow GCE O-level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e204 (49.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGCE O-Level and Above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e207 (50.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDwelling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;3 room HDB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e120 (29.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u0026ndash;5 room HDB/Hybrid/Private\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e291 (70.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWorking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e166 (40.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot working\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e245 (59.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHome ownership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHome owner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e353 (85.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot home owner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58 (14.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLoneliness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLonely\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e88 (21.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot lonely\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e323 (78.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean family social network (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.0 (3.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean friends social network (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.5 (3.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean social participation score (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39.9 (10.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean Barthel Index (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e99.0 (2.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean Lawton \u0026amp; Brody Score (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7.8 (0.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean no. of chronic condition (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.0 (1.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean Composite intrinsic capacity score (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.0 (0.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModified FP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.5 (3.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRobust\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46 (11.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-frail\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e314 (76.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrail\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e51 (12.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCFS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRobust (CFS 1\u0026ndash;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e221 (53.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-frail (CFS 3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e159 (38.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrail (CFS\u0026thinsp;\u0026ge;\u0026thinsp;4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31 (7.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eA. Composite IC scores across different measures of frailty (mFP and CFS).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIC Score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003emFP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c10\" namest=\"c7\"\u003e \u003cp\u003eCFS\u003csup\u003e\u0026yen;\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRobust\u003c/p\u003e \u003cp\u003eN(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePre-frail\u003c/p\u003e \u003cp\u003eN(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFrail\u003c/p\u003e \u003cp\u003eN(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRobust\u003c/p\u003e \u003cp\u003eN(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePre-frail\u003c/p\u003e \u003cp\u003eN(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eFrail\u003c/p\u003e \u003cp\u003eN(%)\u003c/p\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10 (4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e124 (30.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94 (29.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7 (13.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e77 (34.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e45 (28.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2 (6.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e168 (40.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (37.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e137 (43.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14 (27.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e93 (42.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e65 (40.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10 (32.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91 (22.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (10.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66 (21.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20 (38.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e36 (16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e41 (25.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e14 (45.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (4.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9 (17.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5 (16.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eIC\u0026thinsp;=\u0026thinsp;Intrinsic Capacity, mFP\u0026thinsp;=\u0026thinsp;modified Frailty Phenotype\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003e\u003csup\u003e\u0026yen;\u003c/sup\u003eCFS\u0026thinsp;=\u0026thinsp;Clinical Frailty Scale, Robust\u0026thinsp;=\u0026thinsp;CFS 1\u0026ndash;2, Pre-frail\u0026thinsp;=\u0026thinsp;CFS 3, Frail\u0026thinsp;=\u0026thinsp;CFS\u0026thinsp;\u0026ge;\u0026thinsp;4\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eB. IC domains across different measures of frailty (mFP and CFS).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIC Domains\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003emFP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003eCFS\u003csup\u003e\u0026yen;\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRobust\u003c/p\u003e \u003cp\u003eN(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePre-frail\u003c/p\u003e \u003cp\u003eN(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFrail\u003c/p\u003e \u003cp\u003eN(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRobust\u003c/p\u003e \u003cp\u003eN(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePre-frail\u003c/p\u003e \u003cp\u003eN(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eFrail\u003c/p\u003e \u003cp\u003eN(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eN(%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHearing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntact\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (17.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52 (16.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (11.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.665\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e54 (24.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9 (5.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3 (9.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImpaired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (82.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e262 (83.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45 (88.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e167 (75.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e150 (94.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e28 (90.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVision\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntact\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (63.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e168 (53.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24 (47.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e112 (50.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100 (62.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9 (29.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImpaired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (37.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e146 (46.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27 (52.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e109 (49.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e59 (37.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e22 (71.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHearing and/or Vision\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntact\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 (10.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (9.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.813\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36 (16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImpaired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43 (93.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e281 (89.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46 (90.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e185(83.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e155 (97.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e30 (96.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVitality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntact\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43 (93.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e287 (91.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37 (72.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e201 (91.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e140 (88.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e26 (83.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.345\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImpaired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (6.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (8.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (27.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20 (9.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19 (11.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5 (16.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocomotion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntact\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34 (73.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e148 (47.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (23.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e114 (51.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e75 (47.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5 (16.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImpaired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (26.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e166 (52.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39 (76.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e107 (48.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e84 (52.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e26 (83.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntact\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 (78.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e220 (70.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25 (49.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e164 (74.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e103 (64.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14 (45.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImpaired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (21.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94 (29.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (51.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e57 (25.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e56 (35.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e17 (54.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychological\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntact\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (91.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e284 (90.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40 (78.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.048\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e199 (90.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e142 (89.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25 (80.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.272\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImpaired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (8.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (9.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (21.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22 (10.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17 (10.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6 (19.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eIC\u0026thinsp;=\u0026thinsp;Intrinsic Capacity, mFP\u0026thinsp;=\u0026thinsp;modified Frailty Phenotype\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003e\u0026yen;\u003c/sup\u003eCFS\u0026thinsp;=\u0026thinsp;Clinical Frailty Scale, Robust\u0026thinsp;=\u0026thinsp;CFS 1\u0026ndash;2, Pre-frail\u0026thinsp;=\u0026thinsp;CFS 3, Frail\u0026thinsp;=\u0026thinsp;CFS\u0026thinsp;\u0026ge;\u0026thinsp;4\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultinomial regression\u003csup\u003e\u0026infin;\u003c/sup\u003e of composite IC score and IC domains against frailty (mFP and CFS);with robust participants as benchmark.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"14\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003emFP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c14\" namest=\"c8\"\u003e \u003cp\u003eCFS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003ePre-frail\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eFrail\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003ePre-frail*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c14\" namest=\"c11\"\u003e \u003cp\u003eFrail*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% C.I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% C.I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e95% C.I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e95% C.I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComposite IC score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.52 to 1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.340\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.20 to 0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.80 to 1.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.29 to 0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVitality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c14\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntact\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eREF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eREF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eREF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c14\" namest=\"c11\"\u003e \u003cp\u003eREF\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImpaired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.40 to 6.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.32 to 28.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.021\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.34 to 1.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.454\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e0.34 to 5.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.683\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSensory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c14\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntact\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eREF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eREF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eREF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c14\" namest=\"c11\"\u003e \u003cp\u003eREF\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImpaired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.12 to 1.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.06 to 1.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.40 to 24.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e14.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e1.01 to 198.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e0.048\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocomotion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c14\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntact\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eREF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eREF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eREF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c14\" namest=\"c11\"\u003e \u003cp\u003eREF\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImpaired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.00 to 4.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.99 to 16.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.82 to 2.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e1.72 to 18.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c14\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntact\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eREF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eREF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eREF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c14\" namest=\"c11\"\u003e \u003cp\u003eREF\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImpaired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.50 to 2.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.785\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.77 to 5.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.71 to 2.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.487\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e0.96 to 6.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c14\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntact\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eREF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eREF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eREF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c14\" namest=\"c11\"\u003e \u003cp\u003eREF\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImpaired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.25 to 2.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.772\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.41 to 7.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.42 to 2.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.864\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003e0.26 to 3.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.976\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"14\"\u003eIC\u0026thinsp;=\u0026thinsp;Intrinsic Capacity, mFP\u0026thinsp;=\u0026thinsp;modified Frailty Phenotype\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"14\"\u003e\u003csup\u003e\u0026yen;\u003c/sup\u003eCFS\u0026thinsp;=\u0026thinsp;Clinical Frailty Scale, Robust\u0026thinsp;=\u0026thinsp;CFS 1\u0026ndash;2, Pre-frail\u0026thinsp;=\u0026thinsp;CFS 3, Frail\u0026thinsp;=\u0026thinsp;CFS\u0026thinsp;\u0026ge;\u0026thinsp;4\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003csup\u003e\u0026infin;\u003c/sup\u003eValues are adjusted for sociodemographic variables including age, gender, ethnicity, education level, housing type; social vulnerability factors including social network, loneliness, social participation, and number of chronic conditions.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe AUC-ROC and discriminative parameters of IC and the locomotion domain against frailty and functional disability\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003emFP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCFS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIADL\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBADL\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eIC, cut-off 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAUC-ROC (95% C.I.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.72 (0.64\u0026ndash;0.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.74 (0.66\u0026ndash;0.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.68 (0.60\u0026ndash;0.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.68 (0.62\u0026ndash;0.74)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e90.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e76.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYouden index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive predictive value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative predictive value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e93.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eLocomotion domain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAUC-ROC (95% C.I.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.64 (0.57\u0026ndash;0.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.67 (0.60\u0026ndash;0.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.57 (0.50\u0026ndash;0.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.63 (0.57\u0026ndash;0.70)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e75.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e51.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYouden index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive predictive value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNegative predictive value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e97.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e92.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e92.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eAUC-ROC\u0026thinsp;=\u0026thinsp;area under curve of receiver operator characteristics, IC\u0026thinsp;=\u0026thinsp;Intrinsic Capacity, mFP\u0026thinsp;=\u0026thinsp;modified Frailty Phenotype, CFS\u0026thinsp;=\u0026thinsp;Clinical Frailty Scale, IADL\u0026thinsp;=\u0026thinsp;instrumental activities of daily living, BADL\u0026thinsp;=\u0026thinsp;basic activities of daily living\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study explored the level of IC and frailty in the primary care population with multimorbidity and how IC is associated with two commonly used frailty measurements representing different aspects of frailty (i.e. mFP and CFS). Regardless of frailty status, almost all the participants had reduced IC and the most affected IC domains were the sensory domain followed by locomotion and cognition. Although lower IC was associated with frailty regardless of the frailty measure, the IC domains associated with frailty depended on the frailty measure used. We also found that an IC score cut-off of 3 i.e., having losses in two or more domains was able to discriminate moderately against the mFP, CFS and functional disability, but with a high false positive rate.\u003c/p\u003e \u003cp\u003eGiven that a significant proportion of those rated as robust in the general population already had IC losses on screening\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, it is unsurprising that almost all the primary care participants with multimorbidity had reduced IC. The most affected IC domain was the sensory domain and this is similar to the findings from the INSPIRE-ICOPE care programme\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e in which 68.1% and 50.6% of participants had losses in the vision and hearing domains respectively. However, our prevalence of hearing and visual impairments was much higher and this was likely due to our population of patients with the multimorbidity triad of diabetes, hypertension and hyperlipidemia.\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e Additionally, our study found that the cognition and mobility domains were also commonly affected and this was similar to other studies, highlighting the importance of reduced mobility and cognitive abilities in older adults.\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e Our findings will help us plan and expand the resources required for implementation of IC screening and optimisation especially for these domains which will involve specialist referrals for further assessment.\u003c/p\u003e \u003cp\u003eLike other studies on the community dwelling population, we found that locomotion, vitality, and lower IC were associated with mFP frailty.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003eThe mFP assessment included handgrip strength and BMI, both of which are considered components of vitality.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e The assessment also includes gait speed which is part of functional mobility and locomotion. Given such overlap in the IC and FP domains, the significant association between the two is expected. In comparison, sensory domain, locomotion and lower IC were associated with CFS frailty. The CFS is a more global, function-based assessment and our results supported the importance of locomotion\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e and hearing/visual impairment\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e in physical symptoms, physical activity, and activities of daily living.\u003c/p\u003e \u003cp\u003eGiven the close association between reduced IC and impaired locomotion with frailty, our study showed only moderate ability of IC and the locomotion domain in discriminating against frailty. Our findings differed from Ma et al.,\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e who had better results in hospitalised participants, despite both studies having similar prevalences of frailty. This suggests that various screening approaches are required for different patient populations. Although the ICOPE guideline suggests screening for frailty in those with impaired locomotion, the false positive rate in our primary care population with multimorbidity was more than 50%, indicating low yield of such screening.\u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eClinical implications\u003c/h2\u003e \u003cp\u003ePatients with multimorbidity make up more than half of the primary care population with chronic diseases\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e and in our study, almost all of them had losses in IC. This raises concerns about the resources required to support IC screening, assessment, management, and monitoring in primary care, especially if primary care were to support such screening in its own setting as well as in the community. To date, studies on the adoption of ICOPE screening\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e are still ongoing and it remains to be seen if the suggested IC workflow can be sustainably scaled up.\u003c/p\u003e \u003cp\u003eInstead of screening for frailty after IC screening, healthcare providers can consider the reverse i.e., screen for frailty first and then identify IC losses in those who are pre-frail and frail. While this may be against the idea of providing holistic population-based care beyond disease/deficiency states, it can be a compromise to provide such care to higher risk adults in view of the limited healthcare resources and an ageing population. Further studies are required to prove the feasibility and cost-effectiveness of such an approach.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations\u003c/h2\u003e \u003cp\u003eOne strength of this study is the use of different measurements of frailty, including the CFS which is easy to use in the busy primary care setting. Additionally, we used valid instruments e.g., JAMAR dynamometer to measure frailty and intrinsic capacity. However, this study also has a few limitations. Firstly, we sampled participants only from public polyclinics and did not include those from private primary care clinics. Polyclinics provide a wide range of highly subsidised services in-situ including medical, nursing, allied-health, laboratory and basic radiological services while private clinics, being individually-owned or group-owned, have varying services and limited subsidies for patients. Compared to private clinic attendees, polyclinic attendees are older and more likely to have chronic diseases. This is supported by the 2014 Primary care survey which showed that 29% of polyclinic attendees were elderly compared to 11% in private clinics, and 52% of polyclinic consults were for chronic disease management, compared to 20% in private clinics.\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e Thus the representativeness of our primary care sample may be limited. Secondly, we only included older participants who could communicate in English or Mandarin and this could have contributed to the under-representation of Malay and Tamil participants. Lastly, as the study was cross-sectional in nature, causal relationships could not be examined.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study explored the association of IC and frailty screening in older adults from the public primary care population with multimorbidity. Our findings highlighted the very high prevalence of IC losses regardless of frailty status and the high false positive rate of frailty screening in those with impaired IC or impaired locomotion. This may suggest that even in an at-risk population, IC screening followed by frailty screening may not be feasible in primary care due to the healthcare resources required to support it and a modified approach may be required.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cu\u003eEthics approval and consent to participate\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThis study involved human participants and was reviewed and approved by the National Healthcare Group Domain Specific Review Board (NHG DSRB Ref: 2022/00379). The patients/participants provided their written informed consent to participate in this study.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eConsent for publication\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eCompeting interests\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eFUNDING\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Singapore Ministry of Health\u0026rsquo;s National Medical Research Council under the Centre Grant Programme [Reference Number: NMRC/CG/C019/2017].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAUTHORS\u0026rsquo; CONTRIBUTIONS\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eSZS, XN, ESL contributed to the design of the work. SYT, TYGD, SZS, XN were involved in the recruitment of participants. SZS, XN, ESL, HLK, PSSL, SYT contributed to the analysis and interpretation of data. SZS drafted the manuscript and all authors contributed to writing the paper and revising it critically and gave final approval of this version.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eACKNOWLEDGEMENT\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the staff at Ang Mo Kio, Geylang and Hougang Polyclinics for their kind assistance in the study recruitment. We also acknowledge the work of Mr Lum Joon Kit, Ms Chan Pui San, Ms Ong Sin Kee, Ms Nur Atiqah bte Surya Akmaja and Ms Caron Tan in study co-ordination, recruitment, data collection and data entry.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eAVAILABILITY OF DATA AND MATERIAL\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBelloni G, Cesari M. Frailty and Intrinsic Capacity: Two Distinct but Related Constructs. Front Med (Lausanne). 2019;6:133. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fmed.2019.00133\u003c/span\u003e\u003cspan address=\"10.3389/fmed.2019.00133\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChu W, Chang SF, Ho HY. Adverse Health Effects of Frailty: Systematic Review and Meta-Analysis of Middle-Aged and Older Adults With Implications for Evidence-Based Practice. Worldviews Evid Based Nurs. 2021;18(4):282\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/wvn.12508\u003c/span\u003e\u003cspan address=\"10.1111/wvn.12508\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang Y, Ma G, Wei S, et al. Adverse outcomes of intrinsic capacity in older adults: A scoping review. Arch Gerontol Geriatr. 2024;120:105335. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.archger.2024.105335\u003c/span\u003e\u003cspan address=\"10.1016/j.archger.2024.105335\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDent E, Morley JE, Cruz-Jentoft AJ, et al. Physical Frailty: ICFSR International Clinical Practice Guidelines for Identification and Management. J Nutr Health Aging. 2019;23(9):771\u0026ndash;87. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s12603-019-1273-z\u003c/span\u003e\u003cspan address=\"10.1007/s12603-019-1273-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e; World Health Organisation. Integrated care for older people (ICOPE): Guidance for person-centred assessment and pathways in primary care (Internet). Geneva: WHO, 2019. (WHO/FWC/ALC/19.1) (cited 1/5/24). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/publications/i/item/WHO-FWC-ALC-19.1\u003c/span\u003e\u003cspan address=\"https://www.who.int/publications/i/item/WHO-FWC-ALC-19.1\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMorley JE. Frailty and Sarcopenia: The New Geriatric Giants. Rev Invest Clin. 2016;68:59\u0026ndash;67.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSun X, Liu W, Gao Y, et al. Comparative effectiveness of non-pharmacological interventions for frailty: a systematic review and network meta-analysis. Age Ageing. 2023;52(2):afad004. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/ageing/afad004\u003c/span\u003e\u003cspan address=\"10.1093/ageing/afad004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMinistry of Health Singapore. National Frailty Strategy Policy Report [Internet], Singapore. MOH; April 2023 (cited 1/5/2024). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.moh.gov.sg/resources-statistics/reports/frailty-strategy-policy-report\u003c/span\u003e\u003cspan address=\"https://www.moh.gov.sg/resources-statistics/reports/frailty-strategy-policy-report\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWHO Clinical Consortium on Healthy Ageing. Report of consortium meeting 1\u0026ndash;2 December 2016 in Geneva, Switzerland. Geneva: World Health Organization; 2017. (WHO/FWC/ALC/17.2).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeard JR, Jotheeswaran AT, Cesari M, Araujo de Carvalho I. The structure and predictive value of intrinsic capacity in a longitudinal study of ageing. BMJ Open. 2019;9(11):e026119. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmjopen-2018-026119\u003c/span\u003e\u003cspan address=\"10.1136/bmjopen-2018-026119\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 31678933; PMCID: PMC6830681.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTay L, Tay EL, Mah SM, Latib A, Koh C, Ng YS. Association of Intrinsic Capacity with Frailty, Physical Fitness and Adverse Health Outcomes in Community-Dwelling Older Adults. J Frailty Aging. 2023;12(1):7\u0026ndash;15. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.14283/jfa.2022.28\u003c/span\u003e\u003cspan address=\"10.14283/jfa.2022.28\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYu R, Lai D, Leung G, Woo J. Trajectories of Intrinsic Capacity: Determinants and Associations with Disability. J Nutr Health Aging. 2023;27(3):174\u0026ndash;81. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s12603-023-1881-5\u003c/span\u003e\u003cspan address=\"10.1007/s12603-023-1881-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu S, Kang L, Liu X, et al. Trajectory and Correlation of Intrinsic Capacity and Frailty in a Beijing Elderly Community. Front Med (Lausanne). 2021;8:751586. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fmed.2021.751586\u003c/span\u003e\u003cspan address=\"10.3389/fmed.2021.751586\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Published 2021 Dec 9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDent E, Kowal P, Hoogendijk EO. Frailty measurement in research and clinical practice: A review. Eur J Intern Med. 2016;31:3\u0026ndash;10. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ejim.2016.03.007\u003c/span\u003e\u003cspan address=\"10.1016/j.ejim.2016.03.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2016 Mar 31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee ES, Lee PSS, Xie Y, Ryan BL, Fortin M, Stewart M. The prevalence of multimorbidity in primary care: a comparison of two definitions of multimorbidity with two different lists of chronic conditions in Singapore. BMC Public Health. 2021;21(1):1409. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12889-021-11464-7\u003c/span\u003e\u003cspan address=\"10.1186/s12889-021-11464-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTyagi S, Koh V, Koh GC, Low LL, Lee ES. Defining and measuring multimorbidity in primary care in Singapore: Results of an online Delphi study. PLoS ONE. 2022;17(12):e0278559. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0278559\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0278559\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSkou ST, Mair FS, Fortin M, Multimorbidity et al. Nat Rev Dis Primers. 2022;8(1):48. Published 2022 Jul 14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41572-022-00376-4\u003c/span\u003e\u003cspan address=\"10.1038/s41572-022-00376-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVetrano DL, Palmer K, Marengoni A, et al. Frailty and Multimorbidity: A Systematic Review and Meta-analysis. J Gerontol Biol Sci Med Sci. 2019;74(5):659\u0026ndash;66. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/gerona/gly110\u003c/span\u003e\u003cspan address=\"10.1093/gerona/gly110\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen L-K, Woo J, Assantachai P, et al. Asian Working Group for Sarcopenia: 2019 Consensus Update on Sarcopenia Diagnosis and Treatment. J Am Med Dir Assoc. 2020;21(3):300\u0026ndash;e3072. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jamda.2019.12.012\u003c/span\u003e\u003cspan address=\"10.1016/j.jamda.2019.12.012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eL\u0026ouml;we B, Kroenke K, Gr\u0026auml;fe K. Detecting and monitoring depression with a two-item questionnaire (PHQ-2). J Psychosom Res. 2005;58(2):163\u0026ndash;71. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jpsychores.2004.09.006\u003c/span\u003e\u003cspan address=\"10.1016/j.jpsychores.2004.09.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLubben J, Gironda M, Sabbath E, Kong J, Johnson C. Social isolation presents a grand challenge for social work (Grand Challenges for Social Work Initiative Working Paper No. 7) [Internet]. Cleveland, OH: American Academy of Social Work and Social Welfare; 2015 Feb [cited 2024 May 28]. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://grandchallengesforsocialwork.org/wp- content/uploads/2015/12/WP7-with-cover.Pdf\u003c/span\u003e\u003cspan address=\"http://grandchallengesforsocialwork.org/wp- content/uploads/2015/12/WP7-with-cover.Pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHughes ME, Waite LJ, Hawkley LC, Cacioppo JT. A short scale for measuring loneliness in large surveys. Res Aging. 2004;26(6):655\u0026ndash;72. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/0164027504268574\u003c/span\u003e\u003cspan address=\"10.1177/0164027504268574\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJette AM, Haley SM, Kooyoomjian JT, Late-Life FDI. Manual [Internet].MA: Boston University; 2006. [cited 2024 May 28]. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bu.edu/sph/files/2011/06/LLFDI_\u003c/span\u003e\u003cspan address=\"https://www.bu.edu/sph/files/2011/06/LLFDI_\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e Manual_ 2006_ rev.pdf.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMahoney FI, Barthel DW. Functional evaluation: The Barthel Index. Md State Med J. 1965;14:61\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLawton MP, Brody EM. Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist. 1969;9:179\u0026ndash;8635.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChew J, Lim JP, Yew S, et al. Disentangling the Relationship between Frailty and Intrinsic Capacity in Healthy Community-Dwelling Older Adults: A Cluster Analysis. J Nutr Health Aging. 2021;25(9):1112\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s12603-021-1679-2\u003c/span\u003e\u003cspan address=\"10.1007/s12603-021-1679-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRadloff LS, The CES-D, Scale. A Self-Report Depression Scale for Research in the General Population. Appl Psychol Meas. 1977;1(3):385\u0026ndash;401. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/014662167700100306\u003c/span\u003e\u003cspan address=\"10.1177/014662167700100306\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHolbrook M, Skilbeck CE. An activities index for use with stroke patients. Age Ageing. 1983;12(2):166\u0026ndash;70. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/ageing/12.2.166\u003c/span\u003e\u003cspan address=\"10.1093/ageing/12.2.166\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRockwood K, Theou O. Using the Clinical Frailty Scale in Allocating Scarce Health Care Resources. Can Geriatr J. 2020;23(3):210\u0026ndash;5. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.5770/cgj.23.463\u003c/span\u003e\u003cspan address=\"10.5770/cgj.23.463\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eClinical Frailty Scale [mobile application software]. Version 1. United Kingdom: NHS Elect. 2020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePrince MJ, Acosta D, Guerra M, et al. Intrinsic capacity and its associations with incident dependence and mortality in 10/66 Dementia Research Group studies in Latin America, India, and China: A population-based cohort study. PLoS Med. 2021;18(9):e1003097. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pmed.1003097\u003c/span\u003e\u003cspan address=\"10.1371/journal.pmed.1003097\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Published 2021 Sep 14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrowner WS, Newman TB, Hulley SB. Estimating sample size and power: applications and examples. In Hulley SB: Designing Clinical Research (4th Edition). Philadelphia: Lippincott Williams amp; Wilkins; 2013. P 75\u0026thinsp;\u0026ndash;\u0026thinsp;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTavassoli N, de Souto Barreto P, Berbon C, et al. Implementation of the WHO integrated care for older people (ICOPE) programme in clinical practice: a prospective study. Lancet Healthy Longev. 2022;3(6):e394\u0026ndash;404. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S2666-7568(22)00097-6\u003c/span\u003e\u003cspan address=\"10.1016/S2666-7568(22)00097-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmerican Diabetes Association (ADA). Diabetes and hearing loss [Internet]. Virginia, USA: ADA. [cited 2024 May 28]. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://diabetes.org/about-diabetes/complications/hearing-loss/diabetes-and-hearing-loss\u003c/span\u003e\u003cspan address=\"https://diabetes.org/about-diabetes/complications/hearing-loss/diabetes-and-hearing-loss\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTeo ZL, Tham YC, Yu M, et al. Global Prevalence of Diabetic Retinopathy and Projection of Burden through 2045: Systematic Review and Meta-analysis. Ophthalmology. 2021;128(11):1580\u0026ndash;91. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ophtha.2021.04.027\u003c/span\u003e\u003cspan address=\"10.1016/j.ophtha.2021.04.027\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGanmore I, Elkayam I, Ravona-Springer R, et al. Deterioration in Motor Function Over Time in Older Adults With Type 2 Diabetes is Associated with Accelerated Cognitive Decline. Endocr Pract. 2020;26(10):1143\u0026ndash;52. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4158/EP-2020-0289\u003c/span\u003e\u003cspan address=\"10.4158/EP-2020-0289\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCesari M, Araujo de Carvalho I, Amuthavalli Thiyagarajan J, et al. Evidence for the Domains Supporting the Construct of Intrinsic Capacity. J Gerontol Biol Sci Med Sci. 2018;73(12):1653\u0026ndash;60. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/gerona/gly011\u003c/span\u003e\u003cspan address=\"10.1093/gerona/gly011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang DXM, Yao J, Zirek Y, Reijnierse EM, Maier AB. Muscle mass, strength, and physical performance predicting activities of daily living: a meta-analysis. J Cachexia Sarcopenia Muscle. 2020;11(1):3\u0026ndash;25. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/jcsm.12502\u003c/span\u003e\u003cspan address=\"10.1002/jcsm.12502\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu Chiung-ju, Chang P-S, Griffith CF, Hanley SI, Lu Y. October, The Nexus of Sensory Loss, Cognitive Impairment, and Functional Decline in Older Adults: A Scoping Review, The Gerontologist, 62, Issue 8, 2022, Pages e457\u0026ndash;67, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/geront/gnab082\u003c/span\u003e\u003cspan address=\"10.1093/geront/gnab082\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMa L, Chhetri JK, Zhang Y et al. Integrated Care for Older People Screening Tool for Measuring Intrinsic Capacity: Preliminary Findings From ICOPE Pilot in China. Front Med (Lausanne). 2020;7:576079. 2020 Nov 30. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fmed.2020.576079\u003c/span\u003e\u003cspan address=\"10.3389/fmed.2020.576079\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSum G, Lau LK, Jabbar KA et al. The World Health Organization (WHO) Integrated Care for Older People (ICOPE) Framework: A Narrative Review on Its Adoption Worldwide and Lessons Learnt. Int J Environ Res Public Health. 2022;20(1):154. 2022 Dec 22. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijerph20010154\u003c/span\u003e\u003cspan address=\"10.3390/ijerph20010154\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e \u003cspan\u003eWong PYA, Chan FYS, Ong L, Lee KH. A qualitative study of challenges and enablers faced by private general practitioners providing primary care to patients with complex needs in Singapore. BMC Prim Care. 2022;23(1):14. 2022 Jan 19. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12875-022-01625-x\u003c/span\u003e\u003cspan address=\"10.1186/s12875-022-01625-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"intrinsic capacity, frailty, multimorbidity, screening, older adults","lastPublishedDoi":"10.21203/rs.3.rs-4524600/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4524600/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eIntrinsic capacity (IC) co-exists with frailty and multimorbidity in primary care. To improve health outcomes, guidelines recommend IC and frailty screening and it is thought that IC screening can support the concurrent and subsequent evaluation of frailty. For feasible implementation of such screening, it is important to understand the association between IC and frailty, including the discriminative ability of IC against frailty in a primary care population with multimorbidity.\u003c/p\u003e\u003ch2\u003eMethod\u003c/h2\u003e \u003cp\u003eA cross-sectional study was conducted across three primary care clinics. Participants were elderly and had the multimorbidity triad of diabetes mellitus, hypertension, and hyperlipidemia. Data collected included sociodemographic variables, IC (Integrated Care Older People Screening Tool), social vulnerability, chronic conditions, functional disability, modified Frailty Phenotype (mFP), and Clinical Frailty Scale (CFS). Logistic regression was used to assess the association between IC and the two measurements of frailty while area under the curve of the receiver operating characteristic (AUC-ROC) was used to assess the discriminative ability of IC against frailty.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e411 participants were included. Mean age was 69.9 (\u0026plusmn;\u0026thinsp;6.2) years and almost all (98.0%) the participants had reduced IC on screening, of which the most affected domains were the sensory (90.0%), locomotion (44.0%), and cognition (30.9%) domains. 12.4% were mFP frail while 7.4% were CFS frail. While higher IC was associated with reduced odds of frailty regardless of the frailty measure (p\u0026thinsp;\u0026le;\u0026thinsp;0.001), the IC domains associated with frailty depended on the frailty measure used. Vitality and locomotion were associated with being mFP frail while the sensory and locomotion domains were associated with being CFS frail. An IC cut-off score of 3 was able to discriminate moderately against the mFP and CFS (AUC 0.72 and 0.74, respectively), but with a high false-positive rate 85.4% and 81.9%, respectively.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eIn a primary care population with multimorbidity, IC screening discriminates moderately against frailty. In view of the very high prevalence of IC losses, the high false-positive rate of frailty in this population and limited healthcare resources, IC screening followed by frailty screening of selected patients with IC losses may not be feasible and other approaches should be considered.\u003c/p\u003e","manuscriptTitle":"Screening for intrinsic capacity and frailty in the primary care population with multimorbidity using the Integrated Care for Older People Screening Tool and two different frailty measures – the Frailty Phenotype and Clinical Frailty Scale: a cross-sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-27 19:27:54","doi":"10.21203/rs.3.rs-4524600/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-03T07:36:23+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-12T11:24:22+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-12T11:24:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Geriatrics","date":"2024-06-04T02:18:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"de3b67b0-5b76-47a3-a0ca-ee5384a2d0be","owner":[],"postedDate":"June 27th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-24T16:10:01+00:00","versionOfRecord":{"articleIdentity":"rs-4524600","link":"https://doi.org/10.1186/s12877-025-06569-2","journal":{"identity":"bmc-geriatrics","isVorOnly":false,"title":"BMC Geriatrics"},"publishedOn":"2025-11-19 15:58:53","publishedOnDateReadable":"November 19th, 2025"},"versionCreatedAt":"2024-06-27 19:27:54","video":"","vorDoi":"10.1186/s12877-025-06569-2","vorDoiUrl":"https://doi.org/10.1186/s12877-025-06569-2","workflowStages":[]},"version":"v1","identity":"rs-4524600","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4524600","identity":"rs-4524600","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}